Learning experience design for augmented reality

Recent years have seen a growing interest in augmented reality (AR) technologies due to their potential for simulating real-life situations and creating authentic learning tasks. Studies have shown that AR enables engaging and interactive learning experiences (e.g. Bressler and Bodzin 2013; Klopfer and Sheldon 2010) and can benefit student learning (e.g. Bonner and Reinders 2018; Siegle 2019). However, although research in AR for education is not scarce, educators often do not have a learning experience design (LXD) approach that is supported by the recent findings of learning sciences and instructional design models. To bridge this gap, the present study introduces an AR-learning prototype developed by using SAM I (Successive Approximation Model I), and the Threshold Concepts Framework, employed for meaningful integration of AR into the learning process. A pre-survey and a post-survey method were utilised in the data gathering process to gauge students’ experience with the AR module. The findings show that the majority of students have not had educational experiences with AR prior to the study, and they struggled to find ways to incorporate this technology into their content areas in a meaningful way. Nonetheless, participants realised the value of AR and stated that they most likely would use this technology in the future. Based on the findings, the authors present a set of suggestions for instructors and LXDs, and provide recommendations for future research. © 2021 B. Czerkawski and M. Berti.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

The development of autonomous student learning networks: Patterns of interactions in an open world learning environment for teachers exploring teaching with and through computer science

This pilot case study sought to investigate patterns of interactions between learners and their instructor in a teacher education course called “Computer Science for Teachers”. This course was constructed to leverage aspects of open world game design elements in order to investigate the effects of degrees of autonomy in gameplay/learning. This course was conducted in a specially built social learning platform based on Elgg software. Student interactions with the instructor and other students in this course were analyzed to determine the learning networks students constructed during each key learning activity as well as the epistemic spaces defined by these interactions. Descriptive statistics along with social network analysis (SNA) and epistemic network analysis (ENA) were used to investigate these data. The findings indicate that more traditional/less open world gaming type learning activities were associated with learning networks and epistemic spaces that were teacher-centered and narrower, while more open world gaming/high levels of autonomy (student-centric) learning activities were associated with learning networks that were highly decentralized and epistemic spaces that featured students asking and answering questions of/for one another. These findings were consistent with existing research into player behavior in open world type games and learner behavior in settings with high levels of autonomy support. Implications for further research are discussed. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

A study of adaptation experiences of elderly dependent Chinese expatriates in Auckland, New Zealand

Abstract not available