DESIGNING AGAINST GENERATIVE AI “PARROTING”: A PROCESS PORTFOLIO APPROACH TO MINI PROPOSAL ASSESSMENT
DOI:
https://doi.org/10.35631/IJMOE.831029Keywords:
Generative Artificial Intelligence, Higher Education, Parroting Behaviour, Process PortfolioAbstract
The rapid growth of generative artificial intelligence (gen-AI) has raised increasing concerns about parroting behaviour in higher education, particularly in research writing. Parroting behaviour occurs when students reproduce fluent AI-generated text while lacking a meaningful understanding of the ideas it expresses. Instead of addressing this issue through AI detection tools or restrictive policies alone, this study explores how assessment design can discourage parroting by requiring students to demonstrate visible evidence of their learning process. An instrumental case study approach was employed to examine the implementation of a scaffolded process portfolio in an undergraduate research methodology course, with a specific focus on the Background of the Study section of a mini research proposal. Seventeen students, organised into five small groups, developed their writing across four staged submissions and one final submission. Data were collected from staged portfolio drafts, lecturer probing during feedback sessions, and written reflections. Three analytic rubrics were used to assess writing, probing, and reflection. The findings showed an overall pattern of improvement across submissions in students’ writing, their ability to justify and explain ideas during probing, and the depth of reflection on their writing development. The portfolio made students’ reasoning, revision, and conceptual refinement more visible, thereby reducing the usefulness of parroting strategies that depend on producing isolated, surface level text. The study contributes to current discussions on academic integrity in the era of gen-AI by showing how process portfolio assessment can support both learning and integrity through staged, traceable, and feedback enriched writing development.
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