Maximizing AI in the Classroom: Aligning IB ATL Skills with UNESCO’s AI Education Guide

Introduction

With AI’s rapid growth, education is facing a potentially exciting or terrifying change, depending on how educators respond to it. Generative Artificial Intelligence (GenAI) integration into classrooms is not a distant future, if it hasn’t already happened. AI’s ability to generate content, quickly analyze large amounts of data, design learning experiences, offer real-time feedback to students, and so on has great potential for enhancing education. They do, however, carry with them a variety of ethical and pedagogical challenges that educators must navigate.

I have noticed an increase in concerns among teachers about students using AI undetected and the potential for AI to be used for cheating. Schools and teachers need to address these challenges and ensure students’ academic integrity when using AI in the classroom. Furthermore, we also need to ensure that students are well-informed of the potential risks of AI and its potential misuse.

The inspiration for this blog post came from Stephen Taylor’s post titled “Applying UNESCO’s GenAI Guide to International Schools.” In this blog post, I explore how the International Baccalaureate’s (IB) Approaches to Learning (ATL) Skills could be aligned with UNESCO’s AI Education Guide to maximize the benefits of AI in the classroom.

UNESCO’s Guidance for Generative AI in Education and Research

The UNESCO Guidance for Generative AI in Education and Research offers suggestions for schools and teachers to effectively integrate GenAI into the classroom. Firstly, let’s understand what generative AI is.

Generative AI (GenAI) is an artificial intelligence (AI) technology that automatically generates content in response to prompts written in natural-language conversational interfaces. Rather than simply curating existing webpages, by drawing on existing content, GenAI actually produces new content. The content can appear in formats that comprise all symbolic representations of human thinking: texts written in natural language, images (including photographs, digital paintings and cartoons), videos, music and software code. GenAI is trained using data collected from webpages, social media conversations and other online media. It generates its content by statistically analysing the distributions of words, pixels or other elements in the data that it has ingested and identifying and repeating common patterns (for example, which words typically follow which other words).

(Holmes et al.)

It is noted in the guidance that while GenAI can produce new content, it can also lead to misinformation if not properly monitored. This brings us to the main aspects of UNESCO’s guidance: understanding AI, ethical considerations, pedagogical implications, capacity building, and regulatory framework.

Understanding AI

To help students use GenAI effectively in the classroom, teachers first need to understand what AI is, how it works, and how it can be used to teaching and learning. Instead of being concerned about students cheating using AI and how to detect them, we need to change our perspective. Rather, we can focus on teaching students how to utilize GenAI effectively, ethically, and creatively. We should help students learn about how AI might be used to improve their learning as opposed to merely cheating. It is also important to establish an environment of trust in which students feel comfortable with human-machine collaboration and exploring the possibilities of AI. As we become more familiar with AI tools, we will become more confident in our ability to guide students on how to use AI ethically and creatively.

Ethical Considerations

Ethical considerations are an essential aspect of UNESCO’s guidance. It emphasizes that teachers discuss with students and explain to them data privacy, bias, misinformation, and potential misuse. Discussions should also explore how AI might affect society and individuals and the importance of using AI responsibly.

According to a recent Bloomberg article headlined “Humans Are Biased. Generative AI Is Even Worse,” Stable Diffusion, like other text-to-image AI models, has been shown to exaggerate and misrepresent racial and gender inequalities in the images it creates. The analysis of over 5,000 images created with Stable Diffusion revealed extreme distortions of these disparities, illustrating a world in which white male CEOs predominate, women are rarely seen in high-status professions, and people of color are mostly associated with criminal activity or low-wage occupations. This bias is a result of the underlying datasets used by these AI models, which are typically based on existing societal stereotypes. (Nicoletti and Bass)

As part of ethical considerations, it’s also essential to teach students about intellectual property and copyright, particularly as AI can generate content that may mimic or draw largely from existing content from the internet without any owner’s consent.

Pedagogical Implications

Instructional strategies in the classroom should focus on developing students’ awareness of GenAI’s limits and strengths. It is necessary to teach critical thinking skills to students so that they can make sense of the complexity of AI. It involves recognizing its bias potential, possible inaccurate information, and dominant worldviews. Teaching students critical analysis and evaluation of AI responses is part of a human-centered approach.

As previously mentioned regarding ethical considerations, copyright and intellectual property rights should be emphasized. Students need to be aware of the legal and ethical consequences of AI-generated content. While AI-generated material may appear to be original, it may infringe on the rights of original content creators. In addition, we need to continue to encourage diverse perspectives among students and promote different expressions of ideas. It not only adds to the discussion but also encourages critical and creative thinking.

A prompt-engineering approach is highlighted in UNESCO’s guidance. In spite of GenAI’s ease of use, it requires critical literacy and critical thinking skills. In order to obtain the desired outputs, students must learn to input in a language that the AI can comprehend. This entails understanding AI’s limitations and capabilities and adapting their suggestions accordingly. Students should be taught about the precise prompt methods to which AI systems respond more effectively. Additionally, students need to learn how to critically evaluate GenAI-generated suggestions to identify potential errors. This will enable them to make more informed decisions and to create better AI-powered solutions.

While using GenAI can be as simple as typing in a question or other prompt, the reality is that it is still not straightforward for the user to get exactly the output that they want.

(Holmes et al.)

Capacity Building

In order to support students in using GenAI effectively and responsibly, there is a need for ongoing professional development for teachers to keep up with AI developments. Schools are responsible for providing professional development training and developing teachers’ confidence and capabilities in using GenAI. Teachers should also have access to tools to help them understand how to best integrate AI into their classroom instruction. It is suggested in UNESCO’s guidance that schools should carefully evaluate and select appropriate GenAI tools that are suitable for use by teachers and students within the institution.

According to UNESCO’s guidance, the use of AI in education shouldn’t compromise students’ intellectual development. While AI may assist with a variety of educational tasks, it is crucial to emphasize the role of human agency in learning processes. Students need to develop critical thinking, empathy, creativity, and ethical judgment. As a result, we need to build students’ capabilities and promote human thinking.

Regulatory Framework

According to UNESCO’s guidance, a robust regulatory framework is essential to govern the use of AI in education. This framework should ensure data privacy, respect intellectual property rights, and enforce the ethical use of AI. It is critical to design policies that appropriately use AI in education within the school setting. Moreover, we must also consider an age limit for GenAI tools in order to protect younger learners. Our goal is to promote human agency while teaching students how to use GenAI tools.

Aligning IB ATL Skills with UNESCO’s AI Guidance

I created the graphic below several years ago to illustrate how we can develop learning agility by incorporating the Approaches to Learning (ATL) within the IB framework. It was inspired by Aloha Lavina’s blog post entitled “The Agile Learner in a VUCA World.” Unfortunately, Aloha’s blog post is no longer available online. I have been very interested in learning agility since then. This visual representation illustrates the significance of learning agility in the face of volatility, uncertainty, ambiguity, and complexity. My definition of learning agility is being able to learn, relearn, and unlearn quickly in an ever-changing environment. Learning agility requires an individual to be proactive, have a positive attitude, and be comfortable with taking risks.

Learning agility is about knowing how to learn — knowing what to do when you don’t know what to do. It’s about learning from experience and applying it in new ways, adapting to new circumstances and opportunities.

(Center for Creative Leadership)

Human Agency, Learning Agility, and IB ATL Skills

My interpretation of human agency mentioned in UENSCO’s guidance document aligns with learning agility since both emphasize the ability of individuals to adapt, learn, and act appropriately when confronted with changing environments. The concept of human agency, according to the guidance, refers to the ability to use GenAI tools to support and enhance human creativity. In addition, it refers to the ability to make informed decisions responsibly and ethically. It enhances human thinking rather than replacing or undermining it.

The IB ATL skills framework provides a structured approach for developing AI competencies. Skills such as thinking critically, information literacy, media literacy, communicating effectively, among others, directly contribute to the development of learning agility and promote human agency.

I attempted to identify and highlight some key skills within each category of the ATL framework in the context of GenAI based on my analysis and reflection. Developing essential skills will enable students to explore and learn how to use GenAI tools effectively, ethically, and responsibly. As of now, I believe my list of GenAI approaches to learning skills needs to be further developed. My intention is that this blog post will stimulate discussion and encourage educators to participate.

Enhancing MYP ATL Skills with Generative AI

Communication Skills

Interactive Skills

• Participate in conversations regarding ethical issues and the impact of GenAI on society.
• Discuss the benefits and limitations of GenAI tools.
• Experiment with crafting precise prompts for AI, ensuring clear and effective human-machine interactions.

Language Skills

• Use various forms of GenAI-generated writing, media and communication.
• Interpret and evaluate GenAI-generated content before communicating or sharing it.
• Read critically and verify AI-generated content with reliable human sources for accuracy, contradictions, and cultural bias.

Social Skills

Collaboration

• Use various forms of GenAI generated writing, media and communication.
• Interpret and evaluate GenAI generated content before communicating or sharing it.
• Read critically and verify AI-generated content with reliable human sources for accuracy, contradictions, and cultural bias.

Thinking

Critical Thinking

• Evaluate GenAI-generated responses to find potential biases that result from a lack of representation of disadvantaged groups.
• Change the prompt, such as wording, audience, or context, to examine how the resulting responses shifts or adapts.
• Ask different types of questions when interacting with GenAI tools, applying Socratic questions to identify biases or inconsistencies.
• Consider multiple perspectives and alternatives to prevent dominant viewpoints generated by GenAI tools.

Creative Thinking

• Utilize GenAI tools to brainstorm and explore options, but exercise independent thinking to create novel solutions.
• Select, blend, and rework responses generated by GenAI tools to create new, original perspectives.
• Recognize that GenAI tools mix existing data into ideas, but humans can create original ideas and value creation.
• Experiment by modifying the questions or information provided to AI tools, as this may lead to unexpected or new responses.

Transfer

• Connect the responses generated by GenAI tools to prior knowledge and evaluate their relevance.
• Explore multiple solutions and approaches with GenAI tools, rather than settling on the initial response provided.
• Identify and analyze patterns in both GenAI-generated and human-created content, using this knowledge to innovate and highlight ethical concerns.
• Use learned GenAI skills, design and perform project-based learning activities either independently or with teacher guidance.

Self-management

Organization

• Identify, collect, and catagorize GenAI tools that help reach learning goals.
• Apply appropriate strategies to analyze, evaluate, and organize information created by GenAI tools before adding it to own notes.
• Select GenAI tools, with teacher guidance, to assist with complex tasks.
• Maintain a balance between GenAI tools and independent thinking.
• Consider when GenAI tools will be helpful and when independent thinking is better.

Affective Skills

• Attempt to solve problems independently rather than depending on GenAI for immediate solutions.
• Consider how AI might reinforce biases and unfairly impact people.
• Avoid creating content that might violate someone’s privacy or contain private information using GenAI tools.
• Be aware of the threat of misleading or manipulative AI-generated content.
• Take appropriate action if GenAI tools are misused for deep fakes or digital bullying.

Reflection

• Use GenAI as a 1:1 coach and ask for feedback for improvement under teacher guidance.
• Consider GenAI-generated responses critically to develop new solutions rather than passively accepting them.
• Compare GenAI responses with own knowledge and understanding to identify strengths and areas for further practice.
• Practice using GenAI tools, monitor personal progress and adjust strategies for ongoing improvement.

Research

Information Literacy

• Understand the potential legal implications of using copyrighted materials generated by GenAI tools.
• Avoid entering or sharing any personal or confidential information in the prompts when using GenAI tools.
• Experiment with prompting techniques for GenAI tools to elicit desired responses, similar to using specific keywords to conduct internet searches.
• Maintain academic integrity by following instructions to correctly cite any information or resources generated by GenAI tools under teacher guidance.

Media Literacy

• Identify potential manipulated media and misinformation from GenAI, and always verify the source of information before sharing or communicating it.
• Locate, organize, analyze, evaluate, synthesize, and ethically use information from various sources and media to critically examine content generated by AI.
• Stay alert to the potential misuse of AI-generated content for spreading fake news, misleading information, or violating privacy and confidentiality.
• Recognize the ways in which AI can create or perpetuate misinformation and stereotypes.

Conclusion

In conclusion, aligning the IB’s ATL skills with UNESCO’s AI Education Guidance is helpful for integrating GenAI into the classroom. By doing so, we can ensure that students not only use GenAI tools but also develop the necessary skills within the IB framework to apply them effectively. As As we move towards a future increasingly influenced by AI, it is essential to equip students with the skills and tools to become informed and responsible users of GenAI.

References

• Holmes, Wayne, et al. Guidance for Generative AI in Education and Research. UNESCO Publishing, 8 Sept. 2023.
• Center for Creative Leadership. “Tips for Improving Your Learning Agility.” CCL, 2 Dec. 2020, www.ccl.org/articles/leading-effectively-articles/tips-for-improving-your-learning-agility/#:~:text=Learning%20agility%20is%20about%20knowing. Accessed 11 Dec. 2023.
• Nicoletti, Leonardo, and Dina Bass. “Humans Are Biased. Generative AI Is Even Worse.” Bloomberg, 2023, www.bloomberg.com/graphics/2023-generative-ai-bias/.