DeepAI AI Chat
Log In Sign Up

Towards Explainable Student Group Collaboration Assessment Models Using Temporal Representations of Individual Student Roles

by   Anirudh Som, et al.

Collaboration is identified as a required and necessary skill for students to be successful in the fields of Science, Technology, Engineering and Mathematics (STEM). However, due to growing student population and limited teaching staff it is difficult for teachers to provide constructive feedback and instill collaborative skills using instructional methods. Development of simple and easily explainable machine-learning-based automated systems can help address this problem. Improving upon our previous work, in this paper we propose using simple temporal-CNN deep-learning models to assess student group collaboration that take in temporal representations of individual student roles as input. We check the applicability of dynamically changing feature representations for student group collaboration assessment and how they impact the overall performance. We also use Grad-CAM visualizations to better understand and interpret the important temporal indices that led to the deep-learning model's decision.


A Machine Learning Approach to Assess Student Group Collaboration Using Individual Level Behavioral Cues

K-12 classrooms consistently integrate collaboration as part of their le...

Deep-IRT: Make Deep Learning Based Knowledge Tracing Explainable Using Item Response Theory

Deep learning based knowledge tracing model has been shown to outperform...

Experiential Learning in Bioinformatics – Learner Support for Complex Workflow Modelling and Analysis

Bioinformatics is focused on deriving biological understanding from larg...

Assessment Formats and Student Learning Performance: What is the Relation?

Although compelling assessments have been examined in recent years, more...

Who does what? Work division and allocation strategies of computer science student teams

Collaboration skills are important for future software engineers. In com...

Fair and skill-diverse student group formation via constrained k-way graph partitioning

Forming the right combination of students in a group promises to enable ...

Quantitative analysis of approaches to group marking

Group work, where students work on projects to overcome challenges toget...