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Cited by 32Teaching and Learning ProgrammingArduino and IoT ApplicationsArtificial Intelligence in Education

Using ChatGPT with Novice Arduino Programmers: Effects on Performance, Interest, Self-Efficacy, and Programming Ability

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Johnson, Donald M., Doss, Will, Estepp, Christopher M.·2024·Journal of Research in Technical Careers
DOI 10.9741/2578-2118.1152
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Abstract

A posttest-only control group experimental design compared novice Arduino programmers who developed their own programs (self-programming group, n =17) with novice Arduino programmers who used ChatGPT 3.5 to write their programs (ChatGPT-programming group, n = 16) on the dependent variables of programming scores, interest in Arduino programming, Arduino programming self-efficacy, Arduino programming posttest scores, and types of programming errors. Students were undergraduates in an introductory agricultural systems technology course in Fall 2023. The results indicated no significant (p < .10) differences between groups for programming rubric scores (p = .50) or interest in Arduino programming (p = .50). There were significant differences for Arduino programming self-efficacy, (p = .03, Cohen’s d = 0.75) and Arduino posttest scores, (p = .03, Cohen’s d = 0.76); students in the self-programming group scored significantly higher on both measures. Analysis of students’ errors indicated the ChatGPT group made significantly (p < .01) more program punctuation errors. These results indicated novice students writing their own programs developed greater Arduino programming self-efficacy and programming ability than novice students using ChatGPT. Nevertheless, ChatGPT may still play an important role in assisting novices to write microcontroller programs.

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Crossref · 10.9741/2578-2118.1152

Cites

33 of 33 references verified0 citation errors · 0 not checkable

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  • Large language models can respond dynamically to individual questions, provide immediate and iterative feedback, generate alternative explanations, and help students refine ideas or approaches as their understanding develops.

    “Unlike static instructional resources, large language models can respond dynamically to individual questions, provide immediate and iterative feedback, generate alternative explanations, and help students refine ideas or approaches as their understanding develops (Johnson et al. 2024; Abdallah et al. 2025; Qian 2025).”

    From Generative AI Expands the Intellectual Reach of Course Based Undergraduate Research Experiences (CUREs) (2026) · cites this paper as Johnson et al. 2024

  • GenAI tools offer a novel means of extending support to students engaged in complex, open-ended learning.

    “The rise of generative artificial intelligence (GenAI) tools offers a novel means of extending support to students engaged in complex, open-ended learning.”

    From Generative AI Expands the Intellectual Reach of Course Based Undergraduate Research Experiences (CUREs) (2026) · cites this paper as Johnson et al. 2024

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Authors
Johnson, D. M., Doss, W., & Estepp, C. M.
Affiliations
  • University of Arkansas at Fayetteville (US)
  • University of Arkansas
ORCID
Venue
Journal of Research in Technical Careers
Publisher
University Libraries, University of Nevada, Las Vegas
Published
2024-05-06
Volume
8
Issue
1
Pages
1
ISSN
2578-2118 (ISSN-L)
DOI
10.9741/2578-2118.1152
OpenAlex
W4396685819
Cited by
31
References
34
Citations by year
2026: 15 · 2025: 14 · 2024: 2
FWCI
11.72
Type
journal article
Language
en
Open access
Licence
cc-by-nc-nd
Locations
  • Journal of Research in Technical Careers (publishedVersion, cc-by-nc-nd)
  • Journal of the Arkansas Academy of Science (submittedVersion, cc-by)
  • Digital Scholarship - UNLV (University of Nevada Reno) (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Arduino and IoT Applications
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
Keywords
ChatGPT, Arduino programming, novice programmers, programming self-efficacy, coding errors, microcontroller programming, student interest in programming

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