Skip to main content
SpringerLink
Log in

Adaptive Visual Dialog for Intelligent Tutoring Systems

  • Conference paper
  • First Online:
Artificial Intelligence in Education (AIED 2018)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10948))

Included in the following conference series:

Abstract

Conversational dialog systems are well known to be an effective tool for learning. Modern approaches to natural language processing and machine learning have enabled various enhancements to conversational systems but they mostly rely on text- or speech-only interactions, which puts limits on how learners can express and explore their knowledge. We introduce a novel method that addresses such limitations by adopting a visualization that is coordinated with a text-based conversational interface. This allows learners to seamlessly perceive and express knowledge through language and visual representations.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 89.99
Price excludes VAT (USA)
  • 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

Institutional subscriptions

References

  1. Watson Conversation (2018). https://www.ibm.com/watson/services/conversation

  2. Ahn, J., Brusilovsky, P.: Adaptive visualization for exploratory information retrieval. Inf. Process. Manag. 49(5), 1139–1164 (2013)

    Article  Google Scholar 

  3. Ahn, J., Brusilovsky, P., Grady, J., He, D., Syn, S.Y.: Open user profiles for adaptive news systems: help or harm? In: WWW 2007: Proceedings of the 16th International Conference on World Wide Web, pp. 11–20. ACM Press, New York (2007). https://doi.org/10.1145/1242572.1242575

  4. Anderson, J.R., Boyle, C.F., Reiser, B.J.: Intelligent tutoring systems. Science (Washington) 228(4698), 456–462 (1985)

    Article  Google Scholar 

  5. Bakalov, F., Meurs, M.J., König-Ries, B., Sateli, B., Witte, R., Butler, G., Tsang, A.: An approach to controlling user models and personalization effects in recommender systems. In: Proceedings of the 2013 International Conference on Intelligent User Interfaces, IUI 2013, pp. 49–56. ACM, New York (2013)

    Google Scholar 

  6. Bredeweg, B., Forbus, K.D.: Qualitative modeling in education. AI Mag. 24(4), 35 (2003)

    Google Scholar 

  7. Chi, M.T., De Leeuw, N., Chiu, M.H., LaVancher, C.: Eliciting self-explanations improves understanding. Cognit. Sci. 18(3), 439–477 (1994)

    Google Scholar 

  8. Coetzee, D., Fox, A., Hearst, M.A., Hartmann, B.: Chatrooms in moocs: all talk and no action. In: Proceedings of the First ACM Conference on Learning @ Scale Conference, L@S 2014, pp. 127–136. ACM, New York (2014)

    Google Scholar 

  9. Gold, S., Rangarajan, A.: A graduated assignment algorithm for graph matching. IEEE Trans. Pattern Anal. Mach. Intell. 18(4), 377–388 (1996)

    Article  Google Scholar 

  10. Graesser, A.C., Chipman, P., Haynes, B.C., Olney, A.: Autotutor: an intelligent tutoring system with mixed-initiative dialogue. IEEE Trans. Educ. 48(4), 612–618 (2005)

    Article  Google Scholar 

  11. Grawemeyer, B., Cox, R.: A bayesian approach to modelling users’information display preferences. User Model. 2005, 225–230 (2005)

    Google Scholar 

  12. Hearst, M.A.: ‘Natural’ search user interfaces. Commun. ACM 54, 60–67 (2011)

    Article  Google Scholar 

  13. Jacomy, M., Heymann, S., Venturini, T., Bastian, M.: Forceatlas2, a continuous graph layout algorithm for handy network visualization. Medialab center of research 560 (2011)

    Google Scholar 

  14. Leelawong, K., Biswas, G.: Designing learning by teaching agents: the betty’s brain system. Int. J. Artif. Intell. Educ. 18(3), 181–208 (2008)

    Google Scholar 

  15. Lehmann, S., Schwanecke, U., Dörner, R.: Interactive visualization for opportunistic exploration of large document collections. Inf. Syst. 35(2), 260–269 (2010)

    Article  Google Scholar 

  16. Leuski, A., Allan, J.: Interactive information retrieval using clustering and spatial proximity. User Model. User Adapt. Interact. 14(2), 259–288 (2004)

    Article  Google Scholar 

  17. Rosvall, M., Bergstrom, C.T.: Maps of random walks on complex networks reveal community structure. Proc. Natl. Acad. Sci. 105(4), 1118–1123 (2008)

    Article  Google Scholar 

  18. Rus, V., DMello, S., Hu, X., Graesser, A.: Recent advances in conversational intelligent tutoring systems. AI Mag. 34(3), 42–54 (2013)

    Article  Google Scholar 

  19. Shneiderman, B.: A taxonomy and rule base for the selection of interaction styles. In: Shackle, B., Richardson, S.J. (eds.) Human Factors for Informatics Usability, pp. 325–342. Cambridge University Press, Cambridge (1991)

    Google Scholar 

  20. Viegas, F., Smith, M.: Newsgroup crowds and authorlines: visualizing the activity of individuals in conversational cyberspaces. In: Proceedings of the 37th Annual Hawaii International Conference on System Sciences, 2004, 10 pp., January 2004

    Google Scholar 

  21. Woolf, B.P.: Building Intelligent Interactive Tutors: Student-Centered Strategies for Revolutionizing e-learning. Morgan Kaufmann, Boston (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. IBM T.J. Watson Research Center, 1101 Kitchawan Rd, Yorktown Heights, NY, 10598, USA

    Jae-wook Ahn, Maria Chang, Patrick Watson, Ravi Tejwani, Sharad Sundararajan, Tamer Abuelsaad & Srijith Prabhu

Authors
  1. Jae-wook Ahn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Maria Chang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Patrick Watson
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ravi Tejwani
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sharad Sundararajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tamer Abuelsaad
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Srijith Prabhu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jae-wook Ahn .

Editor information

Editors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Carolyn Penstein Rosé

  2. University of Technology, Sydney, NSW, Australia

    Roberto Martínez-Maldonado

  3. University of Duisburg-Essen , Duisburg, Germany

    H. Ulrich Hoppe

  4. UCL Institute of Education, London, UK

    Rose Luckin

  5. UCL Institute of Education, London, UK

    Manolis Mavrikis

  6. UCL Institute of Education, London, UK

    Kaska Porayska-Pomsta

  7. Carnegie Mellon University, Pittsburgh, PA, USA

    Bruce McLaren

  8. University of Sussex, Brighton, UK

    Benedict du Boulay

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Ahn, Jw. et al. (2018). Adaptive Visual Dialog for Intelligent Tutoring Systems. In: Penstein Rosé, C., et al. Artificial Intelligence in Education. AIED 2018. Lecture Notes in Computer Science(), vol 10948. Springer, Cham. https://doi.org/10.1007/978-3-319-93846-2_77

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-93846-2_77

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93845-5

  • Online ISBN: 978-3-319-93846-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation