When talking less is more: exploring outcomes of<i>Twitter</i>usage in the large‐lecture hall

Elavsky, C. Michael; Mislan, Cristina; Elavsky, Steriani

doi:10.1080/17439884.2010.549828

Cited by 104 publications

(67 citation statements)

References 15 publications

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“…Using Web 2.0 tools such as Twitter to gather students' feedback (Elavsky, Mislan, & Elavsky, 2011), and Clickers -instructional technologies that enable lecturers and teachers to obtain structured or semistructured responses from all the students -Blasco-Arcas, Buil, Hernandez-Ortega, and Sese (2013) were successful in encouraging interactions, and improving attendances and learning in large classes. Rehman, Afzal, and Kamran (2013) reported both students and lecturers concurring on the importance of active interactivity in the classrooms to aid students' understanding of the subject content.…”

Section: Introductionmentioning

confidence: 99%

Promoting interactions between lecturers and students in classrooms via mobile technologies: An empirical study

Gan

Balakrishnan

2017

AJET

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The current study sets out to identify determinants affecting tertiary students' behavioural intentions to use mobile technology in lectures. The study emphasises that the reason for using mobile technology in classrooms with large numbers of students is to facilitate interactions among students and lecturers. The proposed conceptual framework has four main antecedents of behavioural intention: system perception, intrinsic motivation, system and information quality, and uncertainty avoidance. Sample data was collected from 396 tertiary students in Malaysia. Results from structural equation modelling on the sample indicated that behavioural intention was significantly influenced by system and information quality, followed by intrinsic motivation, and uncertainty avoidance. System perception was not significantly predictive of behavioural intention. The proposed framework explained 54% of the variance in behavioural intention of mobile technology use in lecture classes. The study findings are indicative of the importance of system development efforts to ensure overall quality system design. The findings further suggest that mobile technology may serve as a tool to facilitate interaction among students and lecturers in large lecture classes.

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Section: Introductionmentioning

confidence: 99%

Promoting interactions between lecturers and students in classrooms via mobile technologies: An empirical study

Gan

Balakrishnan

2017

AJET

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“…Research in this vein has, however, tended to focus on the effectiveness of Twitter as a tool for formal learning, for example to improve linguistic competency (Vazquez Cano, 2012), memory of concepts (Blessing, Blessing, & Fleck, 2012) or the delivery of large-lecture courses (Elavsky, Mislan, & Elavsky, 2011). Where studies have explored the use of Twitter to stimulate more informal learning processes and social relationships (e.g.…”

Section: Introductionmentioning

confidence: 99%

Understanding micro-processes of community building and mutual learning on Twitter: a ‘small data’ approach

Stephansen

Couldry

2014

Information, Communication & Society

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This article contributes to an emerging field of 'small data' research on Twitter by presenting a case study of how teachers and students at a sixth-form college in the north of England used this social media platform to help construct a 'community of practice' that enabled micro-processes of recognition and mutual learning. Conducted as part of a broader action research project that focused on the 'digital story circle' as a site of, and for, narrative exchange and knowledge production, this study takes the form of a detailed analysis of a departmental Twitter account, combining basic quantitative metrics, close reading of selected Twitter data and qualitative interviews with teachers and students. Working with (and sometimes against) Twitter's platform architecture, teachers and students constructed, through distinct patterns of use, a shared space for dialogue that facilitated community building within the department. On the whole, they were able to overcome justified anxieties about professionalism and privacy; this was achieved by building on high levels of pre-existing trust among staff and by performing that mutual trust online through personal modes of communication. Through micro-processes of recognition and a breaking down of conventional hierarchies that affirmed students' agency as knowledge producers, the departmental Twitter account enabled mutual learning beyond curriculum and classroom. The significance of such micro-processes could only have been uncovered through the detailed scrutiny that a 'small data' approach to Twitter, in supplement to some obvious virtues of Big Data approaches, is particularly well placed to provide.

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“…A number of digital environments, however, are not specifically designed for learning and teaching. For instance, designers and educators have used Facebook as a learning management system (Wang et al 2012), Twitter as an instructional tool (Elavsky, Mislan, and Elavsky 2011;Junco, Heiberger, and Loken 2011), YouTube as a learning resource (Burke and Snyder 2008), virtual worlds as experiential learning environments (Jarmon et al 2009), and video game consoles as physical education supplements (Staiano and Calvert 2011). Students have also adopted a number of technologies to supplement course materials, aid their studies, collaborate, and enrich their learning.…”

Section: Repurposed Digital Learning Environments and Their Neutralitymentioning

confidence: 99%

Digital Learning Environments

Veletsianos¹

2016

The Wiley Handbook of Learning Technology

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When talking less is more: exploring outcomes ofTwitterusage in the large‐lecture hall

Cited by 104 publications

References 15 publications

Promoting interactions between lecturers and students in classrooms via mobile technologies: An empirical study

Promoting interactions between lecturers and students in classrooms via mobile technologies: An empirical study

Understanding micro-processes of community building and mutual learning on Twitter: a ‘small data’ approach

Digital Learning Environments

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