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Showing 1 to 15 of 22 results Save | Export
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Conrad Borchers; Hendrik Fleischer; David J. Yaron; Bruce M. McLaren; Katharina Scheiter; Vincent Aleven; Sascha Schanze – Journal of Science Education and Technology, 2025
Intelligent tutoring system (ITS) provides learners with step-by-step problem-solving support through scaffolding. Most ITSs have been developed in the USA and incorporate American instructional strategies. How do non-American students perceive and use ITS with different native problem-solving strategies? The present study compares Stoich Tutor,…
Descriptors: Problem Solving, Intelligent Tutoring Systems, Learning Strategies, Protocol Analysis
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Shakya, Anup; Rus, Vasile; Venugopal, Deepak – International Educational Data Mining Society, 2021
Predicting student problem-solving strategies is a complex problem but one that can significantly impact automated instruction systems since they can adapt or personalize the system to suit the learner. While for small datasets, learning experts may be able to manually analyze data to infer student strategies, for large datasets, this approach is…
Descriptors: Prediction, Problem Solving, Intelligent Tutoring Systems, Learning Strategies
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Conrad Borchers; Jiayi Zhang; Hendrik Fleischer; Sascha Schanze; Vincent Aleven; Ryan S. Baker – Journal of Educational Data Mining, 2025
Think-aloud protocols are a standard method to study self-regulated learning (SRL) during learning by problem-solving. Advances in automated transcription and large language models (LLMs) have automated the transcription and labeling of SRL in these protocols, reducing manual effort. However, while effective in many emerging applications, previous…
Descriptors: Artificial Intelligence, Protocol Analysis, Learning Strategies, Classification
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Nicholas A. Vest; Elena M. Silla; Anna N. Bartel; Tomohiro Nagashima; Vincent Aleven; Martha W. Alibali – Grantee Submission, 2022
One pedagogical technique that promotes conceptual understanding in mathematics learners is self-explanation integrated with worked examples (e.g., Rittle-Johnson et al., 2017). In this work, we implemented self-explanations with worked examples (correct and erroneous) in a software-based Intelligent Tutoring System (ITS) for learning algebra. We…
Descriptors: Algebra, Mathematics Instruction, Intelligent Tutoring Systems, Middle School Students
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Suwicha Wittayakom; Chintana Kanjanavisutt; Methinee Wongwanich Rumpagaporn – Higher Education Studies, 2024
This systematic literature review explores the implementation and effectiveness of active learning approaches in online training environments. The rapid growth of online education necessitates strategies that enhance learner engagement and improve educational outcomes. The review identifies various active learning techniques, such as discussions,…
Descriptors: Online Courses, Training, Active Learning, Learning Strategies
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Hannah Smith; Avery H. Closser; Erin Ottmar; Jenny Yun-Chen Chan – Applied Cognitive Psychology, 2022
Worked examples are effective learning tools for algebraic equation solving. However, they are typically presented in a static concise format, which only displays the major derivation steps in one static image. The current work explores how worked examples that vary in their extensiveness (i.e., detail) and degree of dynamic presentation (i.e.,…
Descriptors: Algebra, Mathematics Instruction, Equations (Mathematics), Problem Solving
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Wang, Tingting; Zheng, Juan; Tan, Chengyi; Lajoie, Susanne P. – Journal of Computer Assisted Learning, 2023
Background: Computer-based scaffolding has been intensively used to facilitate students' self-regulated learning (SRL). However, most previous studies investigated how computer-based scaffoldings affected the cognitive aspect of SRL, such as knowledge gains and understanding levels. In contrast, more evidence is needed to examine the effects of…
Descriptors: Metacognition, Scaffolding (Teaching Technique), Computer Assisted Instruction, Intelligent Tutoring Systems
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Nagashima, Tomohiro; Bartel, Anna N.; Yadav, Gautam; Tseng, Stephanie; Vest, Nicholas A.; Silla, Elena M.; Alibali, Martha W.; Aleven, Vincent – Grantee Submission, 2021
Prior research shows that self-explanation promotes understanding by helping learners connect new knowledge with prior knowledge. However, despite ample evidence supporting the effectiveness of self-explanation, an instructional design challenge emerges in how best to scaffold self-explanation. In particular, it is an open challenge to design…
Descriptors: Teaching Methods, Mathematics Instruction, Algebra, Middle School Students
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Chin, Doris B.; Blair, Kristen P.; Wolf, Rachel C.; Conlin, Luke D.; Cutumisu, Maria; Pfaffman, Jay; Schwartz, Daniel L. – Journal of the Learning Sciences, 2019
Educators aim to equip students with learning strategies they can apply when approaching new problems on their own. Teaching design-thinking strategies may support this goal. A first test would show that the strategies are good for learning and that students spontaneously transfer them beyond classroom instruction. To examine this, we introduce…
Descriptors: Problem Solving, Learning Strategies, Teaching Methods, Design
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Miller, Chyna J.; Bernacki, Matthew L. – High Ability Studies, 2019
The ability to self-regulate learning (SRL) is a skill theorized to transfer across learning environments. Students with this ability can consider a learning task, identify a goal, develop a plan to achieve it, execute that plan, and monitor and adapt learning until the goal is met. This paper examines the educational implications of developing…
Descriptors: Case Studies, Mathematics Achievement, Metacognition, Learning Strategies
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Rastegarmoghadam, Mahin; Ziarati, Koorush – Education and Information Technologies, 2017
Swarm intelligence approaches, such as ant colony optimization (ACO), are used in adaptive e-learning systems and provide an effective method for finding optimal learning paths based on self-organization. The aim of this paper is to develop an improved modeling of adaptive tutoring systems using ACO. In this model, the learning object is…
Descriptors: Teaching Methods, Problem Solving, Intelligent Tutoring Systems, Educational Technology
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Kojima, Kazuaki; Miwa, Kazuhisa; Matsui, Tatsunori – International Journal of Artificial Intelligence in Education, 2013
Problem posing, by which learners create new problems by themselves, is an important activity in mathematics education. However, novice learners have difficulty in posing problems, particularly when formulating appropriate solution structures of problems. Although they are provided with example problems that can serve as hints for composing novel…
Descriptors: Foreign Countries, Mathematics Education, Problem Solving, Learning Strategies
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Lehman, Blair; D'Mello, Sidney; Graesser, Art – Internet and Higher Education, 2012
Folk wisdom holds that being confused is detrimental to learning. However, research on emotions and learning suggest a somewhat more complex relationship between confusion and learning outcomes. In fact, it has been proposed that impasses that trigger states of cognitive disequilibrium and confusion can create opportunities for deep learning of…
Descriptors: Feedback (Response), Learning Strategies, Problem Solving, Intervention
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Waalkens, Maaike; Aleven, Vincent; Taatgen, Niels – Computers & Education, 2013
Intelligent tutoring systems (ITS) support students in learning a complex problem-solving skill. One feature that makes an ITS architecturally complex, and hard to build, is support for strategy freedom, that is, the ability to let students pursue multiple solution strategies within a given problem. But does greater freedom mean that students…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Algebra, Mathematics Instruction
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