There’s a lot out there from folks trying and suggesting and selling ways for teachers to put their fingers in the dike holding back the allegedly inevitable AI tide.

"Assessment and feedback inspires and assures student learning""Formative, instant feedback, repeatable, and evaluative judgement - that's FIRE"In this 36th episode of The Opposite of Cheating Podcast, Pro Vice-Chancellor of Quality & Integrity at Western Sydney University Cath Ellis discusses the evolution of educational integrity in Australia, the role of regulatory frameworks like TEQSA, and how scandal and data paved the way for institutional change. She introduces Western Sydney's Inspire and Assure (IA) Approach to assessment, which is their refinement of the “two-lane” model talked about by Danny Liu in Episode 28, to center faculty on the importance of inspiring learning and assuring assessment validity. Cath shares practical strategies for identifying “enrolled persons” who may not be doing their own work, like oral assessments, and the need to build student capacity while holding institutions accountable for fairness and transparency. She also unpacks the matrix model for assessment reform and…

When teachers know their students are gaming the system and students know their teachers know, the relationship frays

AI-text-detectors can be evaded using simple tricks in academic writing, as repeatedly shown by folks like Dr Mike Perkins and Dr Mark A. Bassett. Advice for how to do this is abundant on YouTube, in videos aimed at students, viewed millions of times. Some videos are about how to ‘cheat’, but others have more positive titles like ‘how to study with AI’. Is there any point trying to stop students using AI to write essays? Or even any value to using asynchronous written essays as summative assessments?   New paper from the great Tomas Foltynek and some bloke called Phil Newton   https://rdcu.be/eKCko

Nobody Learns, Nobody Gains

When it comes to AI in education, I've been seeing more and more conversations pop up about how we can prevent cheating, or even if that's possible anymore. But what if, in our focus on anti-cheating practices, we're missing something deeper? Something that has been on my mind even more than the iss

Generative artificial intelligence provides both opportunities and challenges for higher education. Existing literature has not properly investigated how this technology would impact assessment in higher education. This scoping review took a forward-thinking approach to investigate how generative artificial intelligence transforms assessment in higher education. We used the PRISMA extension for scoping reviews to select articles for review and report the results. In the screening, we retrieved 969 articles and selected 32 empirical studies for analysis. Most of the articles were published in 2023. We used three levels—students, teachers, and institutions—to analyses the articles. Our results suggested that assessment should be transformed to cultivate students’ self-regulated learning skills, responsible learning, and integrity. To successfully transform assessment in higher education, the review suggested that (i) teacher professional development activities for assessment, AI, and digital literacy should be provided, (ii) teachers’ beliefs about human and AI assessment should be strengthened, and (iii) teachers should be innovative and holistic in their teaching to reflect the assessment transformation. Educational institutions are recommended to review and rethink their assessment policies, as well as provide more inter-disciplinary programs and teaching.

With the release of ChatGPT in November 2022, the field of higher education rapidly became aware that generative AI can complete or assist in many of the kinds of tasks traditionally used for assessment. This has come as a shock, on the heels of the shock of the pandemic. How should assessment practices change? Should we teach about generative AI or use it pedagogically? If so, how? Here, we propose that a set of open educational practices, inspired by both the Open Educational Resources (OER) movement and digital collaboration practices popularized in the pandemic, can help educators cope and perhaps thrive in an era of rapidly evolving AI. These practices include turning toward online communities that cross institutional and disciplinary boundaries. Social media, listservs, groups, and public annotation can be spaces for educators to share early, rough ideas and practices and reflect on these as we explore emergent responses to AI. These communities can facilitate crowdsourced curation of articles and learning materials. Licensing such resources for reuse and adaptation allows us to build on what others have done and update resources. Collaborating with students allows emergent, student-centered, and student-guided approaches as we learn together about AI and contribute to societal discussions about its future. We suggest approaching all these modes of response to AI as provisional and subject to reflection and revision with respect to core values and educational philosophies. In this way, we can be quicker and more agile even as the technology continues to change. We give examples of these practices from the Spring of 2023 and call for recognition of their value and for material support for them going forward. These open practices can help us collaborate across institutions, countries, and established power dynamics to enable a richer, more justly distributed emerging response to AI.