Publication Date
| In 2026 | 0 |
| Since 2025 | 9 |
| Since 2022 (last 5 years) | 21 |
| Since 2017 (last 10 years) | 27 |
| Since 2007 (last 20 years) | 32 |
Descriptor
| Artificial Intelligence | 34 |
| Problem Solving | 34 |
| Computation | 32 |
| Thinking Skills | 19 |
| Technology Uses in Education | 16 |
| Foreign Countries | 13 |
| Programming | 10 |
| Teaching Methods | 9 |
| Academic Achievement | 7 |
| Educational Technology | 7 |
| Student Attitudes | 7 |
| More ▼ | |
Source
Author
| Seepersaud, Deborah, Ed. | 3 |
| Simonson, Michael, Ed. | 3 |
| Anass Bayaga | 1 |
| Ashwin T. S. | 1 |
| Barnes, Tiffany, Ed. | 1 |
| Biling Hu | 1 |
| Caitlin Snyder | 1 |
| Chang, Yao-Chung | 1 |
| Chen, Shih-Yeh | 1 |
| Christiane Gresse Von… | 1 |
| Clayton Cohn | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 23 |
| Reports - Research | 17 |
| Collected Works - Proceedings | 6 |
| Dissertations/Theses -… | 4 |
| Reports - Descriptive | 4 |
| Information Analyses | 3 |
| Tests/Questionnaires | 3 |
| Books | 1 |
| Reports - Evaluative | 1 |
Education Level
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Hsiao-Ping Hsu – TechTrends: Linking Research and Practice to Improve Learning, 2025
The advancement of large language model-based generative artificial intelligence (LLM-based GenAI) has sparked significant interest in its potential to address challenges in computational thinking (CT) education. CT, a critical problem-solving approach in the digital age, encompasses elements such as abstraction, iteration, and generalisation.…
Descriptors: Programming, Prompting, Computation, Thinking Skills
Anass Bayaga – International Journal of Technology in Education, 2025
This investigation explored the role of artificial intelligence (AI)-powered gamification on mathematics cognition through a mixed-methods design, blending an intervention with a gamified learning application (app) and a survey to evaluate student engagement and performance. The study explores the nexus of gamification, AI, and mathematics…
Descriptors: Artificial Intelligence, Problem Solving, Game Based Learning, Mathematics Instruction
Skulmowski, Alexander – Educational Psychology Review, 2023
This review is aimed at synthesizing current findings concerning technology-based cognitive offloading and the associated effects on learning and memory. While cognitive externalization (i.e., using the environment to outsource mental computation) is a highly useful technique in various problem-solving tasks, a growing body of research suggests…
Descriptors: Mental Computation, Learning Processes, Memory, Problem Solving
Zhongzhou Chen; Tong Wan – Physical Review Physics Education Research, 2025
This study examines the feasibility and potential advantages of using large language models, in particular GPT-4o, to perform partial credit grading of large numbers of student written responses to introductory level physics problems. Students were instructed to write down verbal explanations of their reasoning process when solving one conceptual…
Descriptors: Grading, Technology Uses in Education, Student Evaluation, Science Education
Clayton Cohn; Caitlin Snyder; Joyce Horn Fonteles; Ashwin T. S.; Justin Montenegro; Gautam Biswas – British Journal of Educational Technology, 2025
Recent advances in generative artificial intelligence (AI) and multimodal learning analytics (MMLA) have allowed for new and creative ways of leveraging AI to support K12 students' collaborative learning in STEM+C domains. To date, there is little evidence of AI methods supporting students' collaboration in complex, open-ended environments. AI…
Descriptors: Cooperation, Researchers, Artificial Intelligence, STEM Education
Liang, Yicong; Zou, Di; Xie, Haoran; Wang, Fu Lee – Smart Learning Environments, 2023
The pretrained large language models have been widely tested for their performance on some challenging tasks including arithmetic, commonsense, and symbolic reasoning. Recently how to combine LLMs with prompting techniques has attracted lots of researchers to propose their models to automatically solve math word problems. However, most research…
Descriptors: Science Instruction, Physics, Artificial Intelligence, Computer Mediated Communication
Jian Liao; Linrong Zhong; Longting Zhe; Handan Xu; Ming Liu; Tao Xie – IEEE Transactions on Learning Technologies, 2024
ChatGPT has received considerable attention in education, particularly in programming education because of its capabilities in automated code generation and program repairing and scoring. However, few empirical studies have investigated the use of ChatGPT to customize a learning system for scaffolding students' computational thinking. Therefore,…
Descriptors: Scaffolding (Teaching Technique), Thinking Skills, Computation, Artificial Intelligence
Tarattakan Pachumwon; Thada Jantakoon; Rukthin Laoha – Higher Education Studies, 2025
This study introduces CAILE, a design thinking-driven conceptual framework for a Creative AI Learning Environment, designed to enhance programming skills. Evaluates clarity, appropriateness, and feasibility through expert judgment. Phase 1 synthesized 34 peer-reviewed studies (2019-2025) to articulate CAILE's structure across three layers: Inputs…
Descriptors: Creativity, Artificial Intelligence, Technology Uses in Education, Programming
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
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
Hao-Yue Jin; Maria Cutumisu – Education and Information Technologies, 2024
Computational thinking (CT) is considered to be a critical problem-solving toolkit in the development of every student in the digital twenty-first century. Thus, it is believed that the integration of deeper learning in CT education is an approach to help students transfer their CT skills beyond the classroom. Few literature reviews have mapped…
Descriptors: Computation, Thinking Skills, Problem Solving, Artificial Intelligence
Jaime Carvalho e Silva – International Journal of Mathematical Education in Science and Technology, 2025
The use of technologies in mathematics education at all levels has been discussed extensively for a number of years. It is one of the few themes that was the object of two ICMI studies, the most recent being published in 2010. Two new approaches, emerging lately in the teaching and learning of Mathematics at all levels, will be discussed:…
Descriptors: Computation, Thinking Skills, Artificial Intelligence, Mathematics Instruction
Noawanit Songkram; Supattraporn Upapong; Heng-Yu Ku; Narongpon Aulpaijidkul; Sarun Chattunyakit; Nutthakorn Songkram – Interactive Learning Environments, 2024
This research proposes the integration of robotic education and scenario-based learning (SBL) paradigm for teaching computational thinking (CT) to enhance the computational abilities of primary school students, based on digital innovation and a teaching assistant robot acceptance model. The sample group consisted of 532 primary school teachers and…
Descriptors: Foreign Countries, Elementary School Students, Elementary School Teachers, Grade 1
Ramon Mayor Martins; Christiane Gresse Von Wangenheim – Informatics in Education, 2024
Information technology (IT) is transforming the world. Therefore, exposing students to computing at an early age is important. And, although computing is being introduced into schools, students from a low socio-economic status background still do not have such an opportunity. Furthermore, existing computing programs may need to be adjusted in…
Descriptors: Information Technology, Socioeconomic Status, Social Class, Computer Literacy
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

Peer reviewed
Direct link
