The ASE is delighted to be hosting its Annual Conference, generously sponsored by AQA, at the University of Nottingham from 9th to 11th January 2025. International sessions are incorporated throughout the event’s 3 days and we will have a great exhibition with lots of exclusive Conference offers. Post-16 focus-day and for those involved in leading and delivering professional development, the Teacher Developers’ Group programme is Thursday. Friday is the dedicated Technicians day, kindly sponsored by Philip Harris, and Early Career Teacher day. Sessions for both Primary and 11-19 are threaded throughout all 3 days with a focus on Research on Saturday.
Book your tickets now at https://ase2025AnnConf.eventbrite.co.uk - and remember, if you are an ASE member you will benefit from hugely discounted prices! Check out our membership here - it’s free for Early Career Teachers and only £25 for Technicians!
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The session delves into the transformative potential of AI in creating a more dynamic and responsive educational environment. The session focuses on practical applications and tangible outcomes for educators, including sharing ideas & strategies from practising teachers and providing valuable insights and practical takeaways for the delegates.
In traditional classrooms, responsiveness to student needs is paramount. Traditional teaching methods, while effective in many respects, often struggle to address the diverse and evolving requirements of individual students. AI technologies offer innovative solutions to bridge this gap, enabling educators to tailor their approaches to better meet the needs of each learner.
Delegates in this exploration of AI technologies for responsive teaching will gain: 1. Understanding of AI Applications: A comprehensive understanding of how AI technologies can be applied to create more responsive and effective teaching environments. 2. Practical Implementation Strategies: Strategies for integrating AI tools into their teaching practices to personalise learning and enhance student engagement. 3. Insight into Data Utilisation: Knowledge of how to leverage data-driven insights to inform instructional decisions and improve student outcomes.
The proposed structure of the talk is detailed below:
>Overview of the Topic - Explain the importance of responsive teaching and the role of AI in education
>Understanding AI Technologies in Education *What is AI? Define AI and provide examples relevant to education. *Key AI Technologies Used in Education: Machine Learning Natural Language Processing Intelligent Tutoring Systems Data Analytics Provide real-world examples and case studies
>Benefits of AI for Responsive Teaching *Personalised Learning Experiences - Discuss how AI can tailor educational content to individual students. *Real-Time Feedback and Assessment- Explain the benefits of immediate feedback and adaptive assessments. *Enhanced Student Engagement - Explore AI tools that make learning more engaging. *Efficient Classroom Management- Describe how AI can automate administrative tasks and support classroom management.
>Practical Implementation Strategies *Integrating AI into Teaching Practices- Step-by-step guide on incorporating AI tools in the classroom. *Case Studies and Success Stories - Share specific examples of schools & teachers successfully using AI for responsive teaching.
>Challenges and Considerations *Technical and Ethical Challenges - Discuss potential challenges such as data privacy, bias in AI, and technical barriers. *Future Trends and Developments -Highlight emerging trends and the future of AI in education.
>Q&A and Interactive Discussion
>Conclusion- Summary of Key Points /Recap the main takeaways from the talk. *Call to Action *Encourage delegates to explore and experiment with AI tools in their teaching practices.
Co-founder & Director of sAInaptic, sAInaptic Limited
sAInaptic is an AI-driven web app for GCSE science that automatically evaluates free-text answers to open-ended questions, providing instant feedback. The feedback includes a predictive score and qualitative, teacher-like information on correct and missed concepts. sAInaptic’s auto-marking... Read More →
sAInaptic is an AI-driven web app for GCSE science that automatically evaluates free-text answers to open-ended questions, providing instant feedback. The feedback includes a predictive score and qualitative, teacher-like information on correct and missed concepts. sAInaptic’s auto-marking... Read More →
Friday January 10, 2025 08:45 - 09:35 GMT
Physics C29
Science Education has always been bound up with technology. Advances in technology mean that we need to re-think not only how we conduct education but also what education is for.
The new generative AI challenges many of the current goals of education. I argue, with examples, that this should return us to valuing the importance of dialogue more. Dialogues supported by AI can help teach students how to think better about science and help induct them into participation in the long-term global dialogue of science.
In recent years, education in England has seen a move towards ‘evidenced-based’ practice with the Department for Education privileging ideas and practice drawn from cognitive science.
An area that has gained significant interest is that of ‘retrieval practice’. On the face of it, retrieval practice appears to be an intuitive and easy to implement strategy for a teacher, as it requires students to retrieve (remember) information from their long-term memory, rather than passively restudy it. The act of deliberately retrieving information then improves the retention and later retrieval of that information, which is often referred to as the ‘testing effect’.
Despite there being strong evidence that retrieval practice supports learning, there are a number of issues that teachers should be aware of when translating the research into effective classroom practice.
This session aims to share some of the issues that retrieval practice research raises for teachers and discusses some key consideration for teachers who already use or want to use retrieval-based strategies in their practice. Drawing on findings from two recent research projects, the concept of retrieval-based learning will be outlined, along with key ideas to support the development of effective and efficient strategies.
The session aims to support secondary school science teachers in the delivery of climate change education through evidence-based teaching materials. The climate change teaching materials were developed through a rigorous and robust scientific process based on the latest climate change evidence.
Every day, a vast quantity of research on climate change is produced. However, the majority of this research is directed primarily towards academic and scientific audiences, leaving a gap in its accessibility to the general public and, crucially, teachers. The specialised focus of current approaches means that the dissemination of climate change research, especially within the social sciences, is as rapid as needed; however, it does not succeed in enabling wider communities to gain an understanding, thus negatively impacting climate action.
Compounding the problem, there exists misinformation or ‘fake evidence’ about climate change that further prevents public understanding. The vast body of rigorous climate change research, combined with its complexity, means that this globally significant topic can be challenging to understand and decipher for those outside the scientific community.
It is imperative that all teachers are informed and kept up to date with the latest verified evidence on climate change to ensure that future generations are equipped with accurate knowledge and are empowered to act. To assist secondary school science teachers in teaching climate change, a set of evidence-based materials was created, incorporating the most recent evidence on climate change.
