Accommodating and Validating a Measure of Learning Environments to Teacher Training Programs by menez

Education Research Frontier December 2015, Volume 5, Issue 4, PP. 113-121

Accommodating and Validating a Measure of Learning Environments to Teacher Training Programs Bing Li College of International Studies, Southwest University, Chongqing, 400715, China

Abstract The principal objective of the present research was to accommodate and validate an instrument of learning environments to the context of teacher training programs. To this end, the 32-item Inventory for Students’ Perceived Learning Environment (ISPLE) was adopted and adapted in a series of three studies with three independent samples (Year 2-Year 4 prospective teachers) from a teachers’ university in Mainland China. Based on the findings from both exploratory factor analysis and confirmatory factor analysis, modifications were executed on the ISPLE, resulting in a shortened 28-item factor solution. Reports of psychometric properties evidenced that the accommodated ISPLE is an adequate measure to capture prospective teachers’ perceptions of their learning environments. Implications for future studies are also talked about. Key Words: ISPLE; Teacher Training Programs; Modifications

1 INTRODUCTION Approximately, an average of 20,000 hours is spent in classrooms before students graduate from university (Fraser, 2001, 2012). Such is likewise the case of prospective teachers undergoing their teacher training programs. Concerns over learning environments of teacher training programs are hence necessitated. Also as documented, learning environments, among the rest, is of central importance for teacher identity development, simply because it is where prospective teachers learn to become teachers (Ottesen, 2006). For years, the idea of constructing appropriate learning environments for university-based teacher training programs has been practiced (Roberts & Graham, 2008). Notwithstanding the importance of learning environments attached to teacher training programs, there is still a lack of effective measure. The present research thus is intended to accommodate and validate a measure of general learning environments to teacher training programs. To this end, a series of three studies were conducted with three independent samples in Mainland China. Multiple methods of validation were employed, resulting in a comprehensive and reliable measure of learning environments of teacher training programs.

2 LITERATURE REVIEW Learning environments are generally conceived as “the social, psychological and pedagogical contexts in which learning occurs and which affect student achievement and attitudes” (Fraser, 1998, p. 3). Broadly speaking, on-or off-campus contexts constitute learning environments, such as school, home, museums, TV, internship units, and fieldwork trips. In a narrow sense, learning environments are meant to only consist of classroom-level and schoollevel environment. For university-based teacher training programs, the major social function is supposedly “not only in enhancing the quality of practitioners in teaching, but also in contributing to the development of the public status of the occupation of teaching” (Sockett, 2008, p. 45). However, teacher training programs have been widely criticized for the “weak connection between theory and practice” and “little attention to the social and cultural context of schooling” (Lauriala, 2000, p. 45). In this case, it is in the interest of the present research to only look at the university-based learning environments (school-level and classroom-level) where teacher training programs are going on. - 113 www.erfrontier.org

Across years, the notions on the nature of the effective learning and the embedded learning environments have evolved, in parallel to changed educational goals from low-literacy to high-literacy (De Corte, Verschaffel, & Masui, 2004). The mainstream trends are behaviorism (Birzer, 2003), cognitivism (Collins, Brown, & Newman, 1989), and constructivism (Şengül, Katranci, & Bozkuş, 2013). Grounded in constructivism, De Corte (1995) drew a good definition of what is meant by effective learning: “It is a constructive, cumulative, self-regulated, goal-oriented, situated, collaborative, and individually different process of knowledge and meaning building” (p. 40). It follows that an effective and powerful environment is “learner-centered, knowledge-centered, assessment-centered, and community-centered” (De Corte et al., 2004, p. 336). Based on this, Fan and Zhang (2013) synthesized four most-talked-about principles that characterize effective and powerful learning environments: constructivist learning, student autonomy, interaction and cooperation, and clear goals and coherence of curricula.

