Big data management is a reality for an increasing number of organizations in many areas and represents a set of challenges involving big data modeling, storage and retrieval, analysis and visualization. However, technological resources, people and processes are crucial to facilitate the management of big data in any kind of organization, allowing information and knowledge from a large volume of data to support decision-making. Big data management can be supported by these three dimensions: technology, people and processes. Hence, this article discusses these dimensions: the technological dimension that is related to storage, analytics and visualization of big data; the human aspects of big data; and, in addition, the process management dimension that involves in a technological and business approach the aspects of big data management.

An algorithm learning tool was developed for an introductory computer science class in a specialized science and technology high school in Japan. The tool presents lessons and simple visualizations that aim to facilitate teaching and learning of fundamental algorithms. Written tests and an evaluation questionnaire were designed and implemented along with the learning tool among the participants. The tool’s effect on the learning performance of the students was examined. The differences of the two types of visualizations offered by the tool, one with more input and control options and the other with fewer options, were analyzed. Based on the evaluation questionnaire, the scales with which the tool can be assessed according to its usability and pedagogical effectiveness were identified. After using the algorithm learning tool there was an increase in the posttest scores of the students, and those who used the visualization with more input and control options had higher scores compared to those who used the one with limited options. The learning objectives used to evaluate the tool correlated with the test performance of the students. Properties comprised of learning objectives, algorithm visualization characteristics, and interface assessment are proposed to be incorporated in evaluating an algorithm learning tool for novice learners.

Agile global software development (AGSD) is an increasingly prevalent software development strategy, as organizations hope to realize the benefits of accessing a larger resource pool of skilled labor, at a potentially reduced cost, while at the same time delivering value incrementally and iteratively. However, the distributed nature of AGSD creates geographic, temporal, socio-cultural distances that challenge collaboration between project stakeholders. The Cloud Computing (CC) service models of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are similar to the aspirant qualities of AGSD as they provide services that are globally accessible, efficient, and stable, with lower predictable operating costs that scale to meet the computational demand. This study focused on the 12 agile principles upon which all agile methodologies are based, therein potentially increasing the potential for the findings to be generalized. Domestication Theory was used to assist in understanding how cloud technologies were appropriated in support of AGSD. The research strategy took the form of case study research. The findings suggest that some of the challenges in applying the agile principles in AGSD may be overcome by using CC.

Aim/Purpose: This study was designed to examine the effectiveness of mentor’s work with immigrant children and adolescents at risk, using the Elements Way. Background: The New Media offers our “screen kids” a lot of information, many behavioral models, and a new type of social communication. The Elements Way is an educational method designed to enhance openness, development, breakthroughs, goal achievement, and transformation in the age of media and social networks. Methodology: The Elements Way was developed following research on communication in the diversified media, especially new media such as Facebook, WhatsApp, and television reality shows, and the study is an examination of the effectiveness of mentors’ work with immigrant children and adolescents at risk, using the Elements Way. All mentors had been trained in the Elements Way. The study population included 640 mentors working with immigrants’ children in Israel. The work was conducted in 2010-2013. The mixed-methods approach was selected to validate findings. Contribution: Empowering children and enhancing their ability to cope; Creating openness and sharing, making children more attentive to the significant adults in their lives; Supporting children who face the complex reality that characterizes our age. Findings: Significant differences were found in the mentors’ conduct with the children. Work programs were designed and implemented with care and consistency, and mentors succeeded in generating change within the children and achieving desired goals. Of the 640 participating mentors, 62 were not able to promote the child, and interviews with them revealed that their work with the children was not consistent with the Elements Way and began from a different vantage point. Recommendations for Practitioners: Success factors: Self-awareness and awareness of one’s surroundings. Empathy. Willingness to engage in significant interactions. Self-cleansing and self-reflection. Ability to engage in a personal and interpersonal dialogue. Ability to accept and contain the child. Cooperation with the child in creating a work program and assisting the child to achieve the goals that were set in the program. Recommendation for Researchers: Future studies should focus on analyzing the discussions of children and adolescents, to add depth to our insights regarding children and adolescents’ perception of the mentors’ work from their perspective. Impact on Society: Finding the “keys” to openness, development, goal achievement, and transformation in our work with “screen kids.” Future Research: Studies that are designed to examine the effectiveness of mentor’s work with immigrant children and adolescents at risk, using the Elements Way.

Aim/Purpose: The proposed Personal Knowledge Management (PKM) for Empowerment (PKM4E) Framework expands on the notions of the Ignorance Map and Matrix to support the educational and informing concept of a PKM system-in-progress. Background: The accelerating information abundance is depleting the very attention our cognitive capabilities are able to master, contributing to widening individual and collective opportunity divides. Support is urgently needed to benefit Knowledge Workers irrespective of space (developed/developing countries), time (study or career phase), discipline (natural or social science), or role (student, professional, leader). Methodology: The Design Science Research (DSR) project conceptualizing the PKM System (PKMS) aims to support a scenario of a ‘Decentralizing KM Revolution’ giving more power and autonomy to individuals and self-organized groups. Contribution: The informing-science-related approach synthesizes and visualizes concepts related to ignorance and entropy, learning and innovation, chance discovery and abduction to inform diverse audiences and potential beneficiaries. Findings: see Recommendation for Researchers Recommendations for Practitioners: The PKM4E learning cycles and workflows apply ‘cumulative synthesis’, a concept which convincingly couples the activities of researchers and entrepreneurs and assists users to advance their capability endowments via applied learning. Recommendation for Researchers: In substituting document-centric with meme-based knowledge bases, the PKMS approach merges distinctive voluntarily shared knowledge objects/assets of diverse disciplines into a single unified digital knowledge repository and provides the means for advancing current metrics and reputation systems. Impact on Society: The PKMS features provide the means to tackle the widening opportunity divides by affording knowledge workers with continuous life-long support from trainee, student, novice, or mentee towards professional, expert, mentor, or leader. Future Research: After completing the test phase of the PKMS prototype, its transformation into a viable PKM system and cloud-based server based on a rapid development platform and a noSQL-database is estimated to take 12 months.