Conference Agenda

In what ways do technology and new advances in AI, such as ChatGPT, support and/or hinder the democratic processes involved in enacting the curriculum at various levels? What is the impact on student learning and assessment? How does AI influence critical thinking and well-being? What does democratic and ethical educational technology look like?

This symposium will present two papers addressing the above-mentioned issues. The first paper will examine AI technology and the ethical dilemmas regarding the use of it in educational settings with Year 1 to 13 grade students. The second paper will explore how AI can be used to support formative assessment for both students and teachers.

Exploring AI is crucial for educational research because it has the potential not only to transform how we teach, but also how we learn throughout our lives. Whether AI and the development we see with ChatGPT is beneficial or not depends on how policy makers, researchers and practitioners work together to exploit the opportunities provided, ultimately leading to a more inclusive and effective education system for everyone.

The symposium will be organized as a combination of paper presentations, demonstrations of different technologies and discussions. AI will be used to demonstrate collective learning.

The theoretical framework for this paper is the concept of deep learning (Fullan et.al 2018) and a framework of AI in education (Wooldridge 2021, Gardner et. al 2021, Learnlab 2023). The main part of the pedagogical framework implies that schools and teachers plan for a period and work with a model with five phases: collective activation, exploration, deepening the knowledge, production, and dialogue.

In the collective activation phase, we use the student's curiosity and prior knowledge as a starting point, to create a sense of relevance, desire to learn and motivation for further work. In the exploration phase, we use the student's identity, interests, and motivation as a starting point from the first phase. Students deepen their knowledge through guidance and follow-up, gain new skills, an understanding of new concepts and professional methods. In the production phase, students work with developing and producing. Student products are created depending on what the student has focused on and how they want to work. They deliver and present their product in the form of a presentation, publication, video, podcast etc. as a basis for dialogue.

AI is revolutionizing current educational practices, and policy makers need to learn more about the threats and possibilities related to the use of AI. Contributors to this symposium are currently in dialogue with ministries and policy makers in several systems (for instance Lithuania, Wales, Scotland, Ireland, Norway, and Denmark) to investigate AI in education. The research questions in this paper will address the following:

1. Who decides the enactment of the curriculum in the AI era?

2. How can we make sure pedagogy drives technology and not the opposite?

3. How can we make sure AI does not make us overestimate our cognitive abilities, where technology is bypassing the human brain?

4. Can we make educational technology systems that are General Data Protection Rules (GDPR) and ethical compliant?

5. In what ways is AI a threat or an opportunity?

Some of the possible threats that will be examined are cheating on tests, the student does not learn to write, the teacher is replaced or underestimated, GDPR breach, Web Content Accessibility Guidelines (WCAG) violation, even more screen time, factual errors are overlooked, the student becomes less critical of sources, theft of content set in system, BIG-TECH takes over, and destruction of current assessment practices.

Some of the possible opportunities that will be examined are support in learning, relevant learning analysis, integration of AI on safe devices, WCAG and GDPR are good, more relevant screen use, students demonstrating competence, less administration for teachers, the learning of the future becomes possible today, documentation of curriculum without tests, students who are critical of and self-regulate their learning, and modelling the assessment practices of the future.

This paper is relevant for everyone in education and particularly for policy makers who have a great impact on whether or how AI can and should be used. The study is also relevant for continuing high quality teaching and learning, and for planning school improvement.

This paper is based on data from 50 schools using AI in formative assessment. The paper will include some of the preliminary findings.

The focus of inquiry is the following:

How can you assess competence and document it without having tests?

How to develop such a practice in a school/ in a school district?

How do students and teacher interact and exploit the use of AI in formative assessment?

How can professional learning communities be used in the process of obtaining quality in this work?

The model with five phases described in paper 1 is being used in these schools. Formative assessment, building on sociocultural theories and supporting the use of dynamic artifacts (Black & Wiliam 2009; Silseth & Gilje 2017; Russel 2020) – such as AI – is used to provide students and teachers with a systematic approach to learning and assessment. During the five phases, students will use self-assessment to reflect on their learning, they will have an overview of their products, they can revise and re-submit works, and AI will provide feedback on their work. The teacher saves time, but both teacher and peers will function as AI feedback moderators by evaluating the feedback provided by AI. At the end of the term, students select the products they would like to submit for final assessment.

Thus, the assessments are process-oriented, feedback is provided by AI and overseen by teachers and/or peers. Students collect, revise and select products.

An online questionnaire will be sent to the teachers at the 50 schools during fall 2023. Five of the 50 schools will be studied more systematically, using classroom observations and interviews with teachers. AI technology is used through participative observation where researchers and technologists work together.

The study will be conducted during fall 2023 and spring 2024.

This study has relevance for theory, practice, and policy. For theory, it relates AI to formative assessment through practical uses. For practice, teachers and students use and develop models of AI and formative assessment, and teachers practice formative assessment and the use of digital technologies. For policy, the study demonstrates collaboration between partners (school, municipality, directorate/ministry, teacher education).

The study is relevant for continuing professional development for teachers and school leaders, supporting teaching and learning by high quality AI, mentoring teachers and school leaders in the use of AI in formative assessment – both principles and procedures by experts in the field, engaging policy makers in large-scale use of AI in formative assessment.