collaborators

5 papers

cs.HC2026

Can providing feedback on gaze and mental-effort synchrony improve pair programming performance?

Anahita Golrang, Kshitij Sharma

Pair programming is a widely used collaborative learning practice in computer science education yet its effectiveness varies substantially due to breakdowns in coordination attenti…

cs.HC2026

Not All Scaffolds Are Equal: How Initiation Mode Determines EMME Effectiveness in Debugging

Anahita Golrang, Kshitij Sharma, Halszka Jarodzka +1

Adaptive learning technologies increasingly rely on real time physiological analytics to trigger instructional support automatically yet how system driven decisions interact with l…

cs.HC2026

RTMS: A Real-Time Multimodal Scaffolding System for Improving Debugging in Computing Education

Anahita Golrang, Kshitij Sharma

Debugging is a demanding aspect of programming yet guidance on how to teach it effectively remains limited. Novices often struggle to recognize impasses regulate their problem solv…

cs.HC2026

Cognitive Alignment Drives Attention: Modeling and Supporting Socially Shared Regulation in Pair Programming

Anahita Golrang, Kshitij Sharma

Grounded in socially shared regulation of learning (SSRL), this paper investigates how joint mental effort (JME) and joint visual attention (JVA) serve as process-level indicators…

cs.HC2026

ProPACT: A Proactive AI-Driven Adaptive Collaborative Tutor for Pair Programming

Anahita Golrang, Kshitij Sharma, olga viberg

Effective pair programming depends on coordination of attention, cognitive effort, and joint regulation over time, yet most adaptive learning systems remain individual-centric and…