2.1 Constructivist Learning In contrary to the traditional perspective of mere knowledge transmission, constructivist learning focuses on knowledge construction, competencies, and social exchange. Mayer, Moreno, Boire, and Vagge (1999) advocated helping students construct integrated mental models that were transferrable to solving emerging problems. Also, Vermunt (2003) argued that students’ high-quality learning should be emphasized for the attainment of conceptual understanding, higher-order skills in cognition and metacognition, self-regulatedness, and self-directedness. Likewise, Sessoms (2008) insisted that students should be “active participants” (p. 89) to complete the knowledge construction sequence, to develop the necessary schemata for new learning, and to learn by doing, for the equilibrium outlined by Piaget (1954). Therefore, in this learning environment, students are required to reach for new knowledge through practice with prior knowledge and experiences, rather than through spoon-fed ideas and information (Hursen & Soykara, 2012). Additionally, students should be allowed to participate in various activities such as internships, discussion forums, and fieldwork trips. In so doing, students could experience in person the whole process of knowledge construction (Fan & Zhang, 2013).

2.2 Student Autonomy Constructivist learning environment is to encourage students’ emotional involvement, to allow students time for selfreflection, and to bring students a sense of growing personal autonomy (Flynn & Soini, 2000). Holec (1981) contended that students should be held accountable for all the decisions in relation to every aspect of learning. Fredricks, Blumenfeld, and Paris (2004) took student autonomy as three types of engagement in school-related issues: behavioral engagement, emotional engagement, and cognitive engagement. Cognitive engagement was highlighted of the three in that this engagement was related to motivational and self-regulated learning, which demanded students to exert efforts for understanding of complex ideas and mastery of sophisticated skills. Thus, teachers in a constructivist learning environment are highly suggested to: a) accept and foster learner-centeredness in teaching and learning, through encouraging students to autonomously construct their skills and knowledge drawing on their own understandings, beliefs, and practice; b) help students be responsible for their own learning by allowing them to follow their own learning styles in the whole learning process; and c) adopt an autonomy-supportive motivating style where students can experience autonomy that enables them to take full charge of their own learning (Ryan & Deci, 2000).

2.3 Interaction and Cooperation Generally, learning environment where problem solving and knowledge discovery are valued often requires teachers to facilitate learning. In a constructivist learning environment where facilitation is more favored, an emphasis is thus placed on interaction and cooperation, from both peers and teachers. With respect to peers, collaboration and peer review are central to the learning experiences. Thus, learning within collaborative relationships is advocated as a function of equal participation among all learners. Similarly, cohort communities need to be established and maintained in that successful cohorts are believed to generate a sense of belonging among members, and more importantly to support knowledge sharing, risk taking, mutual respect, and critical reflection (Brooks, 1998). As - 114 www.erfrontier.org

regards the roles of teachers, De Corte (2004) stressed a “partnership” (p. 373) between teachers and the learners. Moreover, Emdin (2012) put forward three Cs in building a constructivist learning environment. That is, cogenerative dialogues (structured dialogues between students and teachers on a regularly basis for jointly generating ideas or findings), co-teaching (a practice allowing both teachers and students to take on the role of teacher in turn), and cosmopolitanism (an ideal scenario where the above mentioned two Cs, along with co-responsibility and covaluing for one another, becomes daily practices).

2.4 Clear Goals and Coherence of Curricula Criticisms on constructivist learning mainly fall on the minimal guidance in discovery learning (Mayer, 2004). It is far from the case, however, in that a constructivism-based learning environment neither totally leaves students alone nor provides zero guidance; instead it is much goal-oriented and coherent in nature. First, a goal theory is emphasized in constructivist learning with task-focus and consistent measurements (Fredricks et al., 2004). This is in line with Vygotsky’s (1978) zone of proximal development where students are challenged by problems proximal to, yet slightly above, their current developmental levels. Obviously, clear goals need to be finely anchored for this attainment. Second, it is well supported that students learn better when encountering consistent ideas in a constructivist learning continuum (Bransford, Brown, & Cocking, 2000). Therefore, in the design and implementation of a curriculum in constructivist learning, there are two kinds of coherence that need to be taken into account: conceptual coherence and structural coherence. Conceptual coherence is referred to as the consistency in a shared concept that underlies purposefully intertwined theories and practice across learning experiences. Whereas, structural coherence is intended to establish courses that build on and reinforce one another in sequence, through organizing and tuning courses and students’ practice in consistence with a central concept.

3 METHODOLOGY 3.1 Participants In Study 1, participants were 236 (45 male and 191 female) prospective teachers, aged 21.57 ± .51, in their third year of their teacher training program at a teachers’ university in Mainland China. By then, those participants had all completed their one-year-long teaching practicum. In Study 2, participants were 206 (33 male and 173 female) year 2 prospective teachers from the same teachers’ university mentioned above, aged 20.48 ± .66. In Study 3, participants were 1,062 (358 male and 704 female) prospective teachers, aged 22.74 ± .65, in the last year of the teacher training program.

