Abstract: The COVID-19 pandemic has highlighted the importance of online learning. As lear ...
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Abstract: The COVID-19 pandemic has highlighted the importance of online learning. As learner autonomy is relatively high in online environments, learners must engage in self-regulated learning (SRL) to achieve optimal learning outcomes. Because most learners are unable to consistently engage in SRL, gamification interventions are being implemented to improve SRL engagement; however, mixed results cast doubt on the efficacy of this approach. Massively open online courses (MOOCs), a type of online learning environment, are currently experiencing rapid growth due to widespread adoption by many institutions. In MOOCs, there is no instructor intervention; hence, students have difficulty regulating their own learning and are easily distracted. Therefore, this study investigates whether mixed-research results regarding the efficacy of gamification can be attributed to lack of attention to individual learner traits during design. For this purpose, the study analyzes MOOCs as an instance of online learning by applying SRL theory and gamification principles. We altered a traditional MOOC platform to provide different types of gamified performance feedback to facilitate learners’ SRL engagement. We then examined whether this matched with goal orientation, an individual learner trait to influence SRL and learning outcomes. Using learning-analytics tools, we tracked 760 college students’ SRL engagement on a MOOC platform over five weeks. As theorized, SRL engagement and learning outcomes of participants who had a strong performance-avoidance goal orientation increased with positively framed performance feedback that involved no social comparisons; however, the same feedback had a negative impact on participants with a strong mastery goal orientation. Our findings add to SRL theory by demonstrating that gamification designs can enhance SRL engagement and learning outcomes in online learning, but with a caveat—this occurs only when there is a match with learner traits—confirming the gamification principle stating that task improvements and meaningful engagement can only occur through thoughtful gamification design.History: Raghu Santanam, Senior Editor; J. J. Hsieh, Associate Editor.Funding: Financial supported from the University Grants Committee’s (UGC’s) Special Grant for the Strategic Development of Virtual Teaching and Learning [Project Number 6430900], the UGC Teaching and Learning Funding [Project Numbers 6391211 and 6391001], and the Digital Innovation Laboratory of Department of Information Systems, City University of Hong Kong is gratefully acknowledged.Supplemental Material: The online appendix is available at https://doi.org/10.1287/isre.2022.1123.
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Semantic filters:
SASgamification
Topics:
gamification online learning system electronic mail IT skill business intelligence
Methods:
experimental group pilot experiment survey experiment digital trace data
Theories:
learning theory
Can Competition Though Leaderboards Lead to Better Engagement and Learning of Data Science Concepts? An Experimental Study
2021 | Americas Conference on Information Systems | Citations: 0
Abstract: This paper examines the effect of gamification in engaging students to learn in ...
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Abstract: This paper examines the effect of gamification in engaging students to learn introductory concepts of data science, in particular, we study competitiveness through leaderboards. A between-subject experiment was conducted with 37 students and included two conditions: 1) playing against fictious opponents with a competitive leaderboard and, 2) playing alone with a leaderboard ranking only the subject's score. Our results show no effect of the competitive nature of leaderboards on learning and engagement. However, we found that highly efficacious participants with prior predictive modelling knowledge demonstrated higher levels of emotional arousal despite having a lower probability of increasing their knowledge on the subject matter. This suggests that individual differences such as self-efficacy and prior knowledge need to be accounted for when developing data science training that is augmented with competition through leaderboards as these factors may impact the learner's ability to engage with the content.
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Semantic filters:
SASgamification
Topics:
self efficacy gamification analytical information system intrinsic motivation knowledge base
Methods:
machine learning experiment between subject experiment cross sectional research simulation
