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1. Analogies in Geology Textbooks May Create Illusions of Understanding

   Griffin, T D; Jaeger, A; LaDue, N; Adams, L; Wiley, J (July 2024, EasyChair.org)

   Although analogical examples can support better understanding of new science concepts, when analogies are included superficially and without explanation they may have unintended negative effects. In this study, simple inclusion of analogies greatly increased the perceived familiarity and predicted understanding of geology concepts. Higher judgements of familiarity and predicted understanding could produce illusions of understanding when reading texts about these concepts. 

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2. Co-design of analogical and embodied representations with children for child-centered AI learning experiences

   https://doi.org/10.1016/j.ijhcs.2025.103462  

   Zhou, Xiaofei; Gong, Yunfan; Zhou, Yushan; Jiang, Yufei; Bai, Zhen (May 2025, International Journal of Human-Computer Studies)

   AI recommendations shape our daily decisions and our young generation is no exception. The convenience of navigating personalized content comes with the notorious ‘‘filter bubble’’ effect, which can reduce exposure to diverse options and opinions. Children are particularly vulnerable to this due to their limited AI literacy and critical thinking skills. In this study, we explore how to engage children as co-designers to create child-centered experiences for learning AI concepts related to the filter bubble. Leveraging embodied and analogical learning theories, we co-designed an Augmented Reality (AR) application, BeeTrap, with children from underrepresented backgrounds in STEM. BeeTrap not only raises awareness of filter bubbles but also empowers children to understand recommendation system mechanisms. Our contributions include (1) insights into child-centered AI learning using embodied metaphors and analogies as educational representations of AI concepts; and (2) implications for enhancing children’s understanding of AI concepts through co-design processes. 

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3. Understanding the practices, perceptions, and (dis)trust of generative AI among instructors: A mixed-methods study in the U.S. higher education

   https://doi.org/10.1016/j.caeai.2025.100383  

   Lyu, Wenhan; Zhang, Shuang; Chung, Tingting; Sun, Yifan; Zhang, Yixuan (June 2025, Computers and Education: Artificial Intelligence)

   Generative AI (GenAI) has brought opportunities and challenges for higher education as it integrates into teaching and learning environments. As instructors navigate this new landscape, understanding their engagement with and attitudes toward GenAI is crucial. We surveyed 178 instructors from a single U.S. university to examine their current practices, perceptions, trust, and distrust of GenAI in higher education in March 2024. While most surveyed instructors reported moderate to high familiarity with GenAI-related concepts, their actual use of GenAI tools for direct instructional tasks remained limited. Our quantitative results show that trust and distrust in GenAI are related yet distinct; high trust does not necessarily imply low distrust, and vice versa. We also found significant differences in surveyed instructors' familiarity with GenAI across different trust and distrust groups. Our qualitative results show nuanced manifestations of trust and distrust among surveyed instructors and various approaches to support calibrated trust in GenAI. We discuss practical implications focused on (dis)trust calibration among instructors. 

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4. An Exploratory Study of Programmers' Analogical Reasoning and Software History Usage During Code Re-Purposing

   https://doi.org/10.1145/3641822.3641864  

   Allen, John; Kelleher, Caitlin (April 2024, ACM)

   Background: Software development relies on collaborative problem-solving. Understanding previously addressed problems in software is crucial for developers to identify and repurpose functionalities for new problem-solving contexts. Objective: We explore the barriers programmers encounter during code repurposing and investigate how access to historical context about the original developer's goals may affect this process. Method: We present an exploratory study of 16 programmers who completed two code repurposing tasks in different code bases. Participants completed these tasks both with and without access to the historical information of the original developer's goals. We explore how programmers use analogical reasoning to identify and apply existing software artifacts to new goals. Results: We show that programmers often failed to notice analogies, made false analogies, and underestimated the value of reuse. Even when useful analogies were made, programmers struggled to find the relevant code. We also describe the patterns of how participants utilized code histories. Conclusion: We highlight the barriers programmers face in noticing and applying analogies during code reuse. We suggest design recommendations for future tools to allow lightweight evaluation of code to help programmers identify reuse opportunities. 

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5. Music-Evoked Thoughts: Genre and Emotional Expression of Music Impact Concurrent Imaginings

   https://doi.org/10.1525/mp.2024.42.1.3  

   Jakubowski, Kelly; Margulis, Elizabeth Hellmuth; Taruffi, Liila (September 2024, Music Perception: An Interdisciplinary Journal)

   Music listening can evoke a range of extra-musical thoughts, from colors and smells to autobiographical memories and fictional stories. We investigated music-evoked thoughts as an overarching category, to examine how the music’s genre and emotional expression, as well as familiarity with the style and liking of individual excerpts, predicted the occurrence, type, novelty, and valence of thoughts. We selected 24 unfamiliar, instrumental music excerpts evenly distributed across three genres (classical, electronic, pop/rock) and two levels of expressed valence (positive, negative) and arousal (high, low). UK participants (N = 148, Mage = 28.68) heard these 30-second excerpts, described any thoughts that had occurred while listening, and rated various features of the thoughts and music. The occurrence and type of thoughts varied across genres, with classical and electronic excerpts evoking more thoughts than pop/rock excerpts. Classical excerpts evoked more music-related thoughts, fictional stories, and media-related memories, while electronic music evoked more abstract visual images than the other genres. Positively valenced music and more liked excerpts elicited more positive thought content. Liking and familiarity with a style also increased thought occurrence, while familiarity decreased the novelty of thought content. These findings have key implications for understanding how music impacts imagination and creative processes. 

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