Journal of Scholastic Inquiry: Business, Fall 2018 by Center for Scholastic Inquiry

Journal of Scholastic Inquiry: Business

Volume 9, Page 1

Journal of Scholastic Inquiry:

Business

Business Edition, Volume 9, Issue 1 Fall 2018

Published by: Center for Scholastic Inquiry, LLC ISSN: 2330-6807 (online) ISSN: 2330-6815 (print)

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ISSN: 2330-6807 (online) ISSN: 2330-6815 (print)

Journal of Scholastic Inquiry: Business

Fall 2018

Volume 9, Issue 1

www.csiresearch.com

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Journal of Scholastic Inquiry: Business The Center for Scholastic Inquiry (CSI) publishes the Journal of Scholastic Inquiry to recognize, celebrate, and highlight scholarly research, discovery, and evidence-based practice. Academic research emphasizing leading edge inquiry, distinguishing and fostering best practice, and validating promising methods will be considered for publication. Qualitative, quantitative, and mixed method study designs representing diverse philosophical frameworks and perspectives are welcome. The JOSI publishes papers that perpetuate thought-leadership and represent critical enrichment. The JOSI is a rigorously juried journal. If you are interested in publishing in the JOSI, feel free to contact our office or visit our website. Sincerely,

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JOURNAL OF SCHOLASTIC INQUIRY: Business Fall 2018, Volume 9, Issue 1

Managing Editor Dr. Tanya Yerigan

Editor-in-Chief Dr. Dennis Lamb

EDITORIAL ADVISORY BOARD Shirley Barnes, Alabama State University Joan Berry, University of Mary Hardin-Baylor Brooke Burks, Auburn University at Montgomery Timothy Harrington, Chicago State University Michelle Beach, Southwest Minnesota State University Kenneth Goldberg, National University Linda Rae Markert, State University of New York at Oswego Lucinda Woodward, Indiana University Southeast Arina Gertseva, Washington State University Robin Davis, Claflin University

PEER REVIEWERS V. Brooks Poole Jeff McKinnon Joan Berry Rossano Gerald

Andrew Pueschel Mary Tucker Robin Davis

Ana Rosad-Feger Katherine Hartman Elsie Henderson

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TABLE OF CONTENTS

Publication Agreement and Assurance of Integrity Ethical Standards in Publishing Disclaimer of Liability Research Manuscripts

7-102

Using Class Presentations to Educate Business Students about Accreditation and Assurance of Learning Katherine B. Hartman, Ohio University Mary L. Tucker, Ohio University James M. Andzulis, Ohio University

Consideration of Information Overload in Financial Statement Note Disclosures of Canada Pre and Post IFRS Elsie Henderson, Mount Saint Vincent University Jeff McKinnon, Mount Saint Vincent University

Factors that Influence a College Student’s Choice of an Academic Major and Minor Paul A. Stock, University of Mary Hardin-Baylor Eileen M. Stock, Department of Veterans Affairs

Strategic Leadership Development through Energy Management Mary L. Tucker, Ohio University Andrew Pueschel, Ohio University Ana Rosado-Feger, Ohio University Amy Taylor-Bianco, Ohio University

Manuscript Submission Guide

103

Why Read Our Journals

105

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PUBLICATION AGREEMENT AND ASSURANCE OF INTEGRITY By submitting a manuscript for publication, authors confirm that the research and writing is their exclusive, original, and unpublished work. Upon acceptance of the manuscript for publication, authors grant the Center for Scholastic Inquiry, LLC (CSI) the sole and permanent right to publish the manuscript, at its option, in one of its academic research journals, on the CSI's website, in other germane, academic publications; and/or on an alternate hosting site or database. Authors retain copyright ownership of their research and writing for all other purposes. ETHICAL STANDARDS IN PUBLISHING The CSI insists on and meets the most distinguished benchmarks for publication of academic journals to foster the advancement of accurate scientific knowledge and to defend intellectual property rights. The CSI stipulates and expects that all practitioners and professionals submit original, unpublished manuscripts in accordance with its code of ethics and ethical principles of academic research and writing. DISCLAIMER OF LIABILITY The CSI does not endorse any of the ideas, concepts, and theories published within the JOSI: E. Furthermore, we accept no responsibility or liability for outcomes based upon implementation of the individual author’s ideas, concepts, or theories. Each manuscript is the copyrighted property of the author.

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Using Class Presentations to Educate Business Students about Accreditation and Assurance of Learning Katherine B. Hartman Ohio University Mary L. Tucker Ohio University James M. Andzulis Ohio University Abstract This research assesses a presentation designed to increase awareness among undergraduate business students about The Association to Advance Collegiate Schools of Business (AACSB) accreditation, the role of assessment in accreditation, and student benefits from assurance of learning. After the presentation, students completed a survey about students’ (1) awareness of AACSB accreditation and assurance of learning, (2) confidence in attitudes towards quality of education, (3) perceptions about claimed benefits of accreditation and assessment, and (4) behavioral intentions. Findings indicated that this presentation had a strong effect on improving or reinforcing students’ confidence in the quality of their education and curriculum. This group perceived the most important benefits of accreditation and assessment to be the perceived importance of having a competitive advantage after graduation and of earning a degree from an accredited program. Interestingly, the average importance of a competitive advantage ranked higher than the average importance of assuring learning, teaching improvements, and curriculum improvements.

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Keywords: Assurance of learning, accreditation, business students

Introduction Assessment and assurance of learning are cornerstones of the Association to Advance Collegiate Schools of Business (AACSB). AACSB provides internationally recognized, specialized accreditation for business programs that meet or exceed its 15 Standards. Standard 8 requires that, “the school uses well-documented, systematic processes for determining and revising degree program learning goals; designing, delivering, and improving degree program curricula to achieve learning goals; and demonstrating that degree program learning goals have been met” (AACSB, 2017, p 33). In order to better promote the importance of AACSB accreditation, the AACSB (n. d.) website has a section dedicated to promoting accreditation, including a suite of tools and resources to help current students understand the value of attending an AACSB-accredited school. However, the research is sparse on how AACSB accredited business schools are providing current students with information about the importance of AACSB accreditation, the role of assessment in the accreditation process, and how students benefit from the Assurance of Learning (AoL) process. Thus, one Midwestern college of business (COB) designed and launched a promotional campaign shortly before the college’s AACSB reaffirmation review to understand how such efforts are received by students, as well as what impact they have in enhancing perceptions of AACSB accreditation. This paper proceeds as follows. First, a literature review recounts extant work in the area of accreditation and assurance of learning. Next, the paper details the aforementioned

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promotional campaign, research design, measures and student samples employed in this study. Results, including mean comparison tests, and an accompanying discussion reveal insights into this accreditation initiative, including its expansion on previous research. Finally, relevant conclusions for AACSB accreditation and AoL suggest directions for future work as this research illuminates a student perception of competitive advantage related to accreditation. Literature Review The reaffirmation of accreditation bar shifted for business schools in the last decade, when AACSB moved from basing accreditation solely on faculty credentials and teacher/student ratio to also encapsulating student learning outcomes along with continuous program improvement (Abdelsamad et al., 2015; Samson & Betters-Reed, 2008; Zhu & Fleming, 2017; Zocco, 2011). During this same period, new programs and options provided more opportunities and choices for prospective business students (Bennett, Geringer & Taylor, 2015). As a result, accreditation is being marketed more by AACSB and university officials as a competitive advantage for graduates of accredited programs (Sohail & Shaikh, 2004). Stiber (2014) posits that parents and prospective students may consider accreditation when making college choices, although not as much as location, financial aid, and tuition costs (Bennett, et al., 2015; Chapman, 1981; Moogan, Baron, & Harris, 1999; and Soutar & Turner, 2002). Extant research exploring student perceptions of accreditation is sparse. Daily, Farewell, and Kumar (2010) found that AACSB accreditation was an important factor influencing university selection among international students pursuing secondary education in the United States, yet also found that international students do not fully understand the meaning of accreditation by AACSB. Likewise, Mourad and Selim (2011) found that most engineering

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students at one university were not aware of the Accreditation Board for Engineering and Technology (ABET) accreditation process and the benefits of accreditation. Mourad and Selim (2011) recommend making students more aware of accreditation by offering seminars, workshops, posters, and lectures. By comparison, Al-Khourry et al. (2014) surveyed students in Lebanon and found a high awareness of accreditation and a willingness to pay higher tuition fees if the university is internationally accredited. Shurden, Natvig, and Shurden (2009) surveyed approximately 400 business students at a public, southeastern university in the United States about their knowledge of accreditation and found that about half of students (47%) enrolled in the business program were aware that the business program had AACSB accreditation. However, less than one in five students (17%) indicated that their decision to enroll in the program was influenced by its accreditation. The study also found that 96% of students surveyed believe that graduating from an AACSB accredited business school will be beneficial to them in the future. This research demonstrates the important link between educating students as to the benefits of AACSB accreditation and their perception that such accreditation reaffirms the quality of their education, as well as the enhanced competitive advantage it delivers to them at graduation. By making the future benefits in the Shurden et al. (2009) work more tangible to students, this work helps to make the case that AACSB accreditation is one more element of differentiation students and parents should evaluate when selecting university education. The next section details the methodology employed in this research.

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Methodology Researchers in this study developed a quasi-experimental, quantitative survey-based design to capitalize on accreditation efforts at a large Midwestern university housing a wellrespected college of business. The following paragraphs first detail the opportunity, and then the research approach. The university designed a plan with the promotion objective to increase awareness among undergraduate business students about the importance of AACSB accreditation, the role of assessment in the accreditation process, and student benefits from the Assurance of Learning (AoL) process. The first planning activity enlisted student leaders in brainstorming best practices for marketing this promotion to undergraduates. A student organization consisting of junior and senior students, representing the College of Business (COB), met to learn about the proposed marketing promotion and to brainstorm promotion ideas for the project. After this initial meeting, several members of the group volunteered to complete this project and subsequently submitted a short report detailing ideas. Examples of suggestions included short presentations to classes, distribution of informational cards and brochures, social media posts about AACSB and AoL on professional business organization websites, and games with prizes that focused on accreditation knowledge. Presentation Based on the suggestions of the student group, the team planned presentations to all introduction to business classes and two student organizations. The presentation included six content slides focused on information about AACSB and its benefits to students (see Appendix A). The presentation was delivered by a trained graduate student. The intention of the research

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was to be an applied research approach to solve a specific, pragmatic problem related to students’ awareness and understanding of accreditation. Presentations also included distribution of two pieces of marketing collateral: a business card and a tri-fold brochure. The business card provided the college’s mission statement and learning goals. The outside of the tri-fold brochure (see Appendix B) included a title page and tagline, the college’s mission statement, overall learning goals, and the college’s statement about its promise to students. The inside (see Appendix C) included narratives answering three sets of questions: What is AACSB and why should I care? What is Assurance of Learning and how does the college do this? What is continuous improvement and what does it all mean? Data Collection Following the presentations and distribution of marketing collateral, students completed anonymous five-item, scale-based surveys designed to measure their awareness of AACSB accreditation and AoL, their confidence in attitudes towards the quality of education, their perceptions of the importance of benefits of accreditation, and their behavioral intentions after the presentation. The survey, which consisted of three constructs comprised of twenty-one items, including scales ranging from 1 (Not at All) to 5 (A Great Deal), is included in Appendix D. See Appendix D for the full measurement instrument. The quasi-experiment was a one-shot case study with post measures. Participants were obtained using purposive sampling and convenience sampling. For purposive sampling, participants were undergraduate students enrolled in one of two introduction to business courses at a Midwestern public university. This course is designed for underclassmen (typically first or second year students) majoring in business. Research employed a convenience sample for

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comparative purposes. Participants included undergraduate students who were members of one of two student business professional organizations. Procedures The stimulus was a 10-minute presentation about AACSB and AoL within the business college at a Midwestern university. Participants were enrolled as undergraduates majoring in business at the university. The content included information about AACSB business accreditation in general, standards for accreditation, student benefits of AACSB accreditation, AoL in general, AoL goals, the AoL process, and the benefits of AoL for students. The presentation was framed from a student perspective and delivered by a graduate student.

For

example, the presentation discussed recent changes to curriculum, based upon the results of the AoL process. After hearing the presentation, each participant completed an anonymous, selfadministered survey during class or during the student organization meeting. The survey consisted of a series of questions that measured participants’ self-reported (1) awareness of AACSB accreditation and AoL, (2) confidence in attitudes towards quality of education, (3) perceptions of the importance of benefits of accreditation and assessment, and (4) behavioral intentions after the presentation. The survey also used traditional classification scales to collect demographic information including major, class rank, gender, and GPA. Sample The total student population size for the sum of the two introduction to business courses was 310; the total population size for the sum of the two student organizations was 80. Purposive and convenience subjective sampling led to selection of the two groups of students

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surveyed in this research. After excluding two surveys with excessive missing data, the final sample was 235 participants: 168 (71.5%) students enrolled in the introduction to business courses and 67 (28.5%) members of student organizations, for response rates of 54.2% and 83.75%, respectively. All participants were undergraduate university students. Excluding missing data, the majority were female (59% vs. 41% male) and underclassmen (73.9% vs. 26.1% upperclassmen). The sample included a range of business majors including accounting (24.3%), business economics (4.7%), business pre-law (7.7%), entrepreneurship (3%), finance (24.3%), international business (4.7%), management (7.7%), management information systems (18.3%), marketing (20.0%), and other/undecided (22.1%). The distribution of majors in the sample is consistent with the distribution of majors in the undergraduate student population at the university at the time of the study. The sample was skewed towards students reporting cumulative grade point averages 3.01 or higher (80.3% vs. 19.7% reporting 3.00 or less). Most participants were unaware of AACSB Accreditation (66.4%) before the presentation. Likewise, most participants were unaware of AoL (79.2%) prior to the presentation. Measures Three global constructs were measured using multi-item, formative scales. Unlike reflective scales, formative scales assume that a construct is a function of its measures such that the construct is formed by a combination of the measurement items (Diamantopoulos & Winklhofer, 2001). As such, index construction involves construct content specification and indicator specification (Diamantopoulos & Winklhofer, 2001).

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Eight items for measuring confidence in attitudes towards quality of education were generated using the 2013 AACSB business accreditation standards (AACSB, 2013). Items utilized a five-point scale (not-at-all to a-great-deal) and included quality of faculty, curriculum, student services, faculty-student interaction, knowledge acquisition, skill development, effectiveness of teaching and learning, and innovation. Seven items for measuring perception of the importance of benefits of accreditation and assessment were generated using AACSB (n. d.) online promotion materials for students. Items utilized a five-point scale (not-important to very-important) and included AoL, improvements in teaching, curriculum, and courses, opportunities outside the classroom, earning a degree from an accredited program, and competitive advantage(s) post-graduation. Behavioral intentions were measured using six items (five-point scale: not-at-all to agreat-deal) and included motivation to learn more, make efforts on future assessments, word-ofmouth communications, and college recommendation intentions. Results/ Findings Paired sample t-tests were used to test for mean differences among the formative items within each construct. Independent sample t tests and one-way ANOVA were used to test for mean differences among demographic characteristics of the sample.

