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Bahar Radmehr; Adish Singla; Tanja Käser – International Educational Data Mining Society, 2024
There has been a growing interest in developing learner models to enhance learning and teaching experiences in educational environments. However, existing works have primarily focused on structured environments relying on meticulously crafted representations of tasks, thereby limiting the agent's ability to generalize skills across tasks. In this…
Descriptors: Reinforcement, Artificial Intelligence, Educational Environment, Natural Language Processing
MacLellan, Christopher J.; Gupta, Adit – International Educational Data Mining Society, 2021
There has been great progress towards Reinforcement Learning (RL) approaches that can achieve expert performance across a wide range of domains. However, researchers have not yet applied these models to learn expert models for educationally relevant tasks, such as those taught within tutoring systems and educational games. In this paper we explore…
Descriptors: Models, Learning Activities, Relevance (Education), Reinforcement
Süleyman Özdel; Can Sarpkaya; Efe Bozkir; Hong Gao; Enkelejda Kasneci – International Educational Data Mining Society, 2025
Transforming educational technologies through the integration of large language models (LLMs) and virtual reality (VR) offers the potential for immersive and interactive learning experiences. However, the effects of LLMs on user engagement and attention in educational environments remain open questions. In this study, we utilized a fully…
Descriptors: Technology Uses in Education, Educational Technology, Artificial Intelligence, Computer Simulation
Robin Jephthah Rajarathinam; Chris Palaguachi; Jina Kang – International Educational Data Mining Society, 2024
Multimodal Learning Analytics (MMLA) has emerged as a powerful approach within the computer-supported collaborative learning community, offering nuanced insights into learning processes through diverse data sources. Despite its potential, the prevalent reliance on traditional instruments such as tripod-mounted digital cameras for video capture…
Descriptors: Learning Analytics, Cooperative Learning, Photography, Video Technology
Sense, Florian; Krusmark, Michael; Fiechter, Joshua; Collins, Michael G.; Sanderson, Lauren; Onia, Joshua; Jastrzembski, Tiffany – International Educational Data Mining Society, 2021
Cardiopulmonary resuscitation (CPR) is a foundational lifesaving skill for which medical personnel are expected to be proficient. Frequent refresher training is needed to prevent the involved skills from decaying. Regular low-dose, high-frequency training for staff at fixed intervals has proven successful at maintaining CPR competence but does not…
Descriptors: First Aid, Training, Artificial Intelligence, Prediction
Cock, Jade; Marras, Mirko; Giang, Christian; Käser, Tanja – International Educational Data Mining Society, 2021
Interactive simulations allow students to independently explore scientific phenomena and ideally infer the underlying principles through their exploration. Effectively using such environments is challenging for many students and therefore, adaptive guidance has the potential to improve student learning. Providing effective support is, however,…
Descriptors: Prediction, Concept Formation, Scientific Concepts, Physics
Cock, Jade Maï; Marras, Mirko; Giang, Christian; Käser, Tanja – International Educational Data Mining Society, 2022
Interactive simulations allow students to discover the underlying principles of a scientific phenomenon through their own exploration. Unfortunately, students often struggle to learn effectively in these environments. Classifying students' interaction data in the simulations based on their expected performance has the potential to enable adaptive…
Descriptors: Science Instruction, Prediction, Models, Interaction
Li, ZhaoBin; Yee, Luna; Sauerberg, Nathaniel; Sakson, Irene; Williams, Joseph Jay; Rafferty, Anna N. – International Educational Data Mining Society, 2020
Digital educational technologies offer the potential to customize students' experiences and learn what works for which students, enhancing the technology as more students interact with it. We consider whether and when attempting to discover how to personalize has a cost, such as if the adaptation to personal information can delay the adoption of…
Descriptors: Educational Technology, Technology Uses in Education, Student Needs, Student Characteristics
Ju, Song; Zhou, Guojing; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Identifying critical decisions is one of the most challenging decision-making problems in real-world applications. In this work, we propose a novel Reinforcement Learning (RL) based Long-Short Term Rewards (LSTR) framework for critical decisions identification. RL is a machine learning area concerning with inducing effective decision-making…
Descriptors: Decision Making, Reinforcement, Artificial Intelligence, Man Machine Systems
Henderson, Nathan; Min, Wookhee; Emerson, Andrew; Rowe, Jonathan; Lee, Seung; Minogue, James; Lester, James – International Educational Data Mining Society, 2021
Recent years have seen significant interest in multimodal frameworks for modeling learner engagement in educational settings. Multimodal frameworks hold particular promise for predicting visitor engagement in interactive science museum exhibits. Multimodal models often utilize video data to capture learner behavior, but video cameras are not…
Descriptors: Museums, Audiences, Participation, Exhibits
Zhang, Qiao; Maclellan, Christopher J. – International Educational Data Mining Society, 2021
Knowledge tracing algorithms are embedded in Intelligent Tutoring Systems (ITS) to keep track of students' learning process. While knowledge tracing models have been extensively studied in offline settings, very little work has explored their use in online settings. This is primarily because conducting experiments to evaluate and select knowledge…
Descriptors: Electronic Learning, Mastery Learning, Computer Simulation, Intelligent Tutoring Systems
Zhou, Yiqiu; Kang, Jina – International Educational Data Mining Society, 2022
The complex and dynamic nature of collaboration makes it challenging to find indicators of productive learning and quality collaboration. This exploratory study developed a collaboration metric to capture temporal patterns of joint attention (JA) based on log files generated as students interacted with an immersive astronomy simulation using…
Descriptors: Astronomy, Problem Solving, Science Instruction, Cooperative Learning
PaaBen, Benjamin; Bertsch, Andreas; Langer-Fischer, Katharina; Rüdian, Sylvio; Wang, Xia; Sinha, Rupali; Kuzilek, Jakub; Britsch, Stefan; Pinkwart, Niels – International Educational Data Mining Society, 2021
Many modern anatomy curricula teach histology using virtual microscopes, where students inspect tissue slices in a computer program (e.g. a web browser). However, the educational data mining (EDM) potential of these virtual microscopes remains under-utilized. In this paper, we use EDM techniques to investigate three research questions on a virtual…
Descriptors: Anatomy, Science Instruction, Computer Simulation, Computer Software
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Tack, Anaïs; Piech, Chris – International Educational Data Mining Society, 2022
How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…
Descriptors: Artificial Intelligence, Dialogs (Language), Bayesian Statistics, Decision Making
Yang, Kexin Bella; Echeverria, Vanessa; Wang, Xuejian; Lawrence, LuEttaMae; Holstein, Kenneth; Rummel, Nikol; Aleven, Vincent – International Educational Data Mining Society, 2021
Constructing effective and well-balanced learning groups is important for collaborative learning. Past research explored how group formation policies affect learners' behaviors and performance. With the different classroom contexts, many group formation policies work in theory, yet their feasibility is rarely investigated in authentic class…
Descriptors: Grouping (Instructional Purposes), Cooperative Learning, Teaching Methods, Kindergarten
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