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Juan D. Pinto; Luc Paquette – International Educational Data Mining Society, 2025
The increasing use of complex machine learning models in education has led to concerns about their interpretability, which in turn has spurred interest in developing explainability techniques that are both faithful to the model's inner workings and intelligible to human end-users. In this paper, we describe a novel approach to creating a…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Behavior, Models
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Shuanghong Shen; Qi Liu; Zhenya Huang; Yonghe Zheng; Minghao Yin; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Modern online education has the capacity to provide intelligent educational services by automatically analyzing substantial amounts of student behavioral data. Knowledge tracing (KT) is one of the fundamental tasks for student behavioral data analysis, aiming to monitor students' evolving knowledge state during their problem-solving process. In…
Descriptors: Student Behavior, Electronic Learning, Data Analysis, Models
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Cath Ellis; Kane Murdoch – Assessment & Evaluation in Higher Education, 2024
Current approaches used by educational institutions to address the problem of student cheating are not working. This is because the discourse of academic integrity that currently dominates is, on its own, inadequate for addressing the problem. We propose that in order for higher education institutions to challenge cheating effectively, they need…
Descriptors: Cheating, Student Behavior, Barriers, College Students
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Yang, Qi-Fan; Lian, Li-Wen; Zhao, Jia-Hua – International Journal of Educational Technology in Higher Education, 2023
According to previous studies, traditional laboratory safety courses are delivered in a classroom setting where the instructor teaches and the students listen and read the course materials passively. The course content is also uninspiring and dull. Additionally, the teaching period is spread out, which adds to the instructor's workload. As a…
Descriptors: Undergraduate Students, Gamification, Artificial Intelligence, Robotics
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Nisaudzakiah Utami; Agus Setiawan; Ida Hamidah; Thomas Koehler – Educational Process: International Journal, 2025
Background/purpose: This study investigated the effectiveness of Problem-Based Worksheets (PBWs) in improving conceptual understanding of logic gates. PBWs were designed with key characteristics that integrate authentic problem-solving, active student engagement, and conceptual scaffolding to support critical thinking processes. A total of 32…
Descriptors: Problem Based Learning, Worksheets, Item Response Theory, Models
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Ku, Chih-Jung; Hsu, Ying-Shao; Chang, Mei-Chen; Lin, Kuen-Yi – International Journal of STEM Education, 2022
Background: Research on teaching and learning for science, technology, engineering, and mathematics (STEM) subjects has increased, and has demonstrated the importance of integrating interdisciplinary knowledge and skills. Our research model was based on the theory of planned behavior (TPB) and the data were analyzed by partial least…
Descriptors: Middle School Students, STEM Education, Problem Solving, Student Attitudes
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Kinnebrew, John S.; Segedy, James R.; Biswas, Gautam – IEEE Transactions on Learning Technologies, 2017
Research in computer-based learning environments has long recognized the vital role of adaptivity in promoting effective, individualized learning among students. Adaptive scaffolding capabilities are particularly important in open-ended learning environments, which provide students with opportunities for solving authentic and complex problems, and…
Descriptors: Computer Assisted Instruction, Problem Solving, Learning, Student Behavior
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Cocea, Mihaela; Magoulas, George D. – IEEE Transactions on Learning Technologies, 2017
Exploratory learning environments (ELEs) promote a view of learning that encourages students to construct and/or explore models and observe the effects of modifying their parameters. The freedom given to learners in this exploration context leads to a variety of learner approaches for constructing models and makes modelling of learner behavior a…
Descriptors: Generalization, Mathematics Instruction, Computer Simulation, Discovery Learning
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Chen, Binglin; West, Matthew; Ziles, Craig – International Educational Data Mining Society, 2018
This paper attempts to quantify the accuracy limit of "nextitem-correct" prediction by using numerical optimization to estimate the student's probability of getting each question correct given a complete sequence of item responses. This optimization is performed without an explicit parameterized model of student behavior, but with the…
Descriptors: Accuracy, Probability, Student Behavior, Test Items
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Avsec, Stanislav; Sajdera, Jolanta – International Journal of Technology and Design Education, 2019
Engineering thinking enhances real-world learning; it emphasises system thinking, problem finding and creative problem solving as well as visualising, improving, and adapting products and processes. Several studies have investigated how pre-service preschool teachers acquire their knowledge of technology and engineering; however, a clear…
Descriptors: Preschool Teachers, Thinking Skills, Systems Approach, Problem Solving
Alibali, Martha W.; Brown, Sarah A.; Menendez, David – Grantee Submission, 2019
Learning, development, and response to instruction often involve changes in the strategies that learners use to solve problems. In this chapter, our focus is on mathematical problem solving in both children and adults. We offer a selective review of research on three classes of factors that may influence processes of strategy change in…
Descriptors: Learning Strategies, Problem Solving, Mathematics Skills, Mathematics Instruction
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Malkiewich, Laura; Baker, Ryan S.; Shute, Valerie; Kai, Shimin; Paquette, Luc – International Educational Data Mining Society, 2016
Educational games have become hugely popular, and educational data mining has been used to predict student performance in the context of these games. However, models built on student behavior in educational games rarely differentiate between the types of problem solving that students employ and fail to address how efficacious student problem…
Descriptors: Classification, Problem Solving, Educational Games, Models
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Ifenthaler, Dirk, Ed.; Sampson, Demetrios G., Ed.; Isaías, Pedro, Ed. – Cognition and Exploratory Learning in the Digital Age, 2022
This book is about inclusivity and open education in the digital age. It reports the latest data on this topic from the 2021 Cognition and Exploratory Learning in the Digital Age (CELDA) conference. This annual conference focuses on challenges pertaining to the evolution of the learning process, the role of pedagogical approaches and the progress…
Descriptors: Teaching Methods, Educational Innovation, Educational Technology, Technology Uses in Education
Castro, Francisco Enrique Vicente; Adjei, Seth; Colombo, Tyler; Heffernan, Neil – International Educational Data Mining Society, 2015
A great deal of research in educational data mining is geared towards predicting student performance. Bayesian Knowledge Tracing, Performance Factors Analysis, and the different variations of these have been introduced and have had some success at predicting student knowledge. It is worth noting, however, that very little has been done to…
Descriptors: Models, Student Behavior, Intelligent Tutoring Systems, Data Analysis
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Edwards, Oliver W.; Cheeley, Taylor – Children & Schools, 2016
Educational policies require the use of data and progress monitoring frameworks to guide instruction and intervention in schools. As a result, different problem-solving models such as multitiered systems of supports (MTSS) have emerged that use these frameworks to improve student outcomes. However, problem-focused models emphasize negative…
Descriptors: Youth, Youth Programs, Nutrition, Outcomes of Education
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