Artificial Intelligence (AI) in general, and generative AI models such as ChatGPT in particular, is increasingly pervasive, making significant contributions across various fields. At CERN, machine learning and data mining techniques are employed to uncover patterns and anomalies in data, leading to potential discoveries. AI also aids in particle track reconstruction and optimizing complex systems such as accelerator operations and detector calibration. As AI continues to enter our everyday lives, it becomes imperative for shaping future-ready citizens to address teaching and learning with and about AI with educational research and development projects. Such projects could be combination of the following aspects – depending on the pre-knowledge and interests of the applicants:
- Understanding students’ learner characteristics of AI: This topic addresses the identification and evaluation of prevalent learner characteristics that are relevant for an effective use of AI among high-school students, employing a design-based research approach to develop a lab workshop intervention, and measuring its impact through pre- and post-intervention assessments.
- Teaching and learning digital and AI Literacy: This topic addresses the importance of teaching digital and AI literacy to help students and educators critically assess and navigate AI-generated content. This includes understanding the potential for AI to spread misinformation and the need for individuals to develop defences against such misuse.
- Teacher Training to understand and to use AI effectively: This topic addresses the development and evaluation of physics teacher training courses to enable them to effectively incorporate this topic into teaching, highlighting the challenge of keeping high-quality teachers within the education system amidst technological advancements.
Each research project serves as a critical bridge between AI and physics education, empowering learners to not only comprehend and engage with AI but also contribute to its advancements.
The project aims also to bridge educational gaps by making the R&D learning materials of their work accessible to students regardless of their geographical location or socioeconomic background.
Training Value
The successful applicant will learn about different methods in Physics Education Research to design and evaluate virtual and interactive learning units. For the study a mixed methods approach is foreseen, which combines qualitative research methods (e.g., content analysis of interview transcripts) and quantitative research methods (e.g., data collection and analysis using pre-existing measurement instruments). Moreover, the successful applicant will get an insight into the international environment offering on-site and virtual learning activities for students.
Apply now! … by March 11th, 2024
All information about CERN’s Doctoral Student Programme can be found here:
https://jobs.smartrecruiters.com/CERN/743999948454873-doctoral-student-programme
Please mention the code “IR-ECO-TSP-AI” in your application.