Cited by 264Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationIntelligent Tutoring Systems and Adaptive Learning

The DOI matches its Crossref record; 63 of the 63 references it cites were found in a registry or an index.

Students' perceptions of using ChatGPT in a physics class as a virtual tutor

Open access
Ding, Lu, Li, Tong, Jiang, Shiyan, Gapud, Albert·2023·International Journal of Educational Technology in Higher Education

Abstract

The latest development of Generative Artificial Intelligence (GenAI), particularly ChatGPT, has drawn the attention of educational researchers and practitioners. We have witnessed many innovative uses of ChatGPT in STEM classrooms. However, studies regarding students’ perceptions of ChatGPT as a virtual tutoring tool in STEM education are rare. The current study investigated undergraduate students’ perceptions of using ChatGPT in a physics class as an assistant tool for addressing physics questions. Specifically, the study examined the accuracy of ChatGPT in answering physics questions, the relationship between students’ ChatGPT trust levels and answer accuracy, and the influence of trust on students’ perceptions of ChatGPT. Our finding indicates that despite the inaccuracy of GenAI in question answering, most students trust its ability to provide correct answers. Trust in GenAI is also associated with students’ perceptions of GenAI. In addition, this study sheds light on students’ misconceptions toward GenAI and provides suggestions for future considerations in AI literacy teaching and research.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1186/s41239-023-00434-1

Cites

63 of 63 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig. 2 Flowchart of how students interact with ChatGPT
Fig. 2 Flowchart of how students interact with ChatGPTCC-BY · From the PDF
Fig. 3 The elbow point for the clustering analysis of the participants' trust levels
Fig. 3 The elbow point for the clustering analysis of the participants' trust levelsCC-BY · From the PDF
Fig. 4 Students' drawings/pictures of their perceived ChatGPT
Fig. 4 Students' drawings/pictures of their perceived ChatGPTCC-BY · From the PDF

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 59 references

Research works printed but not linked: 3

  1. Bingham, A. J., & Witkowsky, P. (2022). Deductive and inductive approaches to qualitative data analysis. In C. Vanover, P. Mihas, & J. Saldaña (Eds.), Analyzing and interpreting qualitative data: After the interview (pp. 133–146). SAGE Publications.
  2. Hu, K. (2023). ChatGPT sets record for fastest-growing user base. Reuters.
  3. Removed for blinded review.

Cited by

Sorted by citations

Items 101–200 of 264

Metadata

Authors
Ding, L., Li, T., Jiang, S., & Gapud, A.
Affiliations
  • University of South Alabama (US)
  • Ball State University (US)
  • North Carolina State University (US)
Corresponding author
Ding, Lu
Venue
International Journal of Educational Technology in Higher Education
Published
2023-12-22
Volume
20
Issue
1
ISSN
2365-9440 (ISSN-L)
OpenAlex
W4390082902
Cited by
208
References
59
Citations by year
2026: 67 · 2025: 97 · 2024: 44
FWCI
48.82
Type
journal article
Language
en
Open access
Locations
  • International Journal of Educational Technology in Higher Education (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Social Sciences › Education › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
Keywords
ChatGPT, generative AI, online tutoring, physics education, student perceptions, trust in AI, answer accuracy, AI literacy, misconceptions about AI, undergraduate students

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review