Abstract: This study explores the integration of Augmented Reality (AR) and collaborative activities to leverage abstract Computational Thinking (CT) concepts accessible to young students. The instructional design follows Plan, Act, Reflect (PAR) cycles that consist of three types of collaborative activities: Hands-on, AR-integrated, and self-directed robot programming activities. Findings highlight the importance of scaffolding in helping young learners, particularly those with low spatial ability, grasp directional concepts. Role-based collaboration proved effective in fostering engagement and problem-solving skills, though challenges emerged in the AR-based activity. This study contributes to immersive learning by demonstrating practical application of AR technology into K-12 classrooms.
more »
« less
Unequal Impacts of Augmented Reality on Learning and Collaboration During Robot Programming with Peers
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.
more »
« less
- Award ID(s):
- 1917716
- PAR ID:
- 10276293
- Date Published:
- Journal Name:
- Proceedings of the ACM on Human-Computer Interaction
- Volume:
- 4
- Issue:
- CSCW3
- ISSN:
- 2573-0142
- Page Range / eLocation ID:
- 1 to 23
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
This research aims to explore the prediction of student learning outcomes in Augmented Reality (AR) educational settings, focusing on engineering education, by analyzing pupil dilation and problem-solving time as key indicators. In this research, we have created an innovative AR learning platform through the incorporation of eye-tracking technology into the Microsoft HoloLens 2. This enhanced learning platform enables the collection of data on pupil dilation and problem-solving duration as students engage in AR-based learning activities. In this study, we hypothesize that pupil dilation and problem-solving time could be significant predictors of student performance in the AR learning environment. The results of our study suggest that problem-solving time may be a critical factor in predicting student learning success for materials involving procedural knowledge at low difficulty levels. Additionally, both pupil dilation and problem-solving time are predictive indicators of student learning outcomes when dealing with predominantly procedural knowledge at high difficulty levels.more » « less
-
Emerging technologies such as Augmented Reality (AR), have the potential to radically transform education by making challenging concepts visible and accessible to novices. In this project, we have designed a Hololens-based system in which collaborators are exposed to an unstructured learning activity in which they learned about the invisible physics involved in audio speakers. They learned topics ranging from spatial knowledge, such as shape of magnetic fields, to abstract conceptual knowledge, such as relationships between electricity and magnetism. We compared participants' learning, attitudes and collaboration with a tangible interface through multiple experimental conditions containing varying layers of AR information. We found that educational AR representations were beneficial for learning specific knowledge and increasing participants' self-efficacy (i.e., their ability to learn concepts in physics). However, we also found that participants in conditions that did not contain AR educational content, learned some concepts better than other groups and became more curious about physics. We discuss learning and collaboration differences, as well as benefits and detriments of implementing augmented reality for unstructured learning activities.more » « less
-
The field of end-user robot programming seeks to develop methods that empower non-expert programmers to task and modify robot operations. In doing so, researchers may enhance robot flexibility and broaden the scope of robot deployments into the real world. We introduce PRogramAR (Programming Robots using Augmented Reality), a novel end-user robot programming system that combines the intuitive visual feedback of augmented reality (AR) with the simplistic and responsive paradigm of trigger-action programming (TAP) to facilitate human-robot collaboration. Through PRogramAR, users are able to rapidly author task rules and desired reactive robot behaviors, while specifying task constraints and observing program feedback contextualized directly in the real world. PRogramAR provides feedback by simulating the robot’s intended behavior and providing instant evaluation of TAP rule executability to help end users better understand and debug their programs during development. In a system validation, 17 end users ranging from ages 18 to 83 used PRogramAR to program a robot to assist them in completing three collaborative tasks. Our results demonstrate how merging the benefits of AR and TAP using elements from prior robot programming research into a single novel system can successfully enhance the robot programming process for non-expert users.more » « less
-
Peer assessment, as a form of collaborative learning, can engage students in active learning and improve their learning gains. However, current teaching platforms and programming environments provide little support to integrate peer assessment for in-class programming exercises. We identified challenges in conducting such exercises and adopting peer assessment through formative interviews with instructors of introductory programming courses. To address these challenges, we introduce PuzzleMe, a tool to help Computer Science instructors to conduct engaging in-class programming exercises. PuzzleMe leverages peer assessment to support a collaboration model where students provide timely feedback on their peers' work. We propose two assessment techniques tailored to in-class programming exercises: live peer testing and live peer code review. Live peer testing can improve students' code robustness by allowing them to create and share lightweight tests with peers. Live peer code review can improve code understanding by intelligently grouping students to maximize meaningful code reviews. A two-week deployment study revealed that PuzzleMe encourages students to write useful test cases, identify code problems, correct misunderstandings, and learn a diverse set of problem-solving approaches from peers.more » « less
An official website of the United States government

