Publications by Kshitij Sharma

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We study the interaction of the participants in a pair program comprehension task across different time scales in a dual eye-tracking setup. We identify four layers of interaction episodes at different time scales. Each layer spans across the whole interac ...

In the context of MOOCs, “With-me-ness” refers to the extent to which the learner succeeds in following the teacher, specifically in terms of looking at the area in the video that the teacher is explaining. In our previous works, we employed eye-tracking m ...

Students of programming languages in massive on-line open courses (MOOCs) solve programming assignments in order to internalize the concepts. Programming assignments also constitute the assessment procedure for such courses. Depending on their motivation a ...

We report the results from an eye-tracking study to show the differences in gaze patterns across the MOOC learners, while they watch a lecture individually as well as when they collaborate on an add-on activity. 98 university students took part in a study ...

This study presents an analysis of a MOOC on inquiry and technology for in-service teachers, which was designed to scaffold multi- ple disciplinary knowledge communities through common weekly themes, and course-long collaboration scripts happening at diffe ...

To provide beneficial feedback to students during their collaboration, it is important to identify behaviors that are indicative of good collaboration. However, in a collaborative learning session, students engage in a range of behaviors and it can be diff ...

Kshitij Sharma

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Understanding Collaborative Program Comprehension: Interlacing Gaze and Dialogues

A gaze-based learning analytics model: in-video visual feedback to improve learner's attention in MOOCs

Towards Predicting Success in MOOCs: Programming Assignments

Looking AT versus Looking THROUGH: A Dual Eye-tracking study in MOOC Context

Semantically Meaningful Cohorts Enable Specialized Knowledge Sharing in a Collaborative MOOC

An Alternate Statistical Lens to Look at Collaboration Data: Extreme Value Theory