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Peng, Tzu-Hsiang; Wang, Tzu-Hua – Journal of Educational Computing Research, 2022
Pedagogical agents (PAs) are a crucial aspect of the e-learning environment. A PA is defined as a virtual character presented on an interface, and they are designed to promote student learning. PAs have been widely discussed in academic papers. However, an appropriate analysis framework has not been proposed because of the diversity and complexity…
Descriptors: Electronic Learning, Instructional Effectiveness, Intelligent Tutoring Systems, Evaluation Methods
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Zhou, Guojing; Azizsoltani, Hamoon; Ausin, Markel Sanz; Barnes, Tiffany; Chi, Min – International Journal of Artificial Intelligence in Education, 2022
In interactive e-learning environments such as Intelligent Tutoring Systems, pedagogical decisions can be made at different levels of granularity. In this work, we focus on making decisions at "two levels": whole problems vs. single steps and explore three types of granularity: "problem-level only" ("Prob-Only"),…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Decision Making, Problem Solving
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Widodo, Sri Adi; Sari, Desi D.; Maarif, Samsul; Setiana, Dafid S.; Perbowo, Krisna S. – International Journal of Evaluation and Research in Education, 2022
The purpose of this study was to improve the learning achievement of extroverted students on algebraic operations using the tutorial method. This type of research was a single subject with AB design, where A is the baseline condition, and B is an intervention condition. The research subjects were selected based on a purposive sampling technique…
Descriptors: Academic Achievement, Extraversion Introversion, Algebra, Tutoring
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Laine, Joakim; Lindqvist, Timo; Korhonen, Tiina; Hakkarainen, Kai – International Journal of Technology in Education and Science, 2022
Advances in immersive virtual reality (I-VR) technology have allowed for the development of I-VR learning environments (I-VRLEs) with increasing fidelity. When coupled with a sufficiently advanced computer tutor agent, such environments can facilitate asynchronous and self-regulated approaches to learning procedural skills in industrial settings.…
Descriptors: Intelligent Tutoring Systems, Computer Simulation, Industry, Job Skills
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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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Harvinder Singh; Angrej Singh Gill; Pradeep Kumar Choudhury – Research in Post-Compulsory Education, 2024
The paper, based on a primary survey, explores the inequalities in access and household investment on the market-based 'supplemental educational services' (SESs) in post-compulsory school education (i.e. secondary level of education) in Haryana, a northern state in India. We find that around 44% of students access SESs in secondary education in…
Descriptors: Foreign Countries, Access to Education, Family Income, Secondary Education
Adam M. Lavecchia; Philip Oreopoulos; Noah Spencer – National Bureau of Economic Research, 2024
This study finds substantial reductions to criminal activity from the introduction of a comprehensive high school support program for disadvantaged youth living in the largest public housing project in Toronto. The program, called Pathways to Education, bundles supports such as regular coaching, tutoring, group activities, free public…
Descriptors: Crime Prevention, High School Students, Disadvantaged Youth, Poverty
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Lishan Zhang; Linyu Deng; Sixv Zhang; Ling Chen – IEEE Transactions on Learning Technologies, 2024
With the popularity of online one-to-one tutoring, there are emerging concerns about the quality and effectiveness of this kind of tutoring. Although there are some evaluation methods available, they are heavily relied on manual coding by experts, which is too costly. Therefore, using machine learning to predict instruction quality automatically…
Descriptors: Automation, Classification, Artificial Intelligence, Tutoring
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Wu, Ting-Ting; Lee, Hsin-Yu; Li, Pin-Hui; Huang, Chia-Nan; Huang, Yueh-Min – Journal of Educational Computing Research, 2024
This study combines ChatGPT, Apple's Shortcuts, and LINE to create the ChatGPT-based Intelligent Learning Aid (CILA), aiming to enhance self-regulation progress and knowledge construction in blended learning. CILA offers real-time, convergent information to learners' inquiries, as opposed to traditional Google search engine that provide divergent…
Descriptors: Independent Study, Learning Processes, Blended Learning, Artificial Intelligence
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Mohammad M. Khajah – Journal of Educational Data Mining, 2024
Bayesian Knowledge Tracing (BKT) is a popular interpretable computational model in the educational mining community that can infer a student's knowledge state and predict future performance based on practice history, enabling tutoring systems to adaptively select exercises to match the student's competency level. Existing BKT implementations do…
Descriptors: Students, Bayesian Statistics, Intelligent Tutoring Systems, Cognitive Development
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Clarivando Francisco Belizário Júnior; Fabiano Azevedo Dorça; Luciana Pereira de Assis; Alessandro Vivas Andrade – International Journal of Learning Technology, 2024
Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…
Descriptors: Artificial Intelligence, Educational Technology, Individualized Instruction, Cognitive Style
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Aniekan Essien; Oyegoke Teslim Bukoye; Xianghan O'Dea; Marios Kremantzis – Studies in Higher Education, 2024
This study investigates the influence of generative artificial intelligence (GAI), specifically AI text generators (ChatGPT), on critical thinking skills in UK postgraduate business school students. Using Bloom's taxonomy as theoretical underpinning, we adopt a mixed-method research employing a sample of 107 participants to investigate both the…
Descriptors: Foreign Countries, Graduate Students, Business Education, Artificial Intelligence
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Fadoua Balabdaoui; Nora Dittmann-Domenichini; Henry Grosse; Claudia Schlienger; Gerd Kortemeyer – Discover Education, 2024
We report the results of a 4800-respondent survey among students at a technical university regarding their usage of artificial intelligence tools, as well as their expectations and attitudes about these tools. We find that many students have come to differentiated and thoughtful views and decisions regarding the use of artificial intelligence. The…
Descriptors: Foreign Countries, College Students, Artificial Intelligence, Student Attitudes
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Jaeho Jeon; Seongyong Lee; Seongyune Choi – Interactive Learning Environments, 2024
Chatbot research has received growing attention due to the rapid diversification of chatbot technology, as demonstrated by the emergence of large language models (LLMs) and their integration with automatic speech recognition. However, among various chatbot types, speech-recognition chatbots have received limited attention in relevant research…
Descriptors: Literature Reviews, Content Analysis, Second Language Learning, Artificial Intelligence
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Md Jahangir Alam – International Journal of Early Childhood, 2024
Parental involvement with children is crucial for children's school readiness. The inequality in Early Childhood Education (ECE) results in an intellectual divide among children aged 3-5 in Bangladesh. Additionally, cognitive and non-cognitive development significantly contributes to school readiness. This case study research gathered information…
Descriptors: Parent Influence, Parent Background, Educational Background, Early Childhood Education
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