Examining the Role of Generative AI in Enhancing Social Work Education: An Analysis of Curriculum and Assessment Design

Elizabeth Claire Reimer ()
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Elizabeth Claire Reimer: Social Work, Faculty of Health, Southern Cross University, East Lismore, NSW 2480, Australia

Social Sciences, 2024, vol. 13, issue 12, 1-16

Abstract: Generative Artificial Intelligence (GAI) holds significant potential to advance the field of social work, yet it brings forth considerable challenges and risks. Key concerns include the legal and ethical ramifications of GAI application, as well as its effects on the vital human connections inherent in social work. Nonetheless, educators in this field must ready their students for the evolving digital environment, ensuring they are adept at employing GAI thoughtfully, skillfully, and ethically. This article will explore the integration of GAI knowledge and skills within educational settings. It will feature a case study detailing the author’s redesign of community welfare and social work degree assignments to include GAI within a community welfare/social work undergraduate course in Queensland, Australia. The discussion will extend to curriculum and assessment development processes aimed at leveraging GAI to enhance student learning, knowledge retention, and confidence in applying GAI within their academic and professional pursuits. Furthermore, the article will examine the implications for curriculum and assessment design, emphasizing the importance of clear learning objectives, the creation of specific, intricate, and contextualized assessments, the necessity for students to critically evaluate GAI outputs, and the challenge of presenting GAI with tasks beyond its capabilities.

Keywords: generative artificial intelligence; assessment design; social work education; meta-reflection (search for similar items in EconPapers)
JEL-codes: A B N P Y80 Z00 (search for similar items in EconPapers)
Date: 2024
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