Elavsky, C. M., Mislan, C., & Elavsky, S. (2011). When talking less is more: Exploring outcomes of Twitter usage in the large‐lecture hall. Learning, Media and Technology, 36(3), 215-233. doi:10.1080/17439884.2010.549828
“… assess the pedagogical impact and potential of Twitter’s contribution to large-lecture course dynamics.” (p 215)
“… other online sites which are often more immediately compelling to their sense of identity than the lecture at hand.” (p 215)
“Formative research on CMC frequently posited it as an impoverished medium lacking social context cues, which while encouraging social equality also fostered a disregard for social conventions and displays of aggression, focusing primarily on what was lost in internet interactions (Joinson 2005; Kiesler, Siegel, and Mcguire 1984; Kiesler and Sproull 1986). Yet, research also illuminated people’s tendency to disclose more intimate details about themselves in the CMC realm (Bargh, McKenna, and Fitzsimons 2002), what Walther (1996) refers to as ‘hyperpersonal communication,’ stimulated by the relative anonymity such media provide.” (p 217)
“… Ebner and Schiefner found that most students felt better about micro-blogging than normal blogs, as the former more easily allowed users to write ‘quick reflections,’ while the latter were perceived more ‘as tools for knowledge saving, coherent statements and discourse’ (2008, 158).” (p 219)
“Additionally, routinely used textual analysis tools cannot be applied to corpora of tweets in a straightforward manner, due to the creative and fragmentary nature of language used within microblogging. (Ross et al. [forthcoming], 24)” (p 220)
["Analysis two: interpreting Twitter through data (tweet) coding" ...]
“… 11 categories: ID (use of real name or pseudonym), date (week of class), time (in or out of class), URL (in tweet), type (of tweet, i.e., original post, retweet, or direct reply), aim (whom the tweet was directed at), construction (whether and how the tweet was related to class and its discourse), topic (of the tweet), topic o f URL (in the tweet), and collective enterprise (whether the tweet expressed collective sentiment, i.e., ‘we’ or ‘us ‘).” (p 223)
“The analysis indicated that: (1) the students’ use (or not) of their real ID impacted the tone of how they spoke to one another (construction) (p < .001); (2) the date/time (date; in or out of class) did affect what the students talked about (topic) in the tweets (p < .001); (3) the use and topic ofa URL in tweets were related to the number of people their tweets were meant to address (aim; tweet directed to class, specific individual, etc.) (p < .001); and (4) the tweet stream developed in its overall complexity (construction, aim, topics and use of URLs) across the semester (date) (p < .001 for all, respectively). On the whole, the findings suggest that as the students became more comfortable with the technology and its format in relation to class applications, their related skills and acumen increased, positioning as a stronger supplemental asset in developing the course discourse in novel ways that extended it beyond traditional limitations.” (p 223-224)
[Survey results ...]
“… majority of students agreed that it improved: (I) the experience of the class (86.1 %), (2) the impression o f the class size (i.e., smaller and more interconnected) (81.1 %), (3) increased their engagement with the course (78.2%), and (4) made them feel that they had gotten more out of the class (78.2%).” (p 224)
“… the use of Twitter at times also stifled actual oral contributions from students in class, as projecting it as video backdrop outwardly induced students to engage with class/the class discussion as a function of the spectacle of Twitter itself. Moreover, the Twitter feed itself fails as a dataset to account for the ‘lurkers’ who, through their in-class or office hour input, clearly were aware of the Twitter trail as an orienting formation by which they developed their thinking about course ideas, despite the fact that they were not actively contributing to it.” (p 225)
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