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6.5 DiGiComp Integration: Problem Solving

Topic Activity

Think Like a Digital Detective

Aim of the activity

By the end of this session, learners will be able to:

  • Apply the four-step problem-solving cycle (Identify → Explore → Test → Reflect) to at least one digital scenario.

  • Test and evaluate AI-generated troubleshooting advice critically.

  • Collaborate with peers to exchange and validate troubleshooting strategies.

  • Reflect on their own confidence and persistence in solving digital challenges.

Target Group

Adult learners (basic to intermediate digital literacy)

Duration

60 minutes (classroom, online, or blended)

Objective

By the end of this session, learners will be able to:

  • Apply the four-step problem-solving cycle (Identify → Explore → Test → Reflect) to at least one digital scenario.

  • Test and evaluate AI-generated troubleshooting advice critically.

  • Collaborate with peers to exchange and validate troubleshooting strategies.

  • Reflect on their own confidence and persistence in solving digital challenges.

Materials necessary to execute activity

  • Scenario cards with common digital problems (e.g., upload error, connectivity issue, forgotten password).

  • AI/chatbot tool (e.g., ChatGPT or equivalent).

  • Worksheets for documenting problem-solving steps.

  • Padlet or online forum space for peer support simulation.

  • Access to basic digital platforms for demonstration (e.g., Zoom, Moodle, Google Drive).

Steps for implementation

Warm-Up (5 min):

  • Trainer prompts discussion: ‘What was the last digital problem you faced? How did you solve it?’

  • Learners share short experiences.

Mini-Input (10 min):

  • Trainer introduces the problem-solving cycle (Identify → Explore → Test → Reflect).

  • Quick demo: solving a simple problem (e.g., muted microphone in Zoom).

Group Task – Scenario Solving (20 min):

  • Learners work in small groups with scenario cards.

  • Each group applies the problem-solving cycle to propose solutions.

  • Trainer circulates, scaffolds beginners, and challenges advanced learners with complex variations.

AI Troubleshooting Demo (10 min):

  • Trainer shows how to ask AI a troubleshooting question.

  • Groups test AI suggestions, then compare them with official resources.

  • Reflection: ‘What was useful? What was misleading or unsafe?’

Peer Support Forum Simulation (10 min):

  • Learners post one problem to a shared Padlet/forum.

  • Peers respond with possible solutions.

  • Trainer highlights valid, safe, and ethical responses.

 

Wrap-Up (5 min):

  • Learners write down one new strategy they will apply when facing digital challenges.

  • Quick exit poll: ‘Do you feel more confident in solving problems independently now?’

Skills developed with the activity

By the end of this session, learners will be able to:

  • Apply the four-step problem-solving cycle (Identify → Explore → Test → Reflect) to at least one digital scenario.

  • Test and evaluate AI-generated troubleshooting advice critically.

  • Collaborate with peers to exchange and validate troubleshooting strategies.

  • Reflect on their own confidence and persistence in solving digital challenges.

Methodology

Online

Blended

Evaluation

Assessment

Observation: Trainer checks if learners apply the problem-solving cycle correctly.

Peer Review: Groups evaluate each other’s troubleshooting strategies.

Scenario-Based Quiz: Learners choose the best first step for given digital problems.

Self-Reflection: Learners log one real problem they solved during the week using the cycle.

 

Reflection Prompts for Trainers

Self-Awareness

Do I step in too quickly when learners face digital problems, or do I allow them space to try and explore solutions?

How do I personally approach troubleshooting - do I model persistence, flexibility, and critical thinking in front of learners?

 

Pedagogy

How can I scaffold troubleshooting tasks for learners with very low confidence, without overwhelming them?

Do I integrate problem-solving into my regular lessons, or do I only address it reactively when issues occur?

 

AI and Ethics

Am I teaching learners how to use AI responsibly as a co-pilot, not as the only problem-solver?

Do I guide learners to verify AI-generated advice with reliable sources before applying it?

 

Inclusivity and Accessibility

How do I adapt problem-solving activities for learners with limited literacy, language barriers, or low digital experience?

Am I providing multiple entry points (visual guides, checklists, AI tools, peer support) so that all learners can participate?

 

Resilience and Learner Empowerment

Am I reinforcing the idea that mistakes and errors are valuable learning opportunities?

Do I encourage learners to reflect on the process of solving problems, not only the final solution?

How do I celebrate learners’ small wins in troubleshooting to build confidence and independence?

 

Professional Growth

Where do I find reliable troubleshooting resources (forums, FAQs, professional networks) to keep my own skills sharp?

How can I connect with other trainers to share best practices for embedding problem-solving into adult education?

Links & References

Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.

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Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.

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