604
Views
0
CrossRef citations to date
0
Altmetric
Articles

Language teachers and multimodal instructional reflections during video-based online learning tasks

ORCID Icon, ORCID Icon & ORCID Icon
Pages 293-312 | Received 16 Jan 2020, Accepted 09 Aug 2021, Published online: 18 Feb 2022
 

ABSTRACT

This study explores the multiple ways in which a group of five in-service language teachers reflected in an online video-embedded learning environment. The findings suggest that when engaging in video-based reflective tasks, teachers evaluated and interpreted instructional practices presented to them based on multimodal classroom interactions (i.e. both verbal and non-verbal actions such as pause, gaze or body language). Furthermore, through reflecting on the multimodal classroom interactions, teachers also developed new awareness about their instructional practices and zoomed in on teaching techniques essential for language teaching. The findings stressed the importance of approaching teacher reflection from the multimodal perspective afforded by technology such as videos.

Acknowledgments

The authors thank Dr Jessica Lester, Dr Raymond Smith and Dr Thomas Brush for their constructive feedback on this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Ai-Chu Elisha Ding

Ai-Chu Elisha Ding is an Assistant Professor of Educational Technology at Ball State University. She earned her PhD from Indiana University with double majors in Literacy, Culture and Language Education and Instructional Systems Technology. Her research focuses on teachers’ technology integration practices, pedagogies and professional development, especially for literacy and language education. Specifically, she has explored the use of reflective practice and coaching for teacher professional development and the use of Problem-Based Learning (PBL) and Game-Based Learning (GBL) for classroom teaching.

Krista Glazewski

Krista Glazewski, a former middle school teacher, serves as Professor and Department Chair of Instructional Systems Technology at Indiana University exploring means of supporting teachers as they adopt new technological and curricular innovations. More specifically, she is distinguished for her research into the resources and approaches that support teachers to engage students in complex problem-solving environments, such as case-, project-, and problem-based learning. Her partnership work has spanned multiple K–12 contexts to investigate how and under what conditions teachers might adopt and adapt new practices. This work has been supported by a number of federal agencies, including the National Science Foundation, US Department of Education and US Department of Defense.

Faridah Pawan

Faridah Pawan is Professor of ESL/EFL Teacher Professional Development in the School of Education at Indiana University-Bloomington. She designs and researches online and onsite programmes to support mid-career professionals to enhance their expertise in the classroom or the global workplace. In the US, she developed multiple P–12 teacher ESL professional development projects in 25 Indiana school districts funded by the US Department of Education and Indiana state grants. She has also developed similar programmes to support professionals in educational institutions in Costa Rica, China, Turkey, the Republic of North Macedonia, India and several other international locations. Pawan’s current research focuses on culturally and linguistically inclusive instruction and adult education.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 327.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.