Mean Comparisons within Constructs For confidence in attitudes, the highest mean among the eight measures was quality of education: skill development (M = 4.13). The average rating for quality of education: skill development was statistically equal (not significantly different; p > 0.05) to the next three highest

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means: quality of education – knowledge acquisition (M = 4.08), quality of curriculum (M = 4.07), and course innovation (M = 4. 06). By comparison, the average ratings for all four of the items with the highest means were statistically higher (significantly different; p < 0.05) than the three lowest means. Specifically, the mean for quality of education: skill development (M = 4.13) was statistically higher than the mean for quality of student services (M = 3.73), quality of student-faculty interactions (M = 3.76), and quality of faculty (M = 3.80). As such, the results suggest the presentation had a stronger effect on improving or reinforcing students’ confidence in curriculum development and AoL, as compared to the effect on confidence in faculty and support services. Table 1 provides the results of the paired sample t-tests for confidence in attitudes. For the benefits of accreditation and AoL, the two highest means among the seven measures were the perceived importance of having a competitive advantage after graduation (M = 4.71) and the importance of earning a degree from an accredited program (M = 4.69). The results of the paired sample t tests suggest that both the highest rated items were statistically higher than the three lowest rated items (significantly different; p < 0.05). Specifically, the average importance rating for competitive advantage (M = 4.71) was higher than the average importance ratings for assuring learning (M = 4.54), teaching improvements (M = 4.56), and curriculum improvements (M = 4.58). As such, the results suggest students perceived the externally-related benefits of accreditation and AoL as somewhat more important than internallyrated benefits. However, it is also important to note that means for all items exceeded 4.50 on a five-point scale and that the largest effect sizes for mean differences (p < 0.05) were moderate-

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weak. See Table 2 for the results of the paired sample t-tests for benefits of accreditation and AoL. For behavioral intentions, there was wide range of means. The two highest means were: recommend the college to others (M = 4.04) and expend more effort on future AoL assessments (M = 3.39); the lowest means were talk about AoL with others (M = 2.85) and talk about AACSB with others (M = 2.92). Except for learning more about accreditation and learning more about AoL in the future, the results of the paired sample t-tests suggest the means for the six behavioral intention measures were significantly different. As such, the results suggest the presentation had the least effect on direct word-of-mouth communication intentions and the greatest effect on indirect word-of-mouth communication intentions. See Table 3 for the results of the paired sample t-tests for behavioral intentions. Mean Comparisons by Demographic Variables A series of independent sample t-tests suggested very few mean differences among groups for each of the formative items within each construct. For differences between class rank groups, the only difference between groups for the 21 items was the perceived importance of having a competitive advantage after graduation. Specifically, upperclassmen (M = 4.79, SD = 0.51) on average rated this item higher than underclassmen (M = 4.49, SD = 0.85), t (75.73) = 2.60, p < 0.05. As expected, differences between students who listened to the presentation during class rated the perceived importance of having a competitive advantage after graduation lower than students who listened to the presentation during a student organization meeting, p < 0.05. The results of independent sample t-tests for gender found no significant differences

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between gender groups for any of the 21 items. Likewise, the results of a one-way ANOVA test for GPA groups found no significant differences among GPA groups for any of the 21 items. Discussion Most of the business students in this study knew nothing about AACSB Accreditation (66.4%) before the presentation. These findings are supported by Gennett et al. (2015), who indicated that “students in fact hold a positive perception of accreditation, although they possess limited knowledge and awareness of specialized business school accreditation” (2015, p. 78). Similarly, prior to the presentation, most students in the current study (79. 2%) were unaware of AoL. For these students, the presentation had a strong effect on improving or reinforcing their confidence in the quality of their education and curriculum. One possibility is that the highest means were for items that were about student confidence in the outcomes of the educational experience. Because students may be less confident in their ability to successfully assess the quality of the outcomes of their educational experience until after graduation, they may value AACSB accreditation and AoL as a quality check through which external experts review, approve, and validate the quality of their educational experience. By comparison, the lowest means were related to factors associated with the educational experience process (e.g., faculty, faculty-student interactions, student services), which students may feel more comfortable assessing through personal experience throughout the program, rather than relying on expert judgment. All seven items measuring the importance of the benefits of accreditation and assessment had extremely high means (>4.50). However, two items had statistically higher means than the

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other five. This group perceived the most important benefits of accreditation and assessment to be the perceived importance of having a competitive advantage after graduation and of earning a degree from an accredited program. Interestingly, the average importance of a competitive advantage ranked higher than the average importance of assuring learning, teaching improvements, and curriculum improvements. Like the pattern of means for confidence in attitudes, these students emphasized the benefit of external validation of the quality of their degree as compared to benefits associated with the educational experience (e. g., opportunities, courses, curriculum, teaching, and learning). Thus, students believed the externally related benefits of accreditation and AoL to be more important than internally related benefits. This trend was more pronounced with students closer to graduation and students hearing the presentation in a professional organization meeting. For these students, the results suggest that the presentation had a far lesser impact on intended behavioral change. Although students were more motivated to recommend the college to others, the presentation only moderately motivated them to try harder on assessments, learn more about AACSB, and learn more about AoL. The results indicate that students were even less likely to talk about either AACSB or AoL with others. Thus, the results suggest that changes in attitudes do not easily translate into changes in behavior. Although the results of this study cannot be generalized across the global business undergraduate population, it can be used as an indicator that sharing accreditation and AoL information with students attending AACSB institutions is beneficial. Further replication of this study across business schools could provide both validation and extension of study results. Equally important would be research studies designed to identify ways to elevate student

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perceptions of the importance attached to assuring learning, enhancing teaching improvements, and designing curriculum improvements, as each pertains to closing the loop in assessment and AoL. Illuminating this gap between theory and practice, and student understanding, will ensure that the future of student success and university accreditation efforts is most bright. Conclusion Marketing the benefits of AACSB Accreditation and AoL to business students may have a strong effect on improving or reinforcing confidence in the quality of their education and curriculum (Sohail & Shaikh, 2004). In fact, the group of undergraduate business students in this research perceived the most important benefits of accreditation and assessment to be the perceived importance of having a competitive advantage after graduation and of earning a degree from an accredited program. Interestingly, the average importance of a competitive advantage ranked higher that the average importance of assuring learning, teaching improvements, and curriculum improvements. Thus, this research demonstrates the important link between educating students as to the benefits of AACSB accreditation and their perception that such accreditation reaffirms the quality of their education, as well as the enhanced competitive advantage it delivers to them at graduation. By making the future benefits in the Shurden et al. (2009) work more tangible to students, this work helps to make the case that AACSB accreditation is one more element of differentiation that students and parents should evaluate when selecting university education. Future research findings may validate these findings as researchers seek ways to enhance the perceived importance of assuring learning through continuous improvements in teaching and curriculum.

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Author Biographies Katie Hartman (Ph.D., Indiana University) is an Associate Professor and Chair of the Marketing Department in the College of Business at Ohio University. She teaches marketing strategy, marketing research, and consumer behavior. Her teaching and learning research interests include assessment, accreditation, problem-based learning, general education, and intercultural competency. Mary L. Tucker is a Professor of Management at Ohio University. Her PhD was granted by the University of New Orleans; her dissertation research focused on Transformational Leadership. Current research interests include leadership, management pedagogy, and assessing learning. She has provided leadership training for both private and public-sector organizations, including the American Association of Highway Transportation Officials, 3M, and State Farm. James “Mick” Andzulis is an Assistant Professor of Marketing at Ohio University. Mick completed his PhD at University of Alabama and currently teaches foundations of professional sales and sales strategy & technology as Director of Academics with The Ralph and Luci Schey Sales Centre at Ohio University. His research interests include strategy, sales, and technology. References AACSB (2017). Business accreditation standards. Retrieved from: www.aacsb. edu/accreditation/standards AACSB (n. d.). Promoting your accreditation. Retrieved from: www.aacsb. edu/accreditation/resources/promotion Abdelsamad, M., Farmer, B., McNeil, R., & Stevens, G. (2015). Major changes to AACSB standards (2003 compared to 2013). Advanced Management Journal, 80(3), 4-11.

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Al-Khourry, P., Kotob, M., Fares, A. E. K., Eido, M., & Ghandour, M. (2014). Lebanese students’ awareness regarding accreditation in higher education institutions. Business Education & Accreditation, 6(1), 23-32. Bennett, P. J., Geringer, S. D., & Taylor, J. (2015). The effect of accreditation on the university selection of undergraduate business majors: An empirical study. International Journal of Education Research, 10(1), online. Daily, C. M., Farewell, S., & Kumar, G. (2010). Factors influencing the university selection of international students. Academy of Educational Leadership Journal, 14(3), 59-75. Diamantopoulos, A., & Winklhofer, H. M. (2001). Index construction with formative indicators: An alternative to scale development. Journal of Marketing Research, 38(2), 269-277. Mourad, A-H I., & Selim, M.Y. E. (2011). On the awareness of UAE university engineering students with ABET accreditation. Journal of Education Research, 4(2), 113-128. Shurden, S. B., Natvig, D., & Shurden, M. (2009). The pros and cons of accreditation: faculty and student perceptions. 2009 Southeastern INfORMS Conference Proceedings, 122-130. Sohail, M. S., & Shaikh, N. M. (2004). Quest for excellence in business education: A study of student impressions of service quality. The International Journal of Educational Management, 18(1), 58-65. Stiber, G. (2001). Characterizing the decision process leading to enrollment in Master’s programs: Further application of the enrollment process model. Journal of Marketing for Higher Education, 11(2), 91-107. Zocco, D. (2011). A recursive process model for AACSB assurance of learning. Academy of Educational Leadership Journal, 15(4), 67-91.

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Tables & Figures Table 1: Paired Sample t-tests for Confidence in Attitudes Item 1 Quality of education: skill development

Item 2

4.13 0.83 Quality of education: knowledge acquisition Quality of curriculum Innovation in courses Effectiveness of teaching and learning Quality of faculty Quality of student services Quality of facultystudent interactions *P < 0.05

4.08

0.83

1.42 234

4.07 4.06 4.00

0.84 0.93 0.86

1.51 233 0.10 1.49 234 0.10 3.27 234 0.21*

3.80 3.73

0.93 0.93

6.31 234 0.41* 6.95 233 0.45*

3.76

1.01

8.21 231 0.54*

0.09

Table 2: Paired Sample t-tests for Benefits of Accreditation and Assurance of Learning Item 1 Competitive advantage after graduation

M SD Item 2 4.71 0.63 Earning a degree from an accredited program Better opportunities outside the classroom Improvements in courses Improvements in the curriculum Improvements in teaching Assuring students are achieving learning goals *P < 0.05

M 4.69

SD 0.61

T df 0.85 234

d 0.06

4.63

0.65

2.15 234 0.14*

4.62

0.61

2.52 234 0.16*

4.58

0.62

3.45 234 0.23*

4.56

0.67

4.15 234 0.27*

4.54

0.65

4.43 234 0.29*

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Table 3: Paired Sample t-tests for Behavioral Intentions Item 1 Recommend the College to others

M SD Item 2 4.04 1.07 Try harder on AoL Assessments Learn more about Assurance of Learning Learn more about AACSB Talk about AACSB with others Talk about AoL with others *P < 0.05

M 3.39

SD 1.18

T df d 8.62 233 0.56*

3.09

1.18

11.31 233 0.74*

3.05

1.18

12.01 232 0.79*

2.92

1.20

12.74 232 0.83*

2.85

1.07

13.48 233 0.88*

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Appendix A: PowerPoint Presentation

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APPENDIX B: TRI-FOLD BROCHURE INFORMATION (OUTSIDE)

AACSB Accreditation & Assurance of Learning: Ensuring Your Competitive Advantage College of Business (COB) Learning Goals 

Acquire (Knowledge). Our graduates will have knowledge of current business practices and theory.



Integrate (Critical Thinking). Our graduates will apply a holistic, integrated approach to framing and solving business problems.



Demonstrate (Professional Skills). Our graduates will have professional skills and competencies.

College of Business Mission Statement The College of Business provides a distinctive learning environment that actively engages students, faculty, and the business community in developing knowledge and skills relevant for success in a complex, global economy. This environment stimulates student learning and faculty research so that graduates are able to:  Apply a holistic, integrated approach to business problems;  Apply the communication, leadership and technological skills necessary to success;  Understand how to work with diverse populations; and  Understand the social responsibilities and ethics regarding business of individuals. A Transformative Business Education The College of Business is committed to assuring that our graduates acquire business knowledge, apply critical thinking skills, and demonstrate professional abilities relevant to success in a complex, global economy.

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Appendix C: Tri-Fold Brochure Information (Inside)

AACSB Accreditation & Assurance of Learning: Ensuring Your Competitive Advantage

WHAT IS AACSB? Accreditation by the Association to Advance Collegiate Schools of Business (AACSB) is the international seal of approval for business and accounting programs that insures the educational needs of students are met through high quality, continuous improvement and excellence in education. To be an AACBS-accredited, business programs must pass very rigorous quality standards. Less than 5% of the world's 13,000 business programs have earned AACSB Accreditation.

WHY SHOULD I CARE? College is a big investment of money and time. As a student, you want a return on your investment. AACSB standards ensure continuous improvement of curriculum, quality student-faculty interactions, and teaching. As a student in a program with AACSB accreditation, you will have an education that provides the knowledge and skills for success.

Graduates from AACSB-accredited programs have more employers interested in them and receive higher, more competitive salaries than graduates from similar programs without AACSB accreditation.

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WHAT IS ASSURANCE OF LEARNING? Assurance of Learning (AoL) is exactly what it sounds like; it is the assurance of the students learning. The College of Business monitors the extent to which students are able to demonstrate:  Knowledge in accounting, operations management, marketing, management, finance, and business law;  Critical Thinking Skills necessary to analyze business situations quantitatively, conduct industry analyses, make information system recommendations, design digital products, and analyze companies; and  Professional Competencies including skills in effective team work, written communication, and oral communication.

HOW DOES THE COLLEGE OF BUSINESS (COB) DO THIS? Through testing, rubrics, and assignments, a team of faculty identifies strengths and weaknesses in students’ knowledge and skills. The College of Business improves the curriculum and the student learning experience using the results. The cycle of measurement and continuous improvement assures that College of Business students are acquiring knowledge and developing skills necessary for success.

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WHAT IS CONTINUOUS IMPROVEMENT? AACSB Accreditation requires continuous improvement from the College of Business; we are proud to successfully meet in this challenge. Year after year, the College of Business improves:  Innovations in teaching and research;  Quality of faculty and students;  Curriculum content and management;  Student-faculty interactions;  Teaching effectiveness; and  Career resources for students.

