Система исследовательских компетентностей учащихся старшей школы в профильном обучении химии

У статті наведені етапи проектування системи дослідницьких компетентностей учнів старшої школи у профільному навчанні хімії. Визначено внесок кожної компетентності та групи компетентностей у сформованість системи.Introduction. Based on the interpretation of learning research activities of students as a process of succession of its stages, which characterized by complication of methods of performing these activities, as the result are formed the new psychic structures – a research competencies, their formation and development is in the process of students learning research activities. Based on the characteristics of the examined research competence as the integral formation, the research competence of students which are forming and developing at chemistry profile learning can be divided into three groups. Purpose. Design the system of research competencies of high school students at chemistry profile learning. Methods. The main methods of problem investigation are: the theoretical analyze of problem field; the synthesis of initial set of research competencies, which included the 17 general research competencies, 17 research competencies in natural science and 24 research competence in chemistry; the expert evaluation of initial set for the purpose of selection and assessment of system components. Results. The link https://goo.gl/zp2LYW contains the text of a questionnaire aimed at identifying the most significant research competencies of students in chemistry profile learning. In a survey of 75 respondents participated, most of them (76,7 %) – the chemistry teachers (Expert Group 1). Another group of respondents (23,3 %) were scientists and university educators (Expert Group 2). The experience of the respondents were distributed as follows: less than 5 years – 12,3 % of respondents, from 5 to 10 years – 20,5 %, from 11 to 20 years – 23,3 %, from 21 to 30 years – 16,4%, from 31 to 40 years – 23,3 %, more than 40 years – 4,1 %. Originality. Theoretically grounded, designed and evaluated the system of research competencies of high school students at chemistry profile learning. Conclusion. Based on the expert evaluation the system of research competencies of high school students at chemistry profile learning was designed. The system contains a 3 groups of competencies: 6 general scientific competencies, 8 competencies in natural sciences and 15 chemical competencies which contribution to the formation of the system is 20,43 %, 26,53 % and 53,04 % respectively. Among the directions for further research deserves special attention rationale, design and experimental verification of methodics of using ICT as a tool of research competencies formation of students in chemistry profile learning

Social Turing Tests: Crowdsourcing Sybil Detection

As popular tools for spreading spam and malware, Sybils (or fake accounts) pose a serious threat to online communities such as Online Social Networks (OSNs). Today, sophisticated attackers are creating realistic Sybils that effectively befriend legitimate users, rendering most automated Sybil detection techniques ineffective. In this paper, we explore the feasibility of a crowdsourced Sybil detection system for OSNs. We conduct a large user study on the ability of humans to detect today's Sybil accounts, using a large corpus of ground-truth Sybil accounts from the Facebook and Renren networks. We analyze detection accuracy by both "experts" and "turkers" under a variety of conditions, and find that while turkers vary significantly in their effectiveness, experts consistently produce near-optimal results. We use these results to drive the design of a multi-tier crowdsourcing Sybil detection system. Using our user study data, we show that this system is scalable, and can be highly effective either as a standalone system or as a complementary technique to current tools

Fostering the reduction of assortative mixing or homophily into the class

Human societies from the outset have been associated according to race, beliefs, religion, social level, and the like. These behaviors continue even today in the classroom at primary, middle, and superior levels. However, the growth of ICT offers educational researchers new ways to explore methods of team formation that have been proven to be efficient in the field of serious games through the use of computer networks. The selection process of team members in serious games through the use of computer networks is carried out according to their performance in the area of the game without distinction of social variables. The use of serious games in education has been discussed in multiple research studies which state that its application in teaching and learning processes are changing the way of teaching. This article presents an exploratory analysis of the team formation process based on collaboration through the use of ICT tools of collective intelligence called TBT (The best team). The process and its ICT tool combine the paradigms of creativity in swarming, collective intelligence, serious games, and social computing in order to capture the participants’ emotions and evaluate contributions. Based on the results, we consider that the use of new forms of teaching and learning based on the emerging paradigms is necessary. Therefore, TBT is a tool that could become an effective way to encourage the formation of work groups by evaluating objective variable of performance of its members in collaborative works.Postprint (published version

Dendritic Spine Shape Analysis: A Clustering Perspective

Functional properties of neurons are strongly coupled with their morphology. Changes in neuronal activity alter morphological characteristics of dendritic spines. First step towards understanding the structure-function relationship is to group spines into main spine classes reported in the literature. Shape analysis of dendritic spines can help neuroscientists understand the underlying relationships. Due to unavailability of reliable automated tools, this analysis is currently performed manually which is a time-intensive and subjective task. Several studies on spine shape classification have been reported in the literature, however, there is an on-going debate on whether distinct spine shape classes exist or whether spines should be modeled through a continuum of shape variations. Another challenge is the subjectivity and bias that is introduced due to the supervised nature of classification approaches. In this paper, we aim to address these issues by presenting a clustering perspective. In this context, clustering may serve both confirmation of known patterns and discovery of new ones. We perform cluster analysis on two-photon microscopic images of spines using morphological, shape, and appearance based features and gain insights into the spine shape analysis problem. We use histogram of oriented gradients (HOG), disjunctive normal shape models (DNSM), morphological features, and intensity profile based features for cluster analysis. We use x-means to perform cluster analysis that selects the number of clusters automatically using the Bayesian information criterion (BIC). For all features, this analysis produces 4 clusters and we observe the formation of at least one cluster consisting of spines which are difficult to be assigned to a known class. This observation supports the argument of intermediate shape types.Comment: Accepted for BioImageComputing workshop at ECCV 201