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Showing 1 to 15 of 51 results Save | Export
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Wannapon Suraworachet; Qi Zhou; Mutlu Cukurova – Journal of Computer Assisted Learning, 2025
Background: Many researchers work on the design and development of multimodal collaboration support systems with AI, yet very few of these systems are mature enough to provide actionable feedback to students in real-world settings. Therefore, a notable gap exists in the literature regarding students' perceptions of such systems and the feedback…
Descriptors: Graduate Students, Student Attitudes, Artificial Intelligence, Cooperative Learning
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Flora Ji-Yoon Jin; Bhagya Maheshi; Wenhua Lai; Yuheng Li; Danijela Gasevic; Guanliang Chen; Nicola Charwat; Philip Wing Keung Chan; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Learning Analytics, 2025
This paper explores the integration of generative AI (GenAI) in the feedback process in higher education through a learning analytics (LA) tool, examined from a feedback literacy perspective. Feedback literacy refers to students' ability to understand, evaluate, and apply feedback effectively to improve their learning, which is crucial for…
Descriptors: College Students, Student Attitudes, Artificial Intelligence, Learning Analytics
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Christothea Herodotou; Sagun Shrestha; Catherine Comfort; Heshan Andrews; Paul Mulholland; Vaclav Bayer; Claire Maguire; John Lee; Miriam Fernandez – Journal of Learning Analytics, 2025
In this paper, we explore the design of a student-facing dashboard for online and distance learning with a focus on capturing and addressing specific learning needs. A participatory process involving 20 students was employed, which included a screening questionnaire and focus group discussions. The selection of data points to be displayed on the…
Descriptors: Electronic Learning, Distance Education, Student Attitudes, Educational Technology
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Marijn Martens; Ralf De Wolf; Lieven De Marez – Technology, Knowledge and Learning, 2025
Algorithmic decision-making systems such as Learning Analytics (LA) are widely used in an educational setting ranging from kindergarten to university. Most research focuses on how LA is used and adopted by teachers. However, the perspective of students and parents who experience the (in)direct consequences of these systems is underexplored. This…
Descriptors: Algorithms, Decision Making, Learning Analytics, Secondary School Students
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Vanessa Echeverria; Gloria Fernandez Nieto; Linxuan Zhao; Evelyn Palominos; Namrata Srivastava; Dragan Gaševic; Viktoria Pammer-Schindler; Roberto Martinez-Maldonado – Journal of Computer Assisted Learning, 2025
Background: Dashboards play a prominent role in learning analytics (LA) research. In collaboration activities, dashboards can show traces of team participation. They are often evaluated based on students' perceived satisfaction and engagement with the dashboard. However, there is a notable methodological gap in understanding how these dashboards…
Descriptors: Learning Analytics, Educational Technology, Student Attitudes, Reflection
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Sonsoles Lopez-Pernas; Kamila Misiejuk; Rogers Kaliisa; Mohammed Saqr – IEEE Transactions on Learning Technologies, 2025
Despite the growing use of large language models (LLMs) in educational contexts, there is no evidence on how these can be operationalized by students to generate custom datasets suitable for teaching and learning. Moreover, in the context of network science, little is known about whether LLMs can replicate real-life network properties. This study…
Descriptors: Students, Artificial Intelligence, Man Machine Systems, Interaction
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Marijn Martens; Ralf De Wolf; Lieven De Marez – Education and Information Technologies, 2024
Algorithmic systems such as Learning Analytics (LA) are driving the datafication and algorithmization of education. In this research, we focus on the appropriateness of LA systems from the perspective of parents and students in secondary education. Anchored in the contextual integrity framework (Nissenbaum, "Washington Law Review, 79,"…
Descriptors: Parent Attitudes, Student Attitudes, Learning Analytics, Algorithms
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Eduardo Davalos; Namrata Srivastava; Yike Zhang; Amanda Goodwin; Gautam Biswas – Grantee Submission, 2024