3.2 Instrument The Inventory for Students’ Perceived Learning Environment (ISPLE) (Fan, 2013) was adopted in the present research. Most of the previously existing inventories for learning environments were highly limited either to one specific course or to teaching-related variables (e.g., teaching methods and classroom management) (Centra, 1993). Differently, as a conceptualization of constructivism, the ISPLE is intended to capture perceived campus-wide learning environments (De Corte, 2003), composed of eight respects: 1) goal-oriented curriculum; 2) student autonomy; 3) assignment and assessment; 4) teacher-student interaction; 5) student-student cooperation; 6) peer effect; 7) learning facilities; and 8) constructivist learning. In the present research, the ISPLE helped to collect retrospective data concerning such early university learning experiences as in and out of classrooms, with or without appropriate use of digital media, and sufficient or lacking in facilities. The ISPLE is a 32-item self-report inventory. These items were selected from an array of established inventories, for example, The Experiences of Teaching and Learning Questionnaire (Entwistle, McCune, & Hounsell, 2003), Inventory of Perceived Study Environmen (Wierstra, Kanselaar, Linden, & Lodewijks, 1999), and Learning Environment Inventory (Fraser, 1982). Participants’ responses were rated on a seven-point Likert scale, where “1” represents “not at all well” and “7” “extremely well”. High scores in the eight respects indicate highly constructivist learning environments. Two sample items are as follows: 1) “The teaching helps me to think about the evidence underpinning different views” (constructivist learning); and 2) “The courses are well organized in a way that makes - 115 www.erfrontier.org

sense to me” (goal-oriented curriculum). Though rather new, the ISPLE exhibited good reliability and validity. In Fan and Zhang’s （2013） study conducted in Shanghai and Nanjing in Mainland China, the theoretically proposed eight-factor structure was confirmed, while reliability ranged from .63 (learning facilities) to .79 (student-student cooperation).

4 RESULTS 4.1 Study 1 In Study 1, an exploratory factor analysis (EFA) was executed using the Principal Components Analysis (PCA) via varimax rotation. Item loadings lower than an absolute value of .40 were suppressed. As a result, seven factors, rather than eight as theoretically conjectured, were extracted based on eigenvalue-greater-than-1 rule. Approximately 59.77% of the variance in learning environments could be accounted for by these seven factors. Specifically, Factor 3 comprised items for peer effect and student-student cooperation, which made sense in that these two factors were both theoretically proposed to measure emotional ties among students. Factor 4 gathered items for constructivist learning, goal-oriented curriculum, and assignment and assessment. This also made sense because these three factors all theoretically address learning process. The remaining five factors looked unintelligible, however. For example, Factor 1 attracted items from all theoretically proposed factors, while Factors 2, 6, and 7 contained one to four heavily cross-loaded items (e.g., Item 4 with cross loadings of .50 and .50). This problem in item-factor solutions might have partly arisen from contextual differences (Finney, Pieper, & Barron, 2004). The ISPLE was initially developed for learning environments in general, whereas the present research was set in a teachers’ university. The ISPLE apparently needed modifying and re-piloting in a different sample. A careful examination of item communalities indicated no need for item removal (all>.40), while opinions from participants necessitated rewording of some items. One major revision was to limit the scope of the ISPLE to learning environments teacher training programs only (Fan & Zhang, 2013). In the context of the present research, all courses-related statements were reworded to teacher training courses or teacher training. Another major revision concerned the improvement of clarity and relevance (Rattray & Jones, 2007). Take, for example, Item 1 and Item 29: 

Item 1: We are given clear information about the aims and objectives of the courses.



Revised version: We are given clear information about the aims and objectives of the teacher training courses.

Regarding reliability, Cronbach’s alpha coefficients of the eight subscales in Study ranged from .61 (learning facilities) to .76 (peer effect).

