In this episode, we explore the fascinating world of artificial intelligence (AI) and its impact on academic writing. Our guest, Sandie Elsom, Lecturer in Technology Education and AI enthusiast, discusses the challenges of distinguishing AI-generated text from human writing and explores the implications for academic integrity. We'll uncover the linguistic features that often differentiate AI-generated text and examine the effectiveness of current detection tools. Join us as we navigate the complexities of AI in education and discuss strategies for encouraging academic honesty in the age of AI.

Berber Sardinha, T. (2024). AI-generated vs human-authored texts: A multidimensional comparison. Applied Corpus Linguistics, 4(1), 100083-. https://doi.org/10.1016/j.acorp.2023.100083

Liang, W., Izzo, Z., Zhang, Y., Lepp, H., Cao, H., Zhao, X., Chen, L., Ye, H., Liu, S., Huang, Z., McFarland, D. A., & Zou, J. Y. (2024). Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews. arXiv.Org. https://doi.org/10.48550/arxiv.2403.07183

Muñoz-Ortiz, A., Gómez-Rodríguez, C., & Vilares, D. (2023). Contrasting Linguistic Patterns in Human and LLM-Generated Text. arXiv.Org. https://doi.org/10.48550/arxiv.2308.09067

Turnitin AI Technical Staff. (2023). Turnitin’s AI writing detection model architecture and testing protocol. Turnitin. https://www.turnitin.com/

Weber-Wulff, D., Anohina-Naumeca, A., Bjelobaba, S., Foltýnek, T., Guerrero-Dib, J., Popoola, O., Šigut, P., & Waddington, L. (2023). Testing of detection tools for AI-generated text. International Journal for Educational Integrity, 19(1), 26–39. https://doi.org/10.1007/s40979-023-00146-z

In this episode, we focus on the remarkable impact of online education in conflict zones. Our guest, David Falconer, is the Founder and Executive Director of Classrooms Without Walls (CWW), a Canadian organization that has been providing free online education to children living in these challenging environments. Since its inception in November 2022, CWW has launched three programs to support children in Ukraine, Myanmar, and Afghanistan.

If you are interested in volunteering with the CCW program, please contact David via email.

dfalconer@classroomswithoutwalls.ca

Today we're chatting on a topic that's crucial for anyone in the field of education research or anyone curious about quality survey construction and robust survey scale validation. We're talking about Rasch model analysis with Associate Professor Michael Carey. He uses a cake baking metaphor to explain how the Rasch model technique is applied to survey design and validation in plain English. He also refers to some recently published STEM research as examples of how a large 77-item preservice teacher TPACK self-audit instrument was developed and validated:

The development and validation of a self-audit survey instrument that evaluates preservice teachers’ confidence to use technologies to support student learning. Michael D. Carey, David A. Martin, and Natalie McMaster. 2024. International Journal of Research & Method in Education. https://doi.org/10.1080/1743727X.2024.2341714

Assessing primary school preservice teachers' confidence to apply their TPACK in specific categories of technologies using a self-audit survey. David A. Martin, Michael D. Carey, Natalie McMaster and Madeleine Clarkin. 2024. https://doi.org/10.1007/s13384-023-00669-x