Promoting AI literacy in social work education
Lessons from an interdisciplinary course for social work students
Bibliographic Data
| ID | 21495847 |
|---|---|
| Authors | Joshua Weber (0009-0001-1671-1611, FHNW School of Social Work, corresponding author), Lauri Goldkind (0000-0002-0967-3960, Fordham University) |
| Year | 2026 |
| Pages | 1-17 |
| Publication date | 2026-02-24 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Social Work Education (JOURNAL) |
| Journal identifiers | ISSN: 0261-5479 • E-ISSN: 1470-1227 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/02615479.2026.2635471 |
| OpenAlex | W7133950447 |
| Language | EN |
| Citations received | 1 |
| References cited | 41 |
Artificial intelligence (AI), particularly generative AI and large language models (LLMs), are reshaping the landscape of social work practice. Schools of social work are only beginning to respond to these changes. This article presents findings from an interdisciplinary summer school course designed to promote AI literacy among social work students. The curriculum combined a range of interactive learning experiences with time for ethical reflection, and a developmental experience of creating domain-specific CustomGPTs. In order to understand student’s acquisition of AI knowledge and skills, we used an AI literacy measure called the ‘Scale for the assessment of non-experts’ AI literacy’ (SNAIL). We assessed changes in AI literacy through pre- and post-course self-assessments based on the SNAIL questionnaire. The results show statistically significant and potentially meaningful gains in AI literacy. The responses suggest that the course helped increase AI knowledge, enabling students to shift from hesitant observers to confident users of and thinkers about AI tools. This study contributes to the emerging field of AI literacy in social work by offering a model for interdisciplinary teaching on generative AI content
Life course approach · Literacy · Artificial Intelligence in Healthcare and Education · Simulation-Based Education in Healthcare · Social Work Education and Practice · Social Work
What is AI Literacy? Competencies and Design Considerations
Artificial Intelligence in Social Work
A systematic review of AI literacy conceptualization, constructs, and implementation and assessment efforts (2019–2023)
Evaluating AI Courses
Teaching Note—Data Science in the MSW Curriculum
Social Work Educators Innovating With Generative AI
Introducing Generative Artificial Intelligence Into the MSW Curriculum
Digital competences of future social workers
Digital competence in social work education
A History of Digital Media
Considering a Unified Model of Artificial Intelligence Enhanced Social Work
Electronic Information Systems and Social Work
Building a Competency-Based Curriculum in Social Work Education
Use of Electronic Mail to Promote Computer Literacy in Social Work Undergraduates
The Informationalisation of the Australian Community Sector
E-Social work
Artificial Intelligence in Social Work
Child welfare informatics
Social Work Informatics
Social Work and Artificial Intelligence
AI and social work
Social work virtual
Artificial Intelligence (AI) Literacy for Social Work
Data justice
Preparing Social Work Students for Interdisciplinary Practice
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |