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Showing 1 to 15 of 27 results Save | Export
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Siran Li; Jiangyue Liu; Qianyan Dong – Australasian Journal of Educational Technology, 2025
Recent advancements in generative artificial intelligence (GenAI) have drawn significant attention from educators and researchers. However, its effects on learners' programming performance, self-efficacy and learning processes remain inconclusive, while the mechanisms underlying its efficiency-enhancing potential are underexplored. This study…
Descriptors: Artificial Intelligence, Technology Uses in Education, Computer Science Education, Programming
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Umer, Rahila; Susnjak, Teo; Mathrani, Anuradha; Suriadi, Lim – Interactive Learning Environments, 2023
Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…
Descriptors: Prediction, Student Behavior, Models, Academic Achievement
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Jia-Hua Zhao; Shu-Tao Shangguan; Ying Wang – Journal of Computer Assisted Learning, 2025
Background: Computational thinking (CT) is a fundamental ability required of individuals in the 21st-century digital world. Past studies show that generative artificial intelligence (GenAI) can enhance students' CT skills. However, GenAI may produce inaccurate output, and students who rely too much on AI may learn little and be unable to think…
Descriptors: Artificial Intelligence, Technology Uses in Education, Skill Development, Computation
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Kangwa Daniel; Msafiri Mgambi Msambwa; Zhang Wen – European Journal of Education, 2025
This systematic review investigates the impact of generative artificial intelligence (GenAI) tools on developing academic skills in higher education. Analysing 158 studies published between 2021 and 2024, it focuses on the impact of GenAI tools on the development of cognitive, technical and interpersonal skills. The results reveal that 94% of the…
Descriptors: Artificial Intelligence, Academic Ability, Academic Achievement, Skill Development
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Gang Zhao; Lijun Yang; Biling Hu; Jing Wang – Journal of Educational Computing Research, 2025
Human-computer collaboration is an effective way to learn programming courses. However, most existing human-computer collaborative programming learning is supported by traditional computers with a relatively low level of personalized interaction, which greatly limits the efficiency of students' efficiency of programming learning and development of…
Descriptors: Artificial Intelligence, Man Machine Systems, Programming, Learning Strategies
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Dong, Yihuan; Marwan, Samiha; Shabrina, Preya; Price, Thomas; Barnes, Tiffany – International Educational Data Mining Society, 2021
Over the years, researchers have studied novice programming behaviors when doing assignments and projects to identify struggling students. Much of these efforts focused on using student programming and interaction features to predict student success at a course level. While these methods are effective at early detection of struggling students in…
Descriptors: Navigation (Information Systems), Academic Achievement, Learner Engagement, Programming
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Ghadeer Sawalha; Imran Taj; Abdulhadi Shoufan – Cogent Education, 2024
Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…
Descriptors: Cues, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Chun-Chun Chang; Gwo-Haur Hwang – Educational Technology & Society, 2024
Professional trainers are responsible for teaching novice employees. However, the conventional approach to training professional trainers is generally a lecture-based mode, implying that they often lack the opportunity to learn to make use of practical cases encountered by novice employees, to explore problem-solving methods, to objectively…
Descriptors: Artificial Intelligence, Technology Uses in Education, Professional Training, Trainers
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Ted M. Clark; Ellie Anderson; Nicole M. Dickson-Karn; Comelia Soltanirad; Nicolas Tafini – Journal of Chemical Education, 2023
Student performance on open-response calculations involving acid and base solutions before and after instruction in general chemistry and analytical chemistry courses was compared with the output from the artificial intelligence chatbot ChatGPT. Applying a theoretical model of expertise for problem solving that includes problem conceptualization,…
Descriptors: Academic Achievement, College Students, College Science, Chemistry
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Ndudi O. Ezeamuzie; Jessica S. C. Leung; Dennis C. L. Fung; Mercy N. Ezeamuzie – Journal of Computer Assisted Learning, 2024
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…
Descriptors: Educational Policy, Predictor Variables, Computation, Thinking Skills
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Chi-Jen Lin; Husni Mubarok; Rakha Ramadhana A.B.; Samuel Gasperius; Chia-Ying Liu; Salisa Sawettanun; Kantapat Meesomyut; Ling-Rong Zheng – Interactive Learning Environments, 2024
This systematic review aimed to investigate the role of technology as a solution in Speech-Language Pathology (SLP). A total of 49 articles published between 2004 and 2023 were examined to gather information on general aspects, methodology, technology implementation, learning outcomes, and limitations and solutions related to technology-enhanced…
Descriptors: Educational Trends, Technology Uses in Education, Learning Strategies, Speech Language Pathology
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Yuchen Chen; Xinli Zhang; Lailin Hu – Educational Technology & Society, 2024
In conventional ancient Chinese poetry learning, students tend to be under-motivated and fail to understand many aspects of poetry. As generative artificial intelligence (GAI) has been applied to education, image-GAI (iGAI) provides great opportunities for students to generate visualized images based on their descriptions of poems, and to situate…
Descriptors: Elementary School Students, Grade 5, Poetry, Artificial Intelligence
Mohammed Alzaid – ProQuest LLC, 2022
Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…
Descriptors: Learning Analytics, Self Evaluation (Individuals), Programming, Problem Solving
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Ai-Jou Pan; Yu-Che Huang; Chin-Feng Lai – Interactive Learning Environments, 2024
Engineering education emphasizes experiential learning and laboratory experience, an approach which has faced significant challenges during the COVID-19 pandemic. The inability to conduct hands-on laboratory experiments in engineering courses can significantly impede the student's learning experience, as well as their acquisition and retention of…
Descriptors: Learning Management Systems, Hands on Science, Distance Education, Laboratories
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Ching-Yi Chang; Patcharin Panjaburee; Shao-Chen Chang – Interactive Learning Environments, 2024
Educators have recognized the importance of providing a realistic learning environment which helps learners to not only comprehend learning content, but also to link the content to practical problems. Such an environment can hence foster problem-solving skills in nursing training. However, when learners interact in a virtual environment with rich…
Descriptors: Artificial Intelligence, Context Effect, Nursing Education, Technology Integration
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