As online learning tools become more widespread, understanding student behaviors through learning analytics is increasingly important. Traditional methods relying on system log data fall short of capturing the full range of cognitive strategies students use. To address this, we developed an in-depth post-assignment reflection dashboard that…
Descriptors: Visualization, Eye Movements, Electronic Learning, Online Courses
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Gerardo Ibarra-Vazquez; Maria Soledad Ramirez-Montoya; Mariana Buenestado-Fernandez – IEEE Transactions on Learning Technologies, 2024
This article aims to study the performance of machine learning models in forecasting gender based on the students' open education competency perception. Data were collected from a convenience sample of 326 students from 26 countries using the eOpen instrument. The analysis comprises 1) a study of the students' perceptions of knowledge, skills, and…
Descriptors: Gender Differences, Open Education, Cross Cultural Studies, Student Attitudes
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Udi Alter; Carmen Dang; Zachary J. Kunicki; Alyssa Counsell – Teaching Statistics: An International Journal for Teachers, 2024
The biggest difference in statistical training from previous decades is the increased use of software. However, little research examines how software impacts learning statistics. Assessing the value of software to statistical learning demands appropriate, valid, and reliable measures. The present study expands the arsenal of tools by reporting on…
Descriptors: Statistics Education, Student Attitudes, Course Descriptions, Social Sciences
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Nick Hopwood; Tracey-Ann Palmer; Gloria Angela Koh; Mun Yee Lai; Yifei Dong; Sarah Loch; Kun Yu – International Journal of Research & Method in Education, 2025
Student emotions influence assessment task behaviour and performance but are difficult to study empirically. The study combined qualitative data from focus group interviews with 22 students and 4 teachers, with quantitative real-time learning analytics (facial expression, mouse click and keyboard strokes) to examine student emotional engagement in…
Descriptors: Psychological Patterns, Student Evaluation, Learning Analytics, Learner Engagement
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Conrad Borchers; Cindy Peng; Qianru Lyu; Paulo F. Carvalho; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2025
Many AIED systems support self-regulated learning, yet, support for setting and achieving practice goals has received little attention. We examine how middle school students respond to system-recommended practice goals, building on the success of similar data-driven recommendations in other domains. We introduce an adaptive dashboard in an…
Descriptors: Goal Orientation, Student Attitudes, Self Control, Intelligent Tutoring Systems
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Muhittin Sahin – Interactive Learning Environments, 2024
Learning analytics aims to improve learning and teaching in digital learning environments by optimizing them. Real-time feedback, suggestions, directions, and interventions are structured in the digital learning environments. In order to structure more effective interventions, it is crucial to ascertain which of these services offered to students…
Descriptors: Learning Analytics, Intervention, Student Attitudes, Preferences
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Maya Usher; Noga Reznik; Gilad Bronshtein; Dan Kohen-Vacs – Journal of Learning Analytics, 2025
Computational thinking (CT) is a critical 21st-century skill that equips undergraduate students to solve problems systematically and think algorithmically. A key component of CT is computational creativity, which enables students to generate novel solutions within programming constraints. Humanoid robots are increasingly explored as promising…
Descriptors: Computation, Thinking Skills, Creativity, Robotics
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Ignacio Villagrán; Rocio Hernández; Gregory Schuit; Andrés Neyem; Javiera Fuentes; Loreto Larrondo; Elisa Margozzini; María T. Hurtado; Zoe Iriarte; Constanza Miranda; Julián Varas; Isabel Hilliger – Journal of Learning Analytics, 2024
Remote technology has been widely incorporated into health professions education. For procedural skills training, effective feedback and reflection processes are required. Consequently, supporting a self-regulated learning (SRL) approach with learning analytics dashboards (LADs) has proven beneficial in online environments. Despite the potential…
Descriptors: Feedback (Response), Independent Study, Skill Development, Learning Analytics
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