Week 9 Applications and Examples II
In Week 3, we explored a range of example applications of SNA in education. The purpose of that exploration was to expose ourselves to the potential of SNA for educational research and to get acquainted with basic SNA terminologies that were later introduced in the course.
This week, after considerable work on several areas, we’re going to do a ‘deep dive’ in more examples. This time, you are bringing with yourself a collection of SNA concepts, terms, measures, and techniques. By critically examining examples more deeply, the goals of this week’s exploration is to further:
- understand how an SNA study could become theoretically and methodologically aligned
- identify critical decisions of SNA research in action
- understand how specific SNA techniques could be combined with other methods
9.1 Week 9 Activities
9.1.2 Comment
Spend time reading each others’ posts. When reading, try your best to ‘borrow’ ideas from articles introduced by others to inform your own project. Make sure to acknowledge another colleague’s contribution to your thinking via comments.
Please try to comment on at least 2 classmates’ posts. Comments are due by Tuesday, March 23, 11:59PM.
9.1.3 Lists of articles to choose from
Note: Ideally you will choose a reading by yourself that is pertinent to your project idea.
Below is a list of articles grouped by topics (some of which were copied over from Week 3):
Academic success
- Stadtfeld, C., Vörös, A., Elmer, T., Boda, Z., & Raabe, I. J. (2019). Integration in emerging social networks explains academic failure and success. Proceedings of the National Academy of Sciences, 116(3), 792–797. https://doi.org/10.1073/pnas.1811388115
- González Canché, M. S., & Rios-Aguilar, C. (2015). Critical Social Network Analysis in Community Colleges: Peer Effects and Credit Attainment. New Directions for Institutional Research, 2014(163), 75–91. https://doi.org/10.1002/ir.20087
- Gardner, J., & Brooks, C. (2018). Coenrollment Networks and Their Relationship to Grades in Undergraduate Education. In Proceedings of the 8th International Conference on Learning Analytics and Knowledge (pp. 295–304). New York, NY, USA: ACM. https://doi.org/10.1145/3170358.3170373
- Heck, R. h., Price, C. l., & Thomas, S. l. (2004). Tracks as Emergent Structures: A Network Analysis of Student Differentiation in a High School. American Journal of Education , 110(4), 321–353.
- Rienties, B., Héliot, Y., & Jindal-Snape, D. (2013). Understanding social learning relations of international students in a large classroom using social network analysis. Higher Education, 66(4), 489–504. http://doi.org/10.1007/s10734-013-9617-9
Online forums and social media
- Poquet, O., Jovanovic, J., & Dawson, S. (2020). Differences in forum communication of residents and visitors in MOOCS. Computers & Education, 156, 103937. https://doi.org/10.1016/j.compedu.2020.103937
- Chen, B., & Huang, T. (2019). It is about timing: Network prestige in asynchronous online discussions. Journal of Computer Assisted Learning, 35, 503–515. https://doi.org/10.1111/jcal.12355
- Boroujeni, M. S., Hecking, T., Hoppe, H. U., & Dillenbourg, P. (2017). Dynamics of MOOC discussion forums. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference on - LAK ’17 (pp. 128–137). New York, New York, USA: ACM Press. https://doi.org/10.1145/3027385.3027391
- Chen, X., Vorvoreanu, M., & Madhavan, K. (2014). Mining Social Media Data for Understanding Students’ Learning Experiences. IEEE Transactions on Learning Technologies, 7(3), 246–259. https://doi.org/10.1109/TLT.2013.2296520
- Martinez, A., Dimitriadis, Y., Rubia, B., Gómez, E., & de la Fuente, P. (2003). Combining qualitative evaluation and social network analysis for the study of classroom social interactions. Computers & Education, 41(4), 353–368.
Text networks
- Wise, A. F., & Cui, Y. (2019). Top Concept Networks of Professional Education Reflections. In Proceedings of the 9th International Conference on Learning Analytics & Knowledge (pp. 260–264). New York, NY, USA: ACM. https://doi.org/10.1145/3303772.3303840
- Stella, M., Beckage, N. M., Brede, M., & Domenico, M. D. (2018). Multiplex model of mental lexicon reveals explosive learning in humans. Scientific Reports, 8(1), 1–11. https://doi.org/10.1038/s41598-018-20730-5
Networks in professions
- Daly, A. J., & Finnigan, K. S. (2011). The Ebb and Flow of Social Network Ties Between District Leaders Under High-Stakes Accountability. American Educational Research Journal, 48(1), 39–79.
- Roberson, Q. M., & Colquitt, J. A. (2005). Shared and Configural Justice: A Social Network Model of Justice in Teams. Academy of Management Review. Academy of Management, 30(3), 595–607.
- Baker-Doyle, K. (2010). Beyond the Labor Market Paradigm: A Social Network Perspective on Teacher Recruitment and Retention. Education Policy Analysis Archives, 18, 26.
- Hill, M. (2002). Network Assessments and Diagrams: A Flexible Friend for Social Work Practice and Education. Journal of Social Work , 2(2), 233–254.
- Honeycutt, T. (2009). Making Connections: Using Social Network Analysis for Program Evaluation. Mathematica Policy Research, (1), 1–4.
- Wen, Q., Gloor, P. A., Fronzetti Colladon, A., Tickoo, P., & Joshi, T. (2020). Finding top performers through email patterns analysis. Journal of Information Science, 46(4), 508–527. https://doi.org/10.1177/0165551519849519
Creativity
- Hopp, M. D. S., Zhang, Z. S., Hinch, L., O’Reilly, C., & Ziegler, A. (2019). Creative, Thus Connected: The Power of Sociometric Creativity on Friendship Formation in Gifted Adolescents—A Longitudinal Network Analysis of Gifted Students. New Directions for Child and Adolescent Development, 2019(168), 47–73. https://doi.org/10.1002/cad.20324
- Dawson, S., Tan, J. P. L., & McWilliam, E. (2011). Measuring creative potential: Using social network analysis to monitor a learners’ creative capacity. Australasian Journal of Educational Technology, 27(6), 924–942.
Health
- Christley, R. M. (2005). Infection in Social Networks: Using Network Analysis to Identify High-Risk Individuals. American Journal of Epidemiology, 162(10), 1024–1031. http://doi.org/10.1093/aje/kwi308
- Christakis, N. A., & Fowler, J. H. (2007). The spread of obesity in a large social network over 32 years. The New England Journal of Medicine, 357(4), 370–379.
9.2 Notes on the Course Project
Based on our Slack communications (public or private), you are all making progress on your course projects. I want to make a few notes so that you can plan your project:
- The Project Final Artifact is worth 30 points. “Each student will develop a project final artifact that has key components of a research proposal (including research problem, literature review, research questions, methodology, anticipated findings, significance, etc.). Other innovative formats, such as an interactive social network dashboard, are encouraged and should be negotiated in advance with the instructor.” If you still have questions/concerns about your own project, please send Bodong a Direct Message.
- A rubric has been shared with the class to guide your work on the Project Final Artifact. Please use this week’s exploration as an opportunity to make an outline for your Final Artifact. As I’ve mentioned in earlier weeks, what I will be looking for is your capabilities in making theoretically and methodologically sound decisions in a research area you specialize.
Have a wonderful week!