All Digital Training – Empowering Teachers, Educators, Trainers, and Facilitators

• May 8, 2024
• Andrew

Welcome to ALL DIGITAL’s training hub, where we provide a collection of free online courses and open-access resources.

At ALL DIGITAL, our primary mission is to advance the digital transition by enhancing the skills of adult educators and trainers. This website is dedicated to supporting this mission with a compilation of enriching training content from various European projects – ADA, DigCompHub, IBox and GenAIEdu.

Course 1: Introduction to Artificial Intelligence (4 hours)

This course focuses on providing attendees with a comprehensive introduction to Artificial Intelligence (AI) and its practical applications. Attendees will engage in various activities to enhance their understanding of AI concepts and develop critical thinking skills.

1. Understanding AI through LinkedIn: Attendees will complete a series of online modules and assessments provided by LinkedIn. These modules will cover key concepts and principles of Artificial Intelligence. Through these activities, attendees will demonstrate their understanding of AI fundamentals and its significance in various domains.

2. Computational and Critical Thinking for AI: Using content from the Generative AI Toolkit, attendees will participate in interactive exercises designed to develop their computational and critical thinking skills in relation to AI. They will tackle coding challenges, analyze AI algorithms, and provide written reflections on their problem-solving approaches. This activity aims to strengthen their analytical abilities in the context of AI.

3. Exploring the AI Toolbox for Educators: Attendees will be guided through the Generative AI Toolkit’s AI Toolbox specifically designed for educators. They will explore a variety of tools and resources relevant to their teaching practice. As part of this exploration, attendees will select and evaluate a generative AI tool from the toolbox. To showcase its potential educational applications, they will create a presentation or tutorial that highlights the tool’s functionalities and benefits in a learning environment.

4. Promoting Responsible and Ethical Use of Generative AI: Through the Generative AI Toolkit content, attendees will engage with case studies and scenarios that shed light on ethical considerations in the context of Generative AI. They will analyze the ethical implications of using Generative AI, propose solutions or guidelines to address these concerns, and create a resource that promotes the responsible and ethical use of Generative AI in educational settings. This activity encourages critical thinking and ethical decision-making regarding AI applications.

By the end of this course, attendees will have a solid foundation in Artificial Intelligence concepts and principles. They will possess computational and critical thinking skills necessary to harness AI effectively. Additionally, they will be equipped with knowledge 2 about the ethical considerations surrounding the use of Generative AI and will have created resources to promote responsible and ethical practices in educational settings.

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Course 2: Introduction to Generative AI (4 hours)

This course provides an introduction to Generative AI, covering its concepts, applications, and ethical implications. Attendees will engage in various activities to deepen their understanding of Generative AI.

1. Exploring Generative AI: Attendees will be assigned articles and videos that explain the concept of Generative AI. They will read the articles and watch the videos to gain knowledge about Generative AI and its applications in different fields. Afterward, they will complete a short online quiz to assess their understanding of Generative AI and its potential.

2. Evolution of Online Search: Case studies and examples will be provided to showcase the evolution of online search through Generative AI. Attendees will analyze the impact of Generative AI on search results and user experience. They will examine how Generative AI has transformed the way we search for information and discuss its advantages and limitations.

3. Streamlining Work with Microsoft Bing Chat: Attendees will be granted access to Microsoft Bing Chat and will be given a set of tasks to complete using the chatbot. They will interact with the chatbot, perform tasks, and document their experience. Attendees will reflect on the benefits and limitations of using a generative chatbot in streamlining their work and explore its potential applications in various contexts.

4. Ethical Considerations in the Age of Generative AI: Attendees will be presented with ethical considerations and dilemmas associated with Generative AI. They will engage in an online discussion forum where they can share their perspectives on the ethical implications of Generative AI. Attendees will propose strategies and guidelines for responsible use of Generative AI to address ethical concerns. The discussion will encourage critical thinking and ethical awareness in the context of Generative AI.

By the end of this course, attendees will have a comprehensive understanding of Generative AI, its evolution, ethical considerations, and practical applications. They will be equipped with the knowledge to make informed decisions and engage in responsible use of Generative AI in educational settings.

