Identifying efficient determinant factors affecting students’ achievement in learning computer programming

Rong  Phoophuangpairoj

Authors

Rong Phoophuangpairoj Department of Computer Engineering, College of Engineering, Rangsit University, Patumthani 12000, Thailand

Keywords:

self-regulation, satisfaction, usefulness, memory strategy, mobile phone and tablet use, computer programming, achievement

Abstract

This research investigates factors affecting perceived satisfaction, usefulness, self-regulation, and achievement in a computer-programming learning environment. The findings will be useful to educators and administrators to create learning environments, which positively affect learners’ attitudes and behaviors. One hundred university engineering students were asked to answer a questionnaire after three months of studying a computer programming course. Pearson bivariate correlations and multiple linear regression analysis were applied to analyze the data. The results show that perceived satisfaction can be determined by the interactive learning environment and perceived usefulness. Perceived usefulness is a determinant factor of perceived satisfaction. Learners’ perceived satisfaction, perceived usefulness and an interactive learning environment are determinant factors of perceived self-regulation. Memory strategy, which can be predicted using perceived efficacy, perceived anxiety and usefulness, is shown to affect computer-programming achievement. Perceived self-regulation and the use of memory strategies can be improved through students’ realization of perceived usefulness. However, the data do not show that the improper use of mobile applications such as Facebook, Line, and YouTube affect computer-programming achievement.

References

Artino, A. R., & Stephens, J. M. (2009). Academic motivation and self-regulation: a comparative analysis of undergraduate and graduate students learning online. The Internet and Higher Education, 12(3-4), 146-151. DOI: 10.1016/j.iheduc.2009.02.001

Askar, P., & Davenport, D (2009). An investigation of factors related to self-efficacy for Java programming among engineering students. Turkish Online Journal of Education Technology, 8(1), 26-32.

Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs, NJ, USA: Prentice Hall.

Bandura, A. (1997). Self-efficacy: The exercise of control. New York, USA: W.H. Freeman.

Barbeite, F. G., & Weiss, E. M. (2004). Computer self-efficacy and anxiety scales for an Internet sample: testing measurement equivalence of existing measures and development of new scales, Computers in Human Behavior, 20(1), 1-15. DOI: 10.1016/S0747-5632(03)00049-9

Bouhnik, D., & Marcus, T. (2006). Interaction in distance-learning courses. Journal of the American Society for Information Science and Technology, 57(3), 299-305. DOI: 10.1002/asi.20277

Chaiwiwatrakul, S. (2016). The impact of a social networking environment with fully-autonomous and semi-autonomous learning on the English writing abilities of Thai university students. Rangsit Journal of Arts and Sciences, 6(2), 149-164. DOI: 10.14456/rjas.2016.13

Chen, C. M. (2009). Personalized E-learning system with self-regulated learning assisted mechanisms for promoting learning performance. Expert System with Applications, 36(5), 8816-8829. DOI: 10.1016/j.eswa.2008.11.026

Cheng, J. W., & Mitomo, H. (2017). The underlying factors of the perceived usefulness of using smart wearable devices for disaster applications. Telematics and Informatics, 34(2), 528-539. DOI: 10.1016/j.tele.2016.09.010

Chou, C. (2003). Incidence and correlates of Internet anxiety among high school teachers in Taiwan. Computers in Human Behaviors, 19, 731-749. DOI: 10.1016/S0747-5632(03)00010-4

Chu, R. J., & Chu, A. Z. (2010). Multi-level analysis of peer support, Internet self-efficacy and e-learning outcomes – the contextual effects of collectivism and group potency. Computers & Education, 55(1), 145-154. DOI: 10.1016/j.compedu.2009.12.011

Chua, S. L., Chen, D. T., & Wong, A. F. L. (1999). Computer anxiety and its correlates: a meta-analysis. Computers in Human Behavior, 15(5), 609-623.

Cigdem, H. (2015). How does self-regulation affect computer-programming achievement in a blended context? Contemporary Educational Technology, 2015, 6(1), 19-37.

Dabbagh, N., & Kitsantas, A. (2004). Supporting self-regulation in student-centered web-based learning environments. International Journal on E-Learning, 3(1), 40-47.

Delone, W. H., & Mclean, E. R. (2003). The Delone and Mclean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9-30.

