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      The Effects of Video Instructor’s Body Language on Students’ Distribution of Visual Attention: an Eye-tracking Study

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      proceedings-article
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      Proceedings of the 32nd International BCS Human Computer Interaction Conference (HCI)
      Human Computer Interaction Conference
      4 - 6 July 2018
      Video lectures, Social signals, Eye tracking, Embodied pedagogical agents
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            Abstract

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            Author and article information

            Contributors
            Conference
            July 2018
            July 2018
            : 1-5
            Affiliations
            [0001]Beijing University of Posts and Telecommunications
            [0002]Queen Mary University of London
            [0003]Tokyo University of Agriculture and Technology
            Article
            10.14236/ewic/HCI2018.101
            8a1abcdf-5800-4022-9e19-6e2812dad46a
            © Zhang et al. Published by BCS Learning and Development Ltd. Proceedings of British HCI 2018. Belfast, UK.

            This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

            Proceedings of the 32nd International BCS Human Computer Interaction Conference
            HCI
            32
            Belfast, UK
            4 - 6 July 2018
            Electronic Workshops in Computing (eWiC)
            Human Computer Interaction Conference
            History
            Product

            1477-9358 BCS Learning & Development

            Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2018.101
            Self URI (journal page): https://ewic.bcs.org/
            Categories
            Electronic Workshops in Computing

            Applied computer science,Computer science,Security & Cryptology,Graphics & Multimedia design,General computer science,Human-computer-interaction
            Video lectures,Social signals,Eye tracking,Embodied pedagogical agents

            References

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            2. , & (1991). Cognitive load theory and the format of instruction Cognition & Instruction 8(4), 293–332.

            3. , & (2015). Effects of different video lecture types on sustained attention, emotion, cognitive load, and learning performance Computers & Education 80(5), 108–121.

            4. , & (2011). E-learning and the science of instruction: proven guidelines for consumers and designers of multimedia learning. Pfeiffer.

            5. (2015). Eye-Tracking Analytics in Instructional Videos ISECON.

            6. , & (2014). How video production affects student engagement: an empirical study of MOOC videos ACM Conference on Learning @ Scale Conference (Vol.43, pp. 41–50). ACM.

            7. , & (2014). MOOCs: Expectation sand reality. Full Report Center for Benefit Cost Studies of Education, Teachers College Columbia University, NY.

            8. , & (1980). A theory of reading: from eye fixations to comprehension Psychological Review 87(4), 329.

            9. (2014). ANVIL: A Universal Video Research Tool. In (Eds.) Handbook of Corpus Phonology Oxford University Press 420–436.

            10. , & (2014). Showing face in video instruction: effects on information retention, visual attention, and affect 2095–2102.

            11. , & et al. (2013). A review of using eye-tracking technology in exploring learning from 2000 to 2012 Educational Research Review 10(4), 90–115.

            12. , & (2015). Social robots and virtual agents as lecturers for virdo instruction Computers in Human Behavior 55 1222–1230.

            13. (2001). Multimedia Learning Cambridge University Press.

            14. , & (2015). Designing effective video-based modeling examples using gaze and gesture cues Educational Technology & Society 18.

            15. , & (2017). Effects of the instructor's pointing gestures on learning performance in video lectures British Journal of Educational Technology 48(4), 1020–1029.

            16. , & (2014). How Students Learn using MOOCs: An Eye-tracking Insight EMOOCs 2014, the Second MOOC European Stakeholders Summit.

            17. , & (2016). A gaze-based learning analytics model:in-video visual feedback to improve learner's attention in moocs 417–421.

            18. SoftBank Robotics (2017) “Find out more about Pepper”. [Online] Available from: http://www.ald.softbankrobotics.com/en/robots/pepper [accessed 28 March 2018].

            19. , & (2016). Lecturers' Hand Gestures as Clues to Detect Pedagogical Significance in Video Lectures European Conference on Cognitive Ergonomics (pp.2). ACM.

            20. , & (2017). Instructor presence in instructional video: effects on visual attention, recall, and perceived learning Computers in Human Behavior 71 79–89.

            21. , & (2014). Video-Based Learning: A Critical Analysis of The Research Published in 2003-2013 and Future Visions eLmL 2014 : The Sixth International Conference on Mobile, Hybrid, and On-line Learning (pp. 112–119).

            22. (2012). Upper body gestures in lecture videos:indexing and correlating to pedagogical significance ACM International Conference on Multimedia (pp. 1389–1392). ACM.

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