| Title: |
Qualitative Study on the Integration of AI-Powered Peer Review Systems in Learning Management Systems |
| Language: |
English |
| Authors: |
Pravitha Vijaykumar (ORCID 0009-0000-8550-2197); Madhumita Das (ORCID 0009-0008-8165-5389); Mamata Bhandar (ORCID 0000-0002-6178-449X) |
| Source: |
Journal of Educators Online. 2026 23(1). |
| Availability: |
Journal of Educators Online. Grand Canyon University, 23300 West Camelback Road, Phoenix, AZ 85017. e-mail: CIRT@gcu.edu. Web site: https://www.thejeo.com |
| Peer Reviewed: |
Y |
| Page Count: |
17 |
| Publication Date: |
2026 |
| Document Type: |
Journal Articles; Reports - Research |
| Education Level: |
Adult Education; Higher Education; Postsecondary Education |
| Descriptors: |
Peer Evaluation; Artificial Intelligence; Technology Uses in Education; Learning Management Systems; Foreign Countries; Adult Learning; Higher Education; Electronic Learning; Feedback (Response); Assignments; Student Attitudes; Doctoral Programs |
| Geographic Terms: |
Malaysia |
| ISSN: |
1547-500X |
| Abstract: |
The rapid development of AI technologies could add a new dimension to the peer review process in a learning management system (LMS) platform. Peer review is essential to many assessment components, particularly in the LMS but the traditional peer review process has limitations, including the quality of the feedback provided by the peer, the peer's knowledge of the topic, and grammatical errors in the written review. These, in turn, may affect the peer learner's performance in an academic setting. AI technologies are increasingly being utilized in the peer review process in education, notably in research. This qualitative study examines the perceptions of students regarding the peer review process in one or more modules of their doctoral program of study at a Malaysian university, with a focus on enhancing their learning process, discussions, and the pedagogical impact that these AI technologies may have on their learning outcomes. The findings reveal diverse perspectives on the usability, accessibility, ease of use, effectiveness, and insights on the different features that an AI-powered peer review system could incorporate. The findings further highlight both the potential to enhance feedback quality and critical thinking and the challenges related to technical implementation, reliability, and ethical considerations. This study sets the groundwork for further research that is urgently needed to identify optimal ways of integrating AI technologies into the LMS, thereby providing practical guidelines for educational institutions and technology developers to use AI ethically to improve the learning outcomes of students. The findings can also assist LMS and AI solution providers to create a list of features learners expect to be available in the tool. |
| Abstractor: |
As Provided |
| Entry Date: |
2026 |
| Accession Number: |
EJ1499033 |
| Database: |
ERIC |