360-Degree Virtual Reality Utilising Head-Mounted Devices in Undergraduate Nursing and Midwifery Education: A Scoping Review

Immersive Virtual Reality (IVR) is a promising tool for improving the teaching and learning of nursing and midwifery students. However, the preexisting literature does not comprehensively examine scenario development, theoretical underpinnings, duration, and debriefing techniques. The aim of this review was to assess the available evidence of how 360-degree Virtual Reality (VR) utilising head-mounted devices has been used in undergraduate nursing and midwifery education programmes and to explore the potential pedagogical value based on Kirkpatrick’s evaluation model. This review followed the Joanna Briggs Institute (JBI) methodology. A comprehensive electronic search was conducted across five databases. All studies published in English between 2007–2022 were included, regardless of design, if the focus was undergraduate nursing and midwifery programmes and utilised fully immersive 360-degree VR scenarios. Out of an initial pool of 1700 articles, 26 were selected for final inclusion. The findings indicated a limited diversity in scenario design, with only one study employing a participatory approach. Within the Kirkpatrick model, the most measurable outcomes were found at level 2. The main drawback observed in interventional studies was the absence of a theoretical framework and debriefing. The review concludes that the increased use of fully IVR in nursing education has improved student learning outcomes; however, published literature on midwifery education is scarce

Educational data mining and learning analytics in programming: Literature review and case studies

© 2015 ACM. Educational data mining and learning analytics promise better understanding of student behavior and knowledge, as well as new information on the tacit factors that contribute to student actions. This knowledge can be used to inform decisions related to course and tool design and pedagogy, and to further engage students and guide those at risk of failure. This working group report provides an overview of the body of knowledge regarding the use of educational data mining and learning analytics focused on the teaching and learning of programming. In a literature survey on mining students' programming processes for 2005-2015, we observe a significant increase in work related to the field. However, the majority of the studies focus on simplistic metric analysis and are conducted within a single institution and a single course. This indicates the existence of further avenues of research and a critical need for validation and replication to better understand the various contributing factors and the reasons why certain results occur. We introduce a novel taxonomy to analyse replicating studies and discuss the importance of replicating and reproducing previous work. We describe what is the state of the art in collecting and sharing programming data. To better understand the challenges involved in replicating or reproducing existing studies, we report our experiences from three case studies using programming data. Finally, we present a discussion of future directions for the education and research community