Curriculum for the course "Using google services in teachers' work" for full-time and distance learning

The article reveals the content and principles of learning process organization, as well as the modular structure of the full-time and distance course for secondary school teachers «Using Google-services in Teachers` Work». The course was approved in 2010 and introduced into the teacher training education in Lviv region as a potential learning module “IT in Education” in the regional credit-based modular system of teacher training

Network constraints on learnability of probabilistic motor sequences

Human learners are adept at grasping the complex relationships underlying incoming sequential input. In the present work, we formalize complex relationships as graph structures derived from temporal associations in motor sequences. Next, we explore the extent to which learners are sensitive to key variations in the topological properties inherent to those graph structures. Participants performed a probabilistic motor sequence task in which the order of button presses was determined by the traversal of graphs with modular, lattice-like, or random organization. Graph nodes each represented a unique button press and edges represented a transition between button presses. Results indicate that learning, indexed here by participants' response times, was strongly mediated by the graph's meso-scale organization, with modular graphs being associated with shorter response times than random and lattice graphs. Moreover, variations in a node's number of connections (degree) and a node's role in mediating long-distance communication (betweenness centrality) impacted graph learning, even after accounting for level of practice on that node. These results demonstrate that the graph architecture underlying temporal sequences of stimuli fundamentally constrains learning, and moreover that tools from network science provide a valuable framework for assessing how learners encode complex, temporally structured information.Comment: 29 pages, 4 figure

Metrics for Graph Comparison: A Practitioner's Guide

Comparison of graph structure is a ubiquitous task in data analysis and machine learning, with diverse applications in fields such as neuroscience, cyber security, social network analysis, and bioinformatics, among others. Discovery and comparison of structures such as modular communities, rich clubs, hubs, and trees in data in these fields yields insight into the generative mechanisms and functional properties of the graph. Often, two graphs are compared via a pairwise distance measure, with a small distance indicating structural similarity and vice versa. Common choices include spectral distances (also known as $\lambda$ distances) and distances based on node affinities. However, there has of yet been no comparative study of the efficacy of these distance measures in discerning between common graph topologies and different structural scales. In this work, we compare commonly used graph metrics and distance measures, and demonstrate their ability to discern between common topological features found in both random graph models and empirical datasets. We put forward a multi-scale picture of graph structure, in which the effect of global and local structure upon the distance measures is considered. We make recommendations on the applicability of different distance measures to empirical graph data problem based on this multi-scale view. Finally, we introduce the Python library NetComp which implements the graph distances used in this work

Distance education of qualified workers as a problem professional pedagogics

У статті розглядаються питання сутності дистанційного навчання та організаційно-педагогічних умов застосування дистанційних форм і засобів професійного навчання робітничого персоналу на виробництві як проблема професійної педагогіки. Розкриваються форми і засоби дистанційного навчання, можливості й умови його застосування для підвищення кваліфікації персоналу на виробництві. Приділена певна увага модульній технології дистанційного навчання.This paper deals with the nature of distance learning and pedagogical conditions of application of distance learning and the working tools of a professional production staff as a problem of professional pedagogy. Reveals the shape and distance learning , the possibilities and conditions of its use for staff training in the workplace. Paid particular attention to the modular technology of distance learning

A new paradigm for teacher education: supported, open teaching and learning at the Open University

In this paper we draw on our experience over the last twelve years with three large scale distance education programmes for UK teachers to suggest factors which need to be considered by those embarking on large scale distance learning teacher education programmes. We focus on three programmes: a pre-service programme in initial teacher education, the Postgraduate Certificate in Education (PGCE); and two in-service programmes, the Learning Schools Programme (LSP) and TeachandLearn.net. which have made been significant in promoting access, entitlement and diversity. We suggest that in each case the programme structure and design was influenced by the interplay of a number of factors: the nature of teacher professionalism; current policies and priorities; financial constructs; technological tools and the regulatory framework. A number of themes emerge from analysis of participant data together with evaluation evidence back from institutions and individuals participating in these programmes. These can be identified as: (1) linear versus modular structures; (2) the importance of broking between the university and the school settings; (3) interactions of programme elements; (4) the role played by contemporary forms of ICTs. We draw together our experiences and research data for these programmes to suggest characteristics of the next generation of teacher education programmes

What is it like learning with an eportfolio for online distance learners?

This paper reports on a doctoral research project which examines the nature of the learning experience of using an eportfolio and whether it enhances the development of critical thinking among online distance learners. It aims to interrogate the process of the development of critical thinking rather than the product. The project adopts a case study approach, following 24 online distance learners over the course of one academic year in a Dublin based third level institution. The research question for the study is: How can eportfolios enhance the nature of the learning experience and the development of critical thinking among online distance learners? This study is using an exploratory holistic single-case design where the “object of the study” is the of the learner experience of using an eportfolio and the process of developing critical thinking are investigated. The participants are intermediate online distance sociology learners studying a module called Soc3A- Power, Social Order, Crime, Work and Employment as part of the BA (Hons) in Humanities which is a modular humanities programme whereby learners can study a combination of history, sociology, literature, psychology and philosophy. Participants have used their eportfolios to create a critical commentary of their learning and completed five eportfolio entries over the course of one academic year at key points in their learning journey. Eportfolio entries follow a prescribed structured template of critical questions intended to encourage reflection about their learning. Within this case study 37 interviews were conducted for an in-depth exploration of the learner experience of using an eportfolio and the development of criticality. The participants were interviewed with their eportfolios, written, visual and physical artefacts from the participant’s eportfolios were used as stimulus during the interviews using the technique of “photo elicitation”