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Khamisi Kalegele – International Journal of Education and Development using Information and Communication Technology, 2023
Pragmatically, machine learning techniques can improve educators' capacity to monitor students' learning progress when applied to quality data. For developing countries, the major obstacle has been the unavailability of quality data that fits the purpose. This is partly because the in-use information systems are either not properly managed or not…
Descriptors: Artificial Intelligence, Learning Management Systems, Progress Monitoring, Data Use
Randhir Rawatlal; Rubby Dhunpath – Association for Institutional Research, 2023
Although student advising is known to improve student success, its application is often inadequate in institutions that are resource constrained. Given recent advances in large language models (LLMs) such as Chat Generative Pre-trained Transformer (ChatGPT), automated approaches such as the AutoScholar Advisor system affords viable alternatives to…
Descriptors: Academic Advising, Technology Uses in Education, Artificial Intelligence, Progress Monitoring
Aburizaizah, Saeed Jameel – Journal of Education and Learning, 2021
For many justifications, the collection, analysis, and use of educational data are central to the evaluation and improvement of students' progress and learning outcomes. The use of data in educational evaluation and decision making are expected to span all layers--from the institution, teachers, students, and classroom levels, providing a…
Descriptors: Data Use, Decision Making, Progress Monitoring, Learning Analytics
Mozahem, Najib Ali – International Journal of Mobile and Blended Learning, 2020
Higher education institutes are increasingly turning their attention to web-based learning management systems. The purpose of this study is to investigate whether data collected from LMS can be used to predict student performance in classrooms that use LMS to supplement face-to-face teaching. Data was collected from eight courses spread across two…
Descriptors: Integrated Learning Systems, Data Use, Prediction, Academic Achievement
Miller, Cynthia; Cohen, Benjamin; Yang, Edith; Pellegrino, Lauren – MDRC, 2020
College students have a better chance of succeeding in school when they receive high-quality advising. High-quality advising, when characterized by frequent communications between advisers and students, early outreach to students showing signs of academic or nonacademic struggles, and personalized guidance that addresses individual student needs,…
Descriptors: College Students, Academic Advising, Technology Uses in Education, Faculty Advisers
Achieving the Dream, 2018
Helping more students achieve their dreams involves identifying a wider set of student needs--including financial challenges and family responsibilities--and offering redesigned support services to meet them holistically. This holistic student supports approach emphasizes the need for colleges to redefine the way they understand, design, integrate…
Descriptors: Holistic Approach, Program Design, College Programs, Academic Support Services