An interdisciplinary team from Syracuse University School of Education’s Counseling and Human Services and Social Work programs is the recipient of a highly competitive research grant from the Association of Counselor Education and Supervision (ACES).
Receiving a 2026 ACES Small Grants for Studies of AI-Client Simulations—one of four proposals funded from 40 submissions—the research project will investigate artificial intelligence’s potential to transform how graduate students in both counseling and social work learn to diagnose mental health conditions.
The project—“A Quasi-Experimental Investigation of Diagnostic Competence and Cultural Responsiveness Through AI-Simulation and Feedback Intervention in Counselor Education and Social Work”—will be led by Yanhong Liu, Associate Professor of Counseling and Counselor Education.
Working with Liu as co-Principal Investigator is Xihe Tian, a doctoral candidate in SOE’s Counseling and Counselor Education program. “Xihe initiated the idea and has been leading the project as part of her dissertation,” explains Liu, who chairs Tian’s dissertation committee.
Liu adds that the grant proposal also brought in as advisors School of Social Work faculty, who joined the School of Education in July 2025: “Social Work professors Ken Marfilus, Jennifer Genovese, and Nadaya Brantley, along with Counseling and Counselor Education Professor Melissa Luke, have provided outstanding support to the project, and professors Marfilus and Genovese incorporated it into their summer 2026 psychopathology course, which has been instrumental in advancing the work.”
Project Description
Psychopathology training and competence in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (Text Revision)—or DSM-5-TR, the standard diagnostic manual for mental health professionals—are foundational requirements in counseling and social work education. However, research has yet to ask whether those differences lead to meaningfully different diagnostic thinking.
Concurrently, AI simulation has emerged as a promising training modality in health professions education, although its application to diagnostic competence development in counseling and social work contexts remains largely unexplored.
Critically, DSM-5-TR’s integration of cultural considerations into the diagnostic process positions a willingness to discuss (“broach”) racial, ethnic, and cultural factors as not simply a counseling skill but a component of diagnostic competence itself.
This study addresses three significant gaps in the literature:
- Whether disciplinary training orientation produces differential diagnostic outcomes in AI simulation contexts.
- Whether the AI simulation benefits that have been demonstrated in general counseling skill development extend to diagnostic training.
- Whether engagement with culturally diverse AI-simulated clients can shift students’ broaching attitudes and behaviors.
Using a quasi-experimental, mixed-methods design with repeated measures, counseling and social work master degree students enrolled in the same graduate psychopathology course at Syracuse University (an R1 research institution) will complete four AI-simulated client interactions featuring culturally diverse cases with intersecting identities.
Outcomes include diagnostic accuracy trajectories, case conceptualization quality, perceived simulation realism, broaching attitudes and behaviors, and students’ lived experiences of the intervention.
The project’s findings will generate the first empirical evidence base for AI simulation as a diagnostic training tool in counseling education, illuminate whether shared AI training technologies risk inadvertently privileging one disciplinary framework over another, and establish a foundation for inter-professional collaboration in psychopathology training.