WHAT DOES IT ALL MEAN? The College of Business is committed to continuously improving students’ learning experience in order to better insure that students are achieving learning goals. In the past few years, examples include:  Improvements to the content of all core courses in the College of Business;  Improvements to the content, structure, and delivery of the Integrated Business Cluster;  New courses including Introduction to Business and Business Analytics; and  New requirements including an internship experience.

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APPENDIX D: MEASUREMENT INSTRUMENT Did you know about AACSB Accreditation before the presentation?

Yes

Did you know about Assurance of Learning before the presentation?

Yes

1) How much did the information in this presentation improve or reinforce your confidence in the following aspects of the College of Business? Not at Only a Somewhat All Little a. Quality of faculty 1 2 3 b. Quality of curriculum 1 2 3 c. Quality of student services 1 2 3 d. Quality of faculty-student interactions 1 2 3 e. Quality of education: knowledge acquisition 1 2 3 f. Quality of education: skill development 1 2 3 g. Effectiveness of teaching and learning 1 2 3 h. Innovation in courses 1 2 3 2) How important are the benefits of accreditation and assessment to you as a student? Not Somewhat Important Unimportant Neither a. Assuring students are achieving 1 2 3 learning goals b. Improvements in teaching 1 2 3 c. Improvements in the curriculum 1 2 3 d. Improvements in courses 1 2 3 e. Better opportunities outside the 1 2 3 classroom f. Earning a degree from an accredited 1 2 3 program g. Competitive advantage(s) after 1 2 3 graduation 3) How much did the information in this presentation encourage you to do the following? Not at Only a Somewhat All Little a. Learn more about AACSB 1 2 3 b. Learn more about Assurance of Learning (AoL) 1 2 3 c. Try harder on AoL Assessments 1 2 3 d. Talk about AACSB with others 1 2 3 e. Talk about AoL with others 1 2 3 f. Recommend OU-CoB to others 1 2 3

Moderately 4 4 4 4 4 4 4 4

A Great Deal 5 5 5 5 5 5 5 5

Somewhat Important 4

Very Important 5

4 4 4 4

5 5 5 5

Moderately 4 4 4 4 4 4

A Great Deal 5 5 5 5 5 5

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Consideration of Information Overload in Financial Statement Note Disclosures of Canada Pre and Post IFRS Elsie Henderson Mount Saint Vincent University Jeff McKinnon Mount Saint Vincent University Abstract The length of financial statement note disclosures has increased significantly over time leading to concerns there is information overload in the notes (Morunga & Bradbury, 2012; Radin, 2007). While more information is indicative of transparency, the value of the information may be lost if users are not processing the information whether for lack of time, understanding, or complexity of the information (Jackson & Farzaneh, 2012). There is evidence that financial statement note disclosures further increased with the adoption of International Financial Reporting Standards (IFRS) (Morunga & Bradbury, 2012). The researchers examined whether the IFRS adoption in Canada has resulted in increased disclosures, thus contributing to information overload. A sample of public companies was selected for pre-IFRS and post-IFRS. Results indicate that, overall, there was a 36% increase in financial statement note disclosures pre-IFRS and post-IFRS. Results were significant. When considering specific notes, accounting policies notes showed a significant increase pre-IFRS and post-IFRS.

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Keywords: Financial statement note disclosure, information overload, IFRS, disclosures Introduction The purpose of financial statement note disclosure is to provide additional information relevant to decision making. However, the length of financial statement note disclosures has continuously been increasing and there is now concern that there is information overload in the notes (Mourunga & Bradbury, 2012; Radin, 2007). Information overload is a state in which the reader cannot process the information because of the volume, complexity, quality, or relevance (Jackson & Farzaneh, 2012; Morunga & Bradbury, 2012; Paredes, 2003). Moreover, the amount of financial statement note disclosures have resulted in the usefulness of the information being questioned (Bloomfield, 2012; Lawrence, 2013; Morunga & Bradbury, 2012). While more information is indicative of transparency, the value of the information may be lost if users are not processing the information for lack of time or understanding, or because of information volume or complexity (Holton & Chiyi, 2013; Jackson & Farzaneh, 2012). There is evidence that financial statement note disclosures further increased with the adoption of International Financial Reporting Standards (IFRS) (Brown & Tarca, 2012; Morunga & Bradbury, 2012). While more information may be considered ideal, additional information has no value if it is not processed because users experience information overload. The objective of this paper is twofold: first to add emphasis to the theory of information overload as it relates to financial statement note disclosures in Canada and second, to provide empirical evidence to standard setters on the increase of financial statement note disclosures with the adoption of IFRS in Canada. The research will inform standard setters as they continue to assess

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disclosure requirements and will collaborate prior research that reported increased disclosures with the adoption of IFRS. To meet the first objective, a discussion of the theory of information overload is developed and then considered within financial statement note disclosures. This is followed by the empirical analysis for the second objective. Financial statement note disclosures pre-IFRS, and post-IFRS are analyzed for a large sample of Canadian publicly traded companies. Analysis was performed by total length of all financial statement note disclosures and by individual note disclosure length. The results show the increase in financial statement note disclosure with the adoption of IFRS in Canada is statistically significant at p < .001. Specific notes identified as contributing most to the situation are accounting policies notes. The next section of the paper provides a discussion of the literature on information overload and financial reporting including financial statement note disclosures. This is followed by a section on the methodology supporting the empirical evidence and a discussion of the results. Literature Review It has long been touted that markets are more efficient if all players have all relevant information (Alzarouni, Aljifri, Ng, & Tahir, 2011; Avgouleas, 2009; Kieso et al., 2016). This is the foundation of the efficient market hypothesis (EMH) and one that promotes transparency and comparability of information enabling informed decision-making (Alzarouni et al., 2011; Brown & Tarca, 2012). Disclosure has been used as a regulatory tool to protect investors through ensuring the disclosure of all relevant information (Barker et al., 2013; Peredes, 2003). As a result, disclosure requirements have continued to increase. This is problematic, since

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information overload can occur when there is too much information for the reader to process (Edmunds & Morris, 2000; Eppler & Mengis, 2004; Peredes, 2003). Theory of Information Overload While the EMH promotes disclosure of all relevant information for decision-making, the theory of information overload states that there is a point at which the reader cannot process the information because the reader is overloaded (Eppler & Mengis, 2004; Jackson & Farzaneh, 2012). Eppler and Mengis (2004), in their literature review of information overload, indicated the effectiveness of decision-making began to decline at a point when the user of the information became overloaded. This is shown in Figure 1, a depiction of the inverted U-curve based on the earlier work of Schroeder, Driver and Streufert (1967). Figure 1. Information overload as the inverted U- curve taken from Eppler and Mengis, (2004).

Information overload is a complex topic. An underlying concept of the Theory of information overload is the amount of information exceeds the individuals processing capabilities (Chia-Ying, 2016; Eppler & Mengis, 2004; Morunga & Bradbury, 2012). Other researchers have described information overload as the point where one cannot effectively use the information because the information is excessive (Feather, 1998) or when useful information is no longer helpful (Bawden, Holthan, & Courtney, 1999). Although this paper focuses on the amount or volume of information, other factors that can lead to overload are ambiguity,

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complexity, readability, or lack of relevance of the information (Jackson & Farzaneh, 2012). The significant concern of information overload is, if the information is not processed, relevant or important, information for decision-making can be missed. There is a great deal of literature on information overload across disciplines. Holton and Chyi, (2012) discussed communications managers concern of information overload for consumers, while Blummer and Kenton (2014) presented best practices for libraries to reduce information overload for users, as examples. There is specific research on information overload related to financial reporting requirements in annual reports or to the Securities Exchange, often referred to as disclosure overload (Iannaconi & Sinnett, 2011; Morunga & Bradbury, 2012; Radin, 2007) as examples. Casey (1980) used bankruptcy predictors and assessed the accuracy of the results as the amount of information increased. The research showed the decision efficiency decreased as the information increased. There is little empirical evidence of information on disclosure overload exclusively on financial statement note disclosures and none in Canada. This research fills that void. Disclosure Overload Much of the literature on disclosure overload in financial reporting relates to the securities commissions filings and annual reports (Carbone & Sean, 2014; Iannaconi, 2012; Iannaconi & Sinnett, 2011; Morunga & Bradbury, 2012; Radin, 2007). Iannaconi and Sinnett (2011) sent surveys to 6500 financial executives regarding disclosures in annual reports and reported an increase of 28% over a six-year period. Morunga and Bradbury (2012) studied annual reports after companies had adopted International Financial Reporting Standards (IFRS) in New Zealand and found an increase in annual report size of 29%. However, both Iannaconi

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and Sinnett (2011) and Morunga and Bradbury (2012) indicated the increase in the annual reports was largely due to the increase in the financial statement note disclosures. The theory of information overload can be applied to financial statement note disclosures. Over time, the amount of financial statement note disclosures has continued to increase. Concerns have been expressed about the amount of information and overload (Innaconi, 2012; Radin, 2007) yet, there is limited data available on information overload in regards to financial statements note disclosures. As stated, Morunga and Bradbury (2012) performed research on annual reports in Australia and New Zealand and found that information overload was indeed present in these reports. Further, the researchers reported the length of the annual report increased significantly with the adoption of IFRS, with most of the increase attributed to financial statement note disclosure. Henderson (2016) performed a qualitative study where one question asked of some interviewees was whether they felt there was information overload in financial statement note disclosures. These participants indicated there was information overload. Although not empirical, Iannaconi (2012) and Radin (2007) indicated there was anecdotal evidence of information overload in financial statement note disclosures (Iannaconi, 2012; Radin, 2007). Financial Statement Note Disclosures From a practical perspective, financial statement note disclosures are required to provide additional, relevant information to the users of financial statements. The accounting standards, such as IFRS, do have mandatory disclosures: accounting policies, financial instruments, and share capital, as examples. Even these mandatory disclosures can lead to information overload. Brown and Tarca (2012) indicated mandatory disclosure may add complexity and clutter to the

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disclosures. Barker et al. (2013) stated overload can occur with mandatory disclosures alone. A condition of overload is contrary to the financial statement note disclosure objective of providing additional relevant and useful information. There are several possible explanations for the increase in disclosure. The first, mandatory disclosures which focus on standard setting has been identified. A second explanation focuses on the preparer. Although professional judgment is used by the preparer in presenting financial statement note disclosures, there have been criticisms of more disclosure being used as protection of the preparer rather than the information needs of the user (Bloomfield, 2012; Iannaconi & Sinnett, 2011; Radin, 2007). Further, it has indicated that countries using IFRS have noted an increase in note disclosure requirements with the adoption of IFRS (Barker et al. 2013; Iannaconi & Sinnett, 2011; Morunga & Bradbury, 2012). A third explanation may be the disclosure of irrelevant information (Bloomfield, 2012). The notes are to provide relevant and useful information. If irrelevant information is being disclosed, it needlessly adds to the volume and increase of note disclosures and contributes to potential information overload. This is concerning because important information may not be processed if users are overloaded as was the case with the failure of Enron, 2000 (Iannaconi, 2012; Radin, 2007) or the 2008 financial crisis (Avgouleas, 2009). IFRS IFRS became a requirement of public companies in Canada beginning in January, 2011. Prior to IFRS, Canada used Canadian standards. The primary objective of IFRS is to have one set of global standards that results in enhanced reliability and comparability across markets

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(Kieso et al., 2016). Currently, more than 140 jurisdictions worldwide require IFRS for domestic public companies (IFRS, 2018). Research has shown the quality of information has improved with the adoption of IFRS (Epstein, 2009; Latridis, 2010; Roudaki, 2012). However, the increased length of financial statements (specifically note disclosures) has been identified as a negative aspect of IFRS (Bloomfield, 2012; Morunga & Bradbury, 2012). A concern is the increase in information may result in information overload – a condition caused by amount, complexity, or relevance of the information (Blummer & Kenton, 2014; Jackson & Farzaneh, 2012). Since IFRS seeks to provide information useful for decision-making if the end result is too much information, then the added information may be lost to the reader. Financial statements have continued to increase in size, with some statements now being greater than 75 pages in length, largely due to the notes. Pounder (2012), Bloomfield (2012), and Radin (2007) suggested more emphasis should be placed on effective disclosure as standard setters and preparers aim to meet the objective of providing useful and relevant information. A coined phrase “less is more” was applied to the SEC’s (Security & Exchange Commission) disclosure requirements (Carbone & Seem, 2014). The researchers referred to information overload of the investing public and the need to reduce the abundance of information to add value to the user. Bloomfield (2012) criticized existing disclosure requirements for encouraging disclosure of anything relevant, rather than disclosure of value-added information. Although Bloomfield (2012) was speaking more to 10-k disclosures, this same concept can be applied to the professional judgment used in financial statement note disclosures.

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Standard Setters The amount of disclosure has been receiving attention from standard setters as well. In 2011, The Institute of Chartered Accountants of Scotland and the New Zealand Institute of Chartered Accountants published a document titled “Losing the excess baggage-reducing disclosures to what’s important”. Also, Iannaconi and Sinnett (2011) issued a report “Disclosure overload and complexity: hidden in plain sight”. The report indicated that the disclosures had become so excessive, the value of the disclosures was limited. Standard setters have been working on a disclosure framework both for Financial Accounting Standards Board (FASB) in the United States (Herz, 2012) and for IFRS (IFRS, 2018). Hypotheses Development The discussion of information overload as it relates specifically to financial statement note disclosures is limited, with a few comments coming from studies of annual reports (Iannaconi & Sinnett, 2011; Morunga & Bradbury, 2012). There are other studies that consider overall corporate disclosures (Barker et al. 2013; Bloomfield, 2012; Iannaconi, 2012). The study performed by Morunga and Bradbury (2012) reviewed annual reports, although this study did identify the largest increase within annual reports was in financial statement note disclosures. As far as the researchers are aware, there are no empirical studies in Canada related to financial statement length and disclosure or information overload. This research will expand the literature on disclosure or information overload in financial reporting to Canada and further inform standard setters as they develop a disclosure framework. An increase in information can lead to information overload and inefficient decision-making (Jackson & Farzaneh, 2012; Morunga & Bradbury, 2012). It follows that a significant increase

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in the length of financial statements from increased note disclosures under IFRS potentially results in less efficient decision making. Given there is little research on financial statement note disclosures and excess information can lead to information overload and inefficient decision making, we developed the following hypothesis: H1: The adoption of IFRS in Canada has resulted in a significant increase in the amount of financial statement note disclosures, thus contributing to information overload and less efficient decision-making. Financial statement note disclosures are a required element of financial statements, including common note disclosures, such as the basis of accounting, accounting policies, deferred income tax, financial instruments, related party transactions, and subsequent events, for example. The researchers are aware of just one study (Morunga & Bradbury, 2012) that analyzes the increase in some specific financial statement note disclosures with the adoption of IFRS. While it is useful to understand the impact of IFRS on financial statement note disclosures, it would also be informative to identify whether there are specific notes that are contributing to increases in financial statement note disclosures. Therefore, we developed the following hypothesis: H2: There are specific areas of note disclosures that contribute to the significant increase in financial statement note disclosures and potential information overload. Methodology Financial statements of Canadian public companies for the year prior (PRE) to adopting IFRS, the conversion (CONV) to IFRS year (years beginning on or after January 1, 2011), and the year following (POST), the adoption of IFRS were used in this study. A listing of all public

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companies was obtained from Sedar.com, with a random sample of 200 companies chosen from this list. The public financial statements for the sample were available on the company’s website and/or through Sedar.com. In the event that a company had ceased operations or did not publish pre, conversion or post-IFRS financial statements during the three-year time period being observed, the next company on the list was chosen as the sample company. The financial statement note disclosures for each sample company were reviewed for the pre-IFRS year, the conversion year and the post-IFRS year in total and by each type of note for the length of the disclosure. Number of pages were used rather than word count because some data is presented in numeric tables rather than text. Length was assessed in increments of 10% of a page. Total pages were reduced for the amount of blank spaces between notes. A limitation of the study identified by the researchers is companies may use a different font size for the financial statements. The researchers used a standard of 44 lines per page, header omitted. Differences from font size may occur from company to company but are expected to be consistent within companies for the years examined. These differences would be relative to each year of the financial statements and as such, were not identified by the researchers as an issue. Therefore, any differences between companies were assumed to be insignificant to the overall results. Each researcher assessed 30 of the companies in the sample. A research assistant was then trained in the process. The research assistant reviewed completed samples and then gathered the information for the remaining 120 sample items. Prior to data analysis, the researchers each tested 10 samples of the research assistant’s work to ensure validity and consistency of the information.

