Effects of gamification on students’ online interactive patterns and peer-feedback

References

• Alavi, M., & Dufner, D. (2005). Technology-mediated collaborative learning: A research perspective. In S. R. Hiltz & R. Goldman (Eds.), Learning together online: Research on asynchronous learning networks (pp. 191–213). Mahwah, NJ: Erlbaum.
   Google Scholar
• Alkış, N., & Temizel, T. T. (2018). The impact of motivation and personality on academic performance in online and blended learning environments. Journal of Educational Technology & Society, 21(3), 35–47. Retrieved from https://www.jstor.org/stable/26458505
   Web of Science ®Google Scholar
• Anderson, B. (2006). Writing power into online discussion. Computers and Composition, 23, 108–124. doi:10.1016/j.compcom.2005.12.007
   Google Scholar
• Bakker, M., & Wicherts, J. M. (2014). Outlier removal, sum scores, and the inflation of the type I error rate in independent samples t tests: The power of alternatives and recommendations. Psychological Methods, 19, 409. doi:10.1037/met0000014
   PubMed Web of Science ®Google Scholar
• Bälter, O., & Zimmaro, D. (2018). Keystroke-level analysis to estimate time to process pages in online learning environments. Interactive Learning Environments, 26, 476–485. doi:10.1080/10494820.2017.1341941
   Web of Science ®Google Scholar
• Borgatti, S. P., Everett, M. G., & Freeman, L. C. (2002). UCINET for Windows: Software for social network analysis [Computer software]. Harvard, MA: Analytic Technologies.
   Google Scholar
• Buckley, P., & Doyle, E. (2016). Gamification and student motivation. Interactive Learning Environments, 24, 1162–1175. doi:10.1080/10494820.2014.964263
   Web of Science ®Google Scholar
• Buckley, P., & Doyle, E. (2017). Individualising gamification: An investigation of the impact of learning styles and personality traits on the efficacy of gamification using a prediction market. Computers & Education, 106, 43–55. doi:10.1016/j.compedu.2016.11.009
   Web of Science ®Google Scholar
• Butts, C. T. (2006). Exact bounds for degree centralization. Social Networks, 28, 283–296. doi:10.1016/j.socnet.2005.07.003
   Web of Science ®Google Scholar
• Butz, N. T., & Stupnisky, R. H. (2017). Improving student relatedness through an online discussion intervention: The application of self-determination theory in synchronous hybrid programs. Computers & Education, 114, 117–138. doi:10.1016/j.compedu.2017.06.006
   Web of Science ®Google Scholar
• Casquero, O., Ovelar, R., Romo, J., & Benito, M. (2015). Reviewing the differences in size, composition and structure between the personal networks of high- and low-performing students. British Journal of Educational Technology, 46, 16–31. doi:10.1111/bjet.12110
   Web of Science ®Google Scholar
• Cela, K. L., Sicilia, M. Á., & Sánchez, S. (2015). Social network analysis in e-learning environments: A preliminary systematic review. Educational Psychology Review, 27, 219–246. doi:10.1007/s10648-014-9276-0
   Web of Science ®Google Scholar
• Chang, J. W., & Wei, H. Y. (2016). Exploring engaging gamification mechanics in massive online open courses. Journal of Educational Technology & Society, 19(2), 177–203. Retrieved from https://www.j-ets.net/ETS/index.html
   Web of Science ®Google Scholar
• Cho, H., Gay, G., Davidson, B., & Ingraffea, A. (2007). Social networks, communication styles, and learning performance in a CSCL community. Computers & Education, 49(2), 309–329. doi:10.1016/j.compedu.2005.07.003
   Web of Science ®Google Scholar
• Coetzee, D., Fox, A., Hearst, M. A., & Hartmann, B. (2014). Should your MOOC forum use a reputation system? In S. R. Fussell, W. G. Lutters, M. R. Morris, & M. Reddy (Eds.), Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing (pp. 1176–1187). Baltimore, MA: ACM. doi:10.1145/2531602.2531657
   Google Scholar
• Csikszentmihalyi, M. (1978). Intrinsic rewards and emergent motivation. In M. R. Lepper, & D. Greene (Eds.). The hidden costs of reward: New perspectives on the psychology of human motivation (pp. 205–216). Oxford, UK: Earlbaum.
