Abstract
Programming has traditionally been an engineering competence, but recently it is acquiring significant importance in several areas, such as Life Sciences, where it is considered to be essential for problem solving based on data analysis. Therefore, students in these areas need to improve their programming skills related to the data analysis process. Similarly, engineering students with proven technical ability may lack the biological background which is likewise fundamental for problem-solving. Using hackathon and teamwork-based tools, students from both disciplines were challenged with a series of problems in the area of Life Sciences. To solve these problems, we established work teams that were trained before the beginning of the competition. Their results were assessed in relation to their approach in obtaining the data, performing the analysis and finally interpreting and presenting the results to solve the challenges. The project succeeded, meaning students solved the proposed problems and achieved the goals of the activity. This would have been difficult to address with teams made from the same field of study. The hackathon succeeded in generating a shared learning and a multidisciplinary experience for their professional training, being highly rewarding for both students and faculty members.
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Notes
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https://biodatauco.github.io/ (in Spanish).
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Acknowledgements
The teaching innovation project has been funded by the University of Cordoba with reference 2020-2-5003. This work has also been partially subsidised by the “Agencia Española de Investigación (España)” (grant reference: PID2020-115454GB-C22/AEI/10.13039/501100011033); the “Consejería de Salud y Familia (Junta de Andalucía)” (grant reference: PS-2020-780); and the “Consejería de Transformación Económica, Industria, Conocimiento y Universidades (Junta de Andalucía) y Programa Operativo FEDER 2014–2020” (grant references: UCO-1261651 and PY20_00074). David Guijo-Rubio’s teaching was funded by the University of Córdoba through grants to Public Universities for the requalification of the Spanish university system from the Ministry of Universities funded by the European Union - NextGenerationEU (Ref. UCOR01MS). The teaching of Víctor M. Vargas was funded by the Programa Predoctoral de Formación al Profesorado Universitario (FPU) of the Ministry of Science, Innovation and Universities (Ref. FPU18/00358). The teaching of Javier Barbero-Gómez was funded by the Programa Predoctoral de Formación de Personal Investigador (FPI) of the Ministry of Science, Innovation and Universities (Ref. PRE2018-085659). The teaching of José V. Die was funded by the H2020-MSCA-IF-2018 programme (Ref. 844431) and the Ramón y Cajal program (Ref. RYC2019-028188-I/AEI/10.13039/501100011033). The teaching of Pablo González-Moreno was funded by a Juan de la Cierva Incorporación contract (Ref. IJCI-2017-31733) and Plan Propio UCO 2020.
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Guijo-Rubio, D., Vargas, V.M., Barbero-Gómez, J., Die, J.V., González-Moreno, P. (2023). Hackathon in Teaching: Applying Machine Learning to Life Sciences Tasks. In: García Bringas, P., et al. International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022). CISIS ICEUTE 2022 2022. Lecture Notes in Networks and Systems, vol 532. Springer, Cham. https://doi.org/10.1007/978-3-031-18409-3_23
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