Evaluation of Online Education: The Case of Cotabato State University- College of Business and Public Administration

1Emraida C. Ali, DBA,2Noraida C. Ali, PhD

Abstract: Thisutilized the descriptive-survey method to describe the level and to determine the relationship of the respondents’ online self-efficacy, asynchronous interaction, synchronous interaction, and their preference to online education. The results show that respondents’ level of online self-efficacy is manifested by their familiarity to use the Google classroom. Moreover, in terms of the interaction of the respondents in asynchronous, the respondents agree that it offers both an advantage and disadvantage. For instance, if they don’t have good internet connection, no available mobile data, or no power supply they can answer the offline activities at their own time and convenience. However, there are also instances in which they can hardly understand the activities posted in the Google class and teacher intervention is deemed necessary. On the other hand, the interaction of the respondents in synchronous, the respondents explained that they appreciate the online classes because they can listen to the lesson of the professor and its discussion. However, due to financial restrictions, the subscribed mobile data allowance is very limited since web conferencing needs more data usage. The level of preference of the respondents to online education or their desirability to online education shows that the respondents agree to some extent or desired to some extent on the flexibility of schedule and group interaction and collaboration for online education. The Pearson Correlation Coefficients for online self-efficacy is .510; asynchronous interaction is .619; and for synchronous interaction is .604. Using the stepwise method the asynchronous interaction and synchronous interaction are determined to be significantly related with online education. In the model, the R or correlation coefficient is .647 which denotes a moderate correlation.

Keywords: Online education, self- efficacy, asynchronous, synchronous.

I. Introduction

The coronavirus termed as the COVID-19 is a virus type that causes severe acute respiratory syndrome and is declared as a global crisis by the World Health Organization (WHO) on March 12, 2020 (WHO, 2020). This crisis has affected everyone in the globe including the educational institutions. Among any other sectors in the society, the education system is one of the greatly affected sectors brought by this pandemic and eventually requires the development and initiatives of appropriate innovative approaches and management policies (Farzad et al., 2020). Furthermore, it is estimated that 107 countries carried out closures of their educational institutions. These closures affected 862 million people are equivalent to 50% of the world student population (Viner et al., 2020).

In order to control the spread of the virus, several countries have adopted measures such as closures of shops, offices and educational institutions which require them to have continuity of work and activities from home (Anderson et al., 2020) In Pakistan, most of the colleges and universities have shifted to online education in which students are expected to learn through the use of technology (Rafiq et al., 2020).According to UNESCO (2020) the closure of the educational institutions resulted to the suspension of the face-to-face classes from child education to postgraduate studies. This situation greatly affects the performance and progress of the students in school. Thus, Distance Education is considered as an alternative for the traditional learning (Viner et al., 2020).

Distance education is categorized into three types of service delivery. The first type is the traditional distance education in which audio and videotapes or paper-based materials through postal service were utilized. Furthermore, the second type is the computer-based education in which hard drives or CD-ROM materials were used. And the last type of service delivery is the online education that is widely known as web-based education or internet-based education. It is clearly known that this type usually delivers distance education through the use of the internet (Moore &Kearsley, 1996).

However, it was reported that lack of IT infrastructure, insufficient IT knowledge, and limited electronic devices are some of the challenges that they encountered in online education (Rafiq et al., 2020). This is also true with the study of Zhang et al (2020) that this pandemic has brought challenges to online education such as unfavorable home environments. These scenarios are no different in the Cotabato State University-College of Business and Public Administration (CSU-BSBA) where online education has been implemented in substitute for the face-to-face classes since March 2020. For more than two years of implementation of online education in the CSU-BSBA, it is imperative to evaluate this type learning instruction. This evaluation covers the students’ online self-efficacy; interaction both in asynchronous and synchronous type; preference of online education; and the relationship of these variables Therefore, the results of the study can provide information regarding the contents of the evaluation and can become the basis for appropriate innovative learning strategies and management policies.

II. Conceptual Framework

Independent Variable

a. Online Self-Efficacy b. Asynchronous Interaction c. Synchronous Interaction

Dependent Variable

Preference to Online Education

This study utilized the Independent-Dependent Variable. The independent variables are the online self-efficacy and interaction both in asynchronous and synchronous activities. The online self-efficacy refers to the ability of the respondents to use online education. In addition, asynchronous interaction refers to the interaction that does not require real time while synchronous interaction required real time interaction between the students and the professors. The dependent variable is the respondents’ preference to online education or the desirability of the respondents to online education.

III. Statement of the Problem

This study evaluated the online education of the Cotabato State University-College of Business and Public Administration.

Specifically, it answered the following questions:

1. What are the profile characteristics of the respondents in terms of: a. Age b. Sex c. Degree Course

d. Major

e. Year Level

2. What is the level of the respondents’ online self-efficacy?

3. What is the level of the respondents’ asynchronous interaction?

4. What is the level of the respondents’ synchronous interaction?

5 What is the level of the respondents’ preference to online education?

6. Is there a significant relationship between the respondents online self-efficacy, asynchronous interaction, synchronous interaction and preference to online education?

IV. Research Methodology

This study utilized the descriptive-survey method to describe the level of the respondents’ level of online selfefficacy, level of asynchronous interaction, level of synchronous interaction, and level of preference to online education Moreover, the relationship of these variables was also determined leading it to become correlational study. The respondents of the study were the 254 students of the Cotabato State University-College of Business Administration enrolled in the First Semester, School Year 2020-2021. A modified survey questionnaire was used as a major tool in data gathering; survey was conducted using the Google form. Moreover, selected students were interviewed for verification of responses. In terms of ethical consideration, before the conduct of the survey, the purpose of the research was explained to the respondents and they were not forced to participate in the survey. All the data that were gathered were treated objectively.

V. Summary of Findings and Conclusion

1. Profile characteristics of the respondents reveal that majority of them are 18-22 years old; female; taking up Bachelor of Science in Business Administration; and in forth year level.

2. For the online self-efficacy, respondents agree that they are familiar with the usage of Google classroom. Based on the interview conducted with some of the students, they are familiar with Google classroom because even before the pandemic some of their instructors are already using it and they have easy access of the Google classroom because they can download it to their smart phones. On the other hand, the respondents’ agree to some extent or they are familiar with some of the features of the web browsers; Google meet; emails; texts from the websites; interest search, and downloading and saving text from the websites.

3. For interaction of the respondents in asynchronous which means that the students do not need to interact with their professors in real time, the respondents agree to some extent. It is supported and verified through the interview conducted that offline activities are sometimes having an advantage and disadvantage. For example, if they don’t have good internet connection, no available mobile data, or no power supply they can answer the offline activities at their own time and convenience. However, there are also instances in which they can hardly understand the activities posted in the Google class and teacher intervention is deemed necessary.

4. For interaction of the respondents in synchronous which means that the students need to interact with their professors in real time. It is evident that the respondents agree to some extent on all of the statements for synchronous interaction. Based on the interview conducted with some of the respondents, they explained that they appreciate the online classes because they can listen to the lesson of the professor and its discussion. However, due to financial restrictions, the subscribed mobile data allowance is very limited since web conferencing needs more data usage. For most of the time, they have to prioritize what subject to attend to in online classes.

5 For level of preference of the respondents to online education or their desirability to online education, the respondents agree to some extent or desired to some extent on the flexibility of schedule and group interaction and collaboration for online education. However, the respondents are neutral or they neither desired nor not desired the home atmosphere and fitness of online classes. Based on the interview conducted with some of the respondents, they would rather be in the classroom with the presence of their professors and classmates. But they also acknowledge that due to the pandemic, the school has adopted this online education.

6.The Pearson Correlation Coefficients for online self-efficacy is .510; asynchronous interaction is .619; and for synchronous interaction is .604. The three coefficients suggest a moderate relationship with online education. Moreover, all of the correlation coefficients are positive, it simply means that for every unit increase in each of the independent variables there is a corresponding increase in the dependent variable. In addition, the significance of the correlations of the independent variables and dependent variable is also determined. Since the p-values are less than the significance level for the three independent variables such as the online self-efficacy, asynchronous interaction, and synchronous interaction, it is therefore concluded that the correlation for these three variables is significantly differ from zero.

7. The asynchronous interaction and synchronous interaction are determined to be significantly related with online education. In the model, the R or correlation coefficient is .647. This denotes the strength of association of the two significant independent variables to the dependent variable which is the online education. The R or correlation coefficient falls under the range of .40-.70 with the descriptive equivalent of moderate correlation or moderate relationship (Hair et al., 2014). In connection, the R square of the coefficient of determination is .418 which indicates that 41.8% of the variation of online education may be explained by the variation of the asynchronous interaction and synchronous interaction. Furthermore, the adjusted R square is .414 which implies that 41.4% of the variation in the dependent variable (online education) may be explained by the variation of the independent variables as adjusted for the number for independent variables being measured.

8. The F value of the model is90. 265 and considered significant with p-value < .05. This implies that the independent variables asynchronous interaction and synchronous interaction are significantly related to online education. Having this result, the null hypothesis is not accepted.

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