Abstract
This paper demonstrates how eye tracking technologies can understand providers to realize a personalized learning. Although curiosity is an important factor for learning, textbooks have been static and constant among various learners. The motivation of our work is to develop a digital textbook which displays contents dynamically based on students’ interests. As interest is a positive predictor of learning, we hypothesize that students’ learning and understanding will improve when they are presented information which is in line with their current cognitive state. As the first step, we investigate students’ reading behaviors with an eye tracker, and propose attention and comprehension prediction approaches. These methods were evaluated on a dataset including eight participants’ readings on a learning material in Physics. We classified participants’ comprehension levels into three classes, novice, intermediate, and expert, indicating significant differences in reading behavior and solving tasks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Bibliography
Biedert, R., Buscher, G., & Dengel, A. (2010). The eyebook – using eye tracking to enhance the reading experience. Informatik-Spektrum, 33(3), 272–281.
Biedert, R., Hees, J., Dengel, A., & Buscher, G. (2012). A robust realtime reading-skimming classifier. In S. N. Spencer (Ed.), Proceedings of the 2012 Symposium on Eye Tracking Research and Applications (pp. 123–130). Santa Barbara, CA: ACM.
Bolt, R. A., & Starker, I. (1990). A gaze-responsive self-disclosing display. In J. C. Chew & J. Whiteside (Eds.), Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3–10). New York: ACM. https://doi.org/10.1145/97243.97245
Buscher, G., Dengel, A., & van Elst, L. (2008). Eye movements as implicit relevance feedback. In M. Czerwinski & A. Lund (General Chairs), CHI’ 08 Extended Abstracts on Human Factors in Computing Systems (pp. 2991–2996). New York: ACM.
Dengel, A. (2016). Digital co-creation and augmented learning. In L. Uden, I-H. Ting & M. Santos-Trigo (Eds.), Proceedings of the 11th International Knowledge Management in Organizations Conference on the changing face of Knowledge Management Impacting Society (Art. No. 3). New York: ACM. https://doi.org/10.1145/2925995.2926052
Hyrskykari, A., Majaranta, P., Aaltonen, A., & Räihä, K.-J. (2000). Design issues of iDICT: a gaze-assisted translation aid. In A. T. Duchowski (Chairman), Proceedings of the 2000 Symposium on Eye Tracking Research and Applications (pp. 9–14). New York: ACM.
Ishimaru, S., Kunze, K., Kise, K., & Dengel, A. (2016). The wordometer 2.0: estimating the number of words you read in real life using commercial EOG glasses. In P. Lukowicz & A. Krüger (General Chairs), Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct (pp. 293–296). New York: ACM.
Kunze, K., Kawaichi, H., Yoshimura, K., & Kise, K. (2013). The wordometer – estimating the number of words read using document image retrieval and mobile eye tracking. 2013 12th International Conference on Document Analysis and Recognition, 25–29.
Lowe D. G. (1999). Object recognition from local scale-invariant features. In IEEE (Ed.), The proceedings of the seventh IEEE international conference on computer vision (pp. 1150–1157). IEEE Computer Society. https://doi.org/10.1109/ICCV.1999.790410
Murphy R. (2016). Learning-related vision problems. Allaboutvision.com. http://www.allaboutvision.com/parents/learning.htm. Accessed: 12 August 2017.
Rayner, K. (1998). Eye movements in reading and information processing: 20 years of research. Psychological bulletin, 124(3), 372–422.
Toyama, T., Suzuki, W., Dengel, A., & Kise, K. (2013). User attention oriented augmented reality on documents with document dependent dynamic overlay. In IEEE (Ed.), 2013 IEEE International Symposium on Mixed and Augmented Reality - Arts, Media, and Humanities (ISMAR-AMH 2013) (pp. 299–300). Institute of Electrical and Electronics Engineers.
Wade, N. J., & Tatler, B. W. (2009). Did javal measure eye movements during reading? Journal of Eye Movement Research, 2(5), 1–7.
Zlatkin-Troitschanskaia et al. (2017). Positive Learning in the Age of Information. Unpublished Manuscript, Draft Proposal Cluster of Excellence, Johannes Gutenberg University Mainz.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Fachmedien Wiesbaden GmbH
About this chapter
Cite this chapter
Ishimaru, S. et al. (2018). Augmented Learning on Anticipating Textbooks with Eye Tracking. In: Zlatkin-Troitschanskaia, O., Wittum, G., Dengel, A. (eds) Positive Learning in the Age of Information. Springer VS, Wiesbaden. https://doi.org/10.1007/978-3-658-19567-0_23
Download citation
DOI: https://doi.org/10.1007/978-3-658-19567-0_23
Published:
Publisher Name: Springer VS, Wiesbaden
Print ISBN: 978-3-658-19566-3
Online ISBN: 978-3-658-19567-0
eBook Packages: EducationEducation (R0)