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Kerstin Wagner; Agathe Merceron; Petra Sauer; Niels Pinkwart – Journal of Educational Data Mining, 2024
In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…
Descriptors: At Risk Students, Algorithms, Foreign Countries, Course Selection (Students)
Ntema, Ratoeba Piet – Journal of Student Affairs in Africa, 2022
Student dropout is a significant concern for university administrators, students and other stakeholders. Dropout is recognised as highly complex due to its multi-causality, which is expressed in the existing relationship in its explanatory variables associated with students, their socio-economic and academic conditions, and the characteristics of…
Descriptors: College Students, Dropout Characteristics, At Risk Students, Profiles
Yürüm, Ozan Rasit; Taskaya-Temizel, Tugba; Yildirim, Soner – Education and Information Technologies, 2023
Video clickstream behaviors such as pause, forward, and backward offer great potential for educational data mining and learning analytics since students exhibit a significant amount of these behaviors in online courses. The purpose of this study is to investigate the predictive relationship between video clickstream behaviors and students' test…
Descriptors: Video Technology, Educational Technology, Learning Management Systems, Data Collection
De Silva, Liyanachchi Mahesha Harshani; Chounta, Irene-Angelica; Rodríguez-Triana, María Jesús; Roa, Eric Roldan; Gramberg, Anna; Valk, Aune – Journal of Learning Analytics, 2022
Although the number of students in higher education institutions (HEIs) has increased over the past two decades, it is far from assured that all students will gain an academic degree. To that end, institutional analytics (IA) can offer insights to support strategic planning with the aim of reducing dropout and therefore of minimizing its negative…
Descriptors: College Students, Dropouts, Dropout Prevention, Data Analysis
Huang, Anna Y. Q.; Lu, Owen H. T.; Huang, Jeff C. H.; Yin, C. J.; Yang, Stephen J. H. – Interactive Learning Environments, 2020
In order to enhance the experience of learning, many educators applied learning analytics in a classroom, the major principle of learning analytics is targeting at-risk student and given timely intervention according to the results of student behavior analysis. However, when researchers applied machine learning to train a risk identifying model,…
Descriptors: Academic Achievement, Data Use, Learning Analytics, Classification
Rao, A. Ravishshankar – Advances in Engineering Education, 2020
Studies show that a significant fraction of students graduating from high schools in the U.S. is ill prepared for college and careers. Some problems include weak grounding in math and writing, lack of motivation, and insufficient conscientiousness. Academic institutions are under pressure to improve student retention and graduate rates, whereas…
Descriptors: Learner Engagement, Student Motivation, Prediction, Academic Achievement
Lederer, Alyssa M.; Hoban, Mary T.; Lipson, Sarah K.; Zhou, Sasha; Eisenberg, Daniel – Health Education & Behavior, 2021
U.S. college students are a distinct population facing major challenges due to the COVID-19 pandemic. Before the pandemic, students were already experiencing substantial mental health concerns, putting both their health and academic success in jeopardy. College students now face increasing housing and food insecurity, financial hardships, a lack…
Descriptors: College Students, Student Needs, COVID-19, Pandemics
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
Hofer, Andrea-Rosalinde; Brüning, Nora – OECD Publishing, 2022
This country note presents the results of an analysis of undertake Portugal undertaken within the Labour Market Relevance and Outcomes of Higher Education Partnership Initiative project. The project was implemented by the OECD with the support of the European Commission with the aim of helping policy makers and higher education institutions…
Descriptors: Foreign Countries, Labor Market, Relevance (Education), Outcomes of Education