Skip to main content
SpringerLink
Log in

To Resolve or not to Resolve? that is the Big Question About Confusion

  • Conference paper
  • First Online:
Book cover 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

Positive relationships between confusion and learning have been found for the last decade. Most theoretical foundations for confusion hypothesize that it is not the mere occurrence of confusion, but rather the successful resolution that benefits learning. Empirical research has provided some support for this hypothesis, but investigations of the confusion resolution process are still sparse. The present work is a preliminary investigation of the confusion resolution process within two learning environments that experimentally induce confusion (false feedback, contradictory information). Findings showed that learners did benefit from confusion resolution compared to when confusion was unresolved, but it was not merely from increased effort. The nature of the confusion induction method also influenced the positive impact of confusion resolution on learning. Implications for intelligent tutoring systems are discussed.

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. Craig, S., Graesser, A., Sullins, J., Gholson, B.: Affect and learning: An exploratory look into the role of affect in learning. J. Educational Media 29, 241–250 (2004)

    Article  Google Scholar 

  2. D’Mello, S., Graesser, A.: The half-life of cognitive-affective states during complex learning. Cognition & Emotion 25, 1299–1308 (2011)

    Article  Google Scholar 

  3. D’Mello, S., Graesser, A.: Confusion. In: Pekrun, R., Linnenbrink-Garcia, L. (eds.) International handbook of emotions in education, pp. 289–310. Routledge, New York (2014)

    Google Scholar 

  4. D’Mello, S., Graesser, A.: Confusion and its dynamics during device comprehension with breakdown scenarios. Acta psychological 151, 106–116 (2014)

    Article  Google Scholar 

  5. D’Mello, S., Lehman, B., Pekrun, R., Graesser, A.: Confusion can be beneficial for learning. Learning & Instruction 29, 153–170 (2014)

    Article  Google Scholar 

  6. Graesser, A., D’Mello, S.: Emotions during the learning of difficult material. In: Ross, B. (ed.) Psychology of Learning and Motivation, vol. 57, pp. 183–226. Elsevier (2012)

    Google Scholar 

  7. Lehman, B., D’Mello, S., Graesser, A.: False feedback can improve learning when you’re productively confused. (in preparation)

    Google Scholar 

  8. Lehman, B., D’Mello, S., Strain, A., Millis, C., Gross, M., Dobbins, A., Wallace, P., Millis, K., Graesser, A.: Inducing and tracking confusion with contradictions during complex learning. Int. J. Artificial Intelligence in Education 22, 85–105 (2013)

    Google Scholar 

  9. D’Mello, S., Lehman, B., Graesser, A.: A motivationally supportive affect-sensitive AutoTutor. In: Calvo, R., D’Mello, S. (eds.) New Perspectives on Affect and Learning Technologies, pp. 113–126. Springer, New York (2011)

    Chapter  Google Scholar 

  10. Forbes-Riley, K., Litman, D.: Benefits and challenges of real-time uncertainty detection and adaptation in a spoken dialogue computer tutor. Speech Communication 53, 1115–1136 (2011)

    Article  Google Scholar 

  11. Grafsgaard, Joseph F., Boyer, Kristy Elizabeth, Phillips, Robert, Lester, James C.: Modeling confusion: facial expression, task, and discourse in task-oriented tutorial dialogue. In: Biswas, Gautam, Bull, Susan, Kay, Judy, Mitrovic, Antonija (eds.) AIED 2011. LNCS, vol. 6738, pp. 98–105. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  12. Woolf, B., Burleson, W., Arroyo, I., Dragon, T., Cooper, D., Picard, R.: Affect-aware tutors: Recognizing and responding to student affect. Int. J. Learning Technology 4, 129–164 (2009)

    Article  Google Scholar 

  13. Limón, M.: On the cognitive conflict as an instructional strategy for conceptual change: A critical appraisal. Learning & Instruction 11, 357–380 (2001)

    Article  Google Scholar 

  14. Festinger, L.: A theory of cognitive dissonance. Row Peterson, Evanston (1957)

    Google Scholar 

  15. Graesser, A., Lu, S., Olde, B., Cooper-Pye, E., Whitten, S.: Question asking and eye tracking during cognitive disequilibrium: Comprehending illustrated texts on devices when the devices breakdown. Memory & Cognition 33, 1235–1247 (2005)

    Article  Google Scholar 

  16. Piaget, J.: The origins of intelligence. International University Press, New York (1952)

    Book  Google Scholar 

  17. Brown, J., VanLehn, K.: Repair theory: A generative theory of bugs in procedural skills. Cognitive Science 4, 379–426 (1980)

    Article  Google Scholar 

  18. VanLehn, K., Siler, S., Murray, C., Yamauchi, T., Baggett, W.: Why do only some events cause learning during human tutoring? Cognition & Instruction 21, 209–249 (2003)

    Article  Google Scholar 

  19. Chinn, C., Brewer, W.: The role of anomalous data in knowledge acquisition: A theoretical framework and implications for science education. Review of Educational Research 63, 1–49 (1993)

    Article  Google Scholar 

  20. D’Mello, S., Graesser, A.: Dynamics of affective states during complex learning. Learning & Instruction 22, 145–157 (2012)

    Article  Google Scholar 

  21. Lee, Diane Marie C., Rodrigo, MaMercedes T., Baker, Ryan SJd, Sugay, Jessica O., Coronel, Andrei: Exploring the relationship between novice programmer confusion and achievement. In: D’Mello, Sidney, Graesser, Arthur, Schuller, Björn, Martin, Jean-Claude (eds.) ACII 2011, Part I. LNCS, vol. 6974, pp. 175–184. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  22. Liu, Z., Pataranutaporn, V., Ocumpaugh, J., Baker, R.: Sequences of frustration and confusion, and learning. In: D’Mello, S., Calvo, R., & Olney, A. (eds.) EDM 2013, pp. 114–120. International Educational Data Mining Society (2013)

    Google Scholar 

  23. Rodrigo, M., Baker, R., Nabos, J.: The relationships between sequences of affect states and learner achievements. In: Wong, S., Kong, S., Yu, F.-Y. (eds.) Computers in Education, pp. 56–60. Faculty of Educational Studies, Universiti Putra Malaysia, Serdang (2010)

    Google Scholar 

  24. D’Mello, S., Taylor, R., Graesser, A.: Monitoring affective trajectories during complex learning. In: McNamara, D., Trafton, J. (eds.) Cognitive Science Society 2007, pp. 203–208. Cognitive Science Society, Austin (2007)

    Google Scholar 

  25. Halpern, D., Millis, K., Graesser, A., Butler, H., Forsyth, C., Cai, Z.: Operation ARA: A computerized learning game that teaches critical thinking and scientific reasoning. Thinking Skills and Creativity 7, 93–100 (2012)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Educational Testing Service, Princeton, NJ, USA

    Blair Lehman

  2. University of Memphis, Memphis, TN, USA

    Art Graesser

Authors
  1. Blair Lehman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Art Graesser
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Blair Lehman .

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

Lehman, B., Graesser, A. (2015). To Resolve or not to Resolve? that is the Big Question About Confusion. 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_22

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19773-9_22

  • 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