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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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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
Eagle, Michael; Hicks, Drew; Barnes, Tiffany – International Educational Data Mining Society, 2015
Intelligent tutoring systems and computer aided learning environments aimed at developing problem solving produce large amounts of transactional data which make it a challenge for both researchers and educators to understand how students work within the environment. Researchers have modeled student-tutor interactions using complex networks in…
Descriptors: Problem Solving, Prediction, Intelligent Tutoring Systems, Computer Assisted Instruction
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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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Bernacki, Matthew L.; Walkington, Candace – Journal of Educational Psychology, 2018
Context personalization--the incorporation of students' out-of-school interests into learning tasks--has recently been shown to positively affect students' situational interest and their performance and learning in mathematics. However, few studies have shown effects on both interest and achievement, drawing into question whether context…
Descriptors: High School Students, Student Interests, Individualized Instruction, Mathematics Instruction
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Xin, Yan Ping; Tzur, Ron; Hord, Casey; Liu, Jia; Park, Joo Young; Si, Luo – Learning Disability Quarterly, 2017
The Common Core Mathematics Standards have raised expectations for schools and students in the United States. These standards demand much deeper content knowledge from teachers of mathematics and their students. Given the increasingly diverse student population in today's classrooms and shortage of qualified special education teachers,…
Descriptors: Intelligent Tutoring Systems, Computer Assisted Instruction, Mathematics Instruction, Learning Disabilities
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Martins, Igor; de Morais, Felipe; Schaab, Bruno; Jaques, Patricia – International Journal of Information and Communication Technology Education, 2016
In most Intelligent Tutoring Systems, the help messages (hints) are not very clear for students as they are only presented textually and have little connection with the task elements. This can lead to students' undesired behaviors, like gaming the system, associated with low performance. In this paper, the authors aim at evaluating if the gestures…
Descriptors: Teaching Methods, Intelligent Tutoring Systems, Problem Solving, Equations (Mathematics)
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Arnau, David; Arevalillo-Herráez, Miguel; González-Calero, José Antonio – IEEE Transactions on Learning Technologies, 2014
This paper presents an intelligent tutoring system (ITS) for the learning of arithmetical problem solving. This is based on an analysis of (a) the cognitive processes that take place during problem solving; and (b) the usual tasks performed by a human when supervising a student in a one-to-one tutoring situation. The ITS is able to identify the…
Descriptors: Intelligent Tutoring Systems, Arithmetic, Problem Solving, Supervision
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Doleck, Tenzin; Jarrell, Amanda; Poitras, Eric G.; Chaouachi, Maher; Lajoie, Susanne P. – Australasian Journal of Educational Technology, 2016
Clinical reasoning is a central skill in diagnosing cases. However, diagnosing a clinical case poses several challenges that are inherent to solving multifaceted ill-structured problems. In particular, when solving such problems, the complexity stems from the existence of multiple paths to arriving at the correct solution (Lajoie, 2003). Moreover,…
Descriptors: Accuracy, Patients, Computer Simulation, Clinical Diagnosis
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Lee, Young-Jin – Educational Technology & Society, 2015
This study investigates whether information saved in the log files of a computer-based tutor can be used to predict the problem solving performance of students. The log files of a computer-based physics tutoring environment called Andes Physics Tutor was analyzed to build a logistic regression model that predicted success and failure of students'…
Descriptors: Physics, Science Instruction, Computer Software, Accuracy
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Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T. – Journal of Educational Computing Research, 2016
This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…
Descriptors: Mathematics, Tutoring, Mathematics Instruction, Foreign Countries
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Mullins, Dejana; Rummel, Nikol; Spada, Hans – International Journal of Computer-Supported Collaborative Learning, 2011
While some studies found positive effects of collaboration on student learning in mathematics, others found none or even negative effects. This study evaluates whether the varying impact of collaboration can be explained by differences in the type of knowledge that is promoted by the instruction. If the instructional material requires students to…
Descriptors: Video Technology, Feedback (Response), Computer Assisted Instruction, Learning Processes
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Barnes, Tiffany; Stamper, John – Educational Technology & Society, 2010
In building intelligent tutoring systems, it is critical to be able to understand and diagnose student responses in interactive problem solving. However, building this understanding into a computer-based intelligent tutor is a time-intensive process usually conducted by subject experts. Much of this time is spent in building production rules that…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Tutors, Probability
Stamper, John Carroll – ProQuest LLC, 2010
Intelligent Tutoring Systems (ITSs) that adapt to an individual student's needs have shown significant improvement in achievement over non-adaptive instruction (Murray 1999). This improvement occurs due to the individualized instruction and feedback that an ITS provides. In order to achieve the benefits that ITSs provide, we must find a way to…
Descriptors: Intelligent Tutoring Systems, Individualized Instruction, Adjustment (to Environment), Feedback (Response)
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Lynch, Collin; Ashley, Kevin D.; Pinkwart, Niels; Aleven, Vincent – International Journal of Artificial Intelligence in Education, 2009
In this paper we consider prior definitions of the terms "ill-defined domain" and "ill-defined problem". We then present alternate definitions that better support research at the intersection of Artificial Intelligence and Education. In our view both problems and domains are ill-defined when essential concepts, relations, or criteria are un- or…
Descriptors: Definitions, Artificial Intelligence, Problem Solving, Educational Research
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