Skip to main content
SpringerLink
Log in

Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor

  • Conference paper
  • First Online:
Artificial Intelligence in Education (AIED 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9112))

Included in the following conference series:

Abstract

Research shows that expert-crafted worked examples can have a positive effect on student performance. To investigate the potential for data-driven worked examples to achieve similar results, we generated worked examples for the Deep Thought logic tutor, and conducted an experiment to assess their impact on performance. Students who received data-driven worked examples were much more likely to complete the tutor, and completed the tutor in less time. This study demonstrates that worked examples, automatically generated from student data, can be used to improve student learning in tutoring systems.

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 99.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Atkinson, R.K., Derry, S.J., Renkl, A., Wortham, D.: Learning from examples: Instructional principles from the worked examples research. Review of educational research 70(2), 181–214 (2000)

    Article  Google Scholar 

  2. Mostafavi, B., Eagle, M., Barnes, T.: Towards data-driven mastery learning. In: Proc. Learning, Analytics, and Knowledge (LAK 2015) (to appear, 2015)

    Google Scholar 

  3. Najar, A., Mitrovic, A.: Should we use examples in intelligent tutors? In: Proc. Computers in Education, pp. 5–7 (2012)

    Google Scholar 

  4. VanLehn, K.: The Behavior of Tutoring Systems. International Journal of Artificial Intelligence in Education 16(2), 227–265 (2006)

    Google Scholar 

  5. Vanlehn, K., et al.: The Andes physics tutoring system: Lessons learned. International Journal of Artificial Intelligence in Education 15(3), 147–204 (2005)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, North Carolina State University, Raleigh, North Carolina, 27695, US

    Behrooz Mostafavi, Guojing Zhou, Collin Lynch, Min Chi & Tiffany Barnes

Authors
  1. Behrooz Mostafavi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guojing Zhou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Collin Lynch
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Min Chi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tiffany Barnes
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Behrooz Mostafavi .

Editor information

Editors and Affiliations

  1. University of British Columbia, Vancouver, British Columbia, Canada

    Cristina Conati

  2. Computer Science Department, Worcester Polytechnic Institute, Worcester, Massachusetts, USA

    Neil Heffernan

  3. Department of Computer Science and Software Engineering, University of Canterbury, Christchurch, New Zealand

    Antonija Mitrovic

  4. E.T.S.I. Informática, Universidad National de Educacion a Distancia, Madrid, Spain

    M. Felisa Verdejo

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Mostafavi, B., Zhou, G., Lynch, C., Chi, M., Barnes, T. (2015). Data-Driven Worked Examples Improve Retention and Completion in a Logic Tutor. In: Conati, C., Heffernan, N., Mitrovic, A., Verdejo, M. (eds) Artificial Intelligence in Education. AIED 2015. Lecture Notes in Computer Science(), vol 9112. Springer, Cham. https://doi.org/10.1007/978-3-319-19773-9_102

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19773-9_102

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19772-2

  • Online ISBN: 978-3-319-19773-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation