Skip to main content
SpringerLink
Log in

Covering Possible Reasoning Errors for Intelligent Tutoring Systems: Order of Expression Evaluation Case

  • Conference paper
  • First Online:
Intelligent Tutoring Systems (ITS 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13284))

Included in the following conference series:

Abstract

One of the problems in computer-supported education is defining meaningful errors that students can make during a complex automated exercise. A precise set, describing what can go wrong in the student’s reasoning, allows better measurement of students’ knowledge, asking pointed follow-up questions to stimulate the student’s thinking, and providing precise explanatory feedback. We describe a method for building a set of possible low-level errors in reasoning during solving a complex task. We demonstrate an example of using this method for the task of determining the order of evaluation of a programming language expression and discuss prospects of applying the described method.

The reported study was funded by RFBR, project numbers 20-07-00764 and 20-07-00502.

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

Similar content being viewed by others

References

  1. Afzal, S., Shashidhar, V., Sindhgatta, R., Sengupta, B.: Impact of tutor errors on student engagement in a dialog based intelligent tutoring system. In: Nkambou, R., Azevedo, R., Vassileva, J. (eds.) ITS 2018. LNCS, vol. 10858, pp. 267–273. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-91464-0_26

    Chapter  Google Scholar 

  2. Brusilovsky, P.: Domain Modeling for Personalized Guidance, pp. 165–183. Army Research Laboratory (2016)

    Google Scholar 

  3. Holland, J.: A Constraint-based ITS for the Java Programming Language. Master’s thesis, University of Canterbury, Christchurch, New Zealand (2009). https://doi.org/10.26021/1309

  4. Hong, J.: Guided programming and automated error analysis in an intelligent Prolog tutor. Int. J. Hum.-Comput. Stud. 61(4), 505–534 (2004). https://doi.org/10.1016/j.ijhcs.2004.02.001

    Article  Google Scholar 

  5. Hooshyar, D., Ahmad, R.B., Yousefi, M., Fathi, M., Horng, S.J., Lim, H.: SITS: a solution-based intelligent tutoring system for students’ acquisition of problem-solving skills in computer programming. Innov. Educ. Teach. Int. 55(3), 325–335 (2016). https://doi.org/10.1080/14703297.2016.1189346

    Article  Google Scholar 

  6. Laengrich, M., Schulze, J., Kumar, A.N.: Expression tasks for novice programmers: turning the attention to objectivity, reliability and validity. In: 2015 IEEE Frontiers in Education Conference (FIE). IEEE, October 2015. https://doi.org/10.1109/fie.2015.7344070

  7. Li, D., Zhou, H.H.: An intelligent tutoring system with an automated knowledge acquisition mechanism. In: 2015 IEEE International Conference on Computational Intelligence & Communication Technology, pp. 88–91. IEEE, Feburary 2015. https://doi.org/10.1109/cict.2015.97

  8. Mitrovic, A., Martin, B., Suraweera, P.: Intelligent tutors for all: the constraint-based approach. IEEE Intell. Syst. 22(4), 38–45 (2007). https://doi.org/10.1109/mis.2007.74

    Article  Google Scholar 

  9. Ramesh, V.M., Rao, N.J., Ramanathan, C.: Implementation of an intelligent tutoring system using moodle. In: 2015 IEEE Frontiers in Education Conference (FIE), pp. 1–9. IEEE, October 2015. https://doi.org/10.1109/fie.2015.7344313

  10. Rathore, A.S., Arjaria, S.: Intelligent Tutoring System, pp. 121–144. IGI Global (2020). https://doi.org/10.4018/978-1-7998-0010-1.ch006

  11. Shute, V., Zapata-Rivera, D.: Intelligent systems. In: Peterson, P., Baker, E., McGaw, B. (eds.) International Encyclopedia of Education (Third Edition), pp. 75–80. Elsevier, Oxford, third edition edn. (2010). https://doi.org/10.1016/B978-0-08-044894-7.00247-5

  12. Sychev, O.A., Mamontov, D.P.: Automatic error detection and hint generation in the teaching of formal languages syntax using correctwriting question type for moodle lms. In: 2018 3rd Russian-Pacific Conference on Computer Technology and Applications (RPC), pp. 1–4, August 2018. https://doi.org/10.1109/RPC.2018.8482125

  13. Sychev, O., Penskoy, N., Anikin, A., Denisov, M., Prokudin, A.: Improving comprehension: intelligent tutoring system explaining the domain rules when students break them. Educ. Sci. 11(11), 719 (2021). https://doi.org/10.3390/educsci11110719

  14. Wang, M., Wu, W., Liang, Y.: A novel intelligent tutoring system for learning programming. In: 2020 International Conference on Development and Application Systems (DAS), pp. 162–168. IEEE, May 2020. https://doi.org/10.1109/das49615.2020.9108925

  15. Wang, M., Chau, H., Thaker, K., Brusilovsky, P., He, D.: Knowledge annotation for intelligent textbooks. Technol. Knowl. Learn. 1–22 (2021). https://doi.org/10.1007/s10758-021-09544-z

  16. Weragama, D., Reye, J.: The PHP intelligent tutoring system. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS (LNAI), vol. 7926, pp. 583–586. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-39112-5_64

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Volgograd State Technical University, Lenin Ave, 28, Volgograd, 400005, Russia

    Yaroslav Kamennov, Oleg Sychev & Yulia Orlova

Authors
  1. Yaroslav Kamennov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Oleg Sychev
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yulia Orlova
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Oleg Sychev .

Editor information

Editors and Affiliations

  1. Georgia State University, Atlanta, GA, USA

    Scott Crossley

  2. University of Craiova, Craiova, Romania

    Elvira Popescu

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kamennov, Y., Sychev, O., Orlova, Y. (2022). Covering Possible Reasoning Errors for Intelligent Tutoring Systems: Order of Expression Evaluation Case. In: Crossley, S., Popescu, E. (eds) Intelligent Tutoring Systems. ITS 2022. Lecture Notes in Computer Science, vol 13284. Springer, Cham. https://doi.org/10.1007/978-3-031-09680-8_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-09680-8_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-09679-2

  • Online ISBN: 978-3-031-09680-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation