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Navigating the Future of Education: Perspectives on AI Integration


Mar 2024

In today’s dynamic education landscape, the emergence of generative Artificial Intelligence (GAI) heralds unprecedented opportunities and challenges, reshaping pedagogical paradigms and redefining the roles of educators. As the quest for human–AI synergy accelerates, educators navigate ethical considerations, embrace technological advancements, and champion inclusive learning environments. In this article, NIE Associate Professor Tan Seng Chee from the Learning Sciences and Assessment Academic Group and who is also an active researcher in the field of educational technology for schools, sheds some light on the evolving landscape of AI integration in the Singapore education landscape.
A/P Tan discusses AI in education and the various courses NIE is offering on this topic.

How do you see artificial intelligence (AI), particularly generative AI, shaping the future of teacher education and professional development?

The development of artificial intelligence (AI) can be traced back to the 1950s, marked by phases of promise and disillusionment. However, at the turn of the millennium, advancements in big data, computational power, and sophisticated algorithms have reignited enthusiasm for the use of AI, particularly with the emergence of generative AI (GAI) in the last decade. This resurgence in interest has prompted discussions around the potential promises and pitfalls of AI, including concerns about job displacement. Yet, it’s crucial to recognize that the true competition may not lie between humans and machines, but between those who can harness the power of AI effectively and those who do not.
For teachers, the threat is not so much about AI replacing teachers, but whether they can harness the power of AI to enhance their teaching and students’ learning. Teachers, who are shaping the future generations, will need to embrace the reality of AI’s growing presence in society and develop a realistic vision of what AI can or cannot do. They need to equip themselves with the knowledge and skills to leverage AI in transformative ways to enhance teaching and learning experiences, while at the same time, be mindful of the ethical issues and limitations of AI. Moreover, teachers play a pivotal role in preparing students for an AI-driven future. Their attitudes towards AI and ethical considerations in its use can profoundly influence how well-prepared their students are for the challenges and opportunities ahead.
In essence, embracing AI in teacher education and professional development isn’t merely about dispelling the fear of job displacement, but rather, about empowering teachers to adapt and innovate in ways that enrich educational outcomes and equip students with the skills necessary for success in an AI-enhanced world.

How do you define the concept of human–AI synergy and what implications does it have for educators and learners?

Human–AI synergy, some call it human–AI collaboration or human–AI alliance, means clarifying the partnership roles of machines and humans so that this human–AI system can address complex challenges to the ultimate benefit of humans. This requires an understanding of what machines do best, for example, machine can crunch data, structured or unstructured, visible or embedded, within a short period of time, which can provide real-time feedback to the human. As well, we need to know which essential roles of human teachers and students that cannot be replaced.
“In the learning context, one critical consideration is that machines should never take away the critical aspects of learning.”

– Seng Chee, , on the role of machines in student learning

 

NIE Associate Professor Quek Choon Lang, for example, has explored the use of a virtual reality (VR) environment to provide feedback to users about their presentation skills. The VR system can generate feedback about the rate of speech, use of filler words, gestures, or even distribution of eye-gazing patterns on the audience. It also requires an understanding of what humans do best, for example, in showing care and concern, in meta-level thinking such as reflecting on the strategies used in a particular teaching situation.
In the learning context, one critical consideration is that machines should never take away the critical aspects of learning. For instance, if the objective of a lesson is to develop the students’ ability to brainstorm ideas, and to think laterally for more ideas, then even though generative AI is very good at doing this, it should not rob the students of the opportunity to develop this specific skill. Machines, however, can be used as a scaffold, by stimulating students’ creativity by suggesting one or two ideas as a starting point.
In a learning context, we need to differentiate between using GAI as a tool or as a scaffold. As a tool, it can be used by the students at all times. As a scaffold, we want to remove the use of GAI at some point so that the students can develop the ability to perform a task independently.

As AI continues to advance rapidly, what do you believe are the ethical considerations that educators should keep in mind when utilising AI technologies in their practice?

