Date
Publisher
arXiv
The rapid integration of Generative Artificial Intelligence (GenAI) into
higher education presents both opportunities and challenges for assessment
design, particularly within Project-Based Assessment (PBA) contexts.
Traditional assessment methods often emphasise the final product in the PBA,
which can now be significantly influenced or created by GenAI tools, raising
concerns regarding product authenticity, academic integrity, and learning
validation. This paper advocates for a reimagined assessment model for
Project-Based Learning (PBL) or a capstone project that prioritises
process-oriented evaluation, multi-modal and multifaceted assessment design,
and ethical engagement with GenAI to enable higher-order thinking. The model
also emphasises the use of (GenAI-assisted) personalised feedback by a
supervisor as an observance of the learning process during the project
lifecycle. A use case scenario is provided to illustrate the application of the
model in a capstone project setting. The paper concludes with recommendations
for educators and curriculum designers to ensure that assessment practices
remain robust, learner-centric, and integrity-driven in the evolving landscape
of GenAI.
Study at a glance
- Question: How can project-based assessments be redesigned to evaluate student learning authentically and ethically with generative AI?
- Setting and data: Higher education capstone project use case scenario
- Method: Conceptual model development illustrated with an example use case scenario
Why it matters
Traditional project-based assessments often emphasize final products that generative AI can now influence or create. This shift raises concerns about product authenticity, academic integrity, and learning validation.
Key findings
- In higher education project-based assessments, evaluating the learning process, multifaceted designs, and ethical AI engagement enables higher-order thinking and authenticates learning.
- Traditional project-based assessments focusing on final products face integrity risks because generative AI tools can significantly shape or create those products.
- AI-assisted personalized feedback allows supervisors to observe and track student learning processes across the entire project lifecycle.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who age?
Study design
