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Developing Temporal Machine Learning Approaches to Support Modeling, Explaining, and Sensemaking of Academic Success and Risk of Undergraduate Students
Title
Developing Temporal Machine Learning Approaches to Support Modeling, Explaining, and Sensemaking of Academic Success and Risk of Undergraduate Students
Author
Nur, Nasheen
Date Created
2021
Subjects--Topical
Artificial intelligence, Education
Description
The main goal of learning analytics and early detection systems is to extract knowledge from student data to understand students’ trends of activities towards success and risk and design intervention methods to improve learning performance and exp...
Motivating Computer Science Students Beyond Classwork with Games and Gamification
Title
Motivating Computer Science Students Beyond Classwork with Games and Gamification
Author
Watson, Stacey
Date Created
2018
Subjects--Topical
Computer science, Education
Description
Researchers have determined that games have the power to motivate users to engage for long periods of time with unparalleled intensity because they satisfy human psychological and emotional needs. In educational contexts, researchers have examined...
Scaffolding Reflective Practice with an Ecology of Data-Driven Reflection Support Tools
Title
Scaffolding Reflective Practice with an Ecology of Data-Driven Reflection Support Tools
Author
MacNeil, Stephen
Date Created
2019
Subjects--Topical
Computer science, Education, Psychology
Description
Reflection is a process of converting experience into understanding. Through the process of reflection, students actively engage in sense-making around an experience; situating it within their existing experiences, beliefs, and knowledge. Though m...
Sentiment Analysis on Verbal Data from Team Discussions As an Indicator of Individual Performance
Title
Sentiment Analysis on Verbal Data from Team Discussions As an Indicator of Individual Performance
Author
Dehbozorgi, Nasrin
Date Created
2020
Subjects--Topical
Computer science, Education
Description
The inherently complex nature of evaluating teamwork calls for methods to measure and predict students’ performance and provide timely feedback. Analyzing students’ individual performance, particularly in low-stake teams, is a challenge since the ...
Student Sequence Model: A Temporal Model for Exploring and Predicting Risk from Heterogeneous Student Data
Title
Student Sequence Model: A Temporal Model for Exploring and Predicting Risk from Heterogeneous Student Data
Author
Mahzoon, Mohammad Javad
Date Created
2018
Subjects--Topical
Education, Information technology
Description
Data models built for analyzing student data often obfuscate temporal relationships for reasons of simplicity, or to aid in generalization. We present a sequence model that is based on temporal relationships in heterogeneous student data as the ba...