Professional Growth
Generating Difference as a Two-way Conversation: What Are We Told and What Are We Saying When We Create Non-normative Bodies Through Generative AI Image Models?
Paper Presentation in a Themed Session
Aisha Sobey
Generative AI (genAI) image models are becoming increasingly popular and are being embedded within common design platforms such as Adobe and Canva. Previously, AI has been likened to a mirror (Vallor, 2024) and a “disclosing agent for assumptions about humanness” (Suchman, 2019). Due to the way genAI models take large quantities of existing images, created within everyday social lives online, and distil the most probable outcome to a prompt; their outputs can be considered social imaginary. This agglomerative property has also been shown to exacerbate and propagate biases from within the data sets into the pictures that are produced. Building on Benjamin’s (2019) assessment of Dall-E’s prejudiced production of race, this paper seeks to understand how fat bodies are presented by nine different, free-to-use genAI image models in response to a series of text prompts. Using critical visual analysis of the produced images, the first question posed is: what is communicated about fatness? Through auditing, the common features of fatness were found to be high numbers of topless, similarly-featured white men were found. A deeper analysis then highlights the more insidious messaging embedded in portrayals of fatness within lighting, facial expression and background. Secondly, the talk reflects on the complexity of co-creating images with genAI. When the outputs can feel reductive, how can one see themselves, and do we want to? By highlighting the challenging and exploitative genAI ecosystem and the social function images play, the paper concludes by unpacking the tension within the social dialogue created by genAI images.
AI in Education: Addressing the Growing Divide and Ensuring Equity in the Digital Age View Digital Media
Paper Presentation in a Themed Session
Angela Thompson,
Mohammed Abdul Salam,
Richard Manprisio
This research reviews the design and effects of a professional development workshop intended to persuade university faculty to try using AI as a teaching and learning resource by employing research-based pedagogical practices. We designed, promoted, and then held the workshop in Spring 2024. The purpose of the workshop was to demonstrate ways faculty can use AI to enhance teaching and learning instead of being concerned about students cheating with AI. We then asked participants to complete a survey and optionally volunteer to be observed teaching with AI after the workshop. One major finding is that AI is being employed inequitably in classrooms, resulting in only some students and some teachers benefitting from this valuable resource. The other finding is that the timing of professional development can be critical in persuading teachers to modify their practice. This new source of equity needs to be recognized and addressed to help prevent a further divide in the distribution of educational resources.
Optimising Human Engagement with AI: A Critical Realist Exploration of Heuristics, Semiotics, and Sense of Belonging View Digital Media
Paper Presentation in a Themed Session
Sarah Mc Tighe
Humans have long sought comfort in systems, objects, or individuals perceived as "experts," often as a response to the inherent uncertainty of decision-making processes. This tendency becomes increasingly evident as we enter the third golden age of Artificial Intelligence (AI), where the boundaries between human expertise and machine learning, blur significantly. One of the fundamental questions driving this research is: Why do humans seek out expertise, and to what extent does this expertise truly exist in AI systems, or is it merely a reflection of our desire for certainty? The interplay between human cognition and Artificial Intelligence (AI) is transforming societal structures and landscapes. This research embarks on a critical realist exploration of how heuristics and semiotics, key cognitive frameworks, shape trust, usability, and engagement with AI systems. By unravelling the cognitive shortcuts individuals use to interact with AI and the influence of visual and symbolic design, this study aims to redefine the human-AI relationship.At the core of the investigation lies the question of how to foster a genuine sense of belonging in AI-driven educational environments. As adaptive learning systems become ubiquitous, this research probes the challenges and opportunities posed by their integration. With a mixed-methods approach combining quantitative metrics and qualitative insights, the study examines user behaviours and perceptions over time. Feedback from educators and students enriches the findings, ensuring practical relevance. By addressing biases in AI systems and exploring the cultural nuances of interface design, the research sets a new standard for inclusive, equitable AI engagement.
The Effectiveness of AI in Learning French Grammar
Paper Presentation in a Themed Session
Wen Hui Chang
This study investigates Kahoot! as a digital game-based learning in second-language classrooms to resolve students’ lack of motivation in learning French verb conjugations. The goal is to enhance students’ understanding and proficiency in French verb conjugations, thereby improving learning outcomes. Due to the limited research on teaching French in Taiwan, this study is a valuable contribution to filling the gap. First-grade students majoring in French in the Department of Applied Linguistics and Language Studies participated in the study. The researcher used pretest, mid-test, and post-test design for one semester. Traditional teaching methods are used between the pretest and mid-test, while digital game-based teaching methods will be used between the mid-test and post-test. The study is based on collecting and analyzing data through quantitative research, focusing on gathered from pretest, mid-test, and post-test. The findings of this research will contribute to understanding the effectiveness of Kahoot! in improving learning outcomes and motivating Taiwanese students to learn French verb conjugations.
