Grouping University Students Using Social Network Analysis
We have developed and tested a way to reorganize student groups using the Social Network Analysis (SNA) methodology. The problem defined by the administrators of the Faculty of Management at the National Research University — Higher School of Economics (Saint Petersburg) consisted in reorganizing fo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
National Research University Higher School of Economics (HSE)
2014-10-01
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| Series: | Вопросы образования |
| Subjects: | |
| Online Access: | https://vo.hse.ru/article/view/15431 |
| _version_ | 1797902648503959552 |
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| author | Alexander Pronin Elena Veretennik Alexander Semyonov |
| author_facet | Alexander Pronin Elena Veretennik Alexander Semyonov |
| author_sort | Alexander Pronin |
| collection | DOAJ |
| description | We have developed and tested a way to reorganize student groups using the Social Network Analysis (SNA) methodology. The problem defined by the administrators of the Faculty of Management at the National Research University — Higher School of Economics (Saint Petersburg) consisted in reorganizing four existing groups of second-year Bachelor’s students into three new groups. The fundamental requirement was to keep the friendly and collaborative relationships that had developed between students. Technical requirements included ensuring equal sizes of the new groups (26 students) and equivalent levels of academic performance (measured by the average semester grade). We present a solution algorithm which is based on SNA tools and includes two possible strategies for groups with different interaction patterns: 1) the “weak link” strategy (selecting the most fragmented student group that can be easily divided into loosely connected subgroups, breaking it down and distributing the clusters among the other three groups); and 2) the “melting pot” strategy (reorganizing all the four groups into entirely new clusters based on the degree of student interaction). A comparison of performance ranking scores achieved during the following 18 months revealed a growth of the average grade in groups reorganized with regard to interpersonal assessment and interaction. The suggested grouping method may be used to rearrange student groups or courses in situations where some students get dismissed or transferred, or with a view to create project teams for research classes or scientific labs. |
| first_indexed | 2024-04-10T09:21:00Z |
| format | Article |
| id | doaj.art-8b32d00d6cfd4122ad4ef97f373d2685 |
| institution | Directory Open Access Journal |
| issn | 1814-9545 2412-4354 |
| language | English |
| last_indexed | 2024-04-10T09:21:00Z |
| publishDate | 2014-10-01 |
| publisher | National Research University Higher School of Economics (HSE) |
| record_format | Article |
| series | Вопросы образования |
| spelling | doaj.art-8b32d00d6cfd4122ad4ef97f373d26852023-02-20T11:33:15ZengNational Research University Higher School of Economics (HSE)Вопросы образования1814-95452412-43542014-10-013547310.17323/1814-9545-2014-3-54-7315431Grouping University Students Using Social Network AnalysisAlexander Pronin0Elena Veretennik1Alexander Semyonov2Faculty of Management, National Research University — Higher School of Economics (Saint Petersburg)Faculty of Management, National Research University — Higher School of Economics (Saint Petersburg)Independent ResearcherWe have developed and tested a way to reorganize student groups using the Social Network Analysis (SNA) methodology. The problem defined by the administrators of the Faculty of Management at the National Research University — Higher School of Economics (Saint Petersburg) consisted in reorganizing four existing groups of second-year Bachelor’s students into three new groups. The fundamental requirement was to keep the friendly and collaborative relationships that had developed between students. Technical requirements included ensuring equal sizes of the new groups (26 students) and equivalent levels of academic performance (measured by the average semester grade). We present a solution algorithm which is based on SNA tools and includes two possible strategies for groups with different interaction patterns: 1) the “weak link” strategy (selecting the most fragmented student group that can be easily divided into loosely connected subgroups, breaking it down and distributing the clusters among the other three groups); and 2) the “melting pot” strategy (reorganizing all the four groups into entirely new clusters based on the degree of student interaction). A comparison of performance ranking scores achieved during the following 18 months revealed a growth of the average grade in groups reorganized with regard to interpersonal assessment and interaction. The suggested grouping method may be used to rearrange student groups or courses in situations where some students get dismissed or transferred, or with a view to create project teams for research classes or scientific labs.https://vo.hse.ru/article/view/15431social network analysisacademic performancestudent groupscollaborative learning effectsgirvan-newman algorithm |
| spellingShingle | Alexander Pronin Elena Veretennik Alexander Semyonov Grouping University Students Using Social Network Analysis Вопросы образования social network analysis academic performance student groups collaborative learning effects girvan-newman algorithm |
| title | Grouping University Students Using Social Network Analysis |
| title_full | Grouping University Students Using Social Network Analysis |
| title_fullStr | Grouping University Students Using Social Network Analysis |
| title_full_unstemmed | Grouping University Students Using Social Network Analysis |
| title_short | Grouping University Students Using Social Network Analysis |
| title_sort | grouping university students using social network analysis |
| topic | social network analysis academic performance student groups collaborative learning effects girvan-newman algorithm |
| url | https://vo.hse.ru/article/view/15431 |
| work_keys_str_mv | AT alexanderpronin groupinguniversitystudentsusingsocialnetworkanalysis AT elenaveretennik groupinguniversitystudentsusingsocialnetworkanalysis AT alexandersemyonov groupinguniversitystudentsusingsocialnetworkanalysis |