Leading and Assessing AI-Enabled Learning Experiences
Overview
Course Date:
TBA
Registration Period:
TBA
Duration/Frequency:
16 Hours
Mode of Training:
Face-to-Face (Classroom Teaching)
What You Will Learn
This intermediate-level course develops higher-level facilitation, assessment, classroom leadership and quality-assurance capabilities required to lead Artificial Intelligence (AI)-enabled and technology-enhanced learning experiences.
You will practise adaptive questioning, differentiated facilitation, classroom decision-making, learner assessment, supervision of Assistant Trainers, responsible AI governance and quality assurance.
Deepen your ability to lead, assess and assure the quality of artificial intelligence-enabled learning experiences. You will analyse and tailor suitable coaching and mentoring approaches to address learner developmental needs according to the learner's profile. You will also be able to provide appropriate guidance and feedback through coaching and mentoring techniques.
By the end of the course, you will be able to:
Lead an AI-enabled learning experience using facilitation approaches appropriate to learner progress.
Apply questioning, differentiation and feedback strategies to promote learner thinking, interaction, evaluation and reflection.
Manage learner behaviour, lesson timing, safety concerns and technology-related disruptions in classroom scenarios.
Supervise, coach and mentor Assistant Trainers through appropriate allocation of responsibilities, role boundaries and escalation procedures.
Apply quality-assurance, responsible AI and implementation-fidelity requirements to maintain consistent delivery standards.
Analyse appropriate coaching and mentoring approaches to address learner developmental needs
Demonstrate the ability to apply coaching and mentoring approaches to support learners' growth, development, and progression.
Topics to be covered
Higher-level facilitation, adaptive questioning and learner agency
Classroom leadership, differentiation, behaviours, timing and safety
Learner assessment, success criteria and evidence-based decisions
Supervision and deployment of Assistant Trainers
Quality assurance, responsible artificial intelligence governance and implementation fidelity
Reflective practice, calibration and continuous improvement
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