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Cited by 1Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationTechnology-Enhanced Education Studies

ChatGPT for academic assignments: opportunities, challenges, and student perspectives in the digital classroom

Open access
R, Naveen Kumar, M, Janani, B G, Shobha·2026·Journal of Research in Innovative Teaching & Learning
DOI 10.1108/jrit-08-2025-0202
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Abstract

Purpose: This study explores how ChatGPT is being used in higher education, particularly by undergraduate and postgraduate students for completing assignments. It looks beyond simple usage to understand how the tool shapes students’ digital learning experiences. The research focuses on how key factors – digital literacy, perceived usefulness, ethical awareness, and faculty guidance – contribute to the meaningful and responsible use of ChatGPT in academic work. Design/methodology/approach: A total of 304 students participated in the study by responding to a structured questionnaire. To analyze the complex relationships among the core variables, structural equation modeling was used. This approach helped uncover how digital literacy, usefulness perceptions, ethical considerations, and faculty support collectively influence students’ assignment performance when using ChatGPT. Findings: The study found that ChatGPT positively contributes to students’ academic performance. It helps those complete assignments more efficiently, supports personalized learning, and enables better management of time and resources. Digital literacy and perceived usefulness were identified as the strongest predictors of effective engagement with ChatGPT. Additionally, ethical awareness and guidance from faculty played an important role in ensuring that students used the tool responsibly and in academically appropriate ways. Originality/value: This research offers timely empirical evidence on ChatGPT’s evolving role in digital education. It underscores the need for strengthening students’ digital skills, clearly demonstrating the practical value of AI tools, and embedding ethical understanding through active faculty involvement. Together, these elements can enhance academic performance and encourage responsible, informed adoption of AI in higher education.

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Crossref · 10.1108/jrit-08-2025-0202

Cites

50 of 50 references verified0 citation errors · 0 not checkable

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  • Appropriate AI usage is motivated by efficiency enhancement, cognitive load reduction, and access to personalized scaffolding.

    “Appropriate usage is motivated by efficiency enhancement, cognitive load reduction, and access to personalized scaffolding (Kumar et al., 2025; Wang, 2024).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Kumar et al., 2025

    The Discussion and conclusion (section 5; page not available) links ChatGPT’s perceived usefulness—including timely feedback and structured responses—to more strategic use, supporting the efficiency aspect. The Theoretical foundation (section 2.1; page not available) describes personalized guidance and academic support. Neither passage establishes cognitive-load reduction as a motivation for appropriate use; a search for “cognitive load” found no such discussion. (LLM, conf=0.85)

    Experimental — accuracy not yet measured

  • Ethical ambiguity and institutional policy voids enable rationalization of full task delegation as students develop situational interpretations without explicit guidance.

    “Ethical ambiguity and institutional “policy voids” enable rationalization of full task delegation as students develop situational interpretations without explicit guidance (Hanh and Duyen, 2025; Kumar et al., 2025).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Kumar et al., 2025

    The Literature Review (page unavailable) discusses unclear institutional policies, students’ uncertainty about authorship and proper AI use, and the need for guided support. It does not say that these conditions lead students to rationalize delegating entire tasks to ChatGPT or develop situational interpretations in the absence of guidance. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Students demonstrate generally positive orientations toward AI integration, valuing AI for productivity enhancement and immediate feedback.

    “Students demonstrate generally positive orientations, valuing AI for productivity enhancement and immediate feedback (Jeilani and Abubakar, 2025; Kumar et al., 2025).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Kumar et al., 2025

  • Publication bias assessment revealed a "positive-utility" reporting bias favoring successful implementations while null or negative findings remain scarce.

    “Following PRISMA 2020 guidelines, publication bias assessment revealed a “positive-utility” reporting bias favoring successful implementations while null or negative findings remain scarce (Kumar et al., 2025; Shi et al., 2025).”

    From Reimagining writing assessment for the AI era: a systematic review on balancing AI support and authentic skill growth (2026) · cites this paper as Kumar et al., 2025

    The Findings section reports a survey-based structural model, including a nonsignificant result for ethical awareness; it does not assess publication bias. Searches for “positive-utility” reporting bias, PRISMA 2020, and scarce null or negative findings found no passage addressing the attributed claim. (LLM, conf=0.76)

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Cites

1 retracted

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Research works printed but not linked: 9

  1. Alkalai, E.S. (2004), "Digital literacy: a conceptual framework for survival skills in the digital era", Journal of Educational Multimedia and Hypermedia, Vol. 13 No. 1, pp. 93-106.
  2. Arifin, M. (2018), "The influence of ethical awareness on students' academic performance: a study in higher education", Journal of Education and Learning, Vol. 12 No. 3, pp. 321-330.
  3. Budiman, A. (2023), "Digital literacy and academic success among first-year university students", Higher Education Studies, Vol. 13 No. 4, pp. 56-67.
  4. Holm, S. (2025), "Digital literacy and student engagement in online learning environments", Journal of Digital Learning Research, Vol. 18 No. 2, pp. 112-129.
  5. Kline, R.B. (2011), Principles and Practice of Structural Equation Modeling, 3rd ed., Guilford Press.
  6. Prashar, S. (2024), "Effectiveness of plagiarism awareness programs on ethical decision-making", Journal of Academic Ethics, Vol. 22 No. 1, pp. 45-62.
  7. Rua, M. (2024), "Development of the ethical student scale and its implications for academic integrity", Ethics and Education, Vol. 19 No. 2, pp. 133-148.
  8. Sustaningrum, W. (2025), "Perceived usefulness of generative AI tools in higher education learning environments", International Journal of Educational Technology, Vol. 9 No. 1, pp. 76-89.
  9. Waqas, A. (2025), "Mediated digital integrity model: understanding AI-enabled academic misconduct", Journal of Digital Ethics, Vol. 7 No. 1, pp. 22-38.

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Authors
R, N. K., M, J., & B G, S.
Affiliations
  • Kristu Jayanti Deemed to Be University Kristu Jayanti Institute of Management, , ,
  • Kristu Jayanti Deemed to Be University Department of Professional Accounting and Finance, School of Commerce, Accounting and Finance, , ,
ORCID
R, Naveen Kumar
Venue
Journal of Research in Innovative Teaching & Learning
Publisher
Emerald
Published
2026-01-20
Pages
1-17
ISSN
2397-7604 (ISSN-L)
DOI
10.1108/jrit-08-2025-0202
OpenAlex
W7124683655
Cited by
1
References
50
Citations by year
2026: 1
FWCI
8.51
Type
journal article
Language
en
Open access
Licence
Locations
Journal of Research in Innovative Teaching & Learning (publishedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Education › Technology-Enhanced Education Studies
Keywords
ChatGPT, generative AI in education, student assignments, academic performance, digital literacy, perceived usefulness, moral consciousness, faculty guidance, responsible AI use, university students, personalized learning, time management

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