Towards mobile learning deployment in higher learning institutions : a report on the qualitative inquiries conducted in four universities in Tanzania

Over the past two decades, mobile learning (m-learning) has been a purposeful area of research among educational technologists, educators and instructional designers whereby doubts and controversies over its relevancy and applicability have been keenly addressed. This paper explores stakeholders’ perceptions of m-learning deployment in Higher Learning Institutions (HLIs). Spe- cifically, we examine the potential of m-learning for HLIs in Tanzania and the challenges that hinder successful m-learning deployment. We adopt a comparative qualitative case study design in which four HLIs in Tanzania were purposefully selected. The study uses a combination of de- sign science research approach and qualitative methods including grounded theory, document re- views, and observation. The respondents included university lecturers, students and ICT experts, who were selected for the interviews through theoretical sampling. The transcripts were loaded, coded and analyzed in NVIVO software. The results indicate that mobiles (smartphone, tablets, laptops, feature-phones etc.) are widely used in the HLIs. Stakeholders perceive that m-learning deployment is important and useful because it improves the quality of the learning experience. The results further indicate that there are financial, pedagogical, technological, infrastructural, individuals – and policy – related challenges that hinder successful deployment of m-learning in HLIs in Tanzania, such as limited network coverage, some students ́ inability to afford mobiles, lack of qualified staff for preparation of mobile content and administration, gaps in the exist- ing policies, and faulty course design. However, our results show that participants are optimistic about the potential of m-learning in the HLIs of Tanzania. They expect that m-learning will im- prove access to learning resources, teacher-student and student-student interaction without being restricted by time or place. Thus, m-learning is considered to have the potential to address issues of crowded classrooms, expertise, access to learning materials, flexibility of the learners as well as remote connectivity.
 We recommend that HLIs should prioritize m-learning and commit resources to the success of the related projects. We also recommend that the governments and stakeholders provide policy interventions, subsidize mobile technologies, expand network coverage, build capacity within and outside HLIs, and improve digital literacy by integrating ICT education at all levels of education

A Role-Based Approach for Orchestrating Emergent Configurations in the Internet of Things

The Internet of Things (IoT) is envisioned as a global network of connected things enabling ubiquitous machine-to-machine (M2M) communication. With estimations of billions of sensors and devices to be connected in the coming years, the IoT has been advocated as having a great potential to impact the way we live, but also how we work. However, the connectivity aspect in itself only accounts for the underlying M2M infrastructure. In order to properly support engineering IoT systems and applications, it is key to orchestrate heterogeneous 'things' in a seamless, adaptive and dynamic manner, such that the system can exhibit a goal-directed behaviour and take appropriate actions. Yet, this form of interaction between things needs to take a user-centric approach and by no means elude the users' requirements. To this end, contextualisation is an important feature of the system, allowing it to infer user activities and prompt the user with relevant information and interactions even in the absence of intentional commands. In this work we propose a role-based model for emergent configurations of connected systems as a means to model, manage, and reason about IoT systems including the user's interaction with them. We put a special focus on integrating the user perspective in order to guide the emergent configurations such that systems goals are aligned with the users' intentions. We discuss related scientific and technical challenges and provide several uses cases outlining the concept of emergent configurations.Comment: In Proceedings of the Second International Workshop on the Internet of Agents @AAMAS201

Demographic Transformation and the Future of Museums

In 2009 the Center for the Future of Museums commissioned Betty Farrell to produce a report to explore in more detail the demographic trends in American society and their implications for museums. The report identifies, synthesizes, and interprets existing research on demographics, cultural consumer attitudes, museum diversity practices, and related topics. It is meant to help the museum field explore the future of museums in a "majority minority" society. Topics of inquiry include national demographic projections for the next 25 years with a focus on the shifting racial and ethnic composition of the United States; current patterns of museum attendance (and cultural participation more generally) by race, ethnicity, cultural origin and other relevant factors; culturally/ethnically specific attitudes towards museums, including perceptual and behavioral barriers to museum attendance; ways that museums currently reach out to diverse audiences; specific models and best practices; and larger trends in societal attitudes towards racial and other classifications

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

SciTech News Volume 71, No. 3 (2017)

Columns and Reports From the Editor.........................3 Division News Science-Technology Division....5 Chemistry Division....................8 Conference Report, Marion E, Sparks Professional Development Award Recipient..9 Engineering Division................10 Engineering Division Award, Winners Reflect on their Conference Experience..15 Aerospace Section of the Engineering Division .....18 Architecture, Building Engineering, Construction, and Design Section of the Engineering Division................20 Reviews Sci-Tech Book News Reviews...22 Advertisements IEEE..........................................

Energy efficiency in discrete-manufacturing systems: insights, trends, and control strategies

Since the depletion of fossil energy sources, rising energy prices, and governmental regulation restrictions, the current manufacturing industry is shifting towards more efficient and sustainable systems. This transformation has promoted the identification of energy saving opportunities and the development of new technologies and strategies oriented to improve the energy efficiency of such systems. This paper outlines and discusses most of the research reported during the last decade regarding energy efficiency in manufacturing systems, the current technologies and strategies to improve that efficiency, identifying and remarking those related to the design of management/control strategies. Based on this fact, this paper aims to provide a review of strategies for reducing energy consumption and optimizing the use of resources within a plant into the context of discrete manufacturing. The review performed concerning the current context of manufacturing systems, control systems implemented, and their transformation towards Industry 4.0 might be useful in both the academic and industrial dimension to identify trends and critical points and suggest further research lines.Peer ReviewedPreprin

Supporting adaptiveness of cyber-physical processes through action-based formalisms

Cyber Physical Processes (CPPs) refer to a new generation of business processes enacted in many application environments (e.g., emergency management, smart manufacturing, etc.), in which the presence of Internet-of-Things devices and embedded ICT systems (e.g., smartphones, sensors, actuators) strongly influences the coordination of the real-world entities (e.g., humans, robots, etc.) inhabitating such environments. A Process Management System (PMS) employed for executing CPPs is required to automatically adapt its running processes to anomalous situations and exogenous events by minimising any human intervention. In this paper, we tackle this issue by introducing an approach and an adaptive Cognitive PMS, called SmartPM, which combines process execution monitoring, unanticipated exception detection and automated resolution strategies leveraging on three well-established action-based formalisms developed for reasoning about actions in Artificial Intelligence (AI), including the situation calculus, IndiGolog and automated planning. Interestingly, the use of SmartPM does not require any expertise of the internal working of the AI tools involved in the system

Survey on Additive Manufacturing, Cloud 3D Printing and Services

Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacement for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review we provide an overview over CM, AM and relevant domains as well as present the historical development of scientific research in these fields, starting from 2002. Part of this work is also a meta-review on the domain to further detail its development and structure