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Lea Katharina Dietrich; Simone Grassini – Education and Information Technologies, 2025
Artificial intelligence (AI) has garnered significant attention in recent years, especially following the introduction of generative large language model (LLM)-based chatbots. This study investigates the factors influencing the adoption of ChatGPT, a widely used AI-powered chatbot, among students and teachers. Using the Unified Theory of…
Descriptors: Artificial Intelligence, Technology Uses in Education, Foreign Countries, Comparative Education
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Xingshi Gao; Christian D. Schunn; Omid Noroozi; Judith Gulikers; Seyyed Kazem Banihashem; Harm Biemans – Assessment & Evaluation in Higher Education, 2025
The value of peer feedback for learning depends upon students regularly providing high-quality feedback to their peers, but little is known about the factors influencing feedback-providing behaviors. This study explores the consistency of students' feedback-providing behaviors and its relations to students' writing ability (an individual…
Descriptors: Peer Evaluation, Feedback (Response), Writing Skills, Student Characteristics
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Osipenko, Maria – Education and Information Technologies, 2022
A data-driven model where individual learning behavior is a linear combination of certain stylized learning patterns scaled by learners' affinities is proposed. The absorption of stylized behavior through the affinities constitutes "building blocks" in the model. Non-negative matrix factorization is employed to extract common learning…
Descriptors: Behavior Patterns, Models, Undergraduate Students, Preferences
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Jansen, Renée S.; Leeuwen, Anouschka; Janssen, Jeroen; Kester, Liesbeth – Journal of Computer Assisted Learning, 2022
Background: Learners in Massive Open Online Courses (MOOCs) are presented with great autonomy over their learning process. Learners must engage in self-regulated learning (SRL) to handle this autonomy. It is assumed that learners' SRL, through monitoring and control, influences learners' behaviour within the MOOC environment (e.g., watching…
Descriptors: Student Behavior, Learning Processes, Online Courses, Personal Autonomy
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Tabares, Marta S.; Vallejo, Paola; Montoya, Alex; Correa, Daniel – Journal of Computing in Higher Education, 2022
Understanding learners' behavior is the key to the success of any learning process. The more we know about them, the more likely we can personalize learning experiences and provide successful feedback. This paper presents a feedback model implemented in a ubiquitous microlearning environment based on contextual and behavioral information and…
Descriptors: Feedback (Response), Models, Student Behavior, Educational Environment
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Chambers, Brittany; Lowe, Jaylen; Muldrow, Lycurgus – Journal of STEM Education: Innovations and Research, 2022
There remains a need for more diverse STEM students that will be equipped with the necessary skills and growth mindset principles to pursue STEM positions and careers. While previous research has examined broadening participation through interventions geared toward a specific group, the intervention method used in this research case study utilized…
Descriptors: Student Attitudes, STEM Education, College Students, Intervention
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Humida, Thasnim; Al Mamun, Md Habib; Keikhosrokiani, Pantea – Education and Information Technologies, 2022
Digital transformation and emerging technologies open a horizon to a new method of teaching and learning and revolutionizes the e-learning industry. The goal of this study is to scrutinize a proposed research model for predicting factors that influence student's behavioral intention to use e-learning system at Begum Rokeya University, Bangladesh.…
Descriptors: Student Behavior, Intention, Electronic Learning, College Students
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Gillett-Swan, Jenna K.; Lundy, Laura – Oxford Review of Education, 2022
Schools present a unique context for the generation and resolution of conflicts of human rights. While the conflicts that arise are many and various, a default response appears to be the prioritisation of the rights of the majority. Hence the rights of the many then trump the rights of the few. However, the intersection of multiple stakeholders,…
Descriptors: Civil Rights, Conflict Resolution, Student Behavior, Conflict
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Luna, J. M.; Fardoun, H. M.; Padillo, F.; Romero, C.; Ventura, S. – Interactive Learning Environments, 2022
The aim of this paper is to categorize and describe different types of learners in massive open online courses (MOOCs) by means of a subgroup discovery (SD) approach based on MapReduce. The proposed SD approach, which is an extension of the well-known FP-Growth algorithm, considers emerging parallel methodologies like MapReduce to be able to cope…
Descriptors: Online Courses, Student Characteristics, Classification, Student Behavior
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Gao, Zhikai; Erickson, Bradley; Xu, Yiqiao; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2022
In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…
Descriptors: Computer Science Education, College Students, Programming, Coding
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Karnalim, Oscar; Simon; Chivers, William; Panca, Billy Susanto – ACM Transactions on Computing Education, 2022
To help address programming plagiarism and collusion, students should be informed about acceptable practices and about program similarity, both coincidental and non-coincidental. However, current approaches are usually manual, brief, and delivered well before students are in a situation where they might commit academic misconduct. This article…
Descriptors: Computer Science Education, Programming, Plagiarism, Formative Evaluation
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Tay, Hui Yong; Lam, Karen W. L. – Educational Research for Policy and Practice, 2022
The provision of feedback is widely practised as part of formative assessment. However, studies that examine the impact of feedback are usually from the teachers' perspective, focusing on why and how they provide feedback. Fewer studies examine feedback from the students' perspective, especially in the way they experience, make sense of and take…
Descriptors: Learner Engagement, Feedback (Response), Student Attitudes, Essays
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Parks-Leduc, Laura; Guay, Russell P.; Mulligan, Leigh M. – Journal of Academic Ethics, 2022
In this study we examine college cheating behaviors of business students compared to non-business students, and investigate possible antecedents to cheating in an effort to better understand why and when students cheat. We specifically examine power values; we found that they were positively related to academic cheating in our sample, and that…
Descriptors: Values, Cheating, Business Administration Education, Majors (Students)
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Krienert, Jessie L.; Walsh, Jeffrey A.; Cannon, Kevin D. – College Teaching, 2022
Academic dishonesty is pervasive among college students throughout the country. Current research suggests that more than half of students report engaging in cheating behavior while in college. While traditional forms of cheating behavior remain, technology has ushered in new opportunities making cheating more accessible by more students and harder…
Descriptors: Cheating, Student Behavior, Ethics, Achievement Need
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Coppess, Brian – Educational Research: Theory and Practice, 2022
Largely because of its behaviorist roots and despite several progressive education movements, external control has been the primary motivation technique used by educators since the dawn of formal schooling in the United States. Decades of recent research, however, has led to a paradigm shift of sorts, suggesting that by challenging their mental…
Descriptors: Cognitive Processes, Student Motivation, Motivation Techniques, Principals
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