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Michael Wade Ashby – ProQuest LLC, 2024
Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…
Descriptors: Artificial Intelligence, Algorithms, Prediction, Learning Management Systems
Tanjea Ane; Tabatshum Nepa – Research on Education and Media, 2024
Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…
Descriptors: Artificial Intelligence, Prediction, Models, Teaching Methods
Kukkar, Ashima; Mohana, Rajni; Sharma, Aman; Nayyar, Anand – Education and Information Technologies, 2023
Predicting student performance is crucial in higher education, as it facilitates course selection and the development of appropriate future study plans. The process of supporting the instructors and supervisors in monitoring students in order to upkeep them and combine training programs to get the best outcomes. It decreases the official warning…
Descriptors: Academic Achievement, Mental Health, Well Being, Interaction
Kamdjou, Herve D. Teguim – Open Education Studies, 2023
This article revisits the Mincer earnings function and presents comparable estimates of the average monetary returns associated with an additional year of education across different regions worldwide. In contrast to the traditional Ordinary Least Squares (OLS) method commonly employed in the literature, this study applied a cutting-edge approach…
Descriptors: Outcomes of Education, Artificial Intelligence, Human Capital, Regression (Statistics)
David B. Nelson; Anaelle Emma Gackiere; Samantha Elizabeth LeGrand; Daniel A. Guberman – Thresholds in Education, 2025
In response to the significant disruption posed by emergent AI technology, we propose a four part framework for teaching and learning practice and development. Rather than focus on the specific technologies of the moment, this framework provides actionable suggestions for individuals with varying views of AI and its positive and negative…
Descriptors: Teaching Methods, Learning Processes, Algorithms, Artificial Intelligence