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Course 3: Generative AI and Digital Resources (4 hours)

In this course, attendees will explore the relationship between Generative AI and digital resources. They will delve into sourcing, creating, and sharing digital resources while considering ethical considerations and governance principles.

1. Curating Digital Resources: Attendees will conduct research to identify a wide range of digital resources related to Generative AI. They will compile a comprehensive list of these resources, categorizing them based on their relevance and potential application in educational contexts. Attendees will curate a collection of digital resources that they find valuable and share it with the course community. This activity encourages collaboration and knowledge sharing among participants.

2. Data Governance and Responsible Use: Attendees will review case studies and guidelines on data governance and responsible data use in the context of Generative AI. They will critically analyze the ethical considerations and legal obligations associated with handling data in AI applications. Drawing from their analysis, attendees will create a data governance plan outlining best practices for responsibly managing and utilizing data in Generative AI projects. This activity emphasizes the importance of data ethics and responsible data practices.

3. AI Governance and Compliance: Attendees will explore the regulations and policies relevant to AI governance and compliance. They will conduct research and analyze the key requirements and obligations that educational institutions should adhere to when utilizing Generative AI. Based on their findings, attendees will develop a compliance checklist or infographic summarizing the essential regulations and guidelines. This activity promotes a thorough understanding of legal and regulatory considerations when implementing Generative AI in an educational context.

4. Ethical Considerations and AI Ethics Guidelines: Attendees will examine the ethical dimensions associated with Generative AI and AI ethics guidelines specific to this field. They will identify potential ethical challenges that may arise in educational settings and propose strategies to address these challenges effectively. Attendees will create a presentation or infographic that highlights key ethical considerations and guidelines for using Generative AI in education. This activity encourages critical thinking and ethical decision-making in the application of AI.

By the end of this course, attendees will have developed a curated collection of digital resources, gained insights into data governance and responsible data use, familiarized themselves with AI governance and compliance requirements, and explored ethical considerations specific to Generative AI. They will be equipped with valuable resources, knowledge, and strategies to make informed decisions and promote ethical practices when utilizing Generative AI in educational contexts.

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Course 4: Generative AI in Teaching and Learning (4 hours)

In this course, attendees will explore the integration of Generative AI in teaching and learning contexts. They will examine different learning models, address social objectives of education, consider human agency and teacher autonomy, and analyze fairness, bias, and ethical considerations within Generative AI systems.

1. Models of Learning and Pedagogical Assumptions: Attendees will study various models of learning and pedagogical assumptions within the context of Generative AI. They will analyze the strengths and limitations of these models and assumptions in educational settings. To summarize their findings, attendees will create a comparative analysis chart or infographic that highlights the key features of different learning models in Generative AI. This activity promotes critical thinking and understanding of the diverse approaches to learning in the context of Generative AI.

2. Addressing Social Objectives of Education: Attendees will explore how Generative AI can contribute to the social objectives of education, such as promoting inclusivity and fostering collaboration. They will design a lesson plan or activity that incorporates Generative AI to address specific social objectives. Additionally, attendees will create a reflective journal entry or video discussing the potential impact of Generative AI on achieving social objectives in education. This activity encourages attendees to consider the transformative potential of Generative AI in promoting social outcomes.

3. Human Agency and Teacher Autonomy in AI-Enhanced Classrooms: Attendees will reflect on the role of human agency and teacher autonomy in AI-enhanced classrooms. They will analyze how teachers can maintain control and decision-making authority within the context of Generative AI. Attendees will visually represent the relationship between human agency, teacher autonomy, and Generative AI in education using a concept map or other visual representation. This activity prompts attendees to critically examine the balance between technology and human agency in educational settings.

4. Fairness, Bias, and Ethical Considerations in Generative AI Systems: Attendees will examine fairness, bias, and ethical considerations related to Generative AI systems. They will analyze case studies and research on algorithmic bias in Generative AI and its potential impact on educational outcomes. Attendees will propose strategies to mitigate bias and promote fairness in the design and use of Generative AI systems in education. This activity fosters an understanding of the ethical implications and challenges associated with Generative AI.