   Google Scholar
• de Laat, M., Lally, V., Lipponen, L., & Simons, R. J. (2007). Investigating patterns of interaction in networked learning and computer-supported collaborative learning: A role for social network analysis. International Journal of Computer-Supported Collaborative Learning, 2, 87–103. doi:10.1007/s11412-007-9006-4
   Web of Science ®Google Scholar
• de-Marcos, L., Garcia-Lopez, E., & Garcia-Cabot, A. (2016). On the effectiveness of game-like and social approaches in learning: Comparing educational gaming, gamification & social networking. Computers & Education, 95, 99–113. doi:10.1016/j.compedu.2015.12.008
   Web of Science ®Google Scholar
• Ding, L., Er, E., & Orey, M. (2018). An exploratory study of student engagement in gamified online discussions. Computers & Education, 120, 213–226. doi:10.1016/j.compedu.2018.02.007
   Web of Science ®Google Scholar
• Ding, L., Kim, C., & Orey, M. (2017). Studies of student engagement in gamified online discussions. Computers & Education, 115, 126–142. doi:10.1016/j.compedu.2017.06.016
   Web of Science ®Google Scholar
• Ertmer, P. A., Richardson, J. C., Belland, B., Camin, D., Connolly, P., Coulthard, G., Lei., K., Mong, C. Mong, C. (2007). Using peer feedback to enhance the quality of student online postings: An exploratory study. Journal of Computer-Mediated Communication, 12, 412–433. doi:10.1111/j.1083-6101.2007.00331.x
   Web of Science ®Google Scholar
• Festinger, L. (1954). A theory of social comparison processes. Human Relations, 7, 117–140. doi:10.1177/001872675400700202
   Web of Science ®Google Scholar
• Fredericksen, E., Pickett, A., Shea, P., Pelz, W., & Swan, K. (2000). Student satisfaction and perceived learning with on-line courses: Principles and examples from the SUNY learning network. Journal of Asynchronous Learning Networks, 4, 7–41. doi:10.24059/olj.v4i2.1899
   Google Scholar
• Fredricks, J. A., & McColskey, W. (2012). The measurement of student engagement: A comparative analysis of various methods and student self-report instruments. In S. Christenson, A. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 763–782). Boston, MA: Springer.
   Google Scholar
• Garrison, D. R., Anderson, T., & Archer, W. (2001). Critical thinking, cognitive presence, and computer conferencing in distance education. The American Journal of Distance Education, 15(1), 7–23. doi:10.1080/08923640109527071
   Google Scholar
• Garrison, D. R., & Cleveland-Innes, M. (2005). Facilitating cognitive presence in online learning: Interaction is not enough. The American Journal of Distance Education, 19, 133–148. doi:10.1207/s15389286ajde1903_2
   Google Scholar
• Gašević, D., Kovanovic, V., Joksimovic, S., & Siemens, G. (2014). Where is research on massive open online courses headed? A data analysis of the MOOC Research Initiative. The International Review of Research in Open and Distributed Learning, 15(5). doi:10.19173/irrodl.v15i5.1954
   Web of Science ®Google Scholar
• Gašević, D., Zouaq, A., & Janzen, R. (2013). “Choose your classmates, your GPA is at stake!” The association of cross-class social ties and academic performance. American Behavioral Scientist, 57, 1460–1479. doi:10.1177/0002764213479362
   Web of Science ®Google Scholar
• Ge, Z. G. (2018). The impact of a forfeit-or-prize gamified teaching on e-learners’ learning performance. Computers & Education, 126, 143–152. doi:10.1016/j.compedu.2018.07.009
   Web of Science ®Google Scholar
• Gillani, N., & Eynon, R. (2014). Communication patterns in massively open online courses. The Internet and Higher Education, 23, 18–26. doi:10.1016/j.iheduc.2014.05.004
   Web of Science ®Google Scholar
• Greenlaw, S. A., & Deloach, S. B. (2003). Teaching critical thinking with electronic discussion. The Journal of Economic Education, 34, 36–52. doi:10.1080/00220480309595199
   Web of Science ®Google Scholar
• Hanus, M. D., & Fox, J. (2015). Assessing the effects of gamification in the classroom: A longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Computers & Education, 80, 152–161. doi:10.1016/j.compedu.2014.08.019
   Web of Science ®Google Scholar
• Hara, N., Bonk, C. J., & Angeli, C. (2000). Content analysis of online discussion in an applied educational psychology course. Instructional Science, 28, 115–152. doi:10.1023/A:1003764722829
   Web of Science ®Google Scholar
• Hew, K. F., & Cheung, W. S. (2014). Using blended learning: Evidence-based practices. Singapore: Springer.