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Results Total Pages Excel and SPSS were used to analyze the data, which was grouped as Pre and Post for analysis. First, descriptive statistics were analyzed in SPSS for the 200 cases of each group as shown in Table 1. This study focused on the change pre to post. Additional disclosure was required in the conversion year, which would distort the results from the normal required disclosures once IFRS was incorporated. The data were tested for homogeneity of variance. Visual inspections of histograms for pre and post showed data had a positive skew. The values for skewness and kurtosis between 1.96 and +1.96 were considered acceptable, in order to prove normal univariate distribution (Field, 2009). Skewness for pre and post were all less than 1.96; however, kurtosis and standard error were 4.119 and .342 and 3.448 and .342 respectively, indicating a pointy and heavy-tailed distribution (Field, 2009): an indication that there was a problem with the normality of distribution assumption. Because z scores are not valid for sample sizes of 200 or more, z scores were not considered (Field, 2009). To address the issue with the normality of distribution, all outliers were removed from the data and normality was tested on the new data. The results for skewness and kurtosis were all below 1.96 for pre and post. It was concluded tests assuming normality of distribution were appropriate. The adoption of IFRS in Canada was a significant event in the financial reporting environment. As with any significant event, standards require an increased amount of additional disclosure in the year of change. The increase from the pre to conv years or conv to post is not

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indicative of the amounts that normalize after the initial year (pre to post). Since pre and post are the primary indicators, we focus on these results. T-tests were used to analyze Pre to Post. First, the F score was assessed. The results are shown in Table 2. The data indicates the assumption of equality of variances is appropriate for our primary event pre to post, thus providing further support for the homogeneity assumption as it applies to this study’s focus of pre to post. Pre to post. A percentage change calculation from pre to post suggested a 36% increase in financial statement note disclosures with IFRS. On average, the total amount of financial statement note disclosure was significantly higher post IFRS (M= 22.8690, SE = 0.75137) than pre IFRS (M= 16.8223, SE = 0.61912, t (199) = -6.211, p <.001, r = .62. The effect size of .62 is between medium and strong indicating the average amount of financial statement note disclosure in the post-IFRS sample is .62 standard deviations above the average amount of note disclosures in the pre-sample. With a Cohen’s d of 0.62, approximately 73% of the post-IFRS financial statement note disclosures will be above the mean of the pre IFRS financial statement note disclosures (Magnusson, 2014). Thus, there is empirical evidence to support H1 the amount of financial statement note disclosure has significantly increased with the adoption of IFRS in Canada when considering pre-IFRS and post IFRS years. Further, based on the theory and evidence to date on financial statement note disclosures, the increase would potentially contribute to information overload and negatively affect decision-making. Specific Notes The increase in the number of pages was analyzed by type of note. Three notes were selected based on the percentage of total pages of the notes: accounting policies, financial

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instruments, and share capital. Overall, the amount of accounting policies notes increased by 7%, whereas the financial instrument notes decreased by approximately 2% and the share capital note decreased by approximately 4.5% (see Table 3). Accounting policies, financial instruments, and share capital notes, on average, are 48% of the total notes. Further analysis was performed on the accounting policies notes. Correlation tests were performed to explore the degree of correlation between accounting policies and total pages of notes. Based on the results, the amount of accounting policies is strongly related to the total pages of note disclosures, r = .825, p < .01. On average, the total amount of accounting policies note disclosure was significantly higher post-IFRS (M= 6.9838, SE = 0.21565) than pre-IFRS (M= 3.9413, SE = 0.12843, t (199) = -12.122, p <.01, r = .65. Thus, there is evidence to support H2, there are specific areas of note disclosures that significantly impact the amount of financial statement note disclosures. Accounting policies note disclosure is identified as significant. Table 4 provides a summary of the changes in financial statement note disclosures pre and postIFRS. Other Findings While the focus of this paper has been on increases of financial statement note disclosures with the adoption of IFRS, it should be noted that the researchers did identify some decreases in note disclosures. The largest decrease was in share capital at 4.6% followed by financial instruments at 2% and capital management at 1%. All other decreases were less than 1%: tax expense, investment property, contingent liabilities, and subsequent events, as examples.

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There was a wide range of total pages in financial statement note disclosures. The largest total pages post-IFRS was 67.4 for a consumer products company, after considering blank space. The lowest total pages post-IFRS was 6.3 for a real estate project, after considering blank space. Discussion The primary focus of this study was to examine the impact of IFRS on the length of financial statement note disclosure in Canada and consideration of potential information overload resulting in inefficient decision-making. The researchers found there was a significant increase in financial statement note disclosure with the adoption of IFRS. Financial statement note disclosures were examined for the year before adoption and the year post adoption. Using the theory of information overload and practical concerns of those in the field there is support for information overload in financial statement note disclosures. It would be interesting to look at these companies five years later to determine if there is a change since the post-adoption year. Also, since standard setters are focusing on disclosure communications, a later study would determine whether there is any change since the disclosure initiative. Also, it may be of interest to consider the industry when looking at the amount of note disclosure, which this study did not do. It would be interesting to consider whether specific industries drove the significant increase in note disclosures. The study’s results were similar to the findings of another study based out of New Zealand. As in the Morunga and Bradbury (2012) study, there was a significant increase in financial statement note disclosures with the adoption of IFRS. The 36% increase in financial statement note disclosures in this study is similar to the 29% increase in the financial statement notes within the annual reports in the Morunga & Bradbury (2012) New Zealand study. In this

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study, 12% of the sample showed a decrease in the amount of financial statement note disclosure post-IFRS whereas in the New Zealand study 8% had a decrease in the annual report. The decrease in this study for the total pages of note disclosures ranged 0.1 to 12.45 pages. It would be interesting to investigate whether there were specific changes within the company that resulted in the higher decreases. The largest area of increase in note disclosures was in the accounting policies note disclosure. This note made up approximately 30% of all note disclosures and potentially could be an area contributing to overload. More research into accounting policy disclosure would add to the literature on financial statement note disclosures and would inform standard setters and preparers as they focus on the disclosure framework. Implications The first finding of this study was that the notes to financial statements had increased significantly in Canada with the adoption of IFRS. This finding corroborates a New Zealand study by Morunga and Bradbury (2012) related to the adoption of IFRS in New Zealand. Based on the theory of information overload, an implication of the finding is there is potential overload in financial statement note disclosures, which then reduces the efficiency of decision-making based on these notes. While disclosures are important and very necessary, consideration should be given to whether changes can be made to existing disclosure requirements. The finding also further informs standard setters as they engage in the disclosure initiative. A second finding of the study was that accounting policy notes are the area that increased most and thus added to the load. Accounting policy notes have been identified as not being used

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by users in Henderson (2016). The implications of this finding are the accounting policy notes may not be adding value as was intended. Future Research Future research needs to consider whether the increase in information in financial statement note disclosure is leading to better decision-making or whether the information is being used. There is an opportunity for primary research in this area. This research is important as it would inform standard setters by providing information on useful information. A study of the accounting policy notes should be performed to identify key changes that would add value to the note. Author Biographies Dr. Elsie Henderson is a faculty member in accounting at the Department of Business & Tourism, Mount Saint Vincent University where she teaches Intermediate Accounting, Auditing, and Advanced Accounting. She is a professional accountant, CPA, CA, and is motivated to assist students pursuing a career in accounting. She earned her Ph.D. in 2016. Her areas of research interests are ethics, particularly in accounting, and financial statement note disclosures. Contact information: (elsie.henderson@msvu.ca) Jeff McKinnon is a faculty member in accounting at the Department of Business & Tourism, Mount Saint Vincent University. Jeff has his MBA, is a professional accountant, CPA, CMA, and is currently beginning his doctoral studies. He regularly teaches Introductory Accounting, Intermediate Accounting, and Cost Accounting. Jeff is interested in new business ventures and cost of capital.

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References Alzarouni, A., Aljifri, K., Ng, C. & Tahir, M. (2011). The usefulness of corporate financial reports: Evidence from the United Arab Emirates. Accounting & Taxation, 3(2), 17-37. Retrieved from http://www.theibfr.com/ARCHIVE/AT-V3N2-2011.pdf Avgouleas, E. (2009). The global financial crisis and the disclosure paradigm in European financial regulation: The case for reform. European Company and Financial Law Review, 6(4), 440-475. doi: 10.1515/ECFR 2009.440 Barker, R., Barone, E., Birt, J., Gaeremynck, A. McGeachin, A. Marrton, J. & Moldovan, R. (2013). Response to the EAA FRSC to the EFRAG/ANC/FRC discussion paper: Towards a disclosure framework for the notes. Accounting in Europe, 10(2), 1-26. doi: 10.1080/17449480.2013.772715 Bawden, D., C. Holtham, C., & Courtney, N. (1999). Perspectives on information overload. Aslib Proceedings, 51(8), pp. 249-255. doi: 10.1108/EU0000000006984 Bloomfield, R. (2012). A pragmatic approach to more efficient corporate disclosure. Accounting Horizons, 26(2), 357-370. doi: 10.2308/acch-10261 Blummer, B., & Kenton, J. (2014). Reducing patron information overload in academic libraries. College & Undergraduate Libraries, 21, 115-135. doi: 10.1080/10691316.2014.906786 Brown, T., & Tarca, A. (2012). Ten years of IFRS: Practitioners’ comments and suggestions for research. Australian Accounting Review, 63(22), 319-330. doi: 10.1111/j.18352561.2012.00198.x Carbone, D., & Seem, A. (2014). SEC's disclosure reform: Less is more. International Financial Law Review, 33(5), 112.

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Casey, C. (1980). Variation in accounting information load: The effect on loan officers’ predictions of bankruptcy. The Accounting Review, 55(1), 36-49. Retrieved from http://web.b.ebscohost.com.ezproxy.msvu.ca/ehost/detail/detail?vid=0&sid=519180dc3cb1-4826-a689-e546b6cbe4df%40pdc-vsessmgr04&bdata=JnNpdGU9ZWhvc3QtbGl2ZSZzY29wZT1zaXRl#AN=4511338&db =buh Chia-Ying, L. (2016). Why do online consumers experience information overload? An extension of communication theory. Journal of Information Science, 43(6), 835-851. doi: 10.1177/0165551516670096 Edmunds, A. & Morris, A. (2000). The problem of information overload in business organisations: A review of the literature. International Journal of Information Management 20, 17-28. doi: 10.1016/S0268-4012(99)00051-1 Eppler, M., & Mengis, J. (2004). The concept of information overload: A review of literature from organization science, accounting and marketing, MIS and related disciplines. The Information Society, 20, 324-344. doi: 10.1080/01972240490507974 Epstein, B. (2009). The economic effects of IFRS adoption. The CPA Journal (March). 26-31. Retrieved from https://www.nysscpa.org/news/publications/the-cpa-journal/articlepreview?ArticleID=10287#sthash.9xscFWsv.dpbs Feather, J. P. (1998). The information society: A study of continuity and change, (2nd ed.). London: Library Association Publishing. Field, A. (2009). Discovering statistics using SPSS, (3rd ed.). Thousand Oaks, CA: Sage Publications, Ltd.

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Henderson, E. (2016). Users’ perceptions of financial statement note disclosure and the theory of information overload (Doctoral dissertation). ProQuest Dissertations Publishing, (10150219.) Herz, R. (2012, August 28). What’s behind FASB’s new disclosure framework project? Compliance Week. Retrieved from https://www.complianceweek.com/search/site/disclosure%20framework?daterange=2012-01-01:2012-12-31#.Wm37jOdG3IU Holton, A. E., & Chyi, H. I. (2012). News and the overloaded consumer: Factors influencing information overload among news consumers. Cyber Psychology, Behavior, and Social Networking, 15(11), 619-624. doi:10.1089/cyber.2011.0610 Iannaconi, T. (2012). Disclosure overload. Financial Executives, March, 28-31. Retrieved from http://www.financialexecutives.org Iannoconi, T., & Sinnett, W. (2011). Disclosure overload and complexity: Hidden in plain sight. Retrieved from https://www.kpmg.com/US/en/IssuesAndInsights/ArticlesPublications/Documents/KPM G%20FEI%20Disclosure%20Report_final.web.pdf IFRS (2018). International financial reporting standards. Retrieved from http://www.ifrs.org/Use-around-the-world/Pages/Jurisdiction-profiles.aspx Jackson, T., & Farzaneh. P. (2012). Theory-based model of factors affecting information overload. International Journal of Information Management, 32, 523-532. doi: 10.1016/j.ijinfomgt-2012.04.006

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Kieso, D., Weygandt, J., Warfield, T., Young, N., Wiecek, I. & McConomy, B. (2016). Intermediate Accounting, 11th Canadian ed. Mississauga, ON: John Wiley & Sons Canada, Ltd. Latridis, G. (2010). International financial reporting standards and the quality of financial statement information. International Review of Financial Analysis, 19, 193-204. doi:10.1016/j.irfa.2010.02.004 Lawrence, A. (2013). Individual investors and financial disclosure. Journal of Accounting and Economics, 56, 130-147. doi: 10.1016/j.jacceco.2013.05.001 Magnusson K. (2014). Interpreting Cohen’s d effect size: An interactive visualization. Retrieved from http://rpsychologist.com/d3/cohend/ Morunga, M. & Bradbury, M. (2012). The impact of IFRS on annual report length. Australasian Accounting, Business and Finance Journal (AABFJ) 6(5), 47 – 64. Retrieved from http://ro.uow.edu.au/aabfj/vol6/iss5/ Paredes, T. (2003). Blinded by the light: Information overload and its consequences for securities regulation. Washington University Law Quarterly, 81, 417-817. Retrieved from http://openscholarship.wustl.edu/law_lawreview/ Pounder, B. (2012). Full disclosure vs. effective disclosure. Strategic Finance, August, 17-18. Retrieved from http://www.imanet.org/resources-publications/strategic-financemagazine/issues/August%202012 Radin, A. (2007). Have we created financial statement disclosure overload? The CPA Journal, 6, 8-9. Retrieved from http://www.cpajournal.com/

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Roudaki, J. (2012). Quality and quantity of disclosure: The case of Iranian listed companies implementing harmonized IASs. Journal of Accounting- Business & Management, 19(1), 43 – 68. Retrieved from http://jabm.stiemce.ac.id/?page=international&list=yes&volume=19&number=1&month=April&year=2 012 Schroder, H., Driver, M., & Struefert, S. (1967). Human information processing, individuals and groups functioning in complex social situations. New York: Holt, Reinhart & Winston. Tables & Figures

Table 1

Total pages less blank pages Time N 200

16.8233

8.75569

Post

200

22.8690

10.62604

Sig.

Reject null

0.171

Pre to Post

Standard Deviation

Pre

Table 2 Total pages less blank pages Time F

Mean

1.88

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Table 3 Percentage of total pages of notes Time Accounting Policies

Financial Instruments

Share Capital

Pre

23.43

11.59

12.84

Post

30.54

9.42

8.16

Table 4 Change in financial statement note disclosure Pre and Post-IFRS Accounting Policies Total Pages Item

P value

Pre

Post

Value or Change

Pre

Post

Value or Change

Post

0.000

Pre to

Post

0.000

% change

Mean

16.8223

22.809

6.05

3.9413

6.9838

3.04

Standard Deviation

8.75569 10.62604

1.86

1.816

3.049

1.23

Min

1.30

1.90

Max

59.15

67.40

8.25

11.70

19.10

7.40

Median

14.95

20.90

5.95

3.55

6.50

2.95

23.43

30.54

7.11

% Total Pages

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Factors that Influence a College Student’s Choice of an Academic Major and Minor Paul A. Stock University of Mary Hardin-Baylor Eileen M. Stock Department of Veterans Affairs

Abstract We examined factors influencing the decision of an academic major and/or minor by undergraduate students at a private university located in Central Texas. A total of 386 students taking courses in the university’s College of Business were surveyed. Participants were asked to provide the top five factors influencing their choice in an academic major and minor. We also collected information on when the decision of an academic field was determined and how frequently it had changed. Additional factors collected included demographic variants and class standing (i.e. freshman, sophomore, junior, or senior). Our aim was to assist college advisors and faculty in guiding students to choose the appropriate major and minor for them. A key finding of this study was that different majors (accounting, finance, economics, etc.) within the same discipline (Business) have different influencing factors. Another finding was that college students change their major because they lose interest in their current major and they take a course outside their major that interests them. Disclosure: The views and opinions expressed in this article are those of the authors and do not necessarily reflect the views of the Department of Veterans Affairs or the United States Government.

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Keywords: Higher education, Academic major, Academic minor, College of Business Introduction Every year, millions of young high school graduates enter college. It’s an exciting time for them. For many of these young adults, it is the first time living away from their parents. Others are the first generation in their family to attend college. Among all this excitement is the daunting decision of an academic major. Undergraduate students face the challenge of deciding an academic major that may well decide their working career for the next 40+ years. This is one of the most important decisions a college student must make. College advisors and faculty want to assist these students in making a wise decision that fits their unique interests and skills. Some universities even schedule a meeting between the incoming freshman and a college advisor, recruiter, or professor to discuss possible majors and minors most suitable for the student. For this study, we aimed to determine the main factors that currently influence a college student’s choice of an academic major and minor. Knowing the main factors that influence how undergraduate college students currently choose an academic major or minor can help colleges and universities plan their degree offerings and assist college advisors to understand how students make this life-changing decision. This information can also help high school counselors, college administrators, college advisors, professors, and parents to guide the young students toward the right decision for their personality, goals, and talents, as well as reduce the number of times students change their academic major or minor. Most students do not receive a great deal of assistance or advice in their decision of an academic major or minor. This might explain why the majority of college students change their

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major or minor at least once during their college years. Some students even change their major three or four times. Changing an academic major or minor can add an entire semester or more to the student’s total time in college because it requires a change in degree plans. A change of major or minor also requires the student to take different courses and may make some of the courses already completed obsolete in their new degree plan. Besides additional time in college and delayed graduation, a change of major incurs additional cost for tuition, textbooks, and fees. Our main objective of this study was to identify the most influential factors affecting college students’ choice of an academic major or minor. Secondary objectives included assessing what time this decision was made and the number of times it was changed. Reasons for the change of major and measuring the difficulty of deciding an academic field were assessed qualitatively. Literature Review Surprisingly, there is relatively little research on the factors that influence a college student’s choice of an academic major or minor. Each year, approximately 70% of high school graduates enroll in college courses (BLS). It is an exciting time for these 2.2 million college freshmen, but they do face the challenge of choosing an academic major and minor. Prior research suggests 20% to 50% of incoming college freshmen do not have a declared academic major when they start college, and about 75% of college students change their major at least once during their college years (Freedman, 2013). Another research study showed that college students who select an academic major matching their personal interests are more likely to finish their degree plan on time (Sheehy, 2013). However, the same study concludes that most high school graduates are not choosing

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academic majors that match their interests or skills. In fact, the study showed that only 36% of students who chose a college major, while still in high school, selected a major that fit their personal interests well (Sheehy, 2013). It further recommends students wait until college to choose an academic major and take some elective courses early in their college experience to find an academic field that interests them. A study conducted by Liz Freedman of Butler University suggests that all students are likely unprepared at the time of college entry to choose an academic major and minor (Freedman, 2013). Accordingly, colleges and universities have implemented a vast array of resources for assisting students who are undecided on an academic major and minor. The Freedman study further suggests that higher education institutions should encourage students to put off the decision of a major and minor until a student’s sophomore year, when the young adults are more prepared to make a wise choice that will affect their entire career path. Another study by The College Board recommends college students take courses that appeal to their personal interests and then seriously think about which courses motivate them the most (College Board, 2017). This study suggests college students explore different courses and take some risk in their course selection. By doing so, a course a student never planned to take could end up helping them to decide a major or minor. A study by Cecilia Capuzzi Simon explains there are currently over 1,500 different academic majors in the United States and the number of majors is growing (Simon, 2012). It points out that roughly 24% of the current academic majors were just added over the past 10 years, including homeland security and cyberforensics. This trend to increase the number of possible majors and minors makes the decision even harder. Further, the study points out that

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many college students are choosing a double-major or a major/minor combination to give themselves an advantage in the uncertain job market. Methodology A survey was administered to undergraduate students at a private university in central Texas during the last two academic years. A total of 386 undergraduate students taking courses in the university’s College of Business participated in the survey (see Appendix A). Survey Design The first few questions of the survey gathered data on the student’s demographics including class rank (freshman, sophomore, junior, or senior), gender, and age. The survey then asked students to list their current major(s) and minor(s). Students were asked to list the leading five factors that influenced their choice of an academic major, in order of their importance. Students were asked when they decided their current major and minor, with answers varying from before high school to still undecided. They were also asked if they changed their major or minor during this decision-making process. If they did change their major/minor, the students were asked how many times they changed their major/minor and to explain why. Each student was asked to indicate (on a scale of 1 – Not Important to 5 – Very Important) how important 24 variables were in their decision of a major. These variables were divided into four major categories titled ‘career values’, ‘career field’, ‘life values’, and ‘influential factors’. The ‘career values’ included variables like job security, challenging career, family/work balance, and a successful career. The ‘career field’ variables included a flexible work schedule, career advancement, and job availability. The variables under the ‘life values’ category included income, personal goals, and being able to purchase goods in demand. Finally,

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the ‘influential factors’ included the job market, prior work experience, and the reputation of the major/minor area of study. The survey also asked each student how difficult (on a scale of 1 – Not Difficult to 5 – Very Difficult) it was to choose an academic major/minor and why. The survey ended with an open-ended question that allowed the student to write any additional comments or information on the topic of choosing a major and minor. Analysis Plan Descriptive analyses included frequencies (percentages) and means (standard deviations, ranges) of demographic and academic-related data. Chi-square analyses were used to assess relationships between categorical variables. All analyses were conducted in R v3.2.3 (R Foundation for Statistical Computing; Vienna, Austria), assuming a Type I error of 0.05 throughout. Results Of the 386 total participants taking courses in the university’s College of Business, 307 (79.5%) students had a business-related major and 79 (20.5%) students did not have a businessrelated major. Demographics for these 386 participants are displayed in Table 1. Class standing appeared to be equally represented among survey participants, ranging from 22.3% for junior rank students, 25.1% each for sophomores and seniors, and up to 27.5% for freshman students, respectively. Academic Major/Minor The declared majors of the survey participants are displayed in Table 2. The university’s College of Business has the following 10 majors: Accounting, Business Computer Information

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Systems (BCIS), Business Administration, Economics, Entrepreneurship, Finance, International Business, Management, Marketing, and Multimedia Information Technology (MMIT). A total of 59 students (15.3%) had a second major. The academic minors of the survey participants are displayed in Table 3. The university’s College of Business offers 8 minors: Accounting, Business Administration, Economics, Finance, International Business, Management, Marketing, and Multimedia Information Technology (MMIT). Approximately 40 percent of the participants (153 students; 39.6%) had a first minor, and 12 (3.1%) students had a second minor. Factors Influencing Academic Major/Minor Participants were asked to list the Top 5 factors that influenced their choice of major/minor. Results of this inquiry are shown in Table 4. The leading factors that influenced participants’ choice of an academic major/minor were: Personal Interest (35.0%), Parents (18.9%), Potential for Success (10.1%), Potential Income (9.1%), and Prior Work Experience (5.2%). Personal interest was the leading #1 and #2 factors among survey respondents, followed by Potential Income, and then Potential for Success. Own Reading surpassed Personal Interest for Factors listed after #2. While Parents was the second most common #1 factor, it did not seem as influential thereafter. Potential Income appeared more often as a secondary factor influencing the choice of major/minor. Collectively among all factors, Personal Interest was most common, followed by Potential Income, and then the influence of Parents. To assess variations in factors influencing the decision of an academic field across business majors, the leading #1 factors for each major were determined. The top 3, #1 factors influencing each business major are shown in Table 5.

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The leading factor for seven out of the nine (77.8%) business majors was personal interest. However, the leading factor for the Finance major was the potential for success and the leading factor for the Management major was the parents’ influence. The second most important factor was parents’ influence for seven of the nine (77.8%) majors. However, the second factor for Economics was the student’s own research. For Management majors, it was personal interest. The third most important factor in choosing a major was the potential income for six of the nine (66.7%) majors. The third factor for Accounting was teacher/professor influence. For Management majors, it was the potential for success, while MMIT majors had both teacher/professor influence and the potential for success equally represented as a third factor. Economic majors had three factors equally likely for the third leading factor, including potential for success, high school experience, and potential income. Timing and Number of Changes in Academic Major/Minor Of 386 students, about one-third (144; 37.3%) decided their major prior to their freshman year of college, which means approximately two-thirds (242; 62.7%) of the students started their freshman year without deciding on an academic major. An interesting observation from Table 6 is that 51.6% of the participants changed their major at least once. A more detailed analysis of the data shows that 67% of students who changed their major only changed it once. However, 19% of students who changed their major did so twice. About 11% of the students who changed their major did so three times. There were even students who changed their major five, six, and seven times. The average number of times these students changed their major was 1.55 times.

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A change in major was found to be associated with a student’s chosen major (χ2 = 35.6, df = 10, p-value < 0.001). More specifically, MMIT majors had the greatest rate of changing majors (93.8%), while Marketing had the lowest rate of changing majors (29.8%). No difference in choice of Factor #1 with changing majors (χ2 = 17.1, df = 14, p-value = 0.252) or when the decision was made with changing majors (χ2 = 9.7, df = 8, p-value = 0.288) was found. We also asked the students who changed their major to explain why they made the decision. The number 1 reason (N=39; 19.5%) students changed their major was that they lost interest in their first major. The second reason (N=27; 13.6%) was the influence of a college course they took. The third reason (N=14; 7%) was a change in their personal interests and the fourth reason to change their major (N=12; 6%) was the potential job market. We also asked the students how difficult it was to choose a major on a scale from 1 (not difficult) to 5 (very difficult). The average score was 3.07 (SD=1.31), suggesting the decision of a major is neither too difficult nor too easy. The vast majority of students (107 out of 168; 63.7%) decided on a minor in their freshman and sophomore years. A total of 132 students (34.2%) did not have a minor. Most business degree plans at this university do not require a minor. Another interesting observation is that the vast majority (25 out of 27; 92.6%) of students who decided a minor before their freshman year, did not change it. Conversely, the vast majority of students (23 out of 30; 76.7%) who waited until their junior year to decide on a minor, did change it. About 38% of freshman and 61% of sophomores changed their minor. The last section in the survey asked students to indicate (on a scale of 1 to 5) how important 24 variables were in their decision of a major. These variables were divided into four

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major categories titled ‘career values’, ‘career field’, ‘life values’, and ‘influential factors’. The most important ‘career value’ was a successful career. The most important ‘career field’ factor was job availability. The most important ‘life value’ was the ability to set personal goals. Finally, the most important ‘influential factor’ was interacting with co-workers. The last question allowed students to write anything they wanted to add about choosing their major and minor. Here are some of the more interesting comments: 

A person should do what they enjoy and love to do.



I enjoy the courses in my major.



My major was easy to decide but my minor was hard.



My grandma said if I am going to be bossy, I might as well get paid for it.



I really enjoy my major.



I worry that my lack of experience will hurt me in the job market.



I respect my parents’ advice.



My major fits my personality and skills.



My professor influenced my choice of major.



