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Giora Alexandron; Aviram Berg; Jose A. Ruiperez-Valiente – IEEE Transactions on Learning Technologies, 2024
This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…
Descriptors: Cheating, Identification, Online Courses, Artificial Intelligence
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Cleophas, Catherine; Hönnige, Christoph; Meisel, Frank; Meyer, Philipp – INFORMS Transactions on Education, 2023
As the COVID-19 pandemic motivated a shift to virtual teaching, exams have increasingly moved online too. Detecting cheating through collusion is not easy when tech-savvy students take online exams at home and on their own devices. Such online at-home exams may tempt students to collude and share materials and answers. However, online exams'…
Descriptors: Computer Assisted Testing, Cheating, Identification, Essay Tests
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Vatsalan, Dinusha; Rakotoarivelo, Thierry; Bhaskar, Raghav; Tyler, Paul; Ladjal, Djazia – British Journal of Educational Technology, 2022
With Big Data revolution, the education sector is being reshaped. The current data-driven education system provides many opportunities to utilize the enormous amount of collected data about students' activities and performance for personalized education, adapting teaching methods, and decision making. On the other hand, such benefits come at a…
Descriptors: Privacy, Risk, Data, Markov Processes
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Khalid Oqaidi; Sarah Aouhassi; Khalifa Mansouri – International Association for Development of the Information Society, 2022
The dropout of students is one of the major obstacles that ruin the improvement of higher education quality. To facilitate the study of students' dropout in Moroccan universities, this paper aims to establish a clustering approach model based on machine learning algorithms to determine Moroccan universities categories. Our objective in this…
Descriptors: Models, Prediction, Dropouts, Learning Analytics
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Lynnette Brice; Alison Harrison; Alan Cadwallader – Journal of Open, Flexible and Distance Learning, 2023
The purpose of this paper is to share insights gained from the discovery, design, and delivery phases of creating a three-tiered model of non-academic learning support in open, distance, and flexible learning (ODFL): "Learner Engagement and Success Services (LESS)", at Open Polytechnic | Te Pukenga, New Zealand. Presented as a case…
Descriptors: Ethics, Learning Analytics, Intervention, Foreign Countries
Acosta, Alejandra – New America, 2020
Predictive analytics has taken higher education by storm, with its promise of closing equity gaps, raising student retention rates, and increasing tuition revenue by keeping students enrolled. Many colleges and universities have made an investment in predictive analytics for student success initiatives, and even more are looking into implementing,…
Descriptors: Prediction, Learning Analytics, Higher Education, Information Dissemination
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Williams, Janet M.; Pulido, Laurie – American Association for Adult and Continuing Education, 2022
During the COVID-19 pandemic, an adult noncredit program in the California Community College system partnered with Ease Learning to help convert face-to-face courses to an online modality. Subsequent data revealed a misalignment in the courses' Student Learning Outcomes and Instructional Objectives which became a barrier to student success. Wile's…
Descriptors: Best Practices, Teaching Methods, Online Courses, Outcomes of Education
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Hui, Bowen – International Journal of Information and Learning Technology, 2022
Purpose: The purpose of this work is to illustrate the processes involved in managing teams in order to assist designers and developers to build software that support teamwork. A deeper investigation into the role of team analytics is discussed in this article. Design/methodology/approach: Many researchers over the past several decades studied the…
Descriptors: Design, Guidelines, Research Needs, Teamwork