Author
Listed:
- Mike Licuanan
(Northeastern College, Santiago City, Isabela, Philippines)
- Kelly Amarillo
(Northeastern College, Santiago City, Isabela, Philippines)
- Janika Estangki
(Northeastern College, Santiago City, Isabela, Philippines)
- Haide Estonactoc
(Northeastern College, Santiago City, Isabela, Philippines)
- Jocelyn Dupingay
(Northeastern College, Santiago City, Isabela, Philippines)
- Marites Marrero
(Northeastern College, Santiago City, Isabela, Philippines)
- Marie Claire Anselmo
(Northeastern College, Santiago City, Isabela, Philippines)
- Adriano Sabado
(Northeastern College, Santiago City, Isabela, Philippines)
Abstract
Artificial intelligence (AI) continues to transform higher education, particularly through generative tools such as ChatGPT, which support academic writing, research development, and data analysis. This study examined graduate students’ self-efficacy in using ChatGPT for academic tasks at a private higher education institution. A quantitative descriptive–comparative research design was employed, and data were collected from 54 graduate students using a structured questionnaire measuring five domains: academic writing, research skills, data analysis and interpretation, critical thinking and responsible use, and overall academic confidence. The results revealed a high level of self-efficacy across all domains, with an overall mean of 3.13. Among the domains, academic writing self-efficacy obtained the highest mean score, indicating strong confidence in utilizing ChatGPT for writing-related tasks in academic settings. An independent samples t-test showed no significant difference in self-efficacy when grouped by sex. However, a one-way analysis of variance (ANOVA) revealed a significant difference based on the frequency of ChatGPT use, with students who reported always using the tool demonstrating higher self-efficacy than those who rarely used it. Effect size analysis indicated a small practical effect for sex and a moderate effect for frequency of use. These findings suggest that experiential engagement with AI tools plays a more substantial role in shaping academic confidence than demographic characteristics. This study underscores the importance of structured exposure, institutional guidelines, and ethical training to promote responsible and effective AI integration in graduate education.
Suggested Citation
Mike Licuanan & Kelly Amarillo & Janika Estangki & Haide Estonactoc & Jocelyn Dupingay & Marites Marrero & Marie Claire Anselmo & Adriano Sabado, 2026.
"Graduate Students’ Self-Efficacy in Using ChatGPT for Academic Tasks,"
The International Review of Multidisciplinary Research, Vertex International Research and Consultancy, Corp., vol. 1(3), March.
Handle:
RePEc:vtx:vertex:v:1:y:2026:i:3:id:89
DOI: 10.5281/zenodo.19058234
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:vtx:vertex:v:1:y:2026:i:3:id:89. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Managing Director (email available below). General contact details of provider: https://vertexcorp.org/index.php/irmr .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.