Implementing the Mindfulness-Based Interventions; Teaching Assessment Criteria (MBI:TAC) in Mindfulness-Based Teacher
G M Griffith1, R S Crane1, R Baer2
1Centre for Mindfulness Research and Practice, School of Psychology, Bangor University, Bangor, UK.
Global Advances in Health and Medicine
|March 15, 2021
Summary
The Mindfulness-Based Interventions: Teaching Assessment Criteria (MBI:TAC) supports mindfulness teacher training. Its use can enhance teaching quality and prevent the
Area of Science:
- Mindfulness-Based Interventions
- Teacher Training
- Educational Assessment
Background:
- The Mindfulness-Based Interventions: Teaching Assessment Criteria (MBI:TAC) was developed to assess mindfulness program (MBP) teacher competence.
- The MBI:TAC is freely available and used internationally by mindfulness teacher training organizations.
- Its application has evolved from assessment to informal support in MBP teacher training.
Purpose of the Study:
- Examine the rationale for using MBI:TAC in MBP teacher training.
- Provide practical guidance on integrating MBI:TAC into training pathways, acknowledging potential benefits and challenges.
- Offer strategies for using MBI:TAC to deliver effective feedback on trainee teaching practice.
Main Methods:
- Review of MBI:TAC's development and evolving usage in mindfulness teacher training.
- Analysis of the rationale for its implementation in training programs.
- Development of practical guidance for integration and feedback.
Main Results:
- Implementing MBI:TAC can support the quality and integrity of MBP teacher training.
- Effective use of MBI:TAC can help ensure high-quality MBP teachers.
- This approach may mitigate the 'implementation cliff,' where intervention quality declines outside research settings.
Conclusions:
- The MBI:TAC is a valuable tool for enhancing MBP teacher training quality.
- Strategic integration and feedback using MBI:TAC can improve teacher competence.
- Adoption of MBI:TAC can lead to more consistent and effective delivery of mindfulness-based programs in real-world settings.
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