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Submission information
Submission Number: 20
Submission ID: 759
Submission UUID: 63e8923e-b622-4a30-b25e-76394318d858
Submission URI: /2025/abstracts
Created: Wed, 04/02/2025 - 14:44
Completed: Wed, 04/02/2025 - 14:51
Changed: Mon, 05/26/2025 - 15:28
Remote IP address: 103.184.239.118
Submitted by: Anonymous
Language: English
Is draft: No
Current page: Complete
Webform: Abstract
Presenters
Dr.
Philip
Sheena
Bharat mata school of social work
Dr. Sheena Rajan Philip is an Assistant Professor and Senior Faculty at Bharata Mata School of Social Work, Kochi, Kerala. With extensive experience in social work education, she focuses on integrating modern tools, such as Artificial Intelligence, to enhance student learning and critical thinking. Her research interests include the ethical implications of technology in social work and community development. Sheena has contributed to various research projects, including empowering women through agri-business and developing community-based practices. She actively participates in curriculum development, aiming to bridge theory and practical applications in social work education.
No
Abstract
ASSESSING THE IMPACT OF AI TOOLS IN MODERN SOCIAL WORK EDUCATION
THEME 6: Main-streaming Digital and Assessment Tools in Social Work Practice
SUB 6.2 Evaluating the effectiveness of digital tools in Social Work practice.
Oral Presentation
Modern social work education's integration of artificial intelligence (AI) tools is changing professional training, student involvement, and teaching strategies. Adaptive learning platforms, virtual simulations, automated assessments, and natural language processing (NLP) systems—AI-powered solutions improve individualized learning experiences and let students build critical thinking and decision-making abilities. Real-world scenarios created by AI-driven case simulations let students practice client contacts, ethical decision-making, and intervention tactics in a risk-free setting. Artificial intelligence chatbots and virtual assistants also help students with academic direction, mental health services, and research support.
Despite these benefits, the adoption of AI in social work education raises ethical and practical concerns. Issues such as data privacy, algorithmic bias, and the potential reduction of human interaction in learning environments must be addressed. Additionally, the digital divide may limit access to AI-powered learning resources, particularly for students in underprivileged communities. This study assesses the effectiveness and challenges of AI tools in social work education through qualitative and quantitative analysis, including surveys of educators and students, case studies, and expert interviews.
Findings suggest that AI enhances accessibility, efficiency, and engagement in social work education, but it must be integrated thoughtfully to preserve the humanistic and ethical foundations of the discipline. The study recommends a balanced approach, combining AI-enhanced learning with traditional mentoring, ethical guidelines, and digital literacy training. As AI continues to evolve, social work education must adapt responsibly to equip future professionals with both technological competencies and the core values of empathy, advocacy, and social justice.
Key words- Artificial Intelligence (AI) in social work education, Human interaction in learning, Ethical concerns
Despite these benefits, the adoption of AI in social work education raises ethical and practical concerns. Issues such as data privacy, algorithmic bias, and the potential reduction of human interaction in learning environments must be addressed. Additionally, the digital divide may limit access to AI-powered learning resources, particularly for students in underprivileged communities. This study assesses the effectiveness and challenges of AI tools in social work education through qualitative and quantitative analysis, including surveys of educators and students, case studies, and expert interviews.
Findings suggest that AI enhances accessibility, efficiency, and engagement in social work education, but it must be integrated thoughtfully to preserve the humanistic and ethical foundations of the discipline. The study recommends a balanced approach, combining AI-enhanced learning with traditional mentoring, ethical guidelines, and digital literacy training. As AI continues to evolve, social work education must adapt responsibly to equip future professionals with both technological competencies and the core values of empathy, advocacy, and social justice.
Key words- Artificial Intelligence (AI) in social work education, Human interaction in learning, Ethical concerns
Reviewer ONE Feedback
Prof
John
Rautenbach
Yes
Education
Accepted
Reviewer TWO Feedback
Prof
John
Rautenbach
Yes
Education
Accepted