Practices and Challenges in Designing Authentic Assessments Using Artificial - Chuah, Kee Man; Ch'ng, Looi Chin (Routledge, 2026)
This chapter investigates the role of artificial intelligence (AI) in designing authentic assessments within technology-enhanced learning (TEL) environments. It is based on a study involving 82 undergraduate students enrolled in a blended learning class, where all assessments were developed using AI-powered tools. Authentic assessments, which emphasise real-world applications and higher-order thinking, are widely recognised for fostering meaningful and practical learning experiences. The research focuses on the practical application of AI in creating authentic assessments with an emphasis on enhancing students' critical thinking, creativity, and problem-solving skills. Specifically, it examines how AI tools can support the creation of complex and context-rich tasks while addressing issues related to scalability, personalisation, and resource efficiency. Findings from the study reveal both opportunities and challenges associated with adopting AI in assessment practices. On the one hand, AI-enabled tools were found to enhance the efficiency of assessment design especially in generating diverse assessment tasks aligned to the intended learning outcomes. For instance, AI tools can help create problem-based and scenario-based assessments that closely mirror professional and real-life contexts. On the other hand, significant challenges emerged, which includes difficulties in ensuring the relevance and clarity of AI-generated content. There is also a concern regarding inconsistencies in AI outputs, which can lead to confusion and compromise the validity of assessment tasks. To address these challenges, the chapter highlights strategies such as faculty training on AI tools, the establishment of robust evaluation frameworks, and the integration of human intervention in the assessment design process. Furthermore, the need for interdisciplinary collaboration between educators, instructional designers, and AI specialists is emphasised. The chapter concludes by offering practical recommendations for adopting AI in assessment practices particularly to educators and institutions that are keen to leverage AI's potential while maintaining academic rigour.