Explore ways to train Pedagogical Digital Competence (PDC) and measure its effectiveness

Discover how 20+ training programmes develop Pedagogical Digital Competence

Back to PDC Insights
Promoting Independent Learners with GenAI

Training official name: “Digital Pedagogy 2.0: Promoting Independent Learners” 

 Trainer: School Of Education, Tel Aviv University, Israel

Target Group

Pre-service teachers enrolled in teacher education programmes at Tel Aviv University.

Duration

One academic semester (approximately 3 months).

Delivery Mode

Fully online training combining synchronous and asynchronous learning activities.

Training goals

  1. Develop teachers’ knowledge, skills, and instructional practices related to Self-Regulated Learning (SRL) 
  2. Develop teachers’ knowledge, skills, and instructional practices related to Generative Artificial Intelligence (GenAI)  
  3. Strengthen teachers’ knowledge, confidence, and motivation to use Generative Artificial Intelligence (GenAI) to promote students’ Self-Regulated Learning (SRL) skills

How this programme develops Pedagogical Digital Competence?

This pre-service training develops Pedagogical Digital Competence (PDC) by integrating theoretical knowledge, policy awareness, and hands-on experience with technologies that promote Self-Regulated Learning (SRL), with a specific focus on Generative AI (GenAI). Student teachers analyze research and policy documents, experiment with different digital tools that support SRL processes (planning, monitoring, reflection), and design their own pedagogical ideas for integrating GenAI to foster students’ SRL.

Example of training activity from this programme
Designing Policy-Informed GenAI Integration to Promote SRL

Pre-service teachers analyze research and policy documents, design a pedagogically grounded proposal for integrating Generative AI to promote students’ Self-Regulated Learning, and present it through a GenAI-generated song that models meaningful classroom use.

Extended description - Replicable process:

Step 1 – Grounding in theory and policy

Participants read one academic article on SRL and one policy document on AI in education. They identify key SRL principles (planning, monitoring, reflection) and relevant policy considerations (ethics, responsible use, pedagogical alignment).

Step 2 – Linking GenAI to SRL

Participants analyze how Generative AI can meaningfully support different SRL phases and distinguish between superficial tool use and pedagogically grounded integration.

Step 3 – Tool exploration

Participants experiment with a GenAI tool and evaluate its pedagogical affordances, limitations, teacher role, and ethical implications.

Step 4 – Writing a Policy Brief

Using a structured template, participants formulate a concise policy brief that includes: 

  • The educational challenge 
  • The proposed GenAI-supported SRL solution 
  • Pedagogical justification Policy alignment 
  • Ethical considerations
Step 5 – Creative modeling (Suno)

Based on their policy brief, participants create a song using Suno (GenAI music-generation platform) that presents and models meaningful and responsible classroom integration.

Implementation formats

Knowledge Instruction (KI): 

Participants complete all steps individually. 

Collaborative Design (CD): 

 Participants co-construct the policy brief and pedagogical proposal in small groups, negotiate decisions, and jointly produce the Suno-based artifact.