Skip to main content

Using Brain Computer Interaction to Evaluate Problem Solving Abilities

  • Conference paper
  • First Online:
Augmented Cognition (HCII 2021)

Abstract

The ability to solve problems is increasingly important in today’s world, not only for good school performance but also to be successful in today’s world, being one of the most desired skills for the XXI century. However, the existence of tasks with an inadequate cognitive load may discourage the individuals involved in it. Thus, we believe that the effective monitoring of this capacity must be well monitored. To this end, we started an experiment made up of 2 different samples to assess the ability to solve logical problems through the testing of Raven’s Progressive Matrices. The research project developed and presented in this paper sought to assess differences in the ability to solve logical problems considering brain activity when solving them. Therefore, EEG was used to infer the cognitive workload of individuals. Our main interest was to identify specific ERP waveforms, namely the feedback-related negativity (FRN) component about the correctness of the students answers to each question.

The analysis presented in this work shows that it is possible to find the FRN potential associated to a greater negativity meaning a greater astonishment for an unconsciousness of the wrong answer. Therefore, this aspect is related with the performance of the participant based on their knowledge of the abstract principle underlying the task. Despite having only 2 samples with few students, these data indicate that our findings demonstrate that cognitive load can be predicted using these features, even using a low number of channels.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
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. Koczwara, A., Patterson, F., Zibarras, L., Kerrin, M., Irish, B., Wilkinson, M.: Evaluating cognitive ability, knowledge tests and situational judgement tests for postgraduate selection. Med Educ. 46, 399–408 (2012). https://doi.org/10.1111/j.1365-2923.2011.04195.x

    Article  Google Scholar 

  2. Rindermann, H., Neubauer, A.: Processing speed, intelligence, creativity, and school performance: testing of causal hypotheses using structural equation models. Intelligence 32, 573–589 (2004). https://doi.org/10.1016/j.intell.2004.06.005

    Article  Google Scholar 

  3. Wang, T., Ren, X., Altmeyer, M., Schweizer, K.: An account of the relationship between fluid intelligence and complex learning in considering storage capacity and executive attention. Intelligence 41, 537–545 (2013). https://doi.org/10.1016/j.intell.2013.07.008

    Article  Google Scholar 

  4. Kumar, N., Kumar, J.: Measurement of cognitive load in HCI systems using EEG power spectrum: an experimental study. Procedia Comput. Sci. 84, 70–78 (2016). https://doi.org/10.1016/j.procs.2016.04.068. ISSN 1877-0509

    Article  Google Scholar 

  5. Young, J.Q., Irby, D.M., Barilla-LaBarca, M.-L., et al.: Measuring cognitive load: mixed results from a handover simulation for medical students. Perspect. Med. Educ. 5(1), 24–32 (2015). https://doi.org/10.1007/s40037-015-0240-6

    Article  Google Scholar 

  6. Gomes, A., Assuncao Teixeira, A.R.A., Eloy, J., Mendes, A.J.: An Exploratory study of brain computer interfaces in computer science education. IEEE Revista Iberoamericana De Tecnologias Del Aprendizaje-Ieee Rita, 14(4), 152–161 (2019). https://doi.org/10.1109/rita.2019.2952273

  7. Penrose, L.S., Raven, J.C.: A new series of perceptual tests: preliminary communication. Br. J. Med. Psychol. 16(2), 97–104 (1936)

    Article  Google Scholar 

  8. Raven, J.: The raven progressive matrices tests: their theoretical basis and measurement model, chapter 1 (2016)

    Google Scholar 

  9. Raven, J.: The raven’s progressive matrices: change and stability over culture and time. Cogn. Psychol. 41, 1–48 (2000)

    Article  Google Scholar 

  10. Spearman, C.: “General intelligence,” objectively determined and measured. Am. J. Psychol. 15(2), 201 (1904)

    Article  Google Scholar 

  11. Binet, A.: New methods for the diagnosis of the intellectual level of subnormals. L’Annee Psychologique 12, 191–244 (1905)

    Google Scholar 

  12. Thatcher, R.W., North, D., Biver, C.: EEG and intelligence: relations between EEG coherence, EEG phase delay and power. Clin. Neurophysiol. 116, 2129–2141 (2005)

    Article  Google Scholar 

  13. Neubauer, A.C., Grabner, R.H., Fink, A., Neuper, C.: Intelligence and neural efficiency: further evidence of the influence of task content and sex on the brain-IQ relationship. Cogn. Brain Res. 25, 217–225 (2005)

    Article  Google Scholar 

  14. Fink, A., Neubauer, A.: EEG alpha oscillations during the performance of verbal creativity tasks: differential effects of sex and verbal intelligence. Int. J. Psychophysiol. 62(1), 46–53 (2006)

    Article  Google Scholar 

  15. Miltner, W.H.R., Braun, C.H., Coles, M.G.H.: Event-related brain potentials following incorrect feedback in a time-estimation task: evidence for a ‘generic’ neural system for error detection. Cogn. Neurosci. 9(6), 788–798 (1997)

    Article  Google Scholar 

  16. Santos, I.M., et al.: ERP correlates of error processing during performance on the Halstead category test. Int. J. Psychophysiol. 106, 97–105 (2016). https://doi.org/10.1016/j.ijpsycho.2016.06.010

    Article  Google Scholar 

  17. Ferrez, W., Millán, J.D.R.: Error-related EEG potentials generated during simulated brain-computer interaction. IEEE Trans. Biomed. Eng. 55(3), 923–929 (2008)

    Article  Google Scholar 

  18. Emotiv (2021). https://www.emotiv.com/product/emotiv-epoc-14-channel-mobileeeg/. Accessed 25 Jan 2021

  19. Delorme, A., Makeig, S.: EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134, 9–2 (2004)

    Article  Google Scholar 

  20. Sanei, S., Chambers, J.A.: EEG Signal Processing (2013). ISBN 9780470025819. https://doi.org/10.1002/9780470511923

  21. Kappenman, E.S., Luck, S.J.: The Oxford Handbook of Event-Related Potential Components (2012). ISBN 9780199940356. https://doi.org/10.1093/oxfordhb/9780195374148.001.0001

  22. Walsh, M.M., Anderson, J.R.: Learning from experience: event-related potential correlates of reward processing, neural adaptation, and behavioral choice. Neurosci. Biobehav. Rev. 36, 1870–1884 (2012)

    Article  Google Scholar 

  23. Zander, T.O., Kothe, C.: Towards passive brain-computer interfaces: applying brain-computer interface technology to human-machine systems in general. J. Neural Eng. 8(2) (2011). https://doi.org/10.1088/1741-2560/8/2/025005.025005

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ana Rita Teixeira .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Teixeira, A.R., Rodrigues, I., Gomes, A., Abreu, P., Rodríguez-Bermúdez, G. (2021). Using Brain Computer Interaction to Evaluate Problem Solving Abilities. In: Schmorrow, D.D., Fidopiastis, C.M. (eds) Augmented Cognition. HCII 2021. Lecture Notes in Computer Science(), vol 12776. Springer, Cham. https://doi.org/10.1007/978-3-030-78114-9_6

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78114-9_6

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78113-2

  • Online ISBN: 978-3-030-78114-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics