THESIS PROPOSAL: Yanjin Long
When
-
Where
GHC 6115
Description
Gamification of Support for Learning Effective Problem Selection Strategies in Intelligent Tutoring Systems
Yanjin Long
Committee:
Vincent Aleven (Chair) (HCI, CMU)
Kenneth R. Koedinger (HCI & Psychology, CMU)
Jodi Forlizzi (HCI & Design, CMU)
Jesse Schell (Entertainment Technology Center, CMU)
Timothy Nokes-Malach (Psychology, University of Pittsburgh)
Document:
http://www.cs.cmu.edu/~ylong/YanjinLong_thesisProposal.pdf
Abstract:
Many online learning technologies grant students great autonomy and control, which impose high demands for self-regulated learning (SRL) skills. With the fast development of online learning technologies, helping students acquire SRL skills becomes critical to student learning. My proposed work focuses on supporting students’ learning of a central SRL skill, making effective problem selection decisions in online learning environments with the aid of certain kinds of learning analytics that are commonly available in many learning technologies. Research has shown that especially younger learners are poor at selecting problems strategically based on their learning status (how much has been learned for different learning units, as generally displayed by the learning analytics). Prior studies mainly targeted on supporting students’ problem selection in systems where the scaffolding was in effect, but few studies have tried to teach students the transferrable skills that can be applied in new learning environments. My design centers on teaching two rules of effective problem selection, the mastery rule and the rule for interleaved practice, through design and integration of gamified features in an intelligent tutoring system (ITS), with the goal to foster both learning and enjoyment in the system and transfer of the problem selection skills to new learning environments. I will conduct a classroom experiment to evaluate the effectiveness of the gamified designs on supporting students’ learning of the problem selection rules, domain level learning, self-efficacy and enjoyment of learning with the system. The results of my work will shed light on whether and how gamification can be integrated to support learning of transferrable SRL skills in ITSs, and also provide design recommendations for effectively use gamification to support SRL learning, domain level learning and motivation in online learning technologies.