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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
Ean Teng Khor; Dave Darshan – International Journal of Information and Learning Technology, 2024
Purpose: This study leverages social network analysis (SNA) to visualise the way students interacted with online resources and uses the data obtained from SNA as features for supervised machine learning algorithms to predict whether a student will successfully complete a course. Design/methodology/approach: The exploration and visualisation of the…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
Pooja Rana; Mithilesh Kumar Dubey; Lovi Raj Gupta; Amit Kumar Thakur – Interactive Learning Environments, 2024
In recent years, the system of student learning and academic emotions has been taken seriously to re-engineer the teaching-learning process at all levels of education. This research paper considers both aspects of assessing the translation of knowledge i.e. qualitative and quantitative. In the current scenario, quantitative and qualitative…
Descriptors: Educational Assessment, Outcomes of Education, Models, Evaluation 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
Hao Wu; Shan Li; Ying Gao; Jinta Weng; Guozhu Ding – Education and Information Technologies, 2024
Natural language processing (NLP) has captivated the attention of educational researchers over the past three decades. In this study, a total of 2,480 studies were retrieved through a comprehensive literature search. We used neural topic modeling and pre-trained language modeling to explore the research topics pertaining to the application of NLP…
Descriptors: Natural Language Processing, Educational Research, Research Design, Educational Trends
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)
Ho, Chun-Heng; Zhang, Hang-qin; Li, Juan; Zhang, Min-quan – International Journal of Distance Education Technologies, 2023
Digital education has recently become a mainstream education model. Despite digital education's increasing popularity, there remain issues when it comes to teacher-student interactions in digital space, which have made it impossible for this model to achieve the same teaching quality as traditional in-person education. Compared with other academic…
Descriptors: Technology Uses in Education, Electronic Learning, Teacher Student Relationship, Interaction
Sungjin Nam – ProQuest LLC, 2020
This dissertation presents various machine learning applications for predicting different cognitive states of students while they are using a vocabulary tutoring system, DSCoVAR. We conduct four studies, each of which includes a comprehensive analysis of behavioral and linguistic data and provides data-driven evidence for designing personalized…
Descriptors: Vocabulary Development, Intelligent Tutoring Systems, Student Evaluation, Learning Analytics