Emerging trends on the topic of Information Technology in the field of Educational Sciences: a bibliometric exploration

The paper presents a bibliometric analysis on the topic of Information Technology (IT) in the field of Educational Sciences, aimed at envisioning the research emerging trends. The ERIC data base is used as a consultation source; the results were subjected to productivity by authors, journals, and term co-occurrence analysis indicators for the period 2009-2013. The productivity of Computers & Education, and Turkish Online Journal of Educational Technology-TOJET, as well as the preceding authors from Canada, have been emphasized. The more used terms are the following: Information technology, foreign countries, educational technology, technology integration, and student attitudes. Researches performed here seem to have a largely qualitative character, highlighting computers and internet as the mostly explored technological objects. The largest subject matter trend refers to the integration of IT in the higher education learning context, and its incidence over the teaching methods

Wild Patterns: Ten Years After the Rise of Adversarial Machine Learning

Learning-based pattern classifiers, including deep networks, have shown impressive performance in several application domains, ranging from computer vision to cybersecurity. However, it has also been shown that adversarial input perturbations carefully crafted either at training or at test time can easily subvert their predictions. The vulnerability of machine learning to such wild patterns (also referred to as adversarial examples), along with the design of suitable countermeasures, have been investigated in the research field of adversarial machine learning. In this work, we provide a thorough overview of the evolution of this research area over the last ten years and beyond, starting from pioneering, earlier work on the security of non-deep learning algorithms up to more recent work aimed to understand the security properties of deep learning algorithms, in the context of computer vision and cybersecurity tasks. We report interesting connections between these apparently-different lines of work, highlighting common misconceptions related to the security evaluation of machine-learning algorithms. We review the main threat models and attacks defined to this end, and discuss the main limitations of current work, along with the corresponding future challenges towards the design of more secure learning algorithms.Comment: Accepted for publication on Pattern Recognition, 201

"If I join forces with Mr. Kuhn": Polanyi and Kuhn as Mutually Supportive and Corrective

My purpose is to examine how Kuhn and Polanyi might be mutually supportive and corrective so as to join forces in providing a more comprehensive understanding of the progress of science. My presentation will be divided into three parts: (I) The common ground Kuhn shares with Polanyi; (II) Four soft spots in Kuhn and their remedy; (III) Clarifying and upgrading Polanyi appeal to "objective reality.

Electronic Visit Verification: The Weight of Surveillance and the Fracturing of Care

In Electronic Visit Verification: The Weight of Surveillance and the Fracturing of Care, Data & Society Researcher Alexandra Mateescu finds that the surveillance of US home care workers through a state-funded mobile app called electronic visit verification ("EVV") erodes critical support for people with disabilities and older adults while offloading significant, unacknowledged burdens onto both workers and service recipients.Drawing on interviews with advocates, activists, and twenty workers and service recipients across the country, Mateescu describes how the rollout of EVV systems within Medicaid home- and community-based programs was built on a poor understanding of how services are actually provided

Education alignment

This essay reviews recent developments in embedding data management and curation skills into information technology, library and information science, and research-based postgraduate courses in various national contexts. The essay also investigates means of joining up formal education with professional development training opportunities more coherently. The potential for using professional internships as a means of improving communication and understanding between disciplines is also explored. A key aim of this essay is to identify what level of complementarity is needed across various disciplines to most effectively and efficiently support the entire data curation lifecycle