Publications by Kshitij Sharma

Predicting learners' effortful behaviour in adaptive assessment using multimodal data

Many factors influence learners' performance on an activity beyond the knowledge required. Learners' on-task effort has been acknowledged for strongly relating to their educational outcomes, reflecting how actively they are engaged in that activity. Howeve ...

ASSOC COMPUTING MACHINERY2020

Measuring causality between collaborative and individual gaze metrics for collaborative problem-solving with intelligent tutoring systems

Kshitij Sharma, Jennifer Kaitlyn Olsen

When students are working collaboratively and communicating verbally in a technology-enhanced environment, the system cannot track what collaboration is happening outside of the technology, making it difficult to fully assess the collaboration of the stude ...

2021

Eye-tracking and artificial intelligence to enhance motivation and learning

Pierre Dillenbourg, Kshitij Sharma

The interaction with the various learners in a Massive Open Online Course (MOOC) is often complex. Contemporary MOOC learning analytics relate with click-streams, keystrokes and other user-input variables. Such variables however, do not always capture user ...

SPRINGER HEIDELBERG2020

Temporal analysis of multimodal data to predict collaborative learning outcomes

Kshitij Sharma, Jennifer Kaitlyn Olsen

The analysis of multiple data streams is a long-standing practice within educational research. Both multimodal data analysis and temporal analysis have been applied successfully, but in the area of collaborative learning, very few studies have investigated ...

WILEY2020

Stimuli-based Gaze Analytics to Enhance Motivation and Learning in MOOCs

Pierre Dillenbourg, Kshitij Sharma

The interaction with the various learners in a Massive Open Online Course (MOOC) is often complex. Contemporary MOOC learning analytics relate with click-streams, keystrokes and other user-input variables. Such variables however, do not always capture lear ...

IEEE2019

Bridging Multilevel Time Scales in HRI

Pierre Dillenbourg, Thibault Lucien Christian Asselborn, Kshitij Sharma, Wafa Monia Benkaouar Johal

In this article, we present a multi-level time scales framework for the analysis of human-robot interaction (HRI). Such a framework allows HRI scientists to model the inter-relation between measures and factors of an experiment. Our final goal with the int ...

2019

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

Kshitij Sharma, Jennifer Kaitlyn Olsen

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 ...

2019

Learner-Computer Interaction

Pierre Dillenbourg, Kshitij Sharma

Learner-Computer Interaction (LCI) research addresses the design, development and use of interactive technologies to support and amplify human learning. LCI is based on the rationale that learning while interacting with technology is a complex, multi-layer ...

ASSOC COMPUTING MACHINERY2018

Iterative Design of an Upper Limb Rehabilitation Game with Tangible Robots

Francesco Mondada, Pierre Dillenbourg, Kshitij Sharma, Ayberk Özgür, Arzu Güneysu Özgür, Wafa Monia Benkaouar Johal, Friedhelm Christoph Hummel, Maximilian Jonas Wessel

2018

Multimodal teaching analytics: Automated extraction of orchestration graphs from wearable sensor data

Pierre Dillenbourg, Kshitij Sharma, Luis Pablo Prieto Santos, Maria Jesus Rodriguez Triana, Lukasz Kidzinski

2018

NONSTATIONARY MODELLING OF TAIL DEPENDENCE OF TWO SUBJECTS' CONCENTRATION

Valérie Chavez, Pierre Dillenbourg, Kshitij Sharma

2018

Orchestration Load Indicators and Patterns: n-the-Wild Studies Using Mobile Eye-Tracking

Pierre Dillenbourg, Kshitij Sharma, Luis Pablo Prieto Santos, Lukasz Kidzinski

2018

Leveraging mobile eye-trackers to capture joint visual attention in co-located collaborative learning groups

Guillaume Zufferey, Sébastien Cuendet, Pierre Dillenbourg, Bertrand Roland Schneider, Kshitij Sharma

This paper describes a promising methodology for studying co-located groups: mobile eye-trackers. We provide a comprehensive description of our data collection and analysis processes so that other researchers can take advantage of this cutting-edge technol ...

SPRINGER2018

Semantically Meaningful Cohorts Enable Specialized Knowledge Sharing in a Collaborative MOOC

Pierre Dillenbourg, Kshitij Sharma, Stian Haklev

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 ...

2018

Detecting Trends in Job Advertisements

Pierre Dillenbourg, Kshitij Sharma, Khalil Mrini

We present an automatic method for trend detection in job ads. From a job-posting website, we collect job ads from 16 countries and in 8 languages and 6 job domains. We pre-process them by removing stop words, lemmatising and performing cross-domain filter ...

2017

An Application of Extreme Value Theory to Learning Analytics: Predicting Collaboration Outcome from Eye-tracking Data

Valérie Chavez, Kshitij Sharma

The statistics used in education research are based on central trends such as the mean or standard deviation, discarding outliers. This paper adopts another viewpoint that has emerged in Statistics, called the Extreme Value Theory (EVT). EVT claims that th ...

2017

Contextualizing the co-creation of artefacts within the nested social structure of a collaborative MOOC

Pierre Dillenbourg, Kshitij Sharma, Stian Haklev

MOOCs have traditionally been seen as providing an individual learning experience, however there is an increasing trend towards enabling social learning in MOOCs. To make online learning at scale more social and collaborative, some MOOCs have introduced co ...

2017

Using Mobile Eye-Trackers to Unpack the Perceptual Benefits of a Tangible User Interface for Collaborative Learning

Guillaume Zufferey, Sébastien Cuendet, Pierre Dillenbourg, Bertrand Roland Schneider, Kshitij Sharma

In this study, we investigated the way users memorize, analyze, collaborate, and learn new concepts on a Tangible User Interface (TUI). Twenty-seven pairs of apprentices in logistics (N = 54) interacted with an interactive simulation of a warehouse. Their ...

Assoc Computing Machinery2016

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

Pierre Dillenbourg, Patrick Jermann, Hamed Seiied Alavi, Kshitij Sharma

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 ...

ACM2016

Towards Predicting Success in MOOCs: Programming Assignments

Pierre Dillenbourg, Patrick Jermann, Kshitij Sharma, Lukasz Kidzinski

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 ...

Books on Demand GmbH, Norderstedt2016