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1. Tar AR: Bringing the past to life in place-based augmented reality science learning.

   Davis, M. (April 2021, MuseWeb 2021 Annual Meeting Professional Forum)

   null (Ed.)

   Informal science learning spaces such as museums have been exploring the potential of Augmented Reality (AR) as a means to connect visitors to places, times, or types of content that are otherwise inaccessible. This proposal reports on a design-based research project conducted at La Brea Tar Pits, an active paleontological dig site located within a city park in the heart of Los Angeles. The Natural History Museums of Los Angeles County and the University of Southern California engaged in a research practice partnership to enhance place-based science learning through the design and iterative testing of potential AR exhibits. Results from one implementation show that AR technology increased visitor interest in the park and positive emotions around science content. Significant learning gains and decreases in science misconceptions also occurred for participants. We also give guidance on developing scientifically accurate assets for AR experiences and leading users through a virtual narrative. This presentation offers insights into museum and university partnerships for promoting public understanding of science in informal spaces by leveraging place-based learning through technology-enhanced engagement. https://mw21.museweb.net/proposal/tar-ar-bringing-the-past-to-life-in-place-based-augmented-reality-science-learning/ 

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2. Unequal Impacts of Augmented Reality on Learning and Collaboration During Robot Programming with Peers

   https://doi.org/10.1145/3432944  

   Radu, Iulian; Hv, Vivek; Schneider, Bertrand (January 2021, Proceedings of the ACM on Human-Computer Interaction)

   null (Ed.)

   Augmented reality (AR) applications are growing in popularity in educational settings. While the effects of AR experiences on learning have been widely studied, there is relatively less research on understanding the impact of AR on the dynamics of co-located collaborative learning, specifically in the context of novices programming robots. Educational robotics are a powerful learning context because they engage students with problem solving, critical thinking, STEM (Science, Technology, Engineering, Mathematics) concepts, and collaboration skills. However, such collaborations can suffer due to students having unequal access to resources or dominant peers. In this research we investigate how augmented reality impacts learning and collaboration while peers engage in robot programming activities. We use a mixed methods approach to measure how participants are learning, manipulating resources, and engaging in problem solving activities with peers. We investigate how these behaviors are impacted by the presence of augmented reality visualizations, and by participants? proximity to resources. We find that augmented reality improved overall group learning and collaboration. Detailed analysis shows that AR strongly helps one participant more than the other, by improving their ability to learn and contribute while remaining engaged with the robot. Furthermore, augmented reality helps both participants maintain a common ground and balance contributions during problem solving activities. We discuss the implications of these results for designing AR and non-AR collaborative interfaces. 

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3. TAR AR: RESEARCHING THE EFFECTIVENESS OF AUGMENTED REALITY ACTIVITIES FOR VISITOR LEARNING AT LA BREA TAR PITS

   DeNeve Weeks, Danaan (January 2022, SOCIETY OF VERTEBRATE PALEONTOLOGY)

   Digital technologies have the potential to support informal STEM learning by fostering immersion, interactivity, and engagement with scientific material. AR in particular can overlay digital information on real-world objects and places, revealing and allowing interaction with things the public would normally not see. This is particularly valuable for historical sciences like geology, archaeology, and paleontology, where abstract concepts and unusual/restricted access settings (such as geological or fossil sites, and laboratories) spark curiosity, but also create challenges for fostering learning. However, AR as a tool is still in its nascent stages. Current applications are as likely to be “fun gimmicks” as they are to produce actual learning gains. At La Brea Tar Pits (California, USA) we are researching what makes paleontology learning AR good. We have conducted two ARlearning experiences to test whether AR is better at reducing scientific misconceptions relative to traditional static museum signage and test the effectiveness of several modes of AR delivery (VR headset vs handheld, high vs low interactivity). The first experience taught participants about Pleistocene climate, flora, and fauna. We found that handheld high interactivity AR is preferred, and while no AR condition had greater learning outcomes than comparable signage, the AR experience generated greater curiosity. The second experience (currently underway) invites participants to explore how organisms become entrapped in the asphalt seeps in a life-size AR scene. In addition to both of these experiences, we have created versions of each of the extinct Pleistocene animals represented in the AR experiences that can be interacted with Snapchat, Instagram, or native AR on a user’s phone, that is immediately suitable for classroom and off-site use. Funding Sources National Science Foundation AISL grant 

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4. Investigating the Carryover Effects of Calibration of Size Perception in Augmented Reality to the Real World

   https://doi.org/10.1109/ISMAR62088.2024.00096  

   Chiu, Chao-Kuo; Chuang, Jung-Hong; Pagano, Christopher C; Babu, Sabarish V (October 2024, IEEE)

   Many AR applications require users to perceive, estimate and calibrate to the size of objects presented in the scene. Distortions in size perception in AR could potentially influence the effectiveness of skills transferred from the AR to the real world. We investigated the after-effects or carry-over effects of calibration of size perception in AR to the real world (RW), by providing feedback and an opportunity for participants to correct their judgments in AR. In an empirical evaluation, we employed a three-phase experiment design. In the pretest phase, participants made size estimations to target objects concurrently using both verbal reports and physical judgment in RW as a baseline. Then, they estimated the size of targets, and then were provided with feedback and subsequently corrected their judgments in a calibration phase. Followed by which, participants made size estimates to target objects in the real world. Our findings revealed that the carryover effects of calibration successfully transferred from AR to RW in both verbal reports and physical judgment methods. 

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5. Calibrated Passability Perception in Virtual Reality Transfers to Augmented Reality

   https://doi.org/10.1145/3613450  

   Gagnon, Holly; Stefanucci, Jeanine; Creem-Regehr, Sarah; Bodenheimer, Bobby (October 2023, ACM Transactions on Applied Perception)

   As applications for virtual reality (VR) and augmented reality (AR) technology increase, it will be important to understand how users perceive their action capabilities in virtual environments. Feedback about actions may help to calibrate perception for action opportunities (affordances) so that action judgments in VR and AR mirror actors’ real abilities. Previous work indicates that walking through a virtual doorway while wielding an object can calibrate the perception of one’s passability through feedback from collisions. In the current study, we aimed to replicate this calibration through feedback using a different paradigm in VR while also testing whether this calibration transfers to AR. Participants held a pole at 45°and made passability judgments in AR (pretest phase). Then, they made passability judgments in VR and received feedback on those judgments by walking through a virtual doorway while holding the pole (calibration phase). Participants then returned to AR to make posttest passability judgments. Results indicate that feedback calibrated participants’ judgments in VR. Moreover, this calibration transferred to the AR environment. In other words, after experiencing feedback in VR, passability judgments in VR and in AR became closer to an actor’s actual ability, which could make training applications in these technologies more effective. 

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