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Showing 1 to 15 of 209 results Save | Export
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Caitlin Snyder; Clayton Cohn; Joyce Horn Fonteles; Gautam Biswas – Grantee Submission, 2025
Recently, there has been a surge in developing curricula and tools that integrate computing (C) into Science, Technology, Engineering, and Math (STEM) programs. These environments foster authentic problem-solving while facilitating students' concurrent learning of STEM+C content. In our study, we analyzed students' behaviors as they worked in…
Descriptors: Learning Analytics, Problem Solving, STEM Education, Computation
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Corey Schimpf; Ruby Castellani; Molly H. Goldstein – International Journal of Technology and Design Education, 2025
Worldwide, engineering design is seeing an increase in pre-college settings due to changing educational policies and standards. Additionally, these projects can help students develop critical skills for a broad range of problem settings, such as design thinking and reflection. In design and other contexts, reflection is a mental process where…
Descriptors: Engineering Education, Reflection, Educational Technology, Learning Analytics
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Flora Ji-Yoon Jin; Debarshi Nath; Rui Guan; Tongguang Li; Xinyu Li; Rafael Ferreira Mello; Luiz Rodrigues; Cleon Pereira Junior; Heba Abuzayyad-Nuseibeh; Mladen Rakovic; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Computer Assisted Learning, 2025
Background: A key skill for self-regulated learners is the ability to critically interpret and act on feedback--key components of feedback literacy. Yet, the connection between feedback literacy and self-regulated learning (SRL) remains underexplored, particularly in terms of how different levels of feedback literacy influence SRL processes in…
Descriptors: Independent Study, Learning Analytics, Feedback (Response), Literacy
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Joni Lämsä; Justin Edwards; Eetu Haataja; Marta Sobocinski; Paola R. Peña; Andy Nguyen; Sanna Järvelä – Journal of Learning Analytics, 2024
The theory of socially shared regulation of learning (SSRL) suggests that successful collaborative groups can identify and respond to trigger events stemming from cognitive or emotional obstacles in learning. Thus, to develop real-time support for SSRL, novel metrics are needed to identify different types of trigger events that invite SSRL. Our…
Descriptors: Cooperative Learning, Learning Analytics, Linguistics, Physiology
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Halim Acosta; Seung Lee; Daeun Hong; Wookhee Min; Bradford Mott; Cindy Hmelo-Silver; James Lester – International Educational Data Mining Society, 2025
Understanding the relationship between student behaviors and learning outcomes is crucial for designing effective collaborative learning environments. However, collaborative learning analytics poses significant challenges, not only due to the complex interplay between collaborative problem-solving and collaborative dialogue but also due to the…
Descriptors: Learning Analytics, Cooperative Learning, Student Behavior, Prediction
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Richard Lee Davis; Bertrand Schneider; Leah F. Rosenbaum; Paulo Blikstein – Educational Technology Research and Development, 2024
This study investigated the impact of participating in a year-long digital-fabrication course on high-school seniors' problem-solving skills, with a focus on problems involving mechanistic systems. The research questions centered on whether working in a makerspace impacted students' abilities to solve such problems and whether the process data…
Descriptors: Experiential Learning, Learning Analytics, Problem Solving, Expertise
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Belle Dang; Andy Nguyen; Sanna Järvelä – Journal of Learning Analytics, 2024
Socially shared regulation in learning (SSRL) contributes to successful collaborative learning (CL). Empirical research into SSRL has received considerable attention recently, with increasingly available multimodal data, advanced learning analytics (LA), and artificial intelligence (AI) providing promising research avenues. Yet, integrating these…
Descriptors: Learning Analytics, Cooperative Learning, Artificial Intelligence, Epistemology
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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
Juliana Irene Owen Thompson – ProQuest LLC, 2023
Aurelius School District used Curriculum Associates' i-Ready program, which was philosophically aligned to the science of reading and included i-Ready Diagnostic, i-Ready Instruction, and Teacher Toolbox, to improve Cole Middle School students' reading achievement. Because of the high monetary cost of i-Ready, the school district was considering…
Descriptors: Middle Schools, Learning Management Systems, Learning Analytics, Reading Achievement
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Eamon Vale; Garry Falloon – Online Learning, 2024
This research investigated the potential of learning analytics (LA) as a tool for identifying and evaluating K-12 student behaviors associated with active learning when using video learning objects within an online learning environment (OLE). The study focused on the application of LA for evaluating K-12 student engagement in videobased…
Descriptors: Learning Analytics, Elementary School Students, Secondary School Teachers, Electronic Learning
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Onur Karademir; Daniele Di Mitri; Jan Schneider; Ioana Jivet; Jörn Allmang; Sebastian Gombert; Marcus Kubsch; Knut Neumann; Hendrik Drachsler – Journal of Computer Assisted Learning, 2024
Background: Teacher dashboards can help secondary school teachers manage online learning activities and inform instructional decisions by visualising information about class learning. However, when designing teacher dashboards, it is not trivial to choose which information to display, because not all of the vast amount of information retrieved…
Descriptors: Learning Analytics, Secondary School Teachers, Educational Technology, Design
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Teemu Valtonen; Teija Paavilainen; Sonsoles López-Pernas; Mohamed Saqr; Laura Hirsto – Technology, Knowledge and Learning, 2025
This study focuses on learning analytics from the perspective of elementary and secondary classroom teachers (grades one to nine). The aim is to explore teachers' perceptions about the use of learning analytics, the challenges and opportunities associated with the tools, and the future of the analytics. The research is based on qualitative data:…
Descriptors: Elementary School Teachers, Secondary School Teachers, Learning Analytics, Teacher Attitudes
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Nguyen, Andy; Järvelä, Sanna; Rosé, Carolyn; Järvenoja, Hanna; Malmberg, Jonna – British Journal of Educational Technology, 2023
Socially shared regulation contributes to the success of collaborative learning. However, the assessment of socially shared regulation of learning (SSRL) faces several challenges in the effort to increase the understanding of collaborative learning and support outcomes due to the unobservability of the related cognitive and emotional processes.…
Descriptors: Cooperative Learning, Physiology, Arousal Patterns, Cognitive Processes
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Ida Martinez Lunde – Scandinavian Journal of Educational Research, 2024
Learning analytics platforms (LAPs) have become important modes of anticipatory governance in education. Educational futures are governed by utilizing various forms of learning analytics to track student data over time, suggesting that school leaders and teachers are expected to improve school quality by engaging with digital presentations of…
Descriptors: Learning Analytics, Time, Networks, Social Theories
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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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