4.2 Study 2 In Study 2, another EFA was conducted on the data gather based on the refined ISPLE, using the PCA with varimax rotation. The KMO value reached .84 while Bartlett’s test of sphericity was significant (df=496; p<.001), indicating that the data set was fit for a factor analysis. Eight factors with absolute eigenvalues over 1.0 were generated, which was exactly consistent with the theoretical conjecture (Fan & Zhang, 2013). Approximately 65.87% of the variance in learning environments could be explained by this factor structure. More importantly, all the 32 items loaded on where they were theoretically expected. Only one item (Item 20) was found to have cross-loaded on two factors (i.e., constructivist learning and assignment and assessment). This cautioned the researcher to take another careful look at this item later. Alpha coefficients increased appreciably in Study 2 when the revised ISPLE was adopted, ranging from 71 (student autonomy) to .85 (assignment and assessment). However, should Item 25 been deleted, as shown in item-total statistics, the subscale for learning facilities would see a rise in the alpha coefficient. A particular note should be added regarding a problem with multicollinearity for the ISPLE. This problem was diagnosed in the subscales for constructivist learning, peer effect, and student-student cooperation. In the first place, examination on the Tolerance values raised such suspicion. In the regression model involving learning environments - 116 www.erfrontier.org

and job satisfaction, adjusted R2 was .19, suggesting that acceptable Tolerance value should be larger than .81. However, the obtained Tolerance values fell into the range of .37-.56. Secondly, the subscale for constructivist learning was highly correlated with all the other subscales (r=.55-.68) in the ISPLE, and so was the subscale for peer effect with that of student-student cooperation (r=.67) (Cohen, 1988).

4.3 Study 3 In Study 3, the problem with multicollinearity was checked immediately after data collection. As can be seen in Table 1, medium correlations were detected between the subscale for constructivist learning and the others this time (r=.46-.55). This subscale was thus retained, based on Berry and Friedman’s (1985) contention. TABLE 1 PEARSON CORRELATION COEFFICIENTS OF THE EIGHT-DIMENSION ISPLE (TIME 1) 1.Goal-oriented curriculum 2. Student autonomy 3. Assignment and assessment 4. Teacher-student interaction 5. Student-student cooperation 6. Peer effect 7. Learning facilities 8. Constructivist learning

1 2 3 4 5 1.00 .56** 1.00 .44** .39** 1.00 .52** .44** .40** 1.00 .42** .45** .39** .50** 1.00 .43** .42** .35** .47** .60** .37** .35** .35** .40** .34** .55** .54** .46** .51** .51** Notes: **p< .01 (2-tailed); Listwise N=1,062.

1.00 .38** .51**

1.00 .51**

1.00

The subscale for peer effect, however, was again highly correlated with that of student-student cooperation (r=.60). As suggested by Field (2009), these two subscales were aggregated into a composite one, labeled peer morale. The most straightforward theoretical rationale was that these two subscales in nature denoted one common underlying theoretical concept—peer interaction and effect (Fan & Zhang, 2013). Following Marsh, Wen, and Hau’s (2006) practice, the exact procedure was forming four item parcels by taking the averages of the four pairs of items from the original two subscales. This resulting seven-dimension ISPLE was henceforth used for factor analysis. TABLE 2 FACTOR LOADINGS OF THE 28-ITEM ISPLE IN STUDY 3 Scale Peer Morale

Item

19 17 20 18 Assignment & Assessment 10 11 9 12 Goal-oriented curriculum 2 1 3 4 Teacher-student interaction 15 16 14 13 Constructivist learning 28 25 26 27 Learning facilities 23 24 21 22 Student autonomy 6 5 8 7

Factor 1 .882 .791 .785 .776

.903 .808 .613 .564 .984 .744 .671 .564 .829 .794 .706 .637 .870 .775 .764 .613 .807 .720 .655 .400 .970 .674 .462 .424 - 117 www.erfrontier.org

