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Fei Gao

Researcher at Bowling Green State University

Publications -  36
Citations -  1141

Fei Gao is an academic researcher from Bowling Green State University. The author has contributed to research in topics: Collaborative learning & Educational technology. The author has an hindex of 13, co-authored 35 publications receiving 883 citations. Previous affiliations of Fei Gao include Michigan State University & Ohio University.

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Tweeting for learning: A critical analysis of research on microblogging in education published in 2008–2011

TL;DR: The analysis suggests that microblogging has a potential to encourage participation, engagement, reflective thinking as well as collaborative learning under different learning settings, suggesting a need for rigorous research on MIE.
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Designing Asynchronous Online Discussion Environments: Recent Progress and Possible Future Directions.

TL;DR: This paper analyzes how existing features of threaded forums constrain the quality of online discussion and argues that developing alternative discussion environments is highly needed to offer better support for asynchronous online communication.
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Exploring the relationship between online discourse and commitment in Twitter professional learning communities

TL;DR: This study investigated how some key features of online discourse influenced the continued participation of the members of a Twitter-based professional learning community and quantified the influences of these dimensions on users' commitment time to the Twitter community.
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A case study of using a social annotation tool to support collaboratively learning

TL;DR: The findings suggested that students participated actively in the collaborative learning activity and were engaged in a variety of behaviors including self-reflection, elaboration, internalization, and showing support.
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An Investigation of the Influence of Intrinsic Motivation on Students’ Intention to Use Mobile Devices in Language Learning

TL;DR: This paper examined the relationship among intrinsic motivation, critical variables related to technology adoption, and students' behavioral intention in mobile-assisted language learning (MALL) and found that proper instructional design that is aligned with and supports the language learning task was important to increase students’ behavioral intention to adopt mobile devices for language learning.