Principles for an Effort-Aware System

  • David BañeresEmail author
Conference paper
Part of the Lecture Notes on Data Engineering and Communications Technologies book series (LNDECT, volume 13)


Learners require a certain effort to acquire a specific skill or competence. The invested effort can be affected by many factors as previous knowledge, abilities or time available for learning. The evaluation of the effort has been mainly related to cognitive science or instructional psychology due to the relation between effort and mental work. This paper focuses on how the effort can be estimated on e-learning systems. This information can enhance instructional process since teachers can analyze the total time learners invest on acquiring knowledge and they can adjust better the complexity of the course. The paper contributes on principles to design an effort-based system. Finally, a particular application to an intelligent tutoring system is performed.



This work was funded by the Spanish Government through the project: TIN2013-45303-P “ICT-FLAG: Enhancing ICT education through Formative assessment, Learning Analytics and Gamification”.


  1. 1.
    Schuman, H., Walsh, W., Olson, C., Etheridge, B.: Effort and reward: the assumption that college grades are affected by quantity of study. Soc. Forces 4, 945–966 (1985)CrossRefGoogle Scholar
  2. 2.
    Hill, L.: Effort and reward in college: a replication of some puzzling findings. In: James, W.N. (ed.) Replication research in the social sciences, pp. 139–149. Sage Publications, Inc, (1991)Google Scholar
  3. 3.
    Michaels, J.W., Miethe, T.D.: Academic effort and college grades. Soc. Forces 1, 309–319 (1989)CrossRefGoogle Scholar
  4. 4.
    Dobkin, C., Gil, R., Marion, J.: Skipping class in college and exam performance: evidence from a regression discontinuity classroom experiment. Econ. Educ. Rev. 4, 566–575 (2010)CrossRefGoogle Scholar
  5. 5.
    Kanfer, R., Ackerman, P.L., Murtha, T.C., Dugdale, B., Nelson, L.: Goal setting, conditions of practice, and task performance: a resource allocation perspective. J. Appl. Psychol. 79(6), 826 (1994)CrossRefGoogle Scholar
  6. 6.
    Hart, S.G., Staveland, L.E.: Development of NASA-TLX (Task Load Index): Results of empirical and theoretical research. Adv. Psychol. 52, 139–183 (1988)CrossRefGoogle Scholar
  7. 7.
    Paas, F.G., Van Merriënboer, J.J.: Variability of worked examples and transfer of geometrical problem-solving skills: a cognitive-load approach. J. Educ. Psychol. 86(1), 122 (1994)CrossRefGoogle Scholar
  8. 8.
    Gañán, D., Caballé, S., Clarisó, R., Conesa, J., Bañeres, D.: ICT-FLAG: a web-based e-assessment platform featuring learning analytics and gamification. Int. J. Web Inf. Syst. 13(1), 25–54 (2017)CrossRefGoogle Scholar
  9. 9.
    ADL-Co-Laboratories, “Experience API Version 1.0.3.” Last accessed 14 July 2017
  10. 10.
    Arnedo-Moreno, J., Baneres, D., Baró, X., Caballé, S., Guerrero, A.E., Mas, X, Porta, L., Prieto, J: ValID: a trust-based virtual assessment system. In: International Conference on Intelligent Networking and Collaborative Systems (INCoS), pp. 328–335 (2014)Google Scholar
  11. 11.
    Miguel, J., Caballé, S., Xhafa, F.: Intelligent data analysis for e-learning: enhancing security and trustworthiness in online learning systems. In: Intelligent Data-Centric Systems. Elsevier, Amsterdam (2016)Google Scholar
  12. 12.
    Iglewicz, B., Hoaglin, D.: How to detect and handle outliers. In: Mykytka, E.F. (ed.) The ASQC Basic References in Quality Control: Statistical Techniques, vol. 16 (1993)Google Scholar
  13. 13.
    Caroni, C., Karioti, V.: Detecting an innovative outlier in a set of time series. Comput. Stat. Data Anal. 46, 561–570 (2004)CrossRefzbMATHMathSciNetGoogle Scholar
  14. 14.
    Barnett, V., Lewis, T.: Outliers in Statistical Data, 3rd ed., Wiley (1994)Google Scholar
  15. 15.
    Toggl – Time Tracker. Last accessed 14 July 2017
  16. 16.
    Baneres, D., Clariso, R., Jorba, J., Serra, M.: Experiences in digital circuit design courses: a self-study platform for learning support. IEEE Trans. Learn. Technol. (IEEE TTL) 7(3), 1–15 (2014)Google Scholar

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.Open University of CataloniaBarcelonaSpain

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