Skip to main content

Understanding Student Attention to Adaptive Hints with Eye-Tracking

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 7138)

Abstract

Prime Climb is an educational game that provides individualized support for learning number factorization skills. This support is delivered by a pedagogical agent in the form of hints based on a model of student learning. Previous studies with Prime Climb indicated that students may not always be paying attentions to the hints, even when they are justified. In this paper we discuss preliminary work on using eye tracking data on user attention patterns to better understand if and how students process the agent’s personalized hints, with the long term goal of making hint delivery more effective.

Keywords

  • Adaptive help
  • educational games
  • pedagogical agents
  • eye-tracking

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (Canada)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. de Castell, S., Jenson, J.: Digital Games for Education: When Meanings Play. Intermedialities 9, 45–54 (2007)

    Google Scholar 

  2. Van Eck, R.: Building Artificially Intelligent Learning Games. In: Gibson, D., Aldrich, C., Prensky, M. (eds.) Games and Simulations in Online Learning: Research and Development Frameworks, pp. 271–307. Information Science Pub. (2007)

    Google Scholar 

  3. Conati, C., Manske, M.: Evaluating Adaptive Feedback in an Educational Computer Game. In: Ruttkay, Z., Kipp, M., Nijholt, A., Vilhjálmsson, H.H. (eds.) IVA 2009. LNCS, vol. 5773, pp. 146–158. Springer, Heidelberg (2009)

    CrossRef  Google Scholar 

  4. Peirce, N., Conlan, O., Wade, V.: Adaptive Educational Games: Providing Non-invasive Personalised Learning Experiences. In: Second IEEE International Conference on Digital Games and Intelligent Toys Based Education (DIGITEL 2008), Banff, Canada, pp. 28–35 (2008)

    Google Scholar 

  5. Johnson, W.L.: Serious use for a serious game on language learning. In: Proc. of the 13th Int. Conf. on Artificial Intelligence in Education, Los Angeles, USA (2007)

    Google Scholar 

  6. Conati, C., Merten, C.: Eye-tracking for user modeling in exploratory learning environments: An empirical evaluation. Knowl.-Based Syst. 20(6), 557–574 (2007)

    CrossRef  Google Scholar 

  7. Baker, R., Corbett, A., Roll, I., Koedinger, K.: Developing a generalizable detector of when students game the system. User Model. User-Adapt. Interact. 18(3) (2008)

    Google Scholar 

  8. Shih, B., Koedinger, K., Scheines, R.: A Response Time Model For Bottom-Out Hints as Worked Examples. In: EDM 2008, pp. 117–126 (2008)

    Google Scholar 

  9. Amershi, S., Conati, C.: Combining Unsupervised and Supervised Machine Learning to Build User Models for Exploratory Learning Environments. Journal of Educational Data Mining 1(1), 18–71 (2009)

    Google Scholar 

  10. Roll, I., Aleven, V., McLaren, B.M., Ryu, E., Baker, R.S.J.d., Koedinger, K.R.: The Help Tutor: Does Metacognitive Feedback Improve Students’ Help-Seeking Actions, Skills and Learning? In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 360–369. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  11. Just, M., Carpenter, P.: The Psychology of Reading and Language Comprehension, Boston (1986)

    Google Scholar 

  12. Bee, N., Wagner, J., André, E., Charles, F., Pizzi, D., Cavazza, M.: Interacting with a Gaze-Aware Virtual Character. In: Workshop on Eye Gaze in Intelligent Human Machine Interaction, IUI 2010 (2010)

    Google Scholar 

  13. Prasov, Z., Chai, J.: What’s in a gaze? the role of eye-gaze in reference resolution in multimodal conversational interfaces. In: IUI 2008 (2008)

    Google Scholar 

  14. Muldner, K., Christopherson, R., Atkinson, R., Burleson, W.: Investigating the Utility of Eye-Tracking Information on Affect and Reasoning for User Modeling. In: Houben, G.-J., McCalla, G., Pianesi, F., Zancanaro, M. (eds.) UMAP 2009. LNCS, vol. 5535, pp. 138–149. Springer, Heidelberg (2009)

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Muir, M., Conati, C. (2012). Understanding Student Attention to Adaptive Hints with Eye-Tracking. In: Ardissono, L., Kuflik, T. (eds) Advances in User Modeling. UMAP 2011. Lecture Notes in Computer Science, vol 7138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28509-7_15

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-28509-7_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28508-0

  • Online ISBN: 978-3-642-28509-7

  • eBook Packages: Computer ScienceComputer Science (R0)