Through the design and exploratory evaluation of a narrative-based 360-video virtual reality experience, the authors aimed at building empathy in adults towards children who experience challenges in early literacy. This contributes to a limited literature on VR empathetic design by specifically studying caregivers in relation to reading difficulties and utilizing a low-cost immersive medium. This research performed a quasi-experimental pilot study following a pretest-posttest design with 27 participants, collecting measures such as participant empathy, anxiety, immersion, and emotional reactions. This paper explored changes in pre-post measures, correlations between variables, and possible explanations for the observed results. The VR experience increased positive caregiver attitudes towards struggling readers. Participants who reported a high degree of emotional reactions showed increased willingness to donate to help reading difficulties. Participants with teaching experience or with lower starting empathy scores were less likely to be affected.
Technological resources have expanded the goal of education from individual knowledge acquisition to include the development of critical thinking, communication, and collaboration (Griffin, McCaw, Care, 2012; Van Roekel, 2014). This shift requires a reevaluation of what students learn (e.g. content versus skills) and how students learn in formal education settings (Saavedra & Opfer, 2012). Thus, there is a critical need to find ways to create environments that enable embodied, enactive, extended, and embedded learning and develop critical thinking, communication, collaboration and creativity. MIT’s Education Arcade and the MIT Game Lab are exploring ways to meet this need by developing a cross-platform, collaborative educational game with a conceptual focus on cellular biology and a developmental focus on 21st century skills. To this end, we are creating learning environments that incorporate collaborative problem solving that are connected across different contexts.
Purpose This study aims to uncover divergent collaboration in makerspaces using social network analysis to examine ongoing social relations and sequential data pattern mining to invesitgate temporal changes in social activities. Design/methodology/approach While there is a significant body of qualitative work on makerspaces, there is a lack of quantitative research identifying productive interactions in open-ended learning environments. This study explores the use of high frequency sensor data to capture divergent collaboration in a semester-long makerspace course, where students support each other while working on different projects. Findings The main finding indicates that students who diversely mix with others performed better in a semester-long course. Additional results suggest that having a certain balance of working individually, collaborating with other students and interacting with instructors maximizes performance, provided that sufficient alone time is committed to develop individual technical skills. Research limitations/implications These discoveries provide insight into how productive makerspace collaboration can occur within the framework of Divergent Collaboration Learning Mechanisms (Tissenbaum et al., 2017). Practical implications Identifying the diversity and sequence of social interactions could also increase instructor awareness of struggling students and having this data in real-time opens new doors for identifying (un)productive behaviors. Originality/value The contribution of this study is to explore the use of a sensor-based, data-driven, longitudinal approach in an ecologically valid setting to understand divergent collaboration in makerspaces. Finally, this study discusses how this work represents an initial step toward quantifying and supporting productive interactions in project-based learning environments.
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