I’ve always heard there are a lot of jobs in business. Recommendations

A major finding of this two-year study is the Top 3 factors that influence a college student’s decision of an academic major are personal interest, their parents, and potential income. However, when the data were analyzed by major, it was discovered that a few majors varied from this pattern. For example, for Economics majors, the second most common factor was the student’s own research. It is recommended that students who are interested in an Economics

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major be encouraged to conduct their own research about this academic field. An advisor or professor could even provide some useful resources to the student. Also, the top factor for Finance majors was the potential for a successful career. It is recommended that Finance professors educate students about the path to a successful career in the Finance field. Perhaps sharing some specific examples of success or having successful alumni talk to current students would be helpful. Another major with different factors than the majority of majors was Management. The top factor for Management majors was their parents. It is recommended that professors and advisors in the Management field focus on speaking with the student’s parents to ensure the parents have a good understanding of this major’s degree plan and path to success. In this study, we discovered that 63% of incoming college freshmen have not decided on an academic major. Therefore, it is recommended that university administrators, advisors, and professors focus on freshman with an undecided or undeclared major. These students need to be advised on how to find a major that fits their personal interests. There are a number of tests that help undecided college students decide on a major. It is recommended that colleges have students with an undeclared major take one of these tests during their freshman year, in an effort to save both time and cost for the student down the road. Consistent with the literature, we found a majority (51.6%) of students changed their major at least once. Also, the number one reason for changing their major was that they lost interest in their first major. It is recommended that professors and advisors attempt to keep the students interested in their first major. Some ways to accomplish this is to periodically talk about different career paths in the major and share success stories in the major with the students.

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Another helpful strategy is to link the lessons to the real world. Students need to know how the lessons in their major links to the real world after college. The second most common reason for changing majors is the influence of a course the students took. This is an opportunity for professors who offer an introduction or principle course, which attracts many non-majors to attract new students into their major. It is recommended the professors add a lesson about their academic major in the introduction or principles course. For example, a principles of economics course should have at least one lesson about the Economics major that explains the different career paths and what a successful career in economics looks like. The lessons should also give examples of successful people in the field. It might even be useful to invite successful alumni to talk to the class about their decision of a major and their career path. Future Research Since the most influential factor in choosing a major in this study was the student’s personal interest in a field of study, future research should try to divide the category of “personal interest” into some subcategories to better understand exactly what this means. The influence of the student’s parents was the second most influential factor in choosing a major, so future research should try to determine if the father or mother is more influential. It could be that each parent is equally influential, but it would be interesting to determine if one parent was more influential than the other parent. The third influential factor was the potential for success, so future research would want to define how students measure “success” in their career. It might mean achieving career goals, job advancement, or achieving a high level of income.

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We asked students when they chose their current major. For those students who changed their major, it would be interesting to determine when they chose their first major, second major, and subsequent majors. Author Biographies Paul A. Stock is a Professor of Economics at the University of Mary Hardin-Baylor. He received his BBA in Business Administration with an Economics concentration from Clarion University of Pennsylvania, an MBA from Oklahoma City University, and PhD in Economic Education from Ohio University. Dr. Stock teaches and conducts research in macroeconomics and economic education. Eileen M. Stock is a statistician at the Cooperative Studies Program Coordinating Center in the VA Maryland Health Care System located in Perry Point, MD. She received a BS and MS in Mathematics from Tarleton State University. She also earned a MS and PhD in Statistics from Baylor University. Her areas of research include Biostatistics, Computational Statistics, and Bayesian Analysis. References Bureau of Labor Statistics, (April 27, 2017). College enrollment and work activity of 2016 high school graduates, Retrieved from: https://www.bls.gov/news.release/hsgec.nr0.htm Edmonds, J. (2012). Factors influencing choice of college major: What really makes a difference? Theses and Dissertations. 147. Retrieved from http://rdw.rowan.edu/etd/147 Freedman, L. (June 28, 2013). The developmental disconnect in choosing a major: Why institutions should prohibit choice until second year. The Mentor, An Academic Advising

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Journal, Penn State University, Retrieved from: https://dus.psu.edu/mentor/2013/06/disconnect-choosing-major/ Keshishian, F. (2010). Motivating factors influencing college students’ choice of academic major, American Journal of Pharmaceutical Education, 74(3), Article 46. Sheehy, K. (November 11, 2013). Study: High school grads choosing wrong college majors, US News, Retrieved from: http://www.usnews.com/education/blogs/high-schoolnotes/2013/11/11/ The College Board, (2017). The college major: What it is and how to choose one, Retrieved from: https://bigfuture.collegeboard.org/explore-careers/college-majors/ U.S. Department of Education, (2016). Back to school statistics, Digest of Education Statistics, Annual Report to the Commissioner of Education, Retrieved from: https://nces.ed.gov/fastfacts

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Tables & Figures Table 1. Demographics of survey participants Survey Characteristic

Participants (N=386)

Age

21.0 (3.8)

Mean (SD)

20.0 (18, 50)

Median (Min, Max) Gender

N (%)

Female

140 (36.3)

Male

246 (63.7)

Classification

Freshman

106 (27.5)

Sophomore

97 (25.1)

Junior

86 (22.3)

Senior

97 (25.1)

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Table 2. Academic Majors of Survey Participants First Major

Second Major

Academic Field

N (%)

Accounting

34 (8.8)

3 (0.8)

BCIS

7 (1.8)

1 (0.3)

Business

10 (2.6)

3 (0.8)

Economics

17 (4.4)

5 (1.3)

Entrepreneurship

1 (0.3)

0 (0.0)

Finance

23 (6.0)

8 (2.1)

International Business

23 (6.0)

10 (2.6)

Management

77 (19.9)

5 (1.3)

Marketing

84 (21.8)

7 (1.8)

MMIT

16 (4.1)

4 (1.0)

Other

94 (24.4)

13 (3.4)

----

327 (84.7)

Administration

No Second Major

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Table 3. Academic Minors of Survey Participants First Minor

Second Minor

Academic Field

N (%)

Accounting

6 (1.6)

3 (0.8)

Business

22 (5.7)

0 (0.0)

Economics

31 (8.0)

0 (0.0)

Finance

4 (1.0)

2 (0.5)

International Business

9 (2.3)

2 (0.5)

Management

15 (3.9)

0 (0.0)

Marketing

11 (2.8)

0 (0.0)

MMIT

8 (2.1)

0 (0.0)

Other

47 (12.2)

5 (1.3)

153 (39.6)

12 (3.1)

233 (60.4)

374 (96.9)

Administration

Total No Minor

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Table 4. Factors Influencing Decision of Academic Major and Minor Factors

Mother/Father Siblings Other Relative High School Experience Person in Field Potential Income Teacher/Professor College Advisor High School Counselor Prior Work Experience Own Reading Personal Interest Friends Potential for Success Advertising Job Fair/Career Fair Coach Other Unanswered

Factor #1 N = 386 N (%) 73 (18.9)2 5 (1.3) 7 (1.8) 8 (2.1) 7 (1.8) 35 (9.1)

Factor #2 N= 386N (%) 38 (9.8)

Factor #3 N = 386 N (%)

Factor #4 N = 386 N (%)

Factor #5 N = 386 N (%)

Combined N = 1930 N (%)

43 (11.1)

33 (8.5)

28 (7.3)

4 (1.0) 12 (3.1) 12 (3.1)

10 (2.6) 6 (1.6) 14 (3.6)

9 (2.3) 8 (2.1) 14 (3.6)

7 (1.8) 14 (3.6) 18 (4.7)

215 (11.1)3 35 (1.8) 47 (2.4)

19 (4.9) 61 (15.8)1 19 (4.9) 13 (3.4) 1 (0.3)

26 (6.7) 51 (13.2)2 26 (6.7) 25 (6.5) 1 (0.3)

17 (4.4) 31 (8.0)3

15 (3.9) 6 (1.6) 0 (0.0)

0 (0.0) 57 (14.8)3 15 (3.9) 10 (2.6) 0 (0.0)

20 (5.2)

12 (3.1)

18 (4.7)

12 (3.1)

14 (3.6)

24 (6.2) 34 (8.8)3

36 (9.3) 4 (1.0)

23 (6.0) 26 (6.7)

21 (5.4) 25 (6.5)

15 (3.9) 14 (3.6) 2 (0.5)

66 (3.4) 69 (3.6) 235 (12.2)2 90 (4.7) 68 (3.5) 4 (0.2)

15 (3.9) 135 (35.0)1 3 (0.8) 39 (10.1)3 0 (0.0) 0 (0.0)

34 (8.8) 82 (21.2)1 9 (2.3) 62 (16.1)2 2 (0.5) 4 (1.0)

41 (10.6) 46 (11.9)3 5 (1.3) 49 (12.7)2 2 (0.5) 3 (0.7)

4 (1.0) 1 (0.3)

10 (2.6) 8 (2.0)

76 (3.9) 150 (7.8) 301 (15.6)1 61 (3.2) 201 (10.4) 18 (0.9)

16 (0.8) 4 (1.0) 6 (1.6) 20 (1) 4 (1.0) 2 (0.5) 52 (2.7) 61 114 206 (10.7) (15.8)1 (29.5)1 1 2 3 Leading factor within Top Factor; Second most common factor; Third most common factor.

1 (0.3) 17 (4.4) ----

4 (1.0) 23 (6.0) 6 (1.6)

5 (1.3) 6 (1.6) 25 (6.5)

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Table 5. Top Factors by Major Major* Accounting BCIS Bus Admin Economics

Factor #1 (%) Personal Interest (26.5%) Personal Interest (28.6%) Personal Interest (40.0%) Personal Interest (29.4%)

Finance

Potential Success (30.4%) Int’l Personal Interest Business (47.8%) Management Parents (24.7%) Marketing MMIT

Personal Interest (41.72%) Personal Interest (37.5%)

Factor #2 (%) Parents (17.6%) Parents (28.6%) Parents (30.0%) Own Research (17.6%) Parents (26.1%) Parents (13.0%) Personal Interest (20.8%) Parents (15.5%) Parents (25.0%)

*Entrepreneurship was excluded due to small sample size.

Factor #3 (%) Teacher/Professor (11.8%) Potential Income (28.6%) Potential Income (20.0%) Potential Income, High School experience, and Potential Success (11.8%) Potential Income (21.7%) Potential Income (13.0%) Potential Success (18.2%) Potential Income (7.1%) Potential Success and Teacher/Professor (12.5%)

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Table 6. When did Students choose their Major/Minor?

Time Period Before High School In High School Between HS & College Freshman Year Sophomore Year Junior Year Senior Year After College Undecided No Minor Changed Major / Minor Yes No

Decided Major N (%) 5 (1.3) 80 (20.7) 59 (15.3)

Decided Minor N (%) 0 (0.0) 15 (3.9) 12 (3.1)

110 (28.5) 96 (24.9) 25 (6.5) 5 (1.3) 1 (0.3) 5 (1.3) -

53 (13.7) 54 (14.0) 30 (7.8) 4 (1.0) 0 (0.0) 86 (22.3) 132 (34.2)

199 (51.6) 187 (48.4)

67 (23.7) 216 (76.3)

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Appendix A Survey on Academic Majors and Minors Rank: Freshman ________; Sophomore ________; Junior _______; Senior ________; Academic Major #1 _______________;

Academic Major #2 ___________________

Academic Minor #1 _______________; Academic Minor #2 ___________________ Gender:

Male _________;

Female _________

Age: ______ years old 1. Circle all the factors (below) that influenced your decision about your academic major/minor: Mother/Father Potential income My own reading/research Advertising Siblings Teacher/Professor Personal Interest Job Fair Other Relative College Advisor Friends Career Fair High School experience High School counselor Potential for successful career Coach Person in that career My Prior Work Experience Other: ______________ 2. List the Top 5 factors from above in their order of influence (from most influential to least influential) Number 1: _____________________________________ (Most Influential) Number 2: _____________________________________ Number 3: _____________________________________ Number 4: _____________________________________ Number 5: _____________________________________ (Least Influential) 3. When did you decide on your current Major? (Circle the best answer) Before high school In high school Between high school and college Freshman Year in college Sophomore year in college Junior year in college Senior year in college Still undecided Other: _____________________ 4. When did you decide on your current Minor? (Circle the best answer) Before high school In high school Between high school and college Freshman Year in college Sophomore year in college Junior year in college

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Senior year in college _____________________

Still undecided

Other:

5. Have you changed your major since starting college? YES _________

NO ________

(If YES, how many times: ______)

6. Have you changed your minor since starting college? YES _________

NO ________

(If YES, how many times: ______)

7. If you changed your major and/or minor since starting college, then what factors influenced your decision to change it? ______________________________________________________________________ ______________________________________________________________________ 8.

How important are the following “career values” to you? Not Important ----Neutral------ Very Important Having Job security 1 2 3 4 5 Having time for leisure 1 2 3 4 5 Having time for spouse/family/children 1 2 3 4 5 Balancing your personal life with a career 1 2 3 4 5 Having a challenging career 1 2 3 4 5 Having a successful career 1 2 3 4 5 9. How important are the following “career field” values to you? Not Important -----Neutral----- Very Important Graduating in shortest amount of time 1 2 3 4 5 Job availability after graduation 1 2 3 4 5 Work in a field with a good reputation 1 2 3 4 5 Having a flexible work schedule 1 2 3 4 5 Work in an interesting field 1 2 3 4 5 The potential for career advancement 1 2 3 4 5 10. How important are the following “life values” to you? Not Important -----Neutral----- Very Important Earning a lot of money 1 2 3 4 5 Being able to buy things I want 1 2 3 4 5 Setting goals for myself 1 2 3 4 5 Living in an urban area 1 2 3 4 5 Living in an suburban area 1 2 3 4 5 Living in a rural area 1 2 3 4 5 11.

How much did these factors influence your choice of major/minor?

