АГЕНТНОЕ МОДЕЛИРОВАНИЕ ДЛЯ РЕФЛЕКСИИ ОБРАЗОВАТЕЛЬНОЙ ОРГАНИЗАЦИИ
The paper presents a macroscopic approach to the analysis of collaborative network activity. Data about the actions of participants over social objects are transformed into a computer map. Acquaintance of teachers and students with the network science begins with the study of this map. As examples, the maps of the educational projects Letopisi.org and Edu.crowdexpert.ru in the period 2006-2015 were used.
Following the discussion on the role of Internet in the formation of ties across space, this paper seeks to supplement recent findings on prevalence of location-dependent preferential attachment online. We look at networks of online communities specifically aimed at development of location-independent ties. The paper focuses on the 25 largest communities of software developers in the leading Russian social networking site VKontakte, one of the communities being studied in depth. Evidence suggests that membership and friendship ties are overwhelmingly cross-city and even cross-country, while an in-depth analysis gives ground to assume that, commenting and liking in such communities might also be location-independent. This group case study provides some insights into a nature of professional networking and shows independence of the three networks: the friendship network as a means of group identification, the commenting network as an advice-giving tool, and the liking network as a result of approval by occasional visitors.
INTED2018 Proceedings. 12th International Technology, Education and Development Conference Valencia, Spain. 5-7 March, 2018.
A “Network Analysis” section was arranged at the XVIIIth Interna- tional Academic Conference on Economic and Social Development at the Higher School of Economics on 11–12 April 2017. For the third year, this section invited scholars from sociology, political science, management, mathematics, and linguistics who use network analysis in their research projects. During the sessions, speakers discussed the development of mathematical models used in network analysis, studies of collaboration and communication networks, networks’ in- uence on individual attributes, identifcation of latent relationships and regularities, and application of network analysis for the study of concept networks.
The speakers in this section were E. V. Artyukhova (HSE), G. V. Gra- doselskaya (HSE), M. Е. Erofeeva (HSE), D. G. Zaitsev (HSE), S. A. Isaev (Adidas), V. A. Kalyagin (HSE), I. A. Karpov (HSE), A. P. Koldanov (HSE), I. I. Kuznetsov (HSE), S. V. Makrushin (Fi- nancial University), V. D. Matveenko (HSE), A. A. Milekhina (HSE), S. P. Moiseev (HSE), Y. V. Priestley (HSE), A. V. Semenov (HSE), I. B. Smirnov (HSE), D. A. Kharkina (HSE, St. Petersburg), C. F. Fey (Aalto University School of Business), and F. López-Iturriaga (Uni- versity of Valladolid).
In this paper, we present our current research regarding information interaction strategies of students of minor specialization in Data Science. We employed an online platform, consisted of a third-party and our software, to provide students with means of learning and analyse their learning activity. We developed several indicators to estimate their activity: coding activity, friends network size, and Q&A activity. We show that high-achieving and low-achieving students use resources in different ways, with substantial inequality in resource access/use. Based on the research, we propose two features that supposedly would provoke students to participate in a Q&A activity decreasing inequality in the use of these resources.
Nowadays, the e-learning market is rapidly growing both fi nancially and geographically. More and more often, e-learning resources involve a multicultural audience and are becoming available to people with diff erent educational backgrounds. However, there are cognitive specifi city and diff erent approaches to the learning process in diff erent cultures. This paper is devoted to illustrating a possible solution for adaptation of content of an e-learning resource to a multicultural audience. The solution described applies the adaptive content concept based on individual educational trajectories and preparing content according to the individual cultural characteristics of learner and his or her competencies, both obtained and desired. During the research, the learner-centric model of learning processes was developed. In the article, both high-level and detailed models are presented. Principles of planning the individual learning trajectory based on the learner’s obtained and desired competencies, and statistical data about his or her learning style are also described. As an example of the possibility to apply historical data on how learning style aff ects successful passing through the learning course, the statistical analysis is provided. The analysis relies on person-course deidentifi ed dataset from seven courses on HarvardX and MITx platforms provided during the 2013/14 academic year. This analysis demonstrated the statistical signifi cance of several parameters. A comparison of algorithms for estimating the probability of successfully passing the course depending on the learning style, is also presented.
Koli Calling is a vibrant single-track conference with a program including a keynote address, paper presentations and a poster session. At Koli Calling 2017, Professor Katrina Falkner from the University of Adelaide, Australia, presented a keynote address on the topic What Can We Learn about Teaching from MOOCs? Although the conference had a strong Computational Thinking flavour this year, the paper and poster presentations also covered a variety of topics including teaching and learning programming; program design; affect and emotion expression in CS and while programming; reflection, feedback and assessment; program plagiarism; and visualisation tools.
Institutions affect investment decisions, including investments in human capital. Hence institutions are relevant for the allocation of talent. Good market-supporting institutions attract talent to productive value-creating activities, whereas poor ones raise the appeal of rent-seeking. We propose a theoretical model that predicts that more talented individuals are particularly sensitive in their career choices to the quality of institutions, and test these predictions on a sample of around 95 countries of the world. We find a strong positive association between the quality of institutions and graduation of college and university students in science, and an even stronger negative correlation with graduation in law. Our findings are robust to various specifications of empirical models, including smaller samples of former colonies and transition countries. The quality of human capital makes the distinction between educational choices under strong and weak institutions particularly sharp. We show that the allocation of talent is an important link between institutions and growth.