Mentorship in the Age of Generative AI
ChatGPT to Support Self-Regulated Learning of Pre-Service Teachers Before and During Placements
Datos Bibliográficos
| ID | 22047697 |
|---|---|
| Autores | Ngoc Nguyen (0000-0003-2970-7504, The University of Sydney, autor de correspondencia), Walter Barbieri (0000-0003-2993-3114, The University of Adelaide) |
| Año | 2025 |
| Volumen | 15 |
| Número | 6 |
| Páginas | 642 |
| Fecha de publicación | 2025-05-23 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | Education Sciences (JOURNAL) |
| Identificadores de la revista | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Editorial | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci15060642 |
| OpenAlex | W4410622615 |
| Idioma | EN |
| Citas recibidas | 3 |
| Referencias citadas | 66 |
This study investigates the integration of mentorship, self-regulated learning (SRL), and generative artificial intelligence (gen-AI) to support pre-service teachers (PSTs) before and during work-integrated learning (WIL) placements. Utilising the Mentoring and SRL Pyramid Model (MSPM), it examines how mentors’ dual roles as coaches and assessors influence PSTs’ SRL and explores to what extent gen-AI can assist PSTs in meeting the demands of WIL placements. Quantitative and qualitative data from 151 PSTs, including survey, interview, placement scores, and mentor feedback were analysed using statistical correlation analysis and thematic analysis to reveal varied mentorship approaches. Gen-AI tools are highlighted as valuable in enhancing PSTs’ SRL, providing tactical and emotional guidance where traditional mentorship is limited. However, challenges remain in gen-AI’s ability to navigate complex interpersonal dynamics. The study advocates for balanced mentorship training that integrates technical and emotional support, and equitable access to gen-AI tools. These insights are critical for educational institutions aiming to optimise PST experiences and outcomes in WIL through strategic integration of gen-AI and mentorship
Generative grammar · Mathematics education · Medical education · Mentorship · Pedagogy · Service-learning · Artificial Intelligence in Healthcare and Education · Computer Science · Innovations in Medical Education · Medicine · Psychology · Simulation-Based Education in Healthcare · Artificial Intelligence
Artificial intelligence awareness perception acceptance and utilization as predictors of academic publishing competence among academics in Nigerian universities
Placement stress and year-level differences in pre-service teachers’ use of generative AI
Drivers and pathways of AI academic mentor acceptance
Acceptance of artificial intelligence among pre-service teachers
In search of artificial intelligence (AI) literacy in teacher education
TPACK in the age of ChatGPT and Generative AI
Purposeful Sampling for Qualitative Data Collection and Analysis in Mixed Method Implementation Research
The Relation of Students’ Conceptions of Feedback to Motivational Beliefs and Achievement Goals
Development and validation of ChatGPT literacy scale
Using video-elicitation focus group interviews to explore pre-service science teachers’ views and reasoning on artificial intelligence
The factors influencing teacher education students’ willingness to adopt artificial intelligence technology for information-based teaching
Newcomers' relationship-building behavior, mentor information sharing and newcomer adjustment
Potential Risks of Artificial Intelligence Integration into School Education
Thematic Analysis
Generative AI as a “placement buddy”
Mentoring beginning teachers
Pre-service teachers' sense of efficacy
Social and emotional learning in teacher preparation
Mentor teachers’ motivations and implications for mentoring style and enthusiasm
Formative assessment and self-regulated learning
Becoming a Self-Regulated Learner
The Role of Mentor Teacher-Mediated Experiences for Preservice Teachers
Employability skill development in work-integrated learning
Unpacking the learning-work nexus
| Obras citantes distintas | 3 |
|---|---|
| Citas por año | 3 |
| Intervalo de citas | 2026 - 2026 (1) |
| Velocidad de citación | current |
| Altamente citado | No |
| Tipos de cita | Neutras: 2 |