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ENHANCING FORMATIVE ASSESSMENT THROUGH AN AI-ASSISTED
                  FEEDBACK SYSTEM: A CASE STUDY AT OPEN UNIVERSITY MALAYSIA (OUM)


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                       Nantha Kumar Subramaniam* , Jaspal Kaur Naranjan Singh , Nor Aisyah Fadil    3
                                       1, 2, 3  Open University Malaysia, Selangor, Malaysia.
                                             (*E-mail: nanthakumar@oum.edu.my)

                                                         ABSTRACT
                        This study investigates the integration of an AI-assisted feedback system into the
                  assessment practices at Open University Malaysia (OUM) to strengthen formative
                  assessment (assignments) within an Open and Distance Learning (ODL) context.
                  Implemented as a pilot across 12 first-semester courses, the system enabled students to
                  receive automated feedback on draft assignments prior to final submission. It delivered
                  timely, personalised, and constructive input on key writing elements such as structure,
                  language, argumentation, referencing, and grammar. By supporting iterative revision, the
                  system was designed to foster continuous learning and improve the overall quality of
                  student work. To examine user perceptions, a quantitative survey was conducted at the
                  end of a 14-week semester, involving 351 student participants. The data were analysed
                  using descriptive statistics to assess satisfaction, usage intention, and responses to
                  negative feedback. The findings indicate high levels of satisfaction and a strong
                  willingness to continue using the system. Students also showed generally positive
                  reactions to negative feedback and used it to enhance their assignments. These results
                  suggest that AI-assisted feedback can support self-regulated learning, encourage
                  meaningful engagement with feedback, and improve academic writing skills.
                        Keywords: AI-assisted feedback, formative assessment, open and distance learning
                  (ODL).


                        1. Introduction
                        Assessment is a fundamental component of the teaching and learning process, as it
                  is used to determine students’ level of understanding and monitor their academic
                  progress. It also offers insights that enable educators to adjust their teaching approaches
                  and better facilitate student growth. Among the various types of assessment, formative
                  assessment plays a crucial role in promoting ongoing learning and development. It is
                  characterised as a continuous approach in which educators monitor learners’ progress
                  and deliver feedback that guides improvements in both teaching and learning practices
                  (Black & Wiliam, 1998). In contrast to summative assessment, which evaluates final
                  achievement, formative assessment focuses on enhancing learning throughout the
                  instructional process. Through timely and meaningful feedback, students are able to
                  recognise their strengths, address areas needing improvement, and enhance their overall
                  performance. Nevertheless, within large-scale Open and Distance Learning (ODL) settings,
                  delivering prompt and personalized formative feedback to a high volume of students
                  continues to be a major challenge for educators.
                        2. Literature review
                        Formative assessment is widely recognised as a key approach for enhancing student
                  learning, with feedback at its core (Pinto-Llorente & Izquierdo-Álvarez, 2024). Effective
                  feedback helps students identify gaps, reinforce strengths, and move closer to desired


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