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CSCL 2013, University of Wisconsin - Madison, June 18, 2013
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Modeling #Twitter Use: Do Students Notice?
Dr. Vanessa Dennen, Fabrizio Fornara
Florida State University
June 18, 2013
University of Wisconsin – Madison
Why Twitter?
Potential to support collaborative interactions and to foster both community building and knowledge sharing (Ebner et al., 2010; Junco, Heibergert & Loken, 2011; Lee & McLoughlin, 2010; Schroeder, Minocha & Schneider, 2010).
Direct experience building and interacting with a professional learning network.
We focused on the dynamics of students’ activity on Twitter in an educational setting and on the factors that influence this activity.
Purpose: To observe whether the Twitter activity of preservice teachers differs in the presence of an instructor model.
Hypothesis: An ongoing instructor presence that model appropriate tweets might encourage desired knowledge sharing and community building via Twitter within and across class sections.
The Study
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Activity
Activity: Semester-long Twitter assignment. Students were required to regularly post entries on Twitter. The content of posts was not constrained.
Group Class Sections
Follow Classmate
s
Use commo
n hashtag
Follow instructor model
Control 3 X X
Experiment
3 X X X
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Methods
Participants: six sections of approximately twenty students each, three sections per condition (N=117).
Data collection: Students’ tweets, surveys.
Data analysis: Coding categories were emergent in three main categories: Course related School related Non-school related
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Findings: Features
Similar number of tweets and use of hashtags
Overall, few tweets with a link. Students were not heavily interested in sharing resources.
Control group: used the reply feature more, communicated more with peers.
Experiment group: more likely to retweet, especially the instructor’s entries.
Experiment group: More likely to indicate Twitter a valuable tool for interacting with others (survey)
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Findings: Content
Most of the tweets are com- ments about assignments.
Most of the tweets were composed the day before class or during class.
The predominant attitude toward the class and homework was neutral, with a tendency to negative comments for the control
group.
Experiment group tweeted more about educational technology than control group.
The content of the tweets suggests that students were aware of the presence or absence of an instructor.
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Discussion
The presence of a co-tweeting instructor influences how students use Twitter, in terms of both the content of tweets and students’ likelihood to use certain features.
One unintended effect was the student’s orientation toward the instructor in the experiment condition.
In the absence of an active instructor students more freely shared their thoughts about the class.
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Recommendations
Establish desired outcomes and actively and consistently model the types of tweets and interactions that lead to those outcomes.
An ongoing, dynamic model provides students with a continuous reminder of how to complete the activity.
Adjust the instructor model to include interactions that should explicitly connect two or more students.
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Discussion Questions
Can we further shape students’ behavior on Twitter to foster both community building and knowledge sharing? How?
We want preservice teachers to build and interact with a professional learning network. What further steps can we take toward this direction? How far can we go?
Thanks!
Dr. Vanessa Dennen: [email protected], @vdennen
Fabrizio Fornara: [email protected], @ffornara
June 18, 2013
University of Wisconsin – Madison
Codes + tweets
Content analysis codes with example of tweets
Features use
Summary of hashtag and feature use by students (S) and instructor/researcher (I/R)
Tweets content
Content analysis codes and corresponding number and percentage of tweets posted by students of both conditions.
