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Cited by 142Artificial Intelligence in EducationIntelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Healthcare and Education

ChatGPT: Revolutionizing student achievement in the electronic magnetism unit for eleventh-grade students in Emirates schools

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Alneyadi, Saif, Wardat, Yousef·2023·Contemporary Educational Technology
DOI 10.30935/cedtech/13417
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Abstract

The study aimed to examine the influence of ChatGPT on the academic performance and learning perception of eleventh-grade students in a United Arab Emirates school in the field of electronic magnetism. The participants were randomly divided into two groups: an experimental group granted access to ChatGPT and a control group without access to ChatGPT. The research spanned four weeks, during which the experimental group was instructed to utilize ChatGPT whenever they required assistance with the course content. The study employed a mixed-methods design, collecting both quantitative and qualitative data to assess the impact of ChatGPT on student learning and perception. Quantitative data was gathered through pre-/post-test surveys, measuring participants’ course achievement and perception of learning with ChatGPT. Qualitative data was collected via open-ended survey questions, allowing participants to provide feedback and suggestions for improvement. The study revealed that ChatGPT had a positive influence on student achievement and perception of learning in the field of electronic magnetism. The experimental group displayed significant enhancements in their scores on the post-test measuring the impact of ChatGPT on student achievement, exhibiting higher mean scores across all subscales compared to the control group. Furthermore, both male and female participants acknowledged ChatGPT as a valuable learning tool, offering suggestions for enhancing its functionality. The study suggests that ChatGPT is an effective tool for enhancing student learning and achievement in specific academic domains. However, further research is needed to explore its generalizability to other contexts and disciplines, as well as to address potential challenges and limitations of ChatGPT use in education.

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  • Enhancing students' critical thinking and real-world problem-solving practices remains a key objective, with GenAI-supported interactive learning and analytical tasks designed to promote critical analysis, logical reasoning, and the generative use of knowledge to authentic challenges in science and mathematics.

    “Additionally, enhancing students' critical thinking and real-world problem-solving practices remains a key objective. GenAI-supported interactive learning and analytical tasks are designed to promote critical analysis, logical reasoning, and the generative use of knowledge to authentic challenges in science and mathematics.”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [101]

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • Several studies require students to identify incorrect or fabricated AI outputs, which cultivates critical thinking and information discrimination skills.

    “Several studies also require students to identify incorrect or fabricated AI outputs, which cultivates critical thinking and information discrimination skills [100,101,133].”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [101]

    The Limitations section (page not available) says potential inaccuracies in ChatGPT responses necessitate critical thinking and verification against credible sources. It does not describe studies requiring students to identify incorrect or fabricated outputs, or establish that such an exercise cultivates those skills. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • A second stream configures AI as a just-in-time tutor, providing stepwise explanations or sample code when students encounter obstacles, with teachers monitoring and intervening only when needed.

    “A second stream configures AI as a just-in-time tutor. When students encounter obstacles in programming or laboratory work, they query the model and receive stepwise explanations or sample code; teachers monitor frequency and content via dashboards and intervene only when AI misinterprets a problem or students stall for too long [101,148,150].”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [101]

    The Findings report that students in an electronic magnetism class asked ChatGPT questions and received instant explanations and examples, supporting the just-in-time tutoring idea. The paper does not describe programming or laboratory obstacles, sample code, teacher dashboards, or teachers intervening only when students stall or the AI misinterprets a problem (searched for those terms and practices). (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Numerous studies report higher enthusiasm, participation, curiosity, and satisfaction after AI use, alongside a general preference for AI tools as efficient and convenient.

    “Numerous studies report higher enthusiasm, participation, curiosity, and satisfaction after AI use [6,70,74,81,87,91,92,101,104,106,113,114,116,119,131,141,142], alongside a general preference for AI tools as efficient and convenient [99,111,124,127,135,140].”

    From A Systematic Review of Generative AI in K–12: Mapping Goals, Activities, Roles, and Outcomes via the 3P Model (2025) · cites this paper as [101]

    The Findings (page unavailable) report that students found ChatGPT made learning more interactive and engaging, supporting the participation aspect of the first, source-attributed clause. The paper does not report increases in enthusiasm, curiosity, or satisfaction specifically; the efficiency-and-convenience clause has a separate citation group. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

  • The out-performance of ChatGPT may relate to several advantages of ChatGPT, including providing additional learning resources, immediate feedback, helping learners comprehend challenging concepts, overcoming language barriers, bridging gaps for learners with different needs, and organising study materials with instant access to diverse information.

    “This out-performance, based on previous studies, may relate to several advantages of ChatGPT, including providing additional learning resources, immediate feedback, helping learners comprehend challenging concepts, overcoming language barriers, bridging gaps for learners with different needs and organising study materials with instant access to diverse information (Alneyadi and Wardat, 2023; Yusfi”

    From Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance (2025) · cites this paper as Alneyadi and Wardat, 2023

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Cites

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Authors
Alneyadi, S., & Wardat, Y.
Affiliations
  • Al Ain University (AE)
  • Higher Colleges of Technology (AE)
Corresponding author
Wardat, Yousef
ORCID
Venue
Contemporary Educational Technology
Publisher
Bastas Publications
Published
2023-10-01
Volume
15
Issue
4
Pages
ep448
ISSN
1309-517X (ISSN-L)
DOI
10.30935/cedtech/13417
OpenAlex
W4381188835
Cited by
142
References
30
Citations by year
2026: 32 · 2025: 50 · 2024: 49 · 2023: 11
FWCI
33.33
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
Contemporary Educational Technology (publishedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
Keywords
ChatGPT, large language models in education, academic performance, physics education, eleventh grade students, student perceptions of learning

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