For the EFA, the Maximum Likelihood was used to extract factors via promax rotation. The eigenvalue-greater-than1 rule was adopted. A seven-factor structure was yielded as a result, accounting for 59.16% of the variance in learning environments. Moreover, neither dual-loaded item nor unexpected factor was detected, as shown in Table 2. For the CFA, five highly recommended fit indices were adopted (Meyers, Gamst, & Guarino, 2013): the chi-square (x2), the goodness-of-fit index (GFI), the root mean square error of approximation (RMSEA), the comparative fix index (CFI), and the normed fix index (NFI). The seven-factor model of the ISPLE fitted the data well, x2(329, N=1062)=1294.27, p<.001. Modifications were performed post hoc as suggested, where error covariance of three pairs of items (i.e., Items 1 and 2; Items 7 and 8; Items 21 and 22) were set free to reduce the x2 values. This respecified model yielded better fitting results, x2(326, N=1062)=1048.27, p<.001, GFI=.95, RMSEA=.05, CFI=.95, and NFI=.93 (see Figure 1). The values of reliability were: .85 (goal-oriented curriculum), .76 (student autonomy), .84 (assignment and assessment), .85 (teacher-student interaction), .90 (peer morale), .78 (learning facilities), and .86 (constructivist learning). These values indicated sound reliabilities. .54

.37

.43

.57

.58

.53

.59

.54

.37

A10

.22

A11

.57

A12

.41

A13

.42

A14

.43

A15

.34

A16

.27

A17

.33

A18

.26

A19

.37

A20

.75

A21

.67

A22

.36

A23

.51

A24

.47

A25

.38

A26

.38

A27

.38

A28

.68 .80 .79 .76

.66 .66 .68 .64

.68 .79 .88 .68

.77 .75 .76 .81

.85 .82 .86 .79

.50 .63 .80 .70

G-OC

1.00

T-SI

1.00

.73 .79 .79 .79

FIGURE 1 CONFIRMATORY FACTOR MODEL FOR THE ISPLE (TIME 1) Notes: G-OC=goal-oriented curriculum; SA=student autonomy; AA=assignment and assessment; T-SI=teacher-student interaction; PM=peer morale; LF=learning facilities; CL=constructivist learning.

5 DISCUSSION AND CONCLUSION Knowledge of prospective teachersâ&#x20AC;&#x2122; learning environments is for the benefit of teachersâ&#x20AC;&#x2122; own professional lives, - 118 www.erfrontier.org

their students, and education in general (Day, 2012). This knowledge is also what the accommodated ISPLE is intended for in the present research, through adopting and adapting it to the specific environments where teacher training programs are usually happening. Results evidenced that the ISPLE, after being accommodated, was reliable and valid in capturing prospective teachers’ perceptions of teacher training environments. The ISPLE itself had exhibited sound psychometric properties in the seminal study where it was established (Fan & Zhang, 2013). However, the present research showed that the original ISPLE did not fit well into the context of teacher training programs. The results of Study 1 provided a messy factor solution from the EFA, suggesting that refinement should be executed for the ISPLE to be applicable to the teacher training context. Two major instrument modifications were hence exercised to the original ISPLE. One was transforming the general scope to the specific teacher training context. This was achieved by rephrasing the wording course in all items to teacher training courses or teacher training. In so doing, participants were able to respond to specific courses that were intended to prepare them for teachers from the other courses in general, such as physical education, music, or miscellaneous selective courses. The other major instrument modification was aggregating two subscales (i.e., peer effect and student-student cooperation) to make a composite but more sensible subscale (i.e., peer morale). This, on the one hand, helped to reduce the risk of multicollinearity, avoiding the annoying inflation of familywise errors; on the other hand, the resulted 28-item factor solution of the ISPLE was more concise and participant-friendly. The accommodated ISPLE might also be applicable to different prospective teacher populations. Across multiple samples (from Year 2 onward to Year 4 prospective teachers), consistently high internal reliabilities of the accommodated ISPLE were identified with Cronbach’s alphas, indicating that the reliabilities obtained did not capitalize on chance. This is to imply that the ISPLE might be able to assist in garnering both cross-sectional and longitudinal data. There were limitations to the present research, however. It is hoped that in future studies, longitudinal data can be collected among the same samples to assess the growth trajectories in prospective teachers’ perceptions of their learning environments. It is also hoped that the accommodated ISPLE can be validated against the data collected using other methods, such as prospective teachers’ ratings for their teachers and principals’ leadership styles.

ACKNOWLEDGMENT This work was supported by “the Fundamental Research Funds for the Central Universities” (SWU1509457).

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AUTHORS Bing Li (1977-), lecturer in the College of International Studies of Southwest University, China. Major research interests of Li are teacher professional development, occupational and organizational psychology, and the impact of social environment on learning and teaching, and intellectual styles. E-mail: daniel41777@hotmail.com

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