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A non‐verbal teaching behaviour analysis for improving pointing out gestures: The case of asynchronous video lecture analysis using deep learning.

  • Published In: Journal of Computer Assisted Learning, 2024, v. 40, n. 3. P. 1006 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Yoon, Ho Young; Kang, Seokmin; Kim, Sungyeun 3 of 3

Abstract

Background: Research into enhancing the effectiveness of information delivery in asynchronous video lectures remains sparse. This study analyzes the nonverbal teaching behaviours in asynchronous online videos, drawing comparisons between pre‐service and in‐service teachers (ITs). Objectives: This research primarily aims to juxtapose the nonverbal teaching behaviours, such as arm extensions and body orientation, utilized by pre‐service teachers (PTs) and ITs within asynchronous online videos. Methods: Asynchronous video lectures from four pre‐service and four ITs across four diverse subject topics were scrutinized. Leveraging deep learning technology, teachers' poses during their instruction towards a video camera were quantified, with a particular focus on arm stretch range and body orientation in relation to the subject being taught. Results: The findings revealed that PTs were deficient in effectively employing pointing gestures. Their arm stretches and body orientation towards the board were not differentiated across subjects. Conversely, ITs demonstrated subject‐specific variations in their arm extension and body orientation, signalling their effective strategies for knowledge dissemination. Conclusions and Discussion: This study emphasizes the importance of assessing nonverbal teaching behaviours in the development of effective instructional training. It accentuates the need for nonverbal communication and subject‐specific teaching strategy training in PTs. Future investigations could broaden their scope to include larger sample sizes and expanded subject areas to discern more comprehensive trends in nonverbal teaching behaviours. Lay Description: What is already known about this topic: The proliferation of online and distance learning has been largely driven by the widespread utilization of asynchronous video lectures.However, the focus of video analysis regarding teaching practices has predominantly been on in‐class activities. This has resulted in the underdevelopment of methods for delivering knowledge through asynchronous video lectures.Research into enhancing the effectiveness of information delivery within asynchronous video lectures remains sparse. What this paper adds: This study contributes to the development of teaching techniques for asynchronous online lectures through a comparative analysis of nonverbal teaching behaviours between pre‐service and in‐service teachers within asynchronous lecture videos.The findings suggest that pre‐service teachers have a deficiency in knowledge regarding the effective use of demonstrative gestures. Implications for practice and/or policy: Considering the widespread use of asynchronous video lectures – including flipped and blend learning, the training of pre‐school teachers using video analysis is requiredThe creation of a robust metric for developing knowledge delivery methods is feasible and advisable, potentially by leveraging state‐of‐the‐art technology such as deep learning. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Computer Assisted Learning. 2024/06, Vol. 40, Issue 3, p1006
  • Document Type:Article
  • Subject Area:Education
  • Publication Date:2024
  • ISSN:0266-4909
  • DOI:10.1111/jcal.12933
  • Accession Number:177193465
  • Copyright Statement:Copyright of Journal of Computer Assisted Learning is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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