   Google Scholar
• Hew, K. F., Cheung, W. S., & Ng, C. S. L. (2010). Student contribution in asynchronous online discussion: A review of the research and empirical exploration. Instructional Science, 38, 571–606. doi:10.1007/s11251-008-9087-0
   Web of Science ®Google Scholar
• Hew, K. F., Huang, B., Chu, K. W. S., & Chiu, D. K. (2016). Engaging Asian students through game mechanics: Findings from two experiment studies. Computers & Education, 92, 221–236. doi:10.1016/j.compedu.2015.10.010
   Web of Science ®Google Scholar
• Hewitt, J. (2005). Toward an understanding of how threads die in asynchronous computer conferences. The Journal of the Learning Sciences, 14, 567–589. doi:10.1207/s15327809jls1404_4
   Web of Science ®Google Scholar
• Hrastinski, S. (2008). What is online learner participation? A literature review. Computers & Education, 51, 1755–1765. doi:10.1016/j.compedu.2008.05.005
   Web of Science ®Google Scholar
• Hsu, C. C., & Wang, T. I. (2018). Applying game mechanics and student-generated questions to an online puzzle-based game learning system to promote algorithmic thinking skills. Computers & Education, 121, 73–88. doi:10.1016/j.compedu.2018.02.002
   Web of Science ®Google Scholar
• Hsu, T. C., & Hwang, G. J. (2017). Effects of a structured resource-based web issue-quest approach on students’ learning performances in computer programming courses. Journal of Educational Technology & Society, 20(3), 82–94. Retrieved from https://www.jstor.org/stable/26196121
   Web of Science ®Google Scholar
• Hsu, Y. C., Ho, S. N., Tsai, C. C., Hwang, G. J., Chu, H. C., & Wang, C.Y. (2012). Research trends in technology-based learning from 2000 to 2009: A content analysis of publications in selected journals. Journal of Educational Technology & Society, 15(2), 354–370. Retrieved from https://www.jstor.org/stable/26196121
   Web of Science ®Google Scholar
• Hu, M., & Li, H. (2017). Student engagement in online learning: A review. In F. L. Wang, O. Au, K. K. Ng, J. Shang, & R. Kwan (Eds.), Proceedings of the International Symposium on Educational Technology (pp. 39–43). Los Alamitos, CA: IEEE. Retrieved from https://ieeexplore.ieee.org/document/8005384/
   Google Scholar
• Huang, B., & Hew, K. F. (2018). Implementing a theory-driven gamification model in higher education flipped courses: Effects on out-of-class activity completion and quality of artifacts. Computers & Education, 125, 254–272.
   Web of Science ®Google Scholar
• Huang, B., Hew, K. F., & Lo, C. K. (2018). Investigating the effects of gamification-enhanced flipped learning on undergraduate students’ behavioral and cognitive engagement. Interactive Learning Environments. doi:10.1080/10494820.2018.1495653
   Web of Science ®Google Scholar
• Jo, I., Park, Y., & Lee, H. (2017). Three interaction patterns on asynchronous online discussion behaviours: A methodological comparison. Journal of Computer Assisted Learning, 33, 106–122. doi:10.1111/jcal.12168
   Web of Science ®Google Scholar
• Joksimović, S., Manataki, A., Gašević, D., Dawson, S., Kovanović, V., & de Kereki, I. F. (2016). Translating network position into performance: importance of centrality in different network configurations. In D. Gašević, G. Lynch, S. Dawson, H. Drachsler, & C. P. Ros (Eds.), Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (pp. 314–323). New York, NY: ACM. doi:10.1145/2883851.2883928
   Google Scholar
• Kyewski, E., & Krämer, N. C. (2018). To gamify or not to gamify? An experimental field study of the influence of badges on motivation, activity, and performance in an online learning course. Computers & Education, 118, 25–37. doi:10.1016/j.compedu.2017.11.006
   Web of Science ®Google Scholar
• Latham, G. P., & Locke, E. A. (1979). Goal setting: A motivational technique that works. Organizational Dynamics, 8(2), 68–80. doi:10.1016/0090-2616(79)90032-9
   Web of Science ®Google Scholar
• Lee, K. (2018). Everyone already has their community beyond the screen: reconceptualizing online learning and expanding boundaries. Educational Technology Research and Development, 66, 1255–1268. doi:10.1007/s11423-018-9613-y
   Web of Science ®Google Scholar
• Li, L. Y., & Tsai, C. C. (2017). Accessing online learning material: Quantitative behavior patterns and their effects on motivation and learning performance. Computers & Education, 114, 286–297. doi:10.1016/j.compedu.2017.07.007
   Web of Science ®Google Scholar
• Locke, E. A., & Latham, G. P. (2002). Building a practically useful theory of goal setting and task motivation: A 35-year odyssey. American Psychologist, 57, 705. doi:10.1037/0003-066X.57.9.705
   PubMed Web of Science ®Google Scholar
• Long, P., & Siemens, G. (2011, September). Penetrating the fog: Analytics in learning and education. EDUCAUSE Review, 46, 31–40. Retrieved from https://er.educause.edu/articles/2011/9/penetrating-the-fog-analytics-in-learning-and-education
   Google Scholar
• Magen-Nagar, N., & Shonfeld, M. (2018). The impact of an online collaborative learning program on students’ attitude towards technology. Interactive Learning Environments, 26, 621–637. doi:10.1080/10494820.2017.1376336
   Web of Science ®Google Scholar
• Mahatmya, D., Lohman, B. J., Matjasko, J. L., & Farb, A. F. (2012). Engagement across developmental periods. In S. Christenson, A. Reschly, & C. Wylie (Eds.), Handbook of research on student engagement (pp. 45–63). Boston, MA: Springer.
   Google Scholar
• Malone, T. W. (1981). Toward a theory of intrinsically motivating instruction. Cognitive Science, 5, 333–369. doi:10.1016/S0364-0213(81)80017-1
   Web of Science ®Google Scholar
• Parks-Stamm, E. J., Zafonte, M., & Palenque, S. M. (2017). The effects of instructor participation and class size on student participation in an online class discussion forum. British Journal of Educational Technology, 48, 1250–1259. doi:10.1111/bjet.12512
   Web of Science ®Google Scholar
• Phan, T., McNeil, S. G., & Robin, B. R. (2016). Students’ patterns of engagement and course performance in a massive open online course. Computers & Education, 95, 36–44. doi:10.1016/j.compedu.2015.11.015
   Web of Science ®Google Scholar
• Richardson, J. C., & Newby, T. (2006). The role of students’ cognitive engagement in online learning. American Journal of Distance Education, 20(1), 23–37. doi:10.1207/s15389286ajde2001_3
   Google Scholar
• Rovai, A. P. (2002). Sense of community, perceived cognitive learning, and persistence in asynchronous learning networks. The Internet and Higher Education, 5, 319–332. doi:6/S1096-7516(02)00130-6
   Google Scholar
• Ryan, R. M., & Deci, E. L. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist, 55, 68–78. doi:10.1037/0003-066X.55.1.68
   PubMed Web of Science ®Google Scholar
• Saadatmand, M., Uhlin, L., Hedberg, M., Åbjörnsson, L., & Kvarnström, M. (2017). Examining learners’ interaction in an open online course through the community of inquiry framework. European Journal of Open, Distance and E-Learning, 20(1), 61–79. doi:10.1515/eurodl-2017-0004
   Google Scholar
• Scott, J. (2017). Social network analysis. London, UK: Sage.
   Google Scholar
• Seaborn, K., & Fels, D. I. (2015). Gamification in theory and action: A survey. International Journal of Human-Computer Studies, 74, 14–31. doi:10.1016/j.ijhcs.2014.09.006
   Web of Science ®Google Scholar
• Sheskin, D. (2011). Handbook of parametric and nonparametric statistical procedures. Boca Raton, FL: Chapman & Hall/CRC.
   Google Scholar
• Siemens, G. (2010, July 22). 1st International Conference on Learning Analytics and Knowledge [Web announcement]. Retrieved from https://tekri.athabascau.ca/analytics/
   Google Scholar
• Siemens, G., & Baker, R. S. J. (2012, April). Learning analytics and educational data mining: Towards communication and collaboration. In S. Dawson, C. Haythornthwaite, S. B. Shum, D. Gašević, & R. Ferguson (Eds.), Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 252–254). New York, NY: ACM. doi:10.1145/2330601.2330661
   Google Scholar
• Skinner, B. F. (1953). Science and human behavior. New York, NY: Macmillan.
   Google Scholar
• Speily, O. R., & Kardan, A. A. (2018). Increasing information reposting behavior in online learning community. Journal of Educational Technology & Society, 21(4), 100–110. Retrieved from https://www.j-ets.net/ets/
   Web of Science ®Google Scholar
• Su, C. (2017). Designing and developing a novel hybrid adaptive learning path recommendation system (ALPRS) for gamification mathematics geometry course. Eurasia Journal of Mathematics, Science and Technology Education, 13, 2275–2298. doi:10.12973/eurasia.2017.01225a
   Web of Science ®Google Scholar
• Su, C. H., & Cheng, C. H. (2015). A mobile gamification learning system for improving the learning motivation and achievements. Journal of Computer Assisted Learning, 31, 268–286. doi:10.1111/jcal.12088
   Web of Science ®Google Scholar
• Sung, H. Y., Hwang, G. J., & Chang, H. S. (2015). An integrated contextual and web-based issue quest approach to improving students’ learning achievements, attitudes and critical thinking. Journal of Educational Technology & Society, 18(4), 299–311. Retrieved from https://www.jstor.org/stable/26196121
   Web of Science ®Google Scholar
• Tan, K. E. (2017). Using online discussion forums to support learning of paraphrasing. British Journal of Educational Technology, 48(6), 1239–1249. doi:10.1111/bjet.12491
   Web of Science ®Google Scholar
• Tsai, Y. H., Lin, C. H., Hong, J. C., & Tai, K. H. (2018). The effects of metacognition on online learning interest and continuance to learn with MOOCs. Computers & Education, 121, 18–29. doi:10.1016/j.compedu.2018.02.011
   Web of Science ®Google Scholar
• Warmbrodt, J., Sheng, H., & Hall, R. (2008, January). Social network analysis of video bloggers’ community. In R. H. Sprague (Ed.), Proceedings of the 41st Annual Hawaii International Conference on System Sciences (pp. 291–291). IEEE. doi:10.1109/HICSS.2008.402
   Google Scholar
• Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. New York, NY: Cambridge University Press.
   Google Scholar
• White, R. W. (1959). Motivation reconsidered: The concept of competences. Psychological Review, 66, 297–333. doi:10.1037/h0040934
   PubMed Web of Science ®Google Scholar
• Willging, P. A. (2005). Analyzing asynchronous online interactions through social network analysis techniques and visualizations (Doctoral dissertation). Retrieved from http://hdl.handle.net/2142/79879
   Google Scholar
• Yang, Y. T. C., Newby, T. J., & Bill, R. L. (2005). Using Socratic questioning to promote critical thinking skills through asynchronous discussion forums in distance learning environments. The American Journal of Distance Education, 19, 163–181. doi:10.1207/s15389286ajde1903_4
   Google Scholar
• Zhai, X., Fang, Q., Dong, Y., Wei, Z., Yuan, J., Cacciolatti, L., & Yang, Y. (2018). The effects of biofeedback-based stimulated recall on self-regulated online learning: A gender and cognitive taxonomy perspective. Journal of Computer Assisted Learning, 34, 775–786. doi:10.1111/jcal.12284
   Web of Science ®Google Scholar
• Zhang, J., Skryabin, M., & Song, X. (2016). Understanding the dynamics of MOOC discussion forums with simulation investigation for empirical network analysis (SIENA). Distance Education, 37, 270–286. doi:10.1080/01587919.2016.1226230
   Web of Science ®Google Scholar
• Zhu, E. (2006). Interaction and cognitive engagement: An analysis of four asynchronous online discussions. Instructional Science, 34(6), 451–480. doi:10.1007/s11251-006-0004-0
   Web of Science ®Google Scholar