Combining Surveys and Sensors to Explore Student Behaviour
Bibliographic Data
| ID | 22044326 |
|---|---|
| Authors | Inkeri Kontro (0000-0002-1874-3756, University of Helsinki, corresponding author), Mathieu Génois (0000-0001-5492-8750, Centre National de la Recherche Scientifique) |
| Year | 2020 |
| Volume | 10 |
| Issue | 3 |
| Pages | 68 |
| Publication date | 2020-03-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Education Sciences (JOURNAL) |
| Journal identifiers | ISSN: 2227-7102 • E-ISSN: 2227-7102 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/educsci10030068 |
| OpenAlex | W3009213328 |
| Language | EN |
| References cited | 48 |
Student belongingness is important for successful study paths, and group work forms an important part of modern university physics education. To study the group dynamics of introductory physics students at the University of Helsinki, we collected network data from seven laboratory course sections of approximately 20 students each for seven consecutive weeks. The data was collected via the SocioPatterns platform, and supplemented with students’ major subject, year of study and gender. We also collected the Mechanics Baseline Test to measure physics knowledge and the Colorado Learning Attitudes about Science Survey to measure attitudes. We developed metrics for studying the small networks of the laboratory sessions by using connections of the teaching assistant as a constant. In the network, we found both demographically homogeneous and heterogeneous groups that are stable. While some students are consistently loosely connected to their networks, we were not able to identify risk factors. Based on our results, the physics laboratory course is equally successful in building strongly connected groups regardless of student demographics in the sections or the formed small groups. SocioPatterns supplemented with surveys thus provides an opportunity to look into the dynamics of students’ social networks
Belongingness · Demographics · Homogeneous · Library science · Mathematics education · Physics · Physics Education · Social media · Social network analysis · Sociology · World Wide Web · Complex Network Analysis Techniques · Computer Science · Demography · Innovative Teaching and Learning Methods · Online and Blended Learning · Psychology · Social Psychology · Ecology
Social network analysis
Peer Instruction
Community detection in graphs
Force concept inventory
Temporal networks
Within-Class Grouping
Community structure in social and biological networks
An Agent-Based Model of Discourse Pattern Formation in Small Groups of Competing and Cooperating Members
When high achievers and low achievers work in the same group
Short Circuits or Superconductors? Effects of Group Composition on High-Achieving Students’ Science Assessment Performance
Data on face-to-face contacts in an office building suggest a low-cost vaccination strategy based on community linkers
| Citation velocity | historical |
|---|---|
| Highly cited | No |