@incollection{10.1108/978-1-80686-799-820261009,
    author = {Qian, Yufeng},
    isbn = {978-1-80686-800-1},
    title = {Rethinking Learning Assessment in the AI Era},
    booktitle = {Synthetic Intelligence in Education: Transforming Pedagogy with AI},
    publisher = {Emerald Publishing Limited},
    year = {2026},
    month = {05},
    abstract = {In earlier chapters of this book, synthetic intelligence was framed as a dynamic partnership between human cognition and artificial intelligence (AI) – an ecosystem where learners, teachers, and AI systems collaborate to co-create knowledge and action. This chapter explores what happens to assessment when this ecosystem evolves.Generative AI has introduced more than just a new avenue for cheating; it has unsettled the foundational assumptions that have long governed our assessment practices. With a large language model in their pocket, students can now produce well-crafted essays, plausible code, and even passable exam answers, all without fully mastering the underlying skills. Research increasingly shows that traditional take-home assignments no longer reliably reflect a student’s true capabilities (Kizilcec et al., 2024; Xia et al., 2024). At the same time, AI offers the opportunity for rich, personalized feedback at scale – enabling educators to spot patterns and insights in student work that were previously invisible (Ba et al., 2025; Wongvorachan, 2022).},
    doi = {10.1108/978-1-80686-799-820261009},
    url = {https://doi.org/10.1108/978-1-80686-799-820261009},
    eprint = {https://www.emerald.com/book/chapter-pdf/11422123/978-1-80686-799-820261009en.pdf},
}