There are numerous ethical issues related to the use of AI for education. What I describe here is not exhaustive. First, data privacy and security issues. This includes practices like whether consent is sought from the students about the use of their data and whether these data are protected from unauthorised access. Second, the trustworthiness of the AI algorithm and system. The term “AI hallucination” was used to describe a phenomenon in which AI generate content that is not accurate, for example, by fabricating a citation of a research report that does not exist. Reducing such AI hallucinations is an active area of work for many researchers. Third, fairness and equity issues. Students should not be treated unfairly or discriminated against because of inherent bias in an AI system. For example, if an AI system developed in another cultural context was used to predict at-risk students, it might lead to biased predictions unless it has been finetuned and verified with the appropriate set of data.
Researchers such as Muhammad Ali Chaudhry, Multu Cukurova and Rose Luckin have developed an AI Transparency Framework and related AI transparency to other ethical AI dimensions. The Institute for Ethical Al in Education has also developed the Ethical Framework for AI in Education.

What advice would you give to educators who may feel apprehensive or uncertain about incorporating AI into their teaching practice?

Reiterating what I said earlier, the threat is not so much about AI replacing teachers, but whether teachers can harness the power of AI to enhance their teaching and students’ learning. The emergence of new technology has often caused anxiety, uncertainty, fear and frustration. My collaborator and NIE’s graduate Dr Wang Xinghua has also developed an AI Readiness Scale for teachers. This scale evaluates teachers’ readiness in the use of AI for education by assessing their perception on their knowledge, skills, and visions and whether they feel threatened by AI.
One way to overcome these feelings and emotions is to develop the basic foundational knowledge and skills of handling new technology and to have a realistic vision of what it can do, its limitations, and how we maintain the agency for human good.
Four Ways AI Technologies Can Benefit Teacher Education Programmes
There are a few ways that AI technologies can benefit teacher education programmes, that is depicted in the diagram below and illustrated with examples using generative AI.
diagram below and illustrated with examples using generative AI
A. One of the most common applications of generative AI is to support teachers in generating ideas or content for teaching. Teachers can consult ChatGPT to generate teaching ideas, lesson plans, quizzes and so on. Increasingly, there are other platforms that build on generative AI and can facilitate teaching. For example, Education Copilot contains tools and templates that can help teachers generate lesson plans, handouts, project outlines and so on. ClassPoint, a teaching tool with PowerPoint allows teachers to engage their students during the lessons through pre-planned quizzes, and it has an AI tool that can generate quizzes on the fly based on the content of a particular slide. Canva, a presentation tool, features a Magic Studio that can generate presentation slides, images or posters.
B. Teachers can also use generative AI to scaffold students’ learning. This requires some level of technical development. For example, using prompt designs, teachers can “instruct” ChatGPT to interact with students in some pre-conceived approaches. The Learning Sciences and Assessment Academic Group at NIE has developed the TeacherGAIA Chatbot that enables student self-directed learning and self-assessment. I am leading a project team supported by the Incentivising ICT-Use Innovations Grant (I3G) and we have developed several chatbots, including one called Care-Lyn that supports students’ knowledge building about sustainability issues. For example, during a field trip, a student intrigued with a specific plant, animal or object, can capture and upload an image to Care-Lyn, and it will generate relevant background information about the object and suggest related sustainability issues. Care-Lyn helps to support students’ idea generation in their exploration of the environment.
C. Teachers learning about AI or developing AI readiness. This means developing teachers’ knowledge about how AI works, a realistic vision of what it can do and what it cannot do, the ability to leverage AI for teaching and learning, and not being threatened by AI and paying the opportunity cost. Also critical is the understanding of ethical and transparency issues surrounding the use of AI for education, for example, whether the system has inherent biases, and whether the information generated is accurate.

Generative AI can also be used to develop learning companions for teachers. For example, we are developing a learning companion for teachers to learn about knowledge building, and to help teachers design a lesson with knowledge building. Using prompt design, we leverage the power of GPT and other Large Language Models to work as a guide to teachers. This system called Knowledge Building Learning Companion for Teachers (KB LCT), interacts with teachers in a conversational manner, allows teachers to ask questions about knowledge building principles, develop lessons based on knowledge building principles, and brainstorm potential obstacles and ways to overcome challenges when the teachers are ready to implement their lesson plans.
D. Generative AI can also support teachers in their design of a lesson. For example, KB LCT supports teachers in their design of knowledge building lessons. Unlike the use of generative AI to generate lesson plans (as explained in #A), KB LCT asks a teacher to describe a lesson design and provides feedback on the lesson design based on knowledge building principles. It also has the option to let the teacher know the common challenges the teacher might face with a knowledge building lesson, and the strategies that can be employed to address these challenges.

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