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Using Scratch to Improve Undergraduate Students’ Skills on Artificial Intelligence

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International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019) (CISIS 2019, ICEUTE 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 951))

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Abstract

This paper presents several educational applications in Scratch that are proposed for the active participation of undergraduate students in contexts of Artificial Intelligence. The students are asked to understand the mathematics involved in an automatic clustering algorithm and two simple neural networks for data learning. They must practice with the implementation, following closely the short instructions and mathematical theory provided by teachers.

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References

  1. Arimoto, T., Sato, Y.: Rebuilding public trust in science for policy-making. Science 337(6099), 1176–1177 (2012)

    Article  Google Scholar 

  2. Haerlin, B., Parr, D.: How to restore public trust in science. Nature 400(6744), 499 (1999)

    Article  Google Scholar 

  3. MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability. Statistics, vol. 1, pp. 281–297. University of California Press, Berkeley (1967)

    Google Scholar 

  4. McCulloch, W.S., Pitts, W.: A logical calculus of the ideas immanent in nervous activity. Bull. Math. Biophys. 5(4), 115–133 (1943)

    Article  MathSciNet  Google Scholar 

  5. Nielsen, M.A.: Neural Networks and Deep Learning. Determination Press (2015)

    Google Scholar 

  6. OECD: Scientific advice for policy making: the role and responsibility of expert bodies and individual scientists. Technical report 21, OECD Science, Technology and Industry Policy Papers (2015)

    Google Scholar 

  7. Rosenblatt, F.: The perceptron: a probabilistic model for information storage and organization in the brain. Psychol. Rev. 65(6), 386 (1958)

    Article  Google Scholar 

  8. Stone, P., Brooks, R., Brynjolfsson, E., Calo, R., Etzioni, O., Hager, G., Hirschberg, J., Kalyanakrishnan, S., Kamar, E., Kraus, S., et al.: Artificial intelligence and life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel (2016)

    Google Scholar 

  9. Woodford, C.: How neural networks work - a simple introduction (2016)

    Google Scholar 

  10. Resnick, M., Maloney, J., Monroy-Hernndez, A., Rusk, N., Eastmond, E., Brennan, K., Kafai, Y.: Scratch: programming for all. Commun. ACM 52(11), 60–67 (2009)

    Article  Google Scholar 

  11. AI in the UK: ready, willing and able? Technical report. Select Committee on Artificial Intelligence. House of Lords (2018)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. University of the Basque Country (UPV-EHU), Donostia, Spain

    Julian Estevez, Gorka Garate, Jose Manuel López-Guede & Manuel Graña

Authors
  1. Julian Estevez
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  2. Gorka Garate
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  3. Jose Manuel López-Guede
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  4. Manuel Graña
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Corresponding author

Correspondence to Julian Estevez .

Editor information

Editors and Affiliations

  1. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  2. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  3. University of Salamanca, Salamanca, Spain

    José António Sáez Muñoz

  4. Department of Industrial Engineering, University of A Coruña, A Coruña, Spain

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Estevez, J., Garate, G., López-Guede, J.M., Graña, M. (2020). Using Scratch to Improve Undergraduate Students’ Skills on Artificial Intelligence. In: Martínez Álvarez, F., Troncoso Lora, A., Sáez Muñoz, J., Quintián, H., Corchado, E. (eds) International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019). CISIS ICEUTE 2019 2019. Advances in Intelligent Systems and Computing, vol 951. Springer, Cham. https://doi.org/10.1007/978-3-030-20005-3_32

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