Introduction to Twitter in the Classroom SoTL Project

Background

Since my first semester as a faculty here at Stout way back in Fall 2012 I have noted a common issue in my engineering courses is the lack of student engagement with the course curriculum. Often students see themselves as passive consumers of the lecture material and not as active participants in the learning process. To facilitate the shift from passive consumers to active participants or even content creators for my students I started to implement course assignments targeted towards this purpose. These assignments involve tasking the students with identifying and reporting on an example of the course curriculum that they have observed in their daily lives. Originally this assignment was completed in the form of a submission on the course management software, D2L.

However, recently I have shifted this assignment to using Twitter to facilitate broader discussion and community engagement. The transition to Twitter as a platform makes it possible to engage in real-time out-of-class discussion. A secondary benefit of Twitter is that students can engage with the existing engineering community on Twitter as a form of networking and greater professional exposure. My early findings from these efforts is that little improvement in course performance was measured through the use of pre- and post-assessment using a concept inventory quiz. However, informal observations have suggested that students are engaging with the material more meaningfully and frequently. Therefore, I am concerned that my current assessment methods do not adequately measure achievement of the project’s intended learning objectives.

I have presented at one conference on this topic so far [1] and have a second paper submitted for the ASEE Annual Conference coming up in June [2].

Need

What is missing is a more meaningful assessment. I would like to capture student interaction with the course curriculum or maybe engagement. Even if the assignment does not result in improved learning outcomes, does it have other benefits?

Intended Outcomes

These likely still need some work, but the intended outcomes of these activities as I see them right now are:

  1. Enhance student learning through increases engagement with course curriculum. There is some evidence to suggest that this occurs [3-5].
  2. Expose students to the wider engineering community and get them communicating intelligently within this community. Think critically about how they present themselves publicly.
  3. Foster a sense of connection between course curriculum and everyday occurrences or encounters.

What’s Next?

I have submitted this project to the Nakatani Teaching and Learning Center’s Teaching Champions program. If accepted, this will give me the opportunity to connect with a more experienced mentor to help me design proper assessment tools and help me to become a more effective education researcher.

References

  1. D.R. Berg. Experiences with inquiry-based learning in an introductory mechanics course. In Proceedings of the 2013 ASEE North Midwest Section Conference, Fargo, ND, 2013. ASEE Download Paper, View Presentation
  2. D.R. Berg. Evaluation of student learning outcomes due to self-guided engineering analysis of surroundings. In Proceedings of the 2014 ASEE Annual Conference, Indianapolis, IN, 2014. ASEE. Submitted.
  3. R. Junco, G. Heiberger, and E. Loken. The effect of twitter on college student engagement and grades. Journal of Computer Assisted Learning, 27(2):119-132, 2011. doi: 10.1111/j.1365-2729.2010.00387.x.
  4. Ilkyu Ha, Jason J. Jung, and Chonggun Kim. Influence of twitter activity on college classes. In Costin Badica, Ngoc Thanh Nguyen, and Marius Brezovan, editors, Computational Collective Intelligence. Technologies and Applications, volume 8083 of Lecture Notes in Computer Science, pages 612-621. Springer Berlin Heidelberg, January 2013. doi: 10.1007/978-3-642-40495-5_61.
  5. Amandeep Dhir, Khalid Buragga, and Abeer A. Boreqqah. Tweeters on campus: Twitter a learning tool in classroom? Journal of Universal Computer Science, 19(5):672-691, 2013. doi: 10.3217/jucs-019-05-0672.
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