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Showing 1 to 15 of 62 results Save | Export
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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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Qin Ni; Yifei Mi; Yonghe Wu; Liang He; Yuhui Xu; Bo Zhang – IEEE Transactions on Learning Technologies, 2024
Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…
Descriptors: Cognitive Style, Electronic Learning, Prediction, Identification
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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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Anagha Vaidya; Sarika Sharma – Interactive Technology and Smart Education, 2024
Purpose: Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation…
Descriptors: Course Evaluation, Learning Analytics, Formative Evaluation, Information Retrieval
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Ramaswami, Gomathy; Susnjak, Teo; Mathrani, Anuradha; Umer, Rahila – Technology, Knowledge and Learning, 2023
Learning analytics dashboards (LADs) provide educators and students with a comprehensive snapshot of the learning domain. Visualizations showcasing student learning behavioral patterns can help students gain greater self-awareness of their learning progression, and at the same time assist educators in identifying those students who may be facing…
Descriptors: Prediction, Learning Analytics, Learning Management Systems, Identification
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Omer, Uzma; Tehseen, Rabia; Farooq, Muhammad Shoaib; Abid, Adnan – Education and Information Technologies, 2023
Learning analytics (LA) is a significant field of study to examine and identify difficulties the novice programmers face while learning how to program. Despite producing notable research by the community in the specified area, rare work is observed to synthesize these research efforts and discover the dimensions that guide the future research of…
Descriptors: Programming, Learning Analytics, Educational Research, Data
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Liu, Zhi; Kong, Xi; Chen, Hao; Liu, Sannyuya; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
In a massive open online courses (MOOCs) learning environment, it is essential to understand students' social knowledge constructs and critical thinking for instructors to design intervention strategies. The development of social knowledge constructs and critical thinking can be represented by cognitive presence, which is a primary component of…
Descriptors: MOOCs, Cognitive Processes, Students, Models
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Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
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Patterson, Chris R.; York, Emily; Maxham, Danielle; Molina, Rudy; Mabrey, Paul, III – Journal of Learning Analytics, 2023
The anticipation, inclusion, responsiveness, and reflexivity (AIRR) framework (Stilgoe et al., 2013) is a novel framework that has helped those in science and technology fields shift their focus from products to the processes used to create those products. However, the framework has not been known to be applied to the development and…
Descriptors: Learning Analytics, Innovation, School Holding Power, At Risk Students
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Qi Zhou; Wannapon Suraworachet; Mutlu Cukurova – Education and Information Technologies, 2024
Collaboration is argued to be an important skill, not only in schools and higher education contexts but also in the workspace and other aspects of life. However, simply asking students to work together as a group on a task does not guarantee success in collaboration. Effective collaborative learning requires meaningful interactions among…
Descriptors: Learning Analytics, Cooperative Learning, Nonverbal Communication, Speech Communication
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Treice de Oliveira Moreira; Cláudio Azevedo Passos; Flávio Roberto Matias da Silva; Paulo Márcio Souza Freire; Isabel Fernandes de Souza; Cláudia Rödel Bosaipo Sales da Silva; Ronaldo Ribeiro Goldschmidt – Education and Information Technologies, 2024
The problem of propagating disinformation (a.k.a. "fake news") on social media has increased significantly in the last few years. There are several initiatives around the world to combat this serious problem. Maybe the most promising ones involve training people to identify "fake news." The use of digital educational games…
Descriptors: Deception, News Reporting, Misinformation, Portuguese
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Kelly Linden; Neil van der Ploeg; Noelia Roman – Journal of Higher Education Policy and Management, 2023
There is a small window of opportunity at the beginning of semester for a university to provide commencing students with timely and targeted support. However, there is limited information available on interventions that identify and support disengaged students from equity groups without using equity group status as the basis for the contact. The…
Descriptors: Learner Engagement, Identification, Intervention, Learning Analytics
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Davies, Randall; Allen, Gove; Albrecht, Conan; Bakir, Nesrin; Ball, Nick – Education Sciences, 2021
Analyzing the learning analytics from a course provides insights that can impact instructional design decisions. This study used educational data mining techniques, specifically a longitudinal k-means cluster analysis, to identify the strategies students used when completing the online portion of an online flipped spreadsheet course. An analysis…
Descriptors: Data Analysis, Identification, Learning Strategies, Electronic Learning
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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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