Doll, W. J., & Torkzadeh, G. (1988). The measurement of end-user computing satisfaction. MIS Quarterly, 12(2), 259-274. DOI: 10.2307/248851

Durndell, A., & Haag, Z. (2002). Computer self efficacy, computer anxiety, attitudes towards the Internet and reported experience with the Internet, by gender, in an East European sample. Computers in Human Behaviors, 18(5), 521-535. DOI: 10.1016/S0747-5632(02)00006-7

Ekhlas, N. N., & Shangarffam, N. (2013). The relationship between determinant factors of self-regulation strategies and main language skills and overall proficiency. In Arda Arikan, H. Sezgi Sarac, Servet Çelik, Mustafa Caner, Olcay Sert and M. Galip Zorba (Eds.), Procedia - Social and Behavioral Sciences, 70, 137-147. DOI: 10.1016/j.sbspro.2013.01.049

Ganster, D. C., & Schauebrock, J. (1991). Work stress and employee health. Journal of Management, 17(2), 235-271. DOI: 10.1177/014920639101700202

Ghiselli, E. E., Campbell, J. P., & Zedeck, S. (1981). Measurement theory for the behavioral science. San Francisco, CA, USA: W.H. Freeman.

Joiner, R., Brosnan, M., Duffield, J., Gavin, J., & Maras, P. (2007). The relationship between Internet identification, Internet anxiety and Internet use. Computers in Human Behavior, 23(3), 1408-1420. DOI: 10.1016/j.chb.2005.03.002

Kanfer, R., & Heggestad, E. D. (1999). Individual differences in motivation: traits and self-regulatory skills. In P. L., Ackerman, P. C., Kyllonen, & R. D., Roberts, (Eds.), Learning and individual differences: process, trait, and content determinants, 293-313, Washington, DC, USA: American Psychological Association. DOI: 10.1037/10315-013

Kim, G. M., & Ong, S. M. (2005). An exploratory study of factors influencing m-learning success. Journal of Computer Information Systems, 46(1), 92-98.

Kneebone, R. (2003). Simulation in surgical training: educational issues and practical implications. Medical Education, 37(3), 267-277. DOI: 10.1046/j.1365-2923.2003.01440.x

Kramarski, B., & Gutman, M. (2006). How can self-regulated learning be supported in mathematical E learning environments? Journal of Computer Assisted Learning, 22(1), 24-33. DOI: 10.1111/j.1365 2729.2006.00157.x

Leidner, D. E., & Jarvenpaa, S. L. (1995). The use of information technology to enhance management school education: a theoretical view. MIS Quarterly, 19(3), 265-291. DOI: 10.2307/249596

Lewis, C. (2002). Driving factors for e-learning: an organizational perspective. Perspectives, 6(2), 50-54. DOI: 10.1080/13603100120125979

Liaw, S. S. (2004). Considerations for developing constructivist web-based learning. International Journal of Instructional Media, 31(3), 309-321.

Liaw, S. S. (2008). Investigating students’ perceived satisfaction, behavioral intention, and effectiveness of e-learning: a case study of the Blackboard system. Computers & Education, 51(2), 864-873. DOI: 10.1016/j.compedu.2007.09.005

Liaw, S. S., & Huang, H. M. (2007). Developing a collaborative e-learning system based on users’ perceptions. Lecture Notes in Computer Science, 4402, Springer, Berlin, Germany: Heidelberg, 751-759. DOI: 10.1007/978-3-540-72863-4_76

Liaw, S. S., & Huang, H.M. (2013) Perceived satisfaction, perceived usefulness and interactive learning environments as predictors to self-regulation in e-learning environments, Computers & Education, 60(1), 14-24. DOI: 10.1016/j.compedu.2012.07.015

Lindgaard, G., & Dudek, C. (2003). What is this evasive beast we call user satisfaction? Interacting with Computers, 15(3), 429-452. DOI: 10.1016/S0953-5438(02)00063-2

Liu, S. H., Liao, H. L., & Pratt, J. A. (2009). Impact of media richness and flow on e-learning technology acceptance. Computers & Education, 52(3), 599–607. DOI: 10.1016/j.compedu.2008.11.002

Mac Callum, K., Jeffrey, L., & Kinshuk. (2014). Factors impacting teachers’ adoption of mobile learning. Journal of Information Technology Education: Research, 13, 141-162.

