Developing an Integrated Digital Technology-based Instructional Supervision Model to Enhance the Strategic Coaching Competencies of Supervising Instructors and Mentor Teachers

Abstract

Background and Objectives: This study aims to develop a digital technology-integrated instructional supervision model to enhance the coaching and mentoring competencies of supervising instructors and mentor teachers. The GROW (goal, reality, option, and way forward) model was applied to ensure a structured and high-quality approach. The objectives are to: 1) develop a digital technology-integrated instructional supervision model to improve teaching strategy competencies and 2) evaluate its effects on enhancing coaching competencies among supervising instructors and mentor teachers.   

Methodology: This study employed a mixed-methods approach using three research instruments: observation, interviews, and recording forms. The sample included four volunteer supervising teachers and 16 mentor teachers from the Department of Home Economics, Rajamangala University of Technology, Bangkok, during the first semester of the 2020 academic year. Data were analyzed using Index of Item Objective Congruence (IOC), mean (𝑥̅), standard deviation (S.D.), percentage, and content analysis.

Main results: The developed digital technology-integrated instructional supervision model consists of three key components: 1) instructional supervision, which includes stakeholders, supervision methods, teaching strategies, coaching using the GROW Model, supervision techniques, and evaluation; 2) the supervision process, covering preparation and practice, teaching observation, and evaluation; and 3) coaching competency, featuring guidelines for supervising instructors and mentoring techniques for student teachers. Expert evaluation rated the model as highly appropriate (𝑥̅ = 4.53, S.D. = 0.61). Findings showed that supervising instructors’ use of coaching strategies met the 80% performance threshold in all areas, with the highest score in relationship-building techniques (96.43%), while mentoring teachers’ coaching also exceeded 80%, scoring highest in mentoring techniques (94.79%). Additionally, knowledge management techniques for mentoring were effective, with an 82.99% success rate. The structured use of the GROW Model and open-ended questioning enabled student teachers to develop problem-solving and work improvement skills independently.

Discussion: The developed model is found to be appropriate, as it emphasizes self-directed learning and self-development through methods that align with natural learning styles and individual competency levels. This approach enables instructors to develop in the right direction according to their potential. Similarly, the instructional mentoring model for mentor teachers is also deemed suitable, as it reflects the essential skills and responsibilities of mentors. These include providing guidance, sharing relevant information, and encouraging student teachers to develop a broader vision of their organization and their future career paths. The mentor’s role in stimulating student teachers to think critically and strategically about their professional development ensures that they can set clear goals and align their learning with real-world teaching demands.

Conclusion: The integration of digital technology into instructional supervision models effectively enhances the coaching competencies of supervising instructors and mentor teachers. By thoroughly studying and applying coaching strategies, users can significantly improve their own capabilities, making this an appropriate method for developing coaching skills. Implementing the GROW Model coaching process to collaboratively address problems or set development goals among supervising instructors, mentor teachers, and student teachers—through its four structured steps—stimulates student teachers' thinking via open-ended questions posed by supervisors. This approach leads to more effective instructional supervision and maximizes benefits for educational institutions.