By the end of this course, attendees will have a comprehensive understanding of different learning models in Generative AI, the potential of Generative AI in addressing social objectives, the role of human agency and teacher autonomy, and the importance of fairness, bias, and ethical considerations within Generative AI systems. They will be equipped with knowledge and insights to effectively integrate Generative AI in teaching and learning while considering ethical dimensions and promoting equitable educational practices.

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Course 5: Generative AI in Assessment (4 hours)

In this course, attendees will delve into the integration of Generative AI in assessment practices within educational settings. They will explore the enhancement of assessments, analyze algorithmic bias and its mitigation strategies, examine cognitive focus and knowledge assessment in Generative AI systems, and consider the responsible use of AI-based assessment.

1. Enhancing Assessment with Generative AI: Attendees will explore how Generative AI can improve assessment practices in educational settings. They will design an assessment task or rubric that incorporates Generative AI to provide personalized feedback or generate responses. To showcase their understanding, attendees will create a video presentation or tutorial that demonstrates the application of Generative AI in assessment scenarios. This activity encourages attendees to think creatively about leveraging Generative AI to enhance the assessment process.

2. Algorithmic Bias and Mitigation Strategies: Attendees will analyze the concept of algorithmic bias and its implications for assessment when utilizing Generative AI. They will conduct research and propose strategies to identify and mitigate algorithmic bias in assessment systems. Attendees will compile their findings into a guide or infographic that outlines steps to minimize algorithmic bias specifically in Generative AI-based assessments. This activity promotes critical thinking and the development of strategies to address bias in assessment practices.

3. Cognitive Focus and Knowledge Assessment in Generative AI Systems: Attendees will explore how Generative AI systems assess cognitive focus and knowledge within educational contexts. They will critically analyze the strengths and limitations of using Generative AI for knowledge assessment. To summarize their findings, attendees will create a comparative analysis chart or infographic that highlights the different approaches to knowledge assessment in Generative AI systems. This activity fosters an understanding of the diverse methods of evaluating cognitive focus and knowledge using Generative AI.

4. Responsible Use of AI-Based Assessment: Attendees will examine ethical considerations and responsible use guidelines for AI-based assessment. They will reflect on the potential impact of AI-based assessment on student privacy, fairness, and the overall educational experience. Additionally, attendees will create a set of guidelines or a checklist for the responsible and ethical use of AI-based assessment in educational settings. This activity prompts attendees to consider the ethical dimensions and implications associated with AI-based assessment.

By the end of this course, attendees will have a comprehensive understanding of how Generative AI can enhance assessment practices, strategies to mitigate algorithmic bias, approaches to cognitive focus and knowledge assessment using Generative AI systems, and guidelines for the responsible use of AI-based assessment. They will be equipped with the knowledge and tools to effectively leverage Generative AI in assessments while upholding ethical considerations and promoting fairness in educational evaluation.

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Course 6: Empowering Learners with Generative AI (4 hours)

In this course, attendees will explore how Generative AI can empower learners by facilitating personalized learning experiences, addressing individual needs, promoting self-efficacy, and enabling justified choices. They will analyze the potential of Generative AI to enhance inclusion and adapt to diverse student needs while considering ethical implications and monitoring AI outcomes.

1. Personalization and Inclusion through Generative AI: Attendees will conduct research and analysis to understand how Generative AI can facilitate personalized learning experiences. They will design a lesson or activity that leverages Generative AI to address individual learner needs and promote inclusion. To showcase their ideas, attendees will create a video presentation or tutorial demonstrating the implementation of personalized and inclusive practices using Generative AI. This activity encourages attendees to explore the potential of Generative AI in tailoring learning experiences to meet diverse learner requirements.

2. Adapting to Student Needs and Individual Differences: Attendees will reflect on the ability of Generative AI to adapt to diverse student needs and individual differences. They will develop a plan or strategy for incorporating Generative AI tools or resources that can accommodate different learning styles or preferences. To visually represent their strategies, attendees will create a visual representation or infographic illustrating the various ways Generative AI can adapt to student needs. This activity fosters an understanding of the flexibility of Generative AI in catering to diverse learners.

