Course Overview

This qualification aims to equip practicing teachers with advanced skills and knowledge to effectively integrate digital technologies and Artificial Intelligence (AI) into their educational practices. It emphasizes developing innovative, inclusive, and assessment-driven teaching strategies enhanced by AI tools, fostering learner engagement, collaboration, and critical thinking.

Course Structure and Learning Modules

The course broadly extends the Cambridge PDQ Certificate (Module 1) with added focus on AI and corresponds to ASQF Level 3 criteria.

 

Unit 1: Understanding Local Digital Technologies and AI for Learning

  • Analyse locally available digital and AI technologies that support or enable new learning.

  • Examine AI applications in education (adaptive learning platforms, AI tutoring, chatbots, analytics).

  • Relate usage of digital and AI tech to pedagogic concepts and learning theories.

  • Investigate development of 21st-century skills via technology-enhanced learning.

  • Consider ethical, accessibility, and digital wellbeing issues related to AI in education.

 

Unit 2: Designing and Delivering Lessons Using Digital Technologies and AI

  • Plan and teach lessons integrating AI tools (adaptive quizzes, personalized feedback systems, data-driven formative assessment).

  • Foster inclusive, motivating, and active learning environments through technology.

  • Use digital and AI-enabled formative assessments to track learner progress and adapt teaching dynamically.

  • Reflect on lesson plan effectiveness considering AI-enhanced learning analytics and mentor feedback.

 

Unit 3: Evaluating and Collaborating on Digital and AI-supported Teaching Practice

  • Design two distinct AI-enhanced learning activities targeting different skills and learner profiles.

  • Collect and analyse feedback from learners and colleagues on AI and digital technology use.

  • Collaborate with peers and the wider educational community in designing and refining technology-rich learning activities.

  • Critically reflect on the benefits and challenges associated with using AI in teaching and learning.

Assessment

Candidates will be assessed through a portfolio of evidence, demonstrating advanced practice in integrating AI and digital technology:

  • Observation and analysis of AI-supported teaching in local context.

  • Lesson plans, mentor observation feedback, examples of learner work highlighting AI impact.

  • Written assignments exploring theoretical foundations, practical applications, and reflective evaluations.

  • Records of collaboration with peers on AI-enhanced learning designs.