EVALUATING THE IMPACT OF SELF-EFFICACY ON ONLINE LEARNING OUTCOMES OF STEM COLLEGE STUDENTS
DOI:
https://doi.org/10.17501/24246700.2022.8104Keywords:
Self-efficacy, Learning Outcomes, Online EducationAbstract
With the development of Internet globalization and the ongoing pandemic, online education has become the mainstream of higher education. While endowed with great convenience and efficiency, virtual education was also doubted of its impact on self-efficacy and academic performance of college students. This study aims to analyze the mediating effect of self-efficacy on the learning outcomes of college students majoring in STEM (science, technology, engineering and mathematics). This is achieved through reviewing mainstream studies on self-efficacy and learning outcomes to descriptively analyze the correlation between them, especially among college STEM students who received online education. Under the theoretical guidance of Bandura's ternary interaction theory and Self-Determination Theory, our study investigated diverse variables, including the level of self-efficacy and learning outcomes of college STEM students, by a questionnaire with 36 items from existing scales. Through random sampling, a total of 250 college students from 53 universities in 61 cities in China participated in the survey. The primary data were analyzed using linear regression, along with reliability and validity analysis in SPSS. Findings illustrated that college STEM students' self-efficacy in online learning has a positive and noteworthy impact on learning outcomes. Findings of our study have broad implications for theory and practices. This paper made an effort to provide possible applications and avenues to encourage the overall development of online education in STEM fields by examining self-efficacy in such context. Meantime, it offered recommendations on designing appropriate learning methods to facilitate college students learning motivation and maximize their full potential to improve online learning systems.
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Abdullah, F., Ward, R., & Ahmed, E. (2016). Investigating the influence of the most commonly used external variables of TAM on students' Perceived Ease of Use (PEOU) and Perceived Usefulness (PU) of e-portfolios. Computers in Human Behavior, 63, 75–90.
Al-Hattami, A. A. (2020). E-Assessment of Students Performance During the E-Teaching and Learning. International Journal of Advanced Science and Technology, 29(8s), 1537–1547.
Alqahtani, A. Y., & Rajkhan, A. A. (2020). E-learning critical success factors during the covid-19 pandemic: A comprehensive analysis of e-learning managerial perspectives. Education Sciences, 10(9), 216.
Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist's companion. Princeton, NJ: Princeton University Press.
Aslanian, C. B., & Clinefelter, D. L. (2014). Online college students: Comprehensive data on demands and preferences. Louisville, KY: The Learning House, Inc.
Beck, N. (2019). Estimating Grouped Data Models with a Binary-Dependent Variable and Fixed Effects via a Logit versus a Linear Probability Model: The Impact of Dropped Units. Political Analysis, 28(1), 139-145. https://doi.org/10.1017/pan.2019.20
Bergeler, E., & Read, M. F. (2021). Comparing Learning Outcomes and Satisfaction of an Online Algebra-Based Physics Course with a Face-to-Face Course. Journal of Science Education and Technology, 30(1), 97. https://doi-org.ez.xjtlu.edu.cn/10.1007/s10956-020-09878-w
Bradley, R. L., Browne, B. L., & Kelley, H. M. (2017). Examining the Influence of Self-Efficacy and Self-Regulation in Online Learning. College Student Journal, 51(4), 518–530.
Brown, J. C., & Park, H. S. (2016). Longitudinal student research competency: Comparing online and traditional face-to-face learning platforms. Advances in Social Work, 17(1), 44–58.
Cavanaugh, J. K., & Jacquemin, S. J. (2015). A large sample comparison of grade-based student learning outcomes in online vs. face-to-face courses. Online Learning, 19(2), n2.
Chang, F. D., & Chien, C. W. (2015). Determining the relationship between academic self-efficacy and student engagement by meta-analysis. 2nd International Conference on Education Reform and Modern Management, Hong Kong. https://doi.org/10.2991/ermm-15.2015.37.
Choi, D. H., Kim, J., & Kim, S. H. (2007). ERP training with a web-based electronic learning system: The flow theory perspective. International Journal of Human-Computer Studies, 65(3), 223–243.
Deci, E. L., & Ryan, R. M. (1985). Intrinsic Motivation and Self-determination in Human Behavior. Plenum Press.
Dunn, R., Beaudry, J. S., & Klavas, A. (2002). Survey of Research on Learning Styles. California Journal of Science Education, 2(2), 75-98.
Gomila, R. (2021). Logistic or linear? Estimating causal effects of experimental treatments on binary outcomes using regression analysis. Journal of Experimental Psychology: General, 150(4), 700–709. https://doi-org.ez.xjtlu.edu.cn/10.1037/xge0000920
Helms, J. L. (2014). Comparing student performance in online and face-to-face delivery modalities. Journal of asynchronous learning networks, 18(1), n1
Hung, M. L., Chou, C., Chen, C. H., & Own, Z. Y. (2010). Learner readiness for online learning: Scale development and student perceptions. Computers & Education, 55(3), 1080–1090.
