Write a 1,500- to 2,000-word paper that critically analyzes a specific assessment practice and explores how generative artificial intelligence (GAI) may enhance or hinder student learning. The paper must cite at least six of the following core course readings using APA 7th edition format:
- Holmes et al. (2022). Artificial Intelligence and Education: A Critical View Through the Lens of Human Rights, Democracy and the Rule of Law. Council of Europe.
- Swiecki et al. (2022). Assessment in the age of artificial intelligence. Computers and Education: Artificial Intelligence, 3, 100075.
- Hager & Butler (1996). Two models of educational assessment. Assessment and Evaluation in Higher Education, 21(4), 367378.
- Sadler (2007). Perils in the meticulous specification of goals and assessment criteria. Assessment in Education, 14(3), 387392.
- Tan & Deneen (2015). Aligning and Sustaining Meritocracy, Curriculum and Assessment Validity in Singapore. Assessment Matters, 8, 3152.
- Tan (2013). A framework for assessment for learning: Implications for feedback practices within and beyond the gap. ISRN Education, 16.
- Tan (2020). Rubrics for different types of learning and learners. In Assessment rubrics decoded. Routledge.
- Tay (2018). What is authenticity in AA. In Designing Quality Authentic Assessment (pp. 723). Routledge.
- Chai et al. (2024). Grading by AI makes me feel fairer? Frontiers in Psychology.
- Selwyn (2021). Making sense of technology and educational change. In Education and technology (3rd ed.). Bloomsbury.
- Selwyn (2009). The digital native myth and reality. Aslib Proceedings, 61, 364379.
- Lee, Tan & Teo (2023). Designs and practices using generative AI for sustainable student discourse and knowledge creation. Smart Learning Environments, 10(1), 59.
- Ali et al. (2023). Supporting self-directed learning and self-assessment using TeacherGAIA. Learning: Research and Practice, 9(2), 135147.
- Abyaa et al. (2019). Learner modelling: systematic review of the literature from the last 5 years. Education Tech Research Dev, 67, 11051143.
The final submission must include a cover page displaying the Turnitin originality score and the Turnitin AI detection results.
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