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1. On effects that do occur versus effects that can be made to occur

   https://doi.org/10.3389/frsps.2023.1193349  

   Brauer, Markus; Kennedy, Kevin R (August 2023, Frontiers in Social Psychology)

   Following Douglas Mook's lead we distinguish between research on “effects that can be made to occur” and research on “effects that do occur” and argue that both can contribute to the advancement of knowledge. We further suggest that current social psychological research focuses too much on the former type of effects. Given the discipline's emphasis on innovation, many published effects are shown to exist under very specific circumstances, i.e., when numerous moderator variables are set at a particular level. One often does not know, however, how frequently these circumstances exist for people in the real world. Studies on effects that can be made to occur are thus an incomplete test of most theories about human cognition and behavior. Using concrete examples, this article discusses the shortcomings of a field that limits itself to identifying effects that might—or might not—be relevant. We argue that it is just as much a scientific contribution to show that a given effect actually does occur as it is to provide initial evidence for a new effect that could turn out to be important. The article ends with a series of suggestions for researchers who want to increase the theoretical and practical relevance of their research. 

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2. How Do I Do That? Synthesizing 3D Hand Motion and Contacts for Everyday Interactions

   https://doi.org/10.1109/CVPR52734.2025.00659  

   Prakash, Aditya; Lundell, Benjamin; Andreychuk, Dmitry; Forsyth, David; Gupta, Saurabh; Sawhney, Harpreet (June 2025, IEEE)

   We tackle the novel problem of predicting 3D hand motion and contact maps (or Interaction Trajectories) given a single RGB view, action text, and a 3D contact point on the object as input. Our approach consists of (1) Interaction Codebook: a VQVAE model to learn a latent codebook of hand poses and contact points, effectively tokenizing interaction trajectories, (2) Interaction Predictor: a transformer-decoder module to predict the interaction trajectory from test time inputs by using an indexer module to retrieve a latent affordance from the learned codebook. To train our model, we develop a data engine that extracts 3D hand poses and contact trajectories from the diverse HoloAssist dataset. We evaluate our model on a benchmark that is 2.5-10X larger than existing works, in terms of diversity of objects and interactions observed, and test for generalization of the model across object categories, action categories, tasks, and scenes. Experimental results show the effectiveness of our approach over transformer & diffusion baselines across all settings. 

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3. Why Do They Do What They Do? A Model That Describes and Connects the Drivers of Learning Assistant Facilitation Practices

   https://doi.org/10.1002/sce.70048  

   Maggiore, Nicolette M; Karch, Jessica M; Dini, Vesal; Caspari‐Gnann, Ira (December 2025, Science Education)

   Learning assistants (LAs) help implement evidence‐based teaching in undergraduate active‐learning courses and support student learning through their facilitation. Here, we present a drivers‐of‐LA‐action model with empirical evidence that connects across the macro level of LA‐supported course design and the micro level of LA‐student interactions to understand how course activity system design drives LA goals, actions, and student in‐the‐moment learning in interactions. Our study is guided by sociocultural theory, specifically: cultural historical activity theory, which helps us understand how different course components work together; and theory on authoritativeness and dialogicity, which helps us understand the centering of one canonical perspective versus multiple student perspectives. Our embedded multiple case study includes narratives of LA facilitation based on recordings of LA‐student interactions from 37 different LAs in 10 chemistry and physics courses and semistructured stimulated recall interviews with professors as main data sources. Our findings show that course design that supports targeting the canon directly versus through scientific knowledge‐building drives LA purposes to be either uni‐ or multi‐directional, LA facilitation to be authoritative or dialogic, and student in‐the‐moment learning to be LA‐ or student‐centered. We discuss the use of the drivers‐of‐LA‐action model in practice for intentional course design that integrates LAs to meet student learning goals. 

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4. Do You Know that there are Fungi in the Ocean?

   https://doi.org/10.3389/frym.2025.1472709  

   Arroyo, Jennifer; Stajich, Jason E; Ettinger, Cassie L (June 2025, Frontiers for Young Minds)

   Did you know that fungi, like mushrooms and molds, are super important for our planet? Fungi can form critical relationships with other organisms. For example, many plants rely on fungi to help them grow and thrive. However, fungi are not always friendly and sometimes they can hurt plants by causing disease. Did you also know that there are fungi in the ocean? While you might not be able to see these fungi when you go to the beach (because they can only be seen with a microscope), they are found everywhere in the ocean. Marine fungi are pretty cool, but we do not know a lot about them yet or what roles they play in the ocean. Scientists are starting to learn more about how marine fungi help the ocean and keep our planet healthy. This article will explore the amazing world of marine fungi! 

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5. Do students think that objects have a true definite position?

   https://doi.org/10.1103/PhysRevPhysEducRes.20.010154  

   Stump, Emily M; Hughes, Mark; Holmes, N G; Passante, Gina (June 2024, Physical Review Physics Education Research)

   Previous research on student thinking about experimental measurement and uncertainty has primarily focused on students’ procedural reasoning: Given some data, what should students calculate or do next? This approach, however, cannot tell us what beliefs or conceptual understanding leads to students’ procedural decisions. To explore this relationship, we first need to understand the range of students’ beliefs and conceptual understanding of measurement. In this work, we explored students’ philosophical beliefs about the existence of a true value in experimental measurement. We distributed a survey to students from 12 universities in which we presented two viewpoints on the existence of a true definite position resulting from an experiment, asking participants to indicate which view they agreed with more and asking them to explain their choice. We found that participants, both students and experts, varied in their beliefs about the existence of a true definite position and discussed a range of concepts related to quantum mechanics and the experimental process to explain their answers, regardless of whether or not they agreed with the existence of a true value. From these results, we postulate that students who exhibit similar procedural reasoning may hold widely varying philosophical views about measurement. We recommend that future work investigates this potential relationship and whether and how instruction should attend to these philosophical views in addition to students’ procedural decisions. 

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