L’ANALISI DEI TRACCIATI DELL’USO DEI COMPUTER PER SUPPORTARE IL COINVOLGIMENTO DEGLI STUDENTI NELLE ATTIVITÀ DI LABORATORIO
Barra laterale articolo
Pubblicato
apr 1, 2019
Contenuto principale articolo
Abstract
La attività laboratoriali costituiscono oggi una parte significativa delle esperienze didattiche degli studenti. Di conseguenza, è interessante osservare come poter meglio supportare tali attività usando le tecnologie digitali. In questo articolo, gli autori presentano un approccio basato sulle Famiglie Microsoft e sulle reti neurali artificiali che consente di analizzare i tracciati dell’uso dei computer nel laboratorio per identificare gