Analyze competency gap design hybrid approaches to build up positive performance of counsellor
Year: 2025
Type: conference-paper
Abstract: The challenges of the BANI era require college counselors to improve their competencies (knowledge, skills, attitudes), especially in medical schools where students are under high pressure and are accustomed to frequently seeking counselors' help when they encounter problems. This study explored the mismatch between the competencies of medical counselors and the support needs of students in Yunnan Province, China. A random sampling method was used to evaluate 56 medical school counselors. Through purposive sampling, semi-structured interviews were conducted with 13 stakeholders and 8 experts to construct an expected competency model and identify key gaps (hard and soft competencies). The results revealed significant deficiencies in counselors' knowledge, skills, and attitudes and supported the exploration of a hybrid coaching & mentoring model based on the learning pyramid. A gap analysis-driven counselor active learning model (ALM-CG) was developed and validated. Longitudinal tracking and expert evaluation showed that ALM-CG significantly reduced competency gaps and improved counselors' adaptive performance. The intervention further developed participants' self-regulatory and reflective monitoring capacities, which are foundational to advanced metacognitive functioning. These results confirm the effectiveness of ALM-CG in improving counselors' competency and job performance. This study provides evidence for the implementation of targeted active learning interventions and offers a practical approach for the sustainable professional development and lifelong growth of higher education counselors, while also providing valuable reference for enhancing the competence of practitioners working in counseling positions in other industries.
Authors: Jing Gui, Jirawit Yanchinda
Institution: Chiang Mai University
Language: English
Subfield: Social Psychology
Field: Psychology
Domain: Social Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4414336652
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