10 citations · 16 across the 12 of their papers we have counts for
10 papers · 1 filter
Cross-Subject Predictive Validity for Learning Outcomes of Delayed Start Behavior
Jordan Gutterman, Ashish Gurung, Lee Branstetter +2
Behavioral detectors provide valuable insights into learner motivation and self-regulation. Among these, delayed start, a new session-level detector, has shown great promise as a v…
Improving Hybrid Human-AI Tutoring by Differentiating Human Tutor Roles Based on Student Needs
Ashish Gurung, Ge Gao, Jordan Gutterman +6
Hybrid human-AI tutoring, where technology and humans jointly facilitate student learning, can be more beneficial than AI-only tutoring. However, preliminary evidence suggests that…
Coasting Through Class: Learning Opportunity Loss from Practice Avoidance During Individual Seatwork
Ashish Gurung, Jordan Gutterman, Danielle R. Thomas +3
Measures of disengagement provide insights into unproductive use of learning opportunities. Although measures of active disengagement, such as gaming the system and mind-wandering,…
Sticky Help, Bounded Effects: Session-by-Session Analytics of Teacher Interventions in K-12 Classrooms
Qiao Jin, Conrad Borchers, Ashish Gurung +6
Teachers' in-the-moment support is a limited resource in technology-supported classrooms, and teachers must decide whom to help and when during ongoing student work. However, less…
Brief but Impactful: How Human Tutoring Interactions Shape Engagement in Online Learning
Conrad Borchers, Ashish Gurung, Qinyi Liu +3
Learning analytics can guide human tutors to efficiently address motivational barriers to learning that AI systems struggle to support. Students become more engaged when they recei…
Let Me Try Again: Examining Replay Behavior by Tracing Students' Latent Problem-Solving Pathways
Shan Zhang, Siddhartha Pradhan, Ji-Eun Lee +2
Prior research has shown that students' problem-solving pathways in game-based learning environments reflect their conceptual understanding, procedural knowledge, and flexibility.…