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No Influence ----Neutral---- Great Influence Potential future earnings 1 2 3 4 5 Current job market 1 2 3 4 5 Prior work experience 1 2 3 4 5 Enjoy interacting with other people 1 2 3 4 5 Reputation of major/minor at this school 1 2 3 4 5 Reputation of major/minor outside of school 1 2 3 4 5 12. How difficult was it for you to decide on an academic major/minor? Not Difficult -------Neutral--------- Very Difficult 1 2 3 4 5 13. Do you think you will be successful in your major/minor career field? Probably NOT Successful -------Neutral------ Probably VERY Successful 1 2 3 4 5 Why? _______________________________________________________________________ _______________________________________________________________________ 14. Is there any other comments or information you would like to provide about your choice of an academic major and/or minor? ____________________________________________________________ ____________________________________________________________

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Strategic Leadership Development through Energy Management Mary L. Tucker Ohio University Andrew Pueschel Ohio University Ana Rosado-Feger Ohio University Amy Taylor-Bianco Ohio University Abstract University students are increasingly more involved as they juggle managing life away from family, making time for coursework, fulfilling organizational commitments, and honoring social engagements as well as, for many, holding full-time jobs. At a time when students’ lives are more intense than ever, many are at a distinct disadvantage because of inadequate energy management. This research will examine the energy management (or lack thereof) of participating students, while testing the effectiveness of various interventions used to communicate well-being and energy management. This research extends the 2012 study by Spreitzer and Grant that used the Energy Audit as an intervention to assist students in increasing their energy management. To enhance the validity of the previous study, we operationalized it into a three-cell, quasi-experimental design analysis supporting the research hypothesis that students will increase their self-awareness and well-being when primed through helpful, positive interventions. Findings support Spreitzer & Grant's premise; the results of this study indicate

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that priming students though systematic interventions may decrease their perceived stress and enhance their self-awareness and energy management. This research is supported by The Robert D. Walter Center for Strategic Leadership at Ohio University, Athens, Ohio. Keywords: Energy management, energy audit, business pedagogy, university students Introduction Technological advances have enhanced productivity; in fact, since 1960 “productivity has increased almost 30 fold” (Martin, 2018). At the same time that technology has assured increased individual access to knowledge and promoted faster job performance, the National Center for Health Statistics reports the overall suicide rate has increased 24 percent from 19992014 (Tavernise, 2018). Researchers project that the downside of increased productivity expectations of today’s workers has resulted in decreased energy levels. In the rush to get more and more accomplished, optimal energy renewal is not being maintained by 74 percent of today’s employees, resulting in plummeting physical, emotional, mental, and spiritual energy renewal. If not corrected, depression, sickness, and burnout may occur (Lohr & Schwartz, 2003; Sarner, 2018). Researchers from the Centers for Disease Control and Prevention (Singer, 2017) report an increase in teenage depression from 8.3 percent in 2008 to 10.7 percent in 2013. Since more than 60 percent of people who die by suicide suffer from depression, this may be a factor in suicide becoming the second leading cause of death among young adults. Most troubling is the idea that one in twelve college students make a suicide plan (Neuman University, 2018). Thus, it becomes paramount to consider the unhealthy distress that today’s university students may

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struggle through and to devise mechanisms that allow students to maximize their energy to enhance their well-being. Incoming college freshmen are entering one of the most exciting times of their youngadult lives. For the first time, they are allowed to set their own schedules, make their own decisions, and make new friends. Conversely, there is a great deal of anxiety and fear as they become members of a community where they blend instead of standing out. The reality of leaving friends and family back home, juggling life on their own, scheduling classes differently, handling challenging coursework, balancing social and organizational commitments, and, for an increasingly large number of students, holding full-time jobs can become stressful and overwhelming. It is easy to surmise that, while students are experiencing this life-changing event, many develop inadequate energy management habits that put them in a distinct disadvantage for short-term, as well as live-long personal and professional success. In fact, Schwartz and McCarthy (2007) posit that “managing energy, not time, is the key to enduring high performance as well as to health, happiness, and life balance. Whereas our time is limited and finite, energy can be renewed via four main wellsprings in human beings: the body, mind, emotions, and spirit” (p. 2). Spreitzer and Grant (2012) applied Lohr and Schwartz’s (2003) energy management concepts into the university classroom and found qualitative evidence of success. This paper adapted a similar method to prime students to take control of their well-being through energy management of their body, mind, emotions, and spirit. Thus, the current research involved collection of data to determine whether students introduced to ways of renewing their energy would report significant benefits from this intervention.

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Literature Review

“Managing energy, not time, is the fundamental currency of high performance. Performance is grounded in the skillful management of energy.” (Loehr & Schwartz, 2003, p.17) Intuitively, it is easy to agree that technology is creating more rapid change. Thus, our daily workload is intensifying because of the speed in which our lives are moving. Most workers today are experiencing ever-present distractions that encourage task switching. The results of this work environment perpetuate stress and often result in being busy vs being productive. Today’s business landscape reveals company closures, mergers, downsizing, and reorganizing. This often results in job responsibilities changing and increasing for remaining workers who may need to extend working hours in an effort to maximize performance. Thus, time management became the mantra for training workers to achieve new and extended performance goals through daily, weekly, and monthly to-do lists. Then, Lohr and Swartz in 2001 asserted that managing energy (not time) was the better way to maintain high performance and personal renewal. Ericsson and colleagues in 1993 published research that studied expert musicians to determine how their energy is expended and replenished. Using this idea of the flow between intense practices and intermittent rest, Loehr and Schwartz first began to apply the concept in the sports arena to enhance the performance of expert athletes and branched out to consulting with and training leaders in all types of organizations. Their training programs are bolstered by the concept that “if sustainable great performance requires a rhythmic movement between activity and rest, it also depends on tapping multiple sources of energy” (Schwartz, 2010, p. 7). Thus, Loehr and Schwartz, along with colleagues, encourage the management of energy instead of time. Whereas time is finite, energy can be utilized and replenished, enabling an enhanced

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capacity to get things done. This results in maximized performance and an enhanced quality of life (Loehr & Schwartz, 2001; 2003; Mason et al., 2018; Schwartz, 2010, Schwartz & McCarthy, 2007). Loehr and Schwartz proffer that we are, indeed, in an energy crisis. At the same time, “great leaders are stewards of organizational energy. They begin by effectively managing their own energy. As leaders, they must mobilize, focus, invest, channel, renew and expand the energy of others” (Loehr & Schwartz, 2003, p. 17). In order to renew energy, Loehr and Schwartz (2001) identify four sources that must be maintained for optimal positive energy: 

Physical Energy: Regular exercise, balanced nutrition, and appropriate levels of sleep are positive fuels for maintaining heighted energy levels. Student awareness of their current physical energy levels along with how to regulate this dimension will minimize a “possible crash and burn.”



Mental Energy: Setting short-term and long-term productivity goals, focusing on a single task at a time (decreasing multi-tasking), and taking short breaks are key to regulating and achieving increased mental energy.



Emotional Energy: Building enthusiasm for tasks throughout the day requires a positive mindset. Starting the day with a positive disposition assists in overcoming times of negativity, depression, and stress.



Spiritual energy: The is ability to be mindful and thankful can be enhanced through self-talk, gratitude journals, meditation and a sense of one’s life purpose, which will increase spiritual energy and gratefulness. (p. 123)

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Across college campuses, university faculty strive to provide graduates with the technical knowledge for their fields, as well as some breadth of knowledge across the arts and sciences. It is important that, as the leaders of tomorrow, our students become more adept in the skillful management of their energy. Energy management may well be the competitive advantage that sets students apart from peers in work/life balance and career advancement. In fact, Wamp (2009) challenges schools to create a culture of movement and recovery to manage student energy at optimal levels. To this end, Spritzer and Grant (2012), drawing from the work by Loehr and Schwartz (2001), and recovery from work demands literature, introduced energy management into the classroom. They asserted that “the more we can help students develop healthy habits around energy while still in school, the better we can help them sustain their energy for high performance for a lifetime” (2012, p 16). Their longitudinal, qualitative study indicated that respondents reported better understanding of the energy depleting forces (77%). Over two-thirds (69%) stated they had a better understanding of specific strategies to improve their energy management. The respondents represented every academic discipline within the college. This research draws from Loher and Schwartz’s energy management literature (2001; 2003) along with Spreitzer and Grant’s classroom interventions (2012), to introduce energy management into freshman introductory business courses. This paper extends the research by adding data collection to determine statistically whether students’ self-report assessment will show significant growth after the energy management audit. To enhance the validity of the previous study, the research was operationalized it into a three-cell, quasi-experimental design

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analysis supporting the research hypothesis that students will increase their self-awareness and well-being when primed through helpful, positive interventions. Methodology Participants The Energy Audit Survey was offered to three sections of students who were enrolled in the same course in the College of Business at a large university in the Midwest. Volunteer respondents enrolled in each of these sections completed the survey (see Appendix A) twice: at the beginning of the course before any interventions, and at the end of the course after the interventions were implemented. The goal of the interventions was to assist students in managing their energy across four dimensions: physical, mental, emotional, and spiritual. Each of the three sections received different levels of intervention as described previously, with Section 1 receiving minimal exposure and Section 3 receiving the most comprehensive set of interventions. Section 1 (8:30 a.m.) consisted of 35 respondents; section 2 (9:30 a.m.) had 46 respondents, and section 3 (10:30 a.m.) had 75 respondents. As noted in Table 1, all sections averaged 19.7, 19.6, and 19.8 years of age, respectfully. Design This study sought to determine whether students (Section 3) who were primed for enhanced energy management through self-awareness (energy management pre-test), selfanalysis and reflection (energy audit), intervention and plan for change (lecture and activity), and energy management post-test would have greater post-test energy management scores than students (Section 2) who received all but the intervention. Sections 2 and 3 findings could also compare with Section 1, who received only the pre- and post-test. See Table 2 for an overview

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of the methodology of this study including section times and the possible activities including the 5 phases of engagements conducted in this study included a pre-test survey, energy audit administration, energy audit collection, intervention, and post-test survey. Procedures: 5 Phases of Engagement Phase 1. The first phase consisted of the pre-test survey and overview of the study. Introduction to the pre-test survey was communicated through the explanation of the positive impact that each student could make on the study of well-being and professional development. Students received the printed survey that, instead of place for names, included a random 4-digit number written on the top right of the survey. Students were asked to email themselves or take a picture of the 4-digit number for their own records to use on their post-test. Students were then encouraged to close their computers, put away their cellular phones, and take notes for the remainder of the session. The survey itself was explained to the students in 3 sections. The first section consisted of general information such as gender, class year, major, and expected grade that the student thought they would receive in the course. The students were then told that the middle of the survey would consist of information on their current practices and thoughts in regard to the management of their physical, mental, emotional, and spiritual energy. They were not given any information to explain each dimension at this time. The final section of the survey, the students were told, were open-ended questions that they should answer to the best of their ability. Students were given ample time to complete the survey in class. Those not participating were encouraged to simply remain quiet in their seats with the electronic devices remaining away.

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The surveys were then collected and later given to the data analyst. After collection, the extent of the study was then explained to students. Conversation about the study was not engaged in before the survey was given out as not to allow student to give answers based on what they thought the study was looking for. Phase 2. The second phase consisted of the energy audit administration for Sections 2 and 3. Students were once again encouraged to close their computers and put away their cellular phones for the explanation of the energy audit. Once administered, all dimensions of the energy audit were clearly communicated, as the students followed along and asked questions, if desired. The 2-day time duration of the energy tracking audit was first communicated, in order to give the students a finite scope for the project. The first page of the audit was an overview that gave specific instructions on the times in which to track their energy, how to document their levels, and what to do if they were unable to exactly track their levels at the times instructed. If unable to document their levels at a specific time, students were instructed to recall what their energy level was during the missed log-in and return to the next specified time, in order to get back on track. The second page of the audit gave students the opportunity to actually track their levels of energy throughout the day in one-hour increments. The left column tracked their morning energy levels and the right column tracked afternoon and evening energy levels. Both sides allowed the students to track their energy levels from 1-10 with 10 being the highest. The third page of the audit was created to show a graphic representation of the data that the students documented throughout their two-day study of their energy levels. As helpful hints to the students, it was suggested to set hourly alarms on their phones to remind them to track

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their energy levels. It was also suggested they could track energy levels on a task-list via their phone and transfer the data to the audit tool at the end of each day. Once completed, students were asked if there were any questions pertaining to the energy audit tool. Phase 3. The third phase consisted of the energy audit collection for Sections 2 and 3. Two days after being given the energy audit, students who participated in the data collection were thanked for their participation and were asked questions pertaining to their experience while tracking their own energy levels. Conversations centered on student’s new self-awareness about their energy web and flow. Other comments included the ease of the documentation, as well as the challenges associated with the project, resulting in constructive brainstorming on ways in which students could better monitor their habits and self-awareness. The uses of digital devices (phone, apps, ipad, etc.) were suggested, in order to remind students of their energy levels. Phase 4. The fourth phase consisted of the intervention for Section 3. All students (even those who did not participate in the data collection) participated in a full, class time lecture (50 minutes) that reintroduced and further explained the four dimensions of energy management, including physical, emotional, mental, and spiritual energies. After the introduction of each dimension, students were given a template for their own “personal development plan.” This plan suggested ideas specific for the four energy management dimensions and also allowed them space to write in supportive activities that were specific to their own energy management needs. The timing of this intervention was such that the students were getting ready to end their semester. Conversations were extended to include ideas surrounding successful tips for ending the semester and being productive over the summers, as well as into their future.

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Phase 5. The fifth and final phase consisted of the post-test for all Sections. Students received the printed survey and included their 4-digit number on the top right of the survey. Once administered, the students were again encouraged to close their computers, put away their cellular phones, and take notes for the remainder of the session. Those who did not participate were once again encouraged to simply remain quiet in their seats with the electronic devices remaining away. The surveys were then collected and given to the data analyst. The students were thanked for their time and participation in the study. Results/Findings To determine the impact of interventions, we first evaluated whether the respondents started out with similar perceptions or at the same “base level” in the four dimensions of interest. To test this, we used independent-sample t-tests between all section pairs. This analysis resulted in a significant difference in one item, the measure of regular breaks, between Sections 1 and 2 and Section 3. Section 3 had an initial level in this item, which was higher than either of the two sections, and was quite high at a mean of 4.13/5.0. It was difficult for Section 3 to show any positive change in this item, regardless of intervention, though it would be possible to show a negative change. To test the hypothesis that interventions made a difference in how students managed their energy, we compared the pre- and post-survey responses for the students in the three sections. We used SPSS Statistics 23 to conduct the analysis, using paired-sample t-tests. The null hypothesis was that there was no significant difference between the student’s response to the preand post-surveys. Results are summarized in Table 3 and descriptive statistics for each item are given in Table 4. The results suggest that the interventions had an effect in the students’

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responses. Significant differences were observed between the pre- and post-intervention surveys. For reference, positive differences indicate that the post-intervention result was higher than the pre-intervention result, negative differences indicate the reverse. 

In the measures of Physical energy management, Section 2 respondents reported significant negative changes in two items (sleep duration and exercise frequency), and negative (but not significant) changes in two items (breakfast and small meals). Section 3 respondents reported mixed results, with significant negative changes in exercise frequency, but significant positive changes in eating small meals.



In the measures of Mental energy management, Section 2 respondents reported significant positive changes in taking regular breaks and multitasking. Respondents in Section 3 did not report any significant changes in this dimension, but we note again that their initial level of “regular breaks” was quite high. The increase in multitasking, however, was a significant difference between these two groups.



In the measures of Emotional energy management, respondents in Section 2 did not report significant changes in any of these measures. Respondents in Section 3 reported significant decreases in measures of being perceived as a positive person and helping others in need.



In the measures of Spiritual energy management, respondents in both Section 2 and Section 3 reported significant positive changes in writing goals and creating a vision board.

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

All sections reported positive changes in the summative measures for leadership and “tricks and tips.” Sections 2 and 3 reported positive change in the measure regarding stress.



