Pankaj Chejara

Orcid: 0000-0002-7630-5789

According to our database1, Pankaj Chejara authored at least 20 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
How well do collaboration quality estimation models generalize across authentic school contexts?
Br. J. Educ. Technol., July, 2024

The Impact of Attribute Noise on the Automated Estimation of Collaboration Quality Using Multimodal Learning Analytics in Authentic Classrooms.
J. Learn. Anal., 2024

Bringing Collaborative Analytics using Multimodal Data to Masses: Evaluation and Design Guidelines for Developing a MMLA System for Research and Teaching Practices in CSCL.
Proceedings of the 14th Learning Analytics and Knowledge Conference, 2024

2023
Studying teacher withitness in the wild: comparing a mirroring and an alerting & guiding dashboard for collaborative learning.
Int. J. Comput. Support. Collab. Learn., December, 2023

Towards a partnership of teachers and intelligent learning technology: A systematic literature review of model-based learning analytics.
J. Comput. Assist. Learn., October, 2023

CIMLA: A Modular and Modifiable Data Preparation, Organization, and Fusion Infrastructure to Partially Support the Development of Context-aware MMLA Solutions.
J. Univers. Comput. Sci., March, 2023

Impact of window size on the generalizability of collaboration quality estimation models developed using Multimodal Learning Analytics.
Proceedings of the LAK 2023: 13th International Learning Analytics and Knowledge Conference, 2023

How to Build More Generalizable Models for Collaboration Quality? Lessons Learned from Exploring Multi-Context Audio-Log Datasets using Multimodal Learning Analytics.
Proceedings of the LAK 2023: 13th International Learning Analytics and Knowledge Conference, 2023

Multimodal Learning Analytics Research in the Wild: Challenges and Their Potential Solutions.
Proceedings of the 6th Workshop on Leveraging Multimodal Data for Generating Meaningful Feedback (CROSSMMLA 2023) at the 13th International Learning Analytics & Knowledge (LAK 2023), 2023

Exploring Indicators for Collaboration Quality and Its Dimensions in Classroom Settings Using Multimodal Learning Analytics.
Proceedings of the Responsive and Sustainable Educational Futures, 2023

2022
Correction to: Do Teachers Find Dashboards Trustworthy, Actionable and Useful? A Vignette Study Using a Logs and Audio Dashboard.
Technol. Knowl. Learn., 2022

Do Teachers Find Dashboards Trustworthy, Actionable and Useful? A Vignette Study Using a Logs and Audio Dashboard.
Technol. Knowl. Learn., 2022

2021
EFAR-MMLA: An Evaluation Framework to Assess and Report Generalizability of Machine Learning Models in MMLA.
Sensors, 2021

Dataset on an online collaborative learning situation in a computer networks course (Abstract).
Proceedings of the Joint Proceedings of the Workshops at the International Conference on Educational Data Mining 2021 co-located with 14th International Conference on Educational Data Mining (EDM 2021), 2021

2020
Multimodal Data Value Chain (M-DVC): A Conceptual Tool to Support the Development of Multimodal Learning Analytics Solutions.
Rev. Iberoam. de Tecnol. del Aprendiz., 2020

MMLA Approach to Track Participation Behavior in Collaboration in Collocated Blended Settings.
Proceedings of CrossMMLA in practice: Collecting, 2020

Multimodal Learning Analytics for Understanding Collocated Collaboration in Authentic Classroom Settings.
Proceedings of the 20th IEEE International Conference on Advanced Learning Technologies, 2020

Quantifying Collaboration Quality in Face-to-Face Classroom Settings Using MMLA.
Proceedings of the Collaboration Technologies and Social Computing, 2020

2019
An Architecture and Data Model to Process Multimodal Evidence of Learning.
Proceedings of the Advances in Web-Based Learning - ICWL 2019, 2019

Exploring the Triangulation of Dimensionality Reduction When Interpreting Multimodal Learning Data from Authentic Settings.
Proceedings of the Transforming Learning with Meaningful Technologies, 2019


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