Successive relearning involves practicing a task until it is performed correctly and then practicing it again until it is performed correctly during other spaced practice sessions. Despite its widespread use outside of education, few students use this approach to obtain and maintain knowledge in formal educational settings. We review evidence that demonstrates its potency and emphasize how investigations of successive relearning will shift research agendas away from single-session studies in which time on task is fixed toward studies involving multiple practice sessions in which time on task is tailored for students and is treated as an outcome variable of interest. Doing so arguably will align the outcomes of cognitive-education research with real-world learning objectives by revealing not only the benefits of using successive relearning (or any learning technique) but also the time required to obtain those benefits.
This content will become publicly available on October 18, 2024
Augmented reality (AR) has the potential to enhance the learning experience of students by providing collaborative, interactive, and immersive environments. This paper reports a systematic literature review focused on examining the research studies on the use of AR in higher education from January 2018 to October 2022, specifically in the context of collaborative learning. The initial search resulted in a total of 2537 studies, of which 20 were analyzed for final review. The main findings suggest that learning using AR-enabled collaborative learning benefits students’ overall knowledge gain, improves task performance, reduces task errors, and provides a positive collaboration experience in higher education settings. This article concludes by discussing the implications of these findings and their use as guidelines by educators, designers, and researchers for developing effective collaborative AR learning content.
more » « less- Award ID(s):
- 2033801
- NSF-PAR ID:
- 10469871
- Publisher / Repository:
- SAGE Publications
- Date Published:
- Journal Name:
- Proceedings of the Human Factors and Ergonomics Society Annual Meeting
- Volume:
- 67
- Issue:
- 1
- ISSN:
- 1071-1813
- Format(s):
- Medium: X Size: p. 1090-1096
- Size(s):
- p. 1090-1096
- Sponsoring Org:
- National Science Foundation
More Like this
-
Successive Relearning: An Underexplored but Potent Technique for Obtaining and Maintaining Knowledge
-
Augmented Reality (AR) applications can enable geographically distant users to collaborate using shared video feeds or interactive 3D holograms, and may be particularly useful in the socially distant context of the Covid-19 pandemic. However, a good user experience is key for their success and could be negatively impacted by network impairments, which are an inevitable occurrence in today's best-effort Internet. In this paper, we present the findings of an empirical user study, aimed at understanding the effects of network outages, on user experience and behavior, in a collaborative AR task. We highlight how network outages affected users in different ways depending on their role in the collaborative task, and how giving users explicit information about poor network conditions helped them deal with some of these negative effects. Furthermore, we report the strategies that users themselves adopted, to deal with outages, such as batching instructions, or shifting to a different spatial referencing style when communicating with their partners. Lastly, based on our findings, we present some design implications for future remote-collaborative AR applications.more » « less
-
null (Ed.)Augmented Reality (AR) has become a valuable tool for education and training processes. Meanwhile, cloud-based technologies can foster collaboration and other interaction modalities to enhance learning. We combine the cloud capabilities with AR technologies to present Meta-AR-App, an authoring platform for collaborative AR, which enables authoring between instructors and students. Additionally, we introduce a new application of an established collaboration process, the pull-based development model, to enable sharing and retrieving of AR learning content. We customize this model and create two modalities of interaction for the classroom: local (student to student) and global (instructor to class) pull. Based on observations from our user studies, we organize a four-category classroom model which implements our system: Work, Design, Collaboration, and Technology. Further, our system enables an iterative improvement workflow of the class content and enables synergistic collaboration that empowers students to be active agents in the learning process.more » « less
-
Cohen, J ; Solano, G (Ed.)This study is implemented with a focus of discovering how students use the practice of embodied learning to gain knowledge of computational thinking (CT). An intervention was executed at an elementary school in a midwestern state, where students used a marker free virtual reality system to engage in a task that requires them to use the CT concepts and skills. Students participated in the path finding activity within the AR system, and demonstrated accounts of how they use their body to express their understanding of abstract CT concepts. Moreover, the affordances of the AR system were integrated to the student’s learning experience, furthering the discussion of how student’s embodied movement within the virtual world influences their learning outcomes of CT concepts. As an attempt to analyze the embodied learning experience of abstract notions, the researchers developed a coding framework that introduces the mapping of abstract CT concepts and the tangible embodied action that reflects each concept. This short paper thus presents the framework for embodied computational thinking skills, and further elaborates on the future implications of the on-going work.more » « less
-
Irgens, G ; Knight, S (Ed.)Wearable positioning sensors are enabling unprecedented opportunities to model students’ procedural and social behaviours during collaborative learning tasks in physical learning spaces. Emerging work in this area has mainly focused on modelling group-level interactions from low-level x-y positioning data. Yet, little work has utilised such data to automatically identify individual-level differences among students working in co-located groups in terms of procedural and social aspects such as task prioritisation and collaboration dynamics, respectively. To address this gap, this study characterised key differences among 124 students’ procedural and social behaviours according to their perceived stress, collaboration, and task satisfaction during a complex group task using wearable positioning sensors and ordered networked analysis. The results revealed that students who demonstrated more collaborative behaviours were associated with lower stress and higher collaboration satisfaction. Interestingly, students who worked individually on the primary and secondary learning tasks reported lower and higher task satisfaction, respectively. These findings can deepen our understanding of students’ individual-level behaviours and experiences while learning in groups.more » « less