These results were not affected by gender or age of the respondents. The analysis was conducted using both standardized and non-standardized variables, and there was no difference in results. Discussion

The purpose of our study was to collect data to validate the intervention proposed by Spreitzer and Grant (2012). The results suggest that these interventions had an impact on student responses regarding their energy management practices and perceptions. In this section, we will discuss the implications of the survey results for each dimension of energy management and for the summative questions. While the individual energy dimensions showed significant impact from the energy management interventions, it is the global measures regarding course outcomes that truly show their impact. Spreitzer and Grant (2008) suggested that managing energy could result in better stress management. The students in these courses did not receive any specific direct stress reductions or stress assessment interventions. However, the respondents in the sections that participated in the energy management intervention reported a significant positive change in their level of stress (higher levels on this item indicate less stress). This result supports the proposition by Spreitzer and Grant and presents evidence of the value of energy management in contributing to stress reduction and student well-being. For students training to be leaders and managers, awareness of energy management may result in more effective human management

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practices and an improved work atmosphere. These statements are preliminary and will require future study, particularly longitudinal analysis to determine whether these effects are maintained over time. The first dimension of energy management is physical energy. Students recorded decreases in their rating of items referring to sleep and exercise. On first glance, the significant negative effects seem counterproductive: one does not manage one’s energy better by reducing sleep and exercise. However, these results need to be considered within the context. Students responded to the surveys at the beginning and end of the academic semester. The final two weeks of the semester is a known “crunch time” when students tend to have projects or exams that require more time to complete or prepare, and thus tend to get less sleep and have less time for exercise. On the other hand, the energy audit seems to have raised awareness and a desire to monitor and adjust, with students commenting that they used naps to refresh their energy. Students in Section 3 reported an increase in managing their energy by eating smaller meals throughout the day. There was evidence from the medical literature that more frequent small meals can help maintain steadier levels of blood glucose, which is beneficial to maintaining steady energy, instead of experiencing surges and crashes (Caudwell et. al, 2013). Mental energy is the second dimension of energy management. Once again, there was evidence that the interventions had impact on students’ perceptions and actions. Respondents in section two reported higher levels of taking short breaks and increased multitasking. While the short breaks were a tool to manage and maintain energy, multitasking was considered detrimental to energy management. Once again, it was possible that the timing of the survey at the end of the term had an influence on this result, but notably, there was not a significant change

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in these items in the section that did not receive the energy management interventions. Section 3, which received the highest levels of intervention, also did not show a difference, however, we note that the average starting levels of the positive items (frequent breaks, quiet places to do work) were already quite high (4.13 and 4.08 out of 5, respectively), which made it difficult to demonstrate a statistically significant increase given our sample size. Section 3 also had moderate levels of multitasking, which did not show a significant change. Emotional energy was gauged in terms of the individual’s perception of their positive outlook and how others viewed their outlook, as well as the level of helpfulness to others. Interestingly, the only significant change in this dimension was in Section 3, which received the highest level of interventions regarding energy management. Unexpectedly, the significant changes in this dimension were negative, indicating lower levels of perceived positivity and perceived helpfulness. This result was somewhat puzzling and deserves further study. It is possible that the students had internalized the concept of self-energy management and were more focused on their individual energy, rather than in how others were affected. However, it is also possible that the students have increased their awareness of how their actions and attitudes affected others and became more self-critical as a result. We suggest future research to tease out which of these, or perhaps an alternate explanation, is behind this unexpected result. Perceptions regarding spiritual energy were described by gratitude, goal-setting, and vision-boarding. These items tap into an individual’s sources of motivation. While gratitude journals did not make an impact on any of the respondents, students exposed to the energy management intervention reported significant positive changes in the formulation of written goals and the use of vision boards. Creating a personal vision is one way to begin formation of a

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life purpose, which contributes to the spiritual dimension of energy management. Together, these two elements assisted students in identifying, clarifying, and codifying their personal goals, as well as creating a path towards achieving them. Limitations and Future Study Although the results of this study are very promising, there are limitations to the ability to generalize from these results. One important limitation is that participation in this study was completely voluntary and students received no incentive to participate. This may have resulted in respondent bias from self-selection, where students who were already more highly motivated and proactive were more likely to respond to both surveys. A second limitation comes from the timing of the survey administration, which may be confounding intervention effects with time/end-of-term effects, particularly in the items relating to time management, sleep, and exercise. Finally, the sample frame used was a sample of convenience, and may have underlying characteristics that drew students to a particular institution of higher learning. Suggestions for future study can strengthen the research by re-running the experiment at better time during the semester (possibly the first two week of class) with further thought on the impact of increasing the length of duration to maximize student impact. Additional suggestions for future study include the aforementioned longitudinal follow-up to explore the longevity of the effects, particularly for graduates entering the workforce. Energy management could also be a tool for individuals throughout their careers, and a study of the impact of these interventions at different ages and life stages would help pinpoint which elements might be emphasized differently throughout different career stages for continued positive impact on well-being and

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effectiveness. Finally, an extended respondent sampling that allows for further analysis of individual characteristics and their influence on the results of the interventions would also help tailor interventions for maximum impact. References Caudwell, P., Finlayson, G., Gibbons, C., Hopkins, M., King, N., Näslund, E., Blundell, J.E. (2013). Resting metabolic rate is associated with hunger, self-determined meal size, and daily energy intake and may represent a marker for appetite, The American Journal of Clinical Nutrition, 97:1, 7- 14. https://doi.org/10.3945/ajcn.111.029975 Ericsson, K. A., Krampe, R. T., & Tesch-Romer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100:3, 363-406. Loehr, J. & Schwartz, T. (2001). The making of the corporate athlete. Harvard Business Review, 79, 119-128. New York: Free Press. Loehr, J. & Schwartz, T. (2003). The Power of Full Engagement. New York: Free Press. Martin, W. (2018). This chart shows every major technological innovation in the last 150 years—and how they have changed the way we work. Business Insider. Retrieved from http://www.businessinsider.com/barclays-how-technology-has-changed-the-world-20184?utm_source=pocket&utm_medium=email&utm_campaign=pockethits Mason, S.T., Cater, E.W., Wang, C., Goodlett, B.D., Bedrosian, R., Nikolovski, J., Bucher, A. (2018). The Life Benefits of Managing Energy [White paper]. Retrieved from https://www.jjhpi.com/files/JHPI34144%20Managing%20Energy%20White%20Paper% 20NEW%20BRANDING%201-25-2018.pdf

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Neuman University. (2018). National Data on Campus Suicide and Depression. Retrieved from https://www.neumann.edu/life/counseling/mental_health/suicide/national_data.htm Sarner, M. (2018, 21 February). How burnout became a sinister and insidious epidemic. The Guardian. Retrieved from https://www.theguardian.com/society/2018/feb/21/howburnout-became-a-sinister-and-insidiousepidemic?utm_source=pocket&utm_medium=email&utm_campaign=pockethits Singer, J. (2017). Increase in Suicide Rates and Teen Depression. PsychCentral. Retrieved from https://psychcentral.com/lib/increase-in-suicide-rates-and-teen-depression/ Sprietzer, G. M., & Grant, T. (2012). Helping students manage their energy: Taking their pulse with the Energy Audit. Journal of Management Education, XX(X), 1-25. Schwartz, T. (2010). The way we’re working isn’t working. New York: Free Press. Schwartz, T., & McCarthy, C. (2007). Manage your energy, not your time. Harvard Business Review. Reprint R07108. Tavernise, S. (2016). U.S. suicide rate surges to a 30-year high. The New York Times, A1. Retrieved from https://www.nytimes.com/2016/04/22/health/us-suicide-rate-surges-to-a30-year-high.html Wamp, Z. (2009). Creating a culture of movement: The benefits of promoting physical activity in schools and the workplace. American Journal of Preventive Medicine, 36, 55-56.

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Tables & Figures Table 1: Respondent demographics

Section 1 2 3

Total Respondents 35 46 75

Male/Female Ratio (in %) 37/63 39/61 41/59

Average Age 19.7 19.6 19.8

Table 2: Methodology Overview

Section 1 2 3

Time 8:30 a.m. 9:30 a.m. 10:30 a.m.

Pre-Test Yes Yes Yes

Energy Audit No Yes Yes

Intervention No No Yes

Post-Test Yes Yes Yes

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Appendix A: Energy Management Survey Tool The purpose of this survey is to assess the effectiveness of “Taking your pulse with the Energy Audit”. Collected will be analyzed for reoccurring themes to validate theory. 1. Gender

Male = Code 1 Female = Code 2 Other = Code 3

2. Age

18 = Code 1 19 = Code 2 20 = Code 3 Over 21 = Code 4

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Part Time = Code 2 No Job = Code 3 3. 4. 5. 6. 7. What is your area of study:

Education = Code 1 Accounting = Code 2 Finance = Code 3 Marketing = Code 4 Management Information Systems = Code 5 Sports Administration = Code 6 Management = Code 7 Other = Code 8

5. Group Name

M/W 8:30 a.m. = Code 1 M/W 9:30 a.m. = Code 2 M/W 10:30 a.m. = Code 3

6. What grade do you think you will get in this class:

A = Code 1 B = Code 2 C = Code 3 D = Code 4 F = Code 5

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On a scale ranging from Strongly Agree to Strongly Disagree, please place an “X” in the box that best describes how you feel about your accelerated dissertation process. For statements for which you do not have any knowledge, or statements that do not apply to you, place an “X” in the box labeled NA for not applicable. (Managing Physical Energy, Questions 7-10) 7. I get 7-8 hours of sleep most nights Strongly Disagree 

Disagree 

Neutral 

Agree 

Strongly Agree 

N/A 

8. I eat breakfast every day Strongly Disagree Disagree  

Neutral 

Agree 

Strongly Agree 

N/A 

9. I eat 5 to 6 small meals a day Strongly Disagree Disagree  

Neutral 

Agree 

Strongly Agree 

N/A 

10. I work out at least 3 times a week (20-30 minutes) Strongly Disagree Disagree Neutral Agree    

Strongly Agree 

N/A 

(Managing Mental Energy, Questions 11-13) 11. I take regular breaks throughout the day Strongly Disagree Disagree Neutral   

Agree 

Strongly Agree 

N/A 

12. I find quiet places to do my work Strongly Disagree Disagree Neutral   

Agree 

Strongly Agree 

N/A 

13. I find myself multitasking rather than focusing on one task at a time Strongly Disagree Disagree Neutral Agree Strongly Agree     

N/A 

(Managing Emotional Energy, Questions 14-16) 14. I perceive myself to be a positive person most of the time Strongly Disagree Disagree Neutral Agree    

N/A 

Strongly Agree 

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15. Others perceive me to be a positive person most of the time Strongly Disagree Disagree Neutral Agree    

Strongly Agree 

N/A 

16. I often help others in need Strongly Disagree Disagree  

Agree 

Strongly Agree 

N/A 

(Managing Spiritual Energy, Questions 17-19) 17. I utilize a gratitude journal daily Strongly Disagree Disagree Neutral   

Agree 

Strongly Agree 

N/A 

18. I write out my goals Strongly Disagree Disagree  

Agree 

Strongly Agree 

N/A 

19. I have a vision board and post it where it can be easily viewed Strongly Disagree Disagree Neutral Agree Strongly Agree     

N/A 

(Conclusion, Questions 20-22) 20. I am more informed about leadership Strongly Disagree Disagree Neutral   

Agree 

Strongly Agree 

N/A 

21. I have learned tools and tricks to aide me Strongly Disagree Disagree Neutral   

Agree 

Strongly Agree 

N/A 

22. My level of stress and concern is lessened Strongly Disagree Disagree Neutral   

Agree 

Strongly Agree 

N/A 

Neutral 

Open Ended Question: 23. Average hours slept over the past week: 24. When is your energy the highest? What were you doing at those times? 25. When is your energy the lowest? What were you doing at those times? 26. What insights do you have about how to better manage your energy?

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MANUSCRIPT SUBMISSION GUIDE

GENERAL FORMATTING           

American Psychological Association (APA) Sixth Edition Publication Guidelines Microsoft-Word or compatible format (Do not send your manuscript as a PDF or it will be declined) Letter-size (8.5 x 11 inches) format 1.50 spaced text Times New Roman, 12-point font One-inch margins Two spaces following end punctuation Left justification Single column Portrait orientation First-person

MANUSCRIPT ORDER (Please Note: Do not add a running head or page numbers.)

Cover Page: (This page will be removed prior to peer review.)  Manuscript Title o The first letter of each major word should be capitalized. o The title should be in font size 20 and bold.  Author(s) Name o First Name, Middle initial(s), and Last name (omit titles and degrees) o The names should be font size 12. No bold  Institutional Affiliation o Education affiliation – if no institutional affiliation, list city and state of author’s residence o This educational affiliation should be on the line directly under the author’s name. o If there are multiple authors, please place a space between them each set of information (name and affiliation).  Author Biography o If there are multiple authors, please label this section Author Biographies

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o Please be sure to indent the paragraph before the biography begins. If there are multiple authors, please begin a new paragraph for each author. Manuscript: (From this point forward, please be sure your manuscript is FREE of any identifying information.) 



Abstract o The abstract (150-word maximum) should effectively summarize your completed research and findings. o The word “abstract” should be bold. Keywords o This line should be indented. The word “Keywords” should be italicized and followed by a colon and two spaces. o Following the two spaces, list 3 or 4 keywords or key phrases that you would use if you were searching for your article online. o Only the first key word should be capitalized. The actual keywords are not italicized. Body of Paper (sections) ALL of the following sections MUST be present or your manuscript WILL be rejected. o Introduction o Literature Review o Methodology o Results/Findings o Discussion References –this heading is NOT bolded within the manuscript o Manuscripts should be thoroughly cited and referenced using valid sources. o References should be arranged alphabetically and strictly follow American Psychological Association (APA) sixth edition formatting rules. o Only references cited in the manuscript are to be included. Tables and Figures o If tables and figures are deemed necessary for inclusion, they should be properly placed at the end of the text following the reference section. o All tables and figures should be numbered sequentially using Arabic numerals, titled, acknowledged, and cited according to APA guidelines. o If graphs or tables are too wide for portrait orientation, they must be resized or reoriented to be included. Appendices (if applicable) o Must be labeled alphabetically as they appear in the manuscript. o Title centered at the top.

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Volume 9 Page 106

Using Class Presentations to Educate Business Students About Accreditation and Assurance of Learning Katherine B. Hartman, Ohio University Mary L. Tucker, Ohio University James M. Andzulis, Ohio University Consideration of Information Overload in Financial Statement Note Disclosures of Canada Pre and Post IFRS Elsie Henderson, Mount Saint Vincent University Jeff McKinnon, Mount Saint Vincent University Factors that Influence a College Student’s Choice of an Academic Major and Minor Paul A. Stock, University of Mary Hardin-Baylor Eileen M. Stock, Department of Veterans Affairs Strategic Leadership Development through Energy Management Mary L. Tucker, Ohio University Andrew Pueschel, Ohio University Ana Rosado-Feger, Ohio University Amy Taylor-Bianco, Ohio University

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