Teachers guide to generative AI Tools (LS21)

Teachers guide to generative AI Tools (CS21)’s Docs ▸ Teachers guide to generative AI Tools (LS21)

Learning Scenario Identity
Title Teachers guide to generative AI Tools
Creator         Creator Seyma Kocak, Lana Sattelmaier and Jan Pawlowski
Main Idea / Description The increasing proliferation of AI tools brings with it many challenges and considerations. On the one hand, many AI tools are available, offering users a wide range of options. On the other hand, this multitude of options often leads to quality concerns, as not all tools are equally reliable and effective. Technical failures are also a common problem, as AI tools usually do not perform as expected in practice.

Another critical issue is the ethical dilemma associated with the use of AI. Implementing AI technologies raises questions about responsibility, data protection, and the potential negative impact on society. Sharing information about the use of AI tools is crucial in discussing these ethical issues and finding solutions.

In addition, many users lack the skills to use AI tools effectively. This lack of competence can significantly limit these technologies’ successful implementation and benefits. Overall, using AI tools requires careful consideration and a sound understanding to maximize the benefits and minimize the risks.
Target Group (students’ age, learning level, background, disabilities) The scenario is for Teachers

It will take 120 min
Curriculum & Learning Subjects All subjects
Learning Objectives Learning Objectives:

Recognizing reputable AI tools

  • Knowledge: Identify reputable sources and AI platforms.
  • Understanding: Explaining the characteristics of reputable AI tools and interpreting ratings.
  • Application: Applying checklists and comparing AI tools.

Knowledge about the output of AI tools, differences and similarities

  • Knowledge: Describing the types of AI outputs and basic terms.
  • Understanding: Explaining similarities and differences and the quality factors of the outputs.
  • Application: Evaluate outputs and carry out comparative analyses.

Knowledge of boundary conditions, prices, and data protection

    • Knowledge: Describing cost structures and data protection principles.
    • Understanding: Explaining the price-performance ratio and data protection risks.
  • Application: Carrying out cost-benefit analyses and applying data protection measures.
Teachers’ Wellness Competences  Competences Teachers Need for Technostress Mitigation: 

  • Knowledge of technostress risks and mitigation strategies.
  • Ability to identify technostress risks in distance learning scenarios.
  • Ability to design distance learning scenarios that mitigate technostress risks.
  • Ability to support learners who are experiencing technostress.
  • Ability to protect themselves from experiencing technostress.

Select from list of Teacher socioemotional e-competencies (TABLE 1)

  • Emotional e-independence
  • Social e-Comptency
  • E-Self-Management
  • Emotional e-awareness
Learning Scenario Framework
Pedagogical Method
  • What positive learning strategies are incorporated into the scenario to prevent or mitigate technostress?
  • What is the focus of these positive learning strategies?
    • Foster collaboration and support (Teacher-student and peer relationships)
    • Promotion of Individual emotional well-being 
    • Selection of suitable teaching methods for student-centred learning (effectiveness of learning)

Select from list of positive pedagogical interventions  (TABLE 2)

  • Support and work well with others
  • Learn to cope and become resilient
  • Engage in self-directed and dedicated learning
Software & Materials

 

 Distance Learning Context:

  • How will the scenario be delivered to learners? What platform will the scenario be delivered on?

A learning management system (Moodle) and communication tools like Zoom, Webex, etc.

  • What tools and resources will be needed?

Computer and Internet (for example Google account), Microphone, Headphones 

  • How will learners interact with the scenario?

Group work

  • In which space will learning take place on the learner’s side?

Workplace (Table and Chair)

  • Who are the actors involved? (facilitators)

IT-Support

  • How will technostress mitigation be addressed in this distance learning setting? (technology configuration,technology use and network connections)

Knowledge of suitable and trusted AI tools and targeted teacher training will support the reduction of technostress in this distance learning setting. This includes optimized technology configuration, effective use of technology, and stable network connections.

Teacher Training 
Evaluation Tools Assessment

  • How will you assess learners’ learning?

Discussion round

  • How will you provide feedback to learners on their performance?

Online Feedback via communication tools like Zoom, Webex or Microsoft Teams

  • How will you assess the effectiveness of technostress mitigation?

User diary, feedback, or discussion round with other participants. The exchange about possible challenges Assistance

Debriefing:

  • How will you help learners reflect on their learning?
  • What questions will you ask them to think about?

How stressed were you about using the AI tools?

Did the exchange with others help you to minimize your technostress?

  • How will technostress mitigation be discussed in the debriefing?

Experiences about worst and best cases
Learning Scenario Implementation
Learning Activities

 (Description, duration, worksheets         worksheets   etc.)

 Scenario Events:

Introduction: The introduction is given with a PowerPoint presentation explaining what AI tools are and where and how they are used. (10)

Elaboration: In the group, the participants should brainstorm at the beginning which AI tools they know and which they need in their teaching. (20)

Use the tools from the given list and see which ones they can use for their teaching content or work. (50)

Reflection: 

Exchange Discussion

Note-taking of experience reports and group discussion (40)

 

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