3. Promoting Student Self-Efficacy, Self-Image, and Skills Development: Attendees will explore how Generative AI can enhance student self-efficacy, self-image, and skill development. They will develop a set of activities or resources that empower students to take ownership of their learning through the use of Generative AI. To reflect on the potential impact of Generative AI on student motivation and skill development, attendees will create a reflective journal entry or video discussing their findings. This activity encourages attendees to consider the role of Generative AI in fostering student agency and skill acquisition. 4. Justified Choice and Monitoring of AI Outcomes: Attendees will analyze the importance of making justified choices and continuously monitoring AI outcomes in educational contexts. They will create a framework or checklist for evaluating and selecting appropriate Generative AI tools or algorithms based on educational goals. Additionally, attendees will design a plan for monitoring and assessing the effectiveness and ethical implications of using Generative AI in their educational practice. This activity prompts attendees to consider the responsible implementation and evaluation of Generative AI in the learning environment.

By the end of this course, attendees will have gained insights into how Generative AI can empower learners through personalization, inclusion, self-efficacy, and justified choices. They will have developed strategies for adapting Generative AI to diverse student needs and created resources that promote student engagement and skill development. Furthermore, attendees will be equipped with the knowledge and tools to monitor and assess the ethical implications and effectiveness of Generative AI in their educational practice, ensuring responsible and impactful use of these technologies.

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Course 7: Facilitating Learners’ Digital Competence with Generative AI (4 hours)

In this course, attendees will delve into the development of learners’ digital competence and responsible use of AI in the context of Generative AI. They will explore ethical considerations, co-design AI-enabled learning practices, and promote ethical AI use in problem-solving and learner wellbeing.

1. Developing Learners’ Digital Competence and Responsible Use of AI: Attendees will explore the concept of digital competence and responsible AI use within the realm of Generative AI. They will develop a set of learning activities or resources that foster learners’ digital competence and promote responsible use of Generative AI. To showcase their curated resources and activities, attendees will create a digital portfolio or website. This activity encourages attendees to consider the essential skills and ethical considerations related to AI in nurturing learners’ digital competence. 8

2. Teaching AI Ethics and Data Ethics in the Classroom: Attendees will examine the importance of teaching AI ethics and data ethics to learners. They will design a lesson plan or activity that introduces learners to ethical considerations associated with AI and data use in the classroom. To demonstrate their teaching approach and strategies for fostering ethical awareness, attendees will create a multimedia presentation or video. This activity emphasizes the significance of ethical discussions and considerations when incorporating AI into educational contexts.

3. Ethical Considerations in Co-Designing AI-Enabled Learning Practices: Attendees will explore ethical considerations and principles when co-designing AI-enabled learning practices. They will collaborate with peers to co-design an AI-enabled learning activity or project while considering ethical implications. Attendees will then present their co-designed activity or project and actively participate in an online discussion forum, providing feedback and suggestions to their peers. This activity promotes collaborative exploration of ethical considerations in the design and implementation of AI-enabled learning experiences.

4. Promoting Ethical AI Use in Problem-Solving and Wellbeing: Attendees will reflect on the ethical dimensions of using AI in problem-solving and promoting learner wellbeing. They will design a problem-solving activity that incorporates ethical considerations when utilizing Generative AI. Additionally, attendees will create a case study or scenario that highlights the importance of ethical AI use in enhancing learner wellbeing. This activity prompts attendees to critically analyze the ethical implications and consequences of AI applications in problem-solving and learner support.

By the end of this course, attendees will have explored the development of learners’ digital competence and responsible AI use. They will have curated learning activities and resources to foster digital competence and ethical awareness in the context of Generative AI. Furthermore, attendees will have gained insights into teaching AI ethics, co-designing AI-enabled learning practices while considering ethical implications and promoting ethical AI use in problem-solving and learner wellbeing.

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