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Schulz, Sandra; McLaren, Bruce M.; Pinkwart, Niels – International Journal of Artificial Intelligence in Education, 2023
This paper develops a method for the construction and evaluation of cognitive models to support students in their problem-solving skills during robotics in school, aiming to build a basis for an implementation of a tutoring system in the future. Two Wizard-of-Oz studies were conducted, one in the classroom and one in the lab. Based on the…
Descriptors: Cognitive Processes, Models, Intelligent Tutoring Systems, Robotics
Lajoie, Susanne P.; Poitras, Eric G.; Doleck, Tenzin; Huang, Lingyun – Education and Information Technologies, 2023
The present paper builds on the literature that emphasizes the importance of self-regulation for academic learning or self-regulated learning (SRL). SRL research has traditionally focused on count measures of SRL processing events, however, another important measure of SRL is being recognized: time-on-task. The current study captures the influence…
Descriptors: Intelligent Tutoring Systems, Self Management, Time on Task, Correlation
Xuanyan Zhong; Zehui Zhan – Interactive Technology and Smart Education, 2025
Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming, Independent Study
Sharma, Kshitij; Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Journal of Computer Assisted Learning, 2021
When students are working collaboratively and communicating verbally in a technology-enhanced environment, the system cannot track what collaboration is happening outside of the technology, making it difficult to fully assess the collaboration of the students and adapt accordingly. In this article, we propose using gaze measures as a proxy for…
Descriptors: Cooperative Learning, Interpersonal Communication, Eye Movements, Problem Solving
del Olmo-Muñoz, Javier; González-Calero, José Antonio; Diago, Pascual D.; Arnau, David; Arevalillo-Herráez, Miguel – British Journal of Educational Technology, 2022
Problem solving is often regarded as one of the most essential cognitive functions in our daily lives, and, for that reason, educational theorists have long stressed the need for its development. As cognitive flexibility is a fundamental characteristic necessary throughout the problem-solving process, the purpose of this study is to analyse…
Descriptors: Problem Solving, Arithmetic, Grade 5, Grade 6
Zhang, Mengxue; Wang, Zichao; Baraniuk, Richard; Lan, Andrew – International Educational Data Mining Society, 2021
Feedback on student answers and even during intermediate steps in their solutions to open-ended questions is an important element in math education. Such feedback can help students correct their errors and ultimately lead to improved learning outcomes. Most existing approaches for automated student solution analysis and feedback require manually…
Descriptors: Mathematics Instruction, Teaching Methods, Intelligent Tutoring Systems, Error Patterns
Lamia, Mahnane; Mohamed, Hafidi – International Journal of Web-Based Learning and Teaching Technologies, 2019
Nowadays, students are becoming familiar with the computer technology at a very early age. Moreover, the wide availability of the internet gives a new perspective to distance education making e-learning environments crucial to the future of education. Intelligent tutoring systems (ITSs) provide sophisticated tutoring systems using artificial…
Descriptors: Problem Solving, Educational Technology, Technology Uses in Education, Intelligent Tutoring Systems
de Morais, Felipe; Jaques, Patricia A. – Informatics in Education, 2022
Intelligent Tutoring Systems (ITSs) for Math still use traditional data input methods: computers' keyboard and mouse. However, students usually solve math tasks using paper and pen. Therefore, the gap between the manner the students work and the requirements imposed by these typing-based systems expose students to an extraneous cognitive load,…
Descriptors: Intelligent Tutoring Systems, Mathematics Instruction, Educational Technology, Technology Uses in Education
Twenty Years On: Reflections on "Supporting the Use of External Representations in Problem Solving"…
Cox, Richard; Brna, Paul – International Journal of Artificial Intelligence in Education, 2016
We reflect upon a paper we wrote that was published in 1995 (20 years ago). We outline the motivation for the work and situate it in the state of the art at that time. We suggest that a key contribution was to highlight the need to provide support for learners who reason with external representations. The support must be flexible enough to…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Problem Solving, Cognitive Processes
Walkington, Candace; Bernacki, Matthew L. – Journal of Experimental Education, 2018
Instruction can be made relevant to students when it draws upon and utilizes their interests, experiences, and "funds of knowledge" in productive ways to support classroom learning. This approach has been referred to as "context personalization." In this paper, we discuss the cognitive basis of personalization interventions,…
Descriptors: Individualized Instruction, Instructional Design, Relevance (Education), Cognitive Processes
Kamsa, Imane; Elouahbi, Rachid; El Khoukhi, Fatima – Journal of Information Technology Education: Research, 2017
Aim/Purpose: To identify and rectify the learning difficulties of online learners. Background: The major cause of learners' failure and non-acquisition of knowledge relates to their weaknesses in certain areas necessary for optimal learning. We focus on e-learning because, within this environment, the learner is mostly affected by these…
Descriptors: Foreign Countries, Graduate Students, Masters Programs, Learning Disabilities
Liu, Ran; Koedinger, Kenneth R. – Journal of Educational Data Mining, 2017
As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it…
Descriptors: Educational Technology, Technology Uses in Education, Data Collection, Data Analysis
Miwa, Kazuhisa; Kojima, Kazuaki; Terai, Hitoshi – International Association for Development of the Information Society, 2014
Tutoring systems provide students with various types of on-demand and context-sensitive hints. Students are required to consciously adapt their help-seeking behavior, proactively seek help in some situations, and solve problems independently without supports in other situations. We define the latter behavior as stoic behavior in hint seeking. In…
Descriptors: Help Seeking, Student Behavior, Cues, Goal Orientation
Baker, Ryan S. J. d.; Corbett, Albert T.; Gowda, Sujith M. – Journal of Educational Psychology, 2013
Recently, there has been growing emphasis on supporting robust learning within intelligent tutoring systems, assessed by measures such as transfer to related skills, preparation for future learning, and longer term retention. It has been shown that different pedagogical strategies promote robust learning to different degrees. However, the student…
Descriptors: Intelligent Tutoring Systems, Educational Technology, Genetics, Science Instruction
Seal, Kala Chand; Przasnyski, Zbigniew H.; Leon, Linda A. – Decision Sciences Journal of Innovative Education, 2010
Do students learn to model OR/MS problems better by using computer-based interactive tutorials and, if so, does increased interactivity in the tutorials lead to better learning? In order to determine the effect of different levels of interactivity on student learning, we used screen capture technology to design interactive support materials for…
Descriptors: Spreadsheets, Intelligent Tutoring Systems, Learning Processes, Interaction
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