With close to 20.4 billion devices connected to the Internet to be deployed by 2020, Internet of things (IoT) is already being leveraged in diverse sectors. Now, because of the ubiquitous nature of IoT devices, schools and academic institutions are looking to incorporate IoT in educational activities. With the increased use of IoT in the education domain, it is of utmost importance to study how this technology with its distinguished system functions such as sensing and decision making can support and challenge the pedagogical processes for all interrelated actors (faculty, students, and staff) as well as all involved assets (e.g., libraries, classrooms, and labs). Although there have been several contributions on the inclusion of IoT into the education domain, there is still a lack of consolidated and coherent views on this subject. Hence, we are motivated to close the gap of knowledge and embarked on mapping out the published studies available. This study presents the results of a systematic literature review focusing on the benefits and the challenges faced in education in integrating IoT into the curriculum and educational environments. Different mapping views of the extracted studies are provided as long as a summary of the already implemented tools and a list of gap research questions yet to be investigated.

Healthcare is a data-intensive domain, once a considerable volume of data is daily to monitoring patients, managing clinical research, producing medical records, and processing medical insurance claims. While the focus of applications of blockchain in practice has been to build distributed ledgers involving virtual tokens, the impetus of this emerging technology has now extended to the medical domain. With the increased popularity, it is crucial to study how this technology accompanied with a system for smart contracts can support and challenge the healthcare domain for all interrelated actors (patients, physicians, insurance companies, regulators) and involved assets (e.g. patients' data, physician's data, equipment's and drug's supply chain, etc.). The contributions of this paper are the following: (i) report the results of a systematic literature review conducted to identify, extract, evaluate and synthesize the studies on the symbiosis of blockchain in healthcare; (ii) summarize and categorize existing benefits/challenges on incorporating blockchain in healthcare domain; (iii) provide a framework that will facilitate new research activities; and (iv) establish the state of evidence with in-depth assessment.

Working collaboratively in teams is an essential element in systems engineering: Interdisciplinary teams are formed to tackle large-scale, heterogeneous problems requiring skill and knowledge across a wide array of engineering and technical disciplines. While this is widely accepted as necessary, little attention is given to the problem of ensuring effective collaboration across the diverse team. Attention is given to the processes that will be followed, and tools are provided to aid communication; but the critical cognitive aspects that ensure that the team works effectively and efficiently towards a common objective are frequently absent. Instead, managers and team members assume that their disparate mental models have no impact on their collaborative efforts, or that any cognitive dissonance will evaporate naturally and organically. In reality, neither assumption is true, and if these issues are not directly addressed, a team will fall into cooperative rather than collaborative work, which is less effective and efficient. We introduce a framework, the Cognitive Collaborative Model, that explicitly promotes the cognitive collaborative processes necessary for effective engineering teams, and demonstrate its effectiveness in controlled system design and development experiments. Further, we investigate whether this improvement is due to convergence of the individual team member mental models into a shared, or team, mental model, often cited as the basis for high-performing teams. Finally, we propose a novel multistage evaluation process for mental model convergence using concept maps and Pathfinder analysis.

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Background Cognitive style has been shown to influence the number, type, and organization of an individual's ideas. Concept maps are used regularly to assess students' organization and mastery of knowledge (their cognitive level) in engineering courses, yet very few studies have analyzed concept maps with respect to cognitive style.Purpose/Hypothesis This study sought to investigate the relationship between cognitive style and concept mapping performance. Using principles of cognitive psychology and concept mapping assessment, we hypothesized that correlations between cognitive style and the selected concept map metrics are not statistically significant.Design/Method Concept maps from 104 engineering undergraduates in a first-year design course were analyzed using 12 traditional scoring metrics and four holistic scoring metrics. One holistic metric was expanded to allow more detailed evaluation, bringing the number of map metrics to 20. Cognitive style was measured using the Kirton Adaption-Innovation Inventory, a psychometric instrument previously applied in engineering education contexts. Relationships between the concept map metrics and cognitive style were investigated using standard linear techniques.Results Results show substantial support for the null hypothesis that cognitive style and concept mapping performance are uncorrelated.Conclusions Engineering educators can be confident that the concept map metrics used here reflect cognitive level and not cognitive style. Cognitive style inventories and concept maps are likely measuring two separate aspects of an individual's cognition and are therefore complementary rather than duplicative. Journal of Engineering EducationV C 2015 ASEE.