Social Network Analysis as an Analytic Tool for Interaction Patterns in Primary Care Practices

The purpose of this chapter is to present graduate students’ views of their Technological Pedagogical Content Knowledge (TPACK) development. These graduate students are also teachers. Data was collected using a mixed method approach founded on the TPACK Framework and social network analysis. Koehler and Mishra (2006) claim that effective teaching with technology requires TPACK, or an ability to integrate content, pedagogy and technology flexibly during the act of teaching. As part of a graduate course on new literacies and media, participants were required to design and implement lessons that incorporated a range of technologies, produce written reflections about their experiences, and engage in online interactions with participants in the class. Qualitative results from participants’ written reflections revealed four themes relative to TPACK. Additionally, a social network analysis demonstrated a positive relationship between participants’ views on their TPACK development and their interaction patterns within the online learning environment. This study shows that the TPACK framework can be a useful tool, giving educators a productive way to think about technology integration as they navigate the rapid changes prompted by emerging technologies.

Download Full-text

Social Network Analysis to Examine Interaction Patterns in Knowledge Building Communities

Canadian Journal of Learning and Technology / La revue canadienne de l’apprentissage et de la technologie ◽

10.21432/t2w01f ◽

2010 ◽

Vol 36 (1) ◽

Cited By ~ 5

Author(s):

Donald N. Philip

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Knowledge Building ◽

Group Processes ◽

Interaction Patterns ◽

Face To Face ◽

Grade 5 ◽

Teachers And Students ◽

Building Community

This paper describes use of social network analysis to examine student interaction patterns in a Grade 5/6 Knowledge Building class. The analysis included face-to-face interactions and interactions in the Knowledge Forum® Knowledge Building environment. It is argued that sociogram data are useful to reveal group processes; in sociological terms, the community lies in the connections among the group. A classroom of unconnected individuals is unlikely to form as a Knowledge Building community; data analyses reported in this study show promise in understanding the dynamics of Knowledge Building in a consistent and measurable way. The strength of the work is not in particular patterns demonstrated but in new forms of assessment and their potential to inform work as it proceeds. The research reported shows that teachers and students are finding social network analysis useful and that through their engagement research-practitioner-engineer teams are better positioned to develop tools to advance Knowledge Building pedagogy.

Download Full-text

Social Network Analysis to Delineate Interaction Patterns That Predict Weight Loss Performance

2014 IEEE 27th International Symposium on Computer-Based Medical Systems ◽

10.1109/cbms.2014.67 ◽

2014 ◽

Cited By ~ 3

Author(s):

Taridzo Chomutare ◽

Anna Xu ◽

M. Sriram Iyengar

Keyword(s):

Weight Loss ◽

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Interaction Patterns ◽

Predict Weight Loss

Download Full-text

Social Network Analysis as an Analytic Tool for Task Group Research: A Case Study of an Interdisciplinary Community of Practice

The Journal for Specialists in Group Work ◽

10.1080/01933922.2017.1301610 ◽

2017 ◽

Vol 42 (2) ◽

pp. 152-175 ◽

Cited By ~ 4

Author(s):

Naorah C. Lockhart

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Community Of Practice ◽

Task Group ◽

Analytic Tool ◽

Group Research

Download Full-text

Passing Network Analysis of Positional Attack Formations in Handball

Journal of Human Kinetics ◽

10.2478/hukin-2019-0044 ◽

2019 ◽

Vol 70 (1) ◽

pp. 209-221 ◽

Cited By ~ 2

Author(s):

Florian Korte ◽

Martin Lames

Keyword(s):

Social Network ◽

Social Network Analysis ◽

Network Analysis ◽

Suitable Method ◽

Interaction Patterns ◽

Optimal Position ◽

Key Players ◽

Sport Teams ◽

The Individual ◽

General Balance

Abstract The aim of this study was to characterize handball from a social network analysis perspective by analyzing 22 professional matches from the 2018 European Men's Handball Championship. Social network analysis has proven successful in the study of sports dynamics to investigate the interaction patterns of sport teams and the individual involvement of players. In handball, passing is crucial to establish an optimal position for throwing the ball into the goal of the opponent team. Moreover, different tactical formations are played during a game, often induced by two-minute suspensions or the addition of an offensive player replacing the goalkeeper as allowed by the International Handball Federation since 2016. Therefore, studying the interaction patterns of handball teams considering the different playing positions under various attack formations contributes to the tactical understanding of the sport. Degree and flow centrality as well as density and centralization values were computed. As a result, quantification of the contribution of individual players to the overall organization was achieved alongside the general balance in interplay. We identified the backcourt as the key players to structure interplay across tactical formations. While attack units without a goalkeeper were played longer, they were either more intensively structured around back positions (7 vs. 6) or spread out (5 + 1 vs. 6). We also found significant differences in the involvement of wing players across formations. The additional pivot in the 7 vs. 6 formation was mostly used to create space for back players and was less involved in interplay. Social network analysis turned out as a suitable method to govern and quantify team dynamics in handball.

Download Full-text