Motiwalla, L. F. (2007). Mobile learning: a framework and evaluation. Computers & Education, 49(3), 581-596. DOI: 10.1016/j.compedu.2005.10.011

Panangalage, R., Virtusa, C., & Pasqual, A. (2008). Impact of ICT on learning and teaching. IEEE International Symposium on Technology and Society, 1-10. DOI: 10.1109/ISTAS.2008.4559788

Pintrich, P. R. (2000). A motivational science perspective on the role of student motivation in learning and teaching contexts. Journal of Educational Psychology, 95(4), 667-686. DOI: 10.1037/0022-0663.95.4.667

Presno, C. (1998). Taking the byte out of Internet anxiety: instructional techniques that reduce computer/Internet anxiety in the classroom. Journal of Educational Computing Research, 18(2), 147-161. DOI: 10.2190/UY72-5TG8-0LT5-AU4L

Roca, J. C., & Gagne, M. (2008). Understanding e-learning continuance intention in the workplace: a self determination theory perspective. Computers in Human Behavior, 24, 1585-1604. DOI: 10.1016/j.chb.2007.06.001

Sharma, S., Dick, G., Chin, W. W., & Land, L. (2007). Self-regulation and e-learning. in Proceedings of the 15th European Conference on Information Systems, ECIS 2007, pp. 383-394

Shee, D. Y., & Wang, Y. H. (2008). Multi-criteria evaluation of the web-based e-learning system: a methodology based on learner satisfaction and its applications. Computers & Education, 50, 894 905. DOI: 10.1016/j.compedu.2006.09.005

Spielberger, C. D., Gorsuch, R. L., & Lushene, R. E. (1970). Manual for the state-trait anxiety inventory. Palo Alto, CA, USA: Consulting Psychologists Press.

Sun, P. C., Tsai, R. J., Finger, G., Chen, Y. Y., & Yeh, D. (2008). What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Computers & Education, 50(4), 1183-1202. DOI: 10.1016/j.compedu.2006.11.007

Thomas, D. (2015). Factors impacting on educational motivation among

international students in Thailand. Rangsit Journal of Arts and Sciences, 5(2), 117-129. DOI: 10.14456/rjas.2015.11

Torkzadeh, G., Chang, J. C. J., & Demirhan, D. (2006). A contingency model of computer and Internet self efficacy. Information & Management, 43(4), 541-550. DOI: 10.1016/j.im.2006.02.001

Tsai, M. J. (2009). The model of strategic e-learning: understanding and evaluating student e-learning from metacognitive perspective. Educational Technology & Society, 12(1), 34-48.

Vighnarajah, S., Wong, S. L., & Kamariah, A. B. (2009). Qualitative findings of students’ perception on practice of self-regulated strategies in online community discussion. Computers & Education, 53(1), 94-103. DOI: 10.1016/j.compedu.2008.12.021

Virvou, M., & Katsionis, G. (2008). On the usability and likeability of virtual reality games for education: the case of VR-ENGAGE. Computers & Education, 50(1), 154-178. DOI: 10.1016/j.compedu.2006.04.004

Zimmerman, B. J., & Martinez-Pons, M. (1986). Development of a structured interview for assessing student use of self-regulated learning strategies. American, Educational Research Journal, 23(4), 614-628. DOI: 10.3102/00028312023004614

Zimmerman, B. J. (1989). A social cognitive view of self-regulated academic learning. Journal of Educational Psychology, 81(3), 329-339. DOI: 10.1037/0022-0663.81.3.329

Zimmerman, B. J., Bandura, A., & Martinez-Pons, M. (1992). Self-motivation for academic attainment: the role of self-efficacy beliefs and personal goal setting. American Educational Research Journal, 29(3), 663-676. DOI: 10.3102/00028312029003663

Zimmerman, B. J., & Schunk, D. (2001). Reflections on theories of self-regulated learning and academic achievement. In B. J. Zimmerman, & D. Schunk (Eds.), Self-regulated learning and academic achievement: Theoretical perspectives (2nd ed.), 289-307, Mahwah, NJ, USA: Erlbaum.

Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64-70. DOI: 10.1207/s15430421tip4102_2