Jeong, J. S., Gómez-Gonzalez, D., Cañada-Cañada, F., Gallego-Pico, A., & Bravo, J. C. (2019). Effects of active learning methodologies on the students' emotions, self-efficacy beliefs and learning outcomes in a science distance learning course. Journal of Technology and Science Education, 9(2), 217-227. https://doi.org/10.3926/jotse.530.
Kim, B., & Park, M. J. (2018). Efect of personal factors to use ICTs on e-learning adoption: Comparison between learner and instructor in developing countries. Information Technology for Development, 24(4), 706–732.
Kustyarini, K. (2020). Self-Efficacy and Emotional Quotient in Mediating Active Learning Effect on Students' Learning Outcome. International Journal of Instruction, 13(2), 663–676.
Lack, K. A. (2013). Current Status of Research on Online Learning in Post-Secondary Education. Ithaka S+R, zuletzt geprüft am.
León, J., Núñez, J. L., & Liew, J. (2015). Self-determination and STEM education: efects of autonomy, motivation, and self-regulated learning on high school math achievement. Learning and Individual Differences, 43, 156–163.
MacKenzie, L. M. (2019). Improving Learning Outcomes: Unlimited vs. Limited Attempts and Time for Supplemental Interactive Online Learning Activities. Journal of Curriculum and Teaching, 8(4), 36–45.
Mathew, N. G., Sreehari, P., & Al-Rubaat, A. M. (2019). Challenges and implications of virtual e-learning platform in EFL context: Perceptions of teachers. International Journal of English Language Teaching, 7(2), 100–116.
Means, B., Toyama, Y., Murphy, R., & Baki, M. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. Teachers College Record, 115(3), 1–47.
Mosquera, L. H. (2017). Impact of implementing a virtual learning environment (vle) in the ef classroom. Íkala: Revista de Lenguaje y Cultura, 22(3), 479–498.
Neuhauser, C. (2002). Learning Style and Effectiveness of Online and Face-to-Face Instruction. American Journal of Distance Education, 16(2), 99–113.
Noreen, S., Hasan, A., Batool, I., & Ali, A. (2018). The Impacts of Academic SelfEfficacy on Academic Outcomes: The Mediating effect of Student Engagement. International Journal of Academic Research in Business and Social Sciences, 8(11), 315–327. doi: 10.6007/IJARBSS/v8-i11/4904.
O'Hara, R. E., & Sparrow, B. (2019). A Summer Nudge Campaign to Motivate Community College STEM Students to Re-enroll. AERA Open, 5(3).
Olson, C. B., Land, R., Anselmi, T., & Aubuchon, C. (2010). Teaching secondary english learners to understand, analyze, and write interpretive essays about theme. Journal of Adolescent & Adult Literacy, 54(4), 245-256.
Pathak, B. K. (2019). Study of e-Learning Outcomes: The Role of Late-Registration and Self-Selection. E-Journal of Business Education and Scholarship of Teaching, 13(1), 13–19.
Shen, D., Cho, M. H., Tsai, C. L., & Marra, R. (2013). Unpacking online learning experiences: Online learning self-efficacy and learning satisfaction. The Internet and Higher Education, 19, 10–17.
Schoenfeld-Tacher, R., McConnell, S., Graham, M. (2001). Do no harm-A comparison of the effects of on-line vs. traditional delivery media on a science course. Journal of Science Education and Technology, 10(3), 257–265.
Tanyel, F., & Griffin, J. (2014). A ten-year comparison of outcomes and persistence rates in online versus face-to-face courses. Retrieved from https://www.westga.edu/~bquest/2014/onlinecourses2014.pdf
Wu, Y. (2020). The Enlightenment of Bandura's Social Learning Theory to Children's Moral Education. Journal of Changchun Education Institute, 36(9), 74–80.
Xie et al. (2011). Research on the Structural Influencing Factors and Cultivation Strategies of College Students' Self-efficacy in Online Learning. E-Education Research, 10(30), 30-34. Retrieved from https://www-wanfangdata-com-cn.ez.xjtlu.edu.cn/sns/perio/dhjyyj
Xu, D., & Jaggars, S. S. (2013). The impact of online learning on students' course outcomes: Evidence from a large community and technical college system. Economics of Education Review, 37, 46–57.
Yi, R., & Rui, R. D. (2011). Research on the Correlation between the Network Learning Environment and College Students' Learning Self-efficacy. Distance Education in China, 10, 50–53. https://doi-org.ez.xjtlu.edu.cn/10.3969/j.issn.1009-458X.2011.10.015
Yokoyama, S. (2019). Academic self-efcacy and academic performance in online learning: A mini review. Frontiers in Psychology, 9, 2794.
Zhang, H. Y., & Guo G. S. (2019). An Empirical Study on the Mechanism of Learning Outcomes among Science and Engineering University Students. University Education Science, 3(3), 68–75. https://doi-org.ez.xjtlu.edu.cn/10.3969/j.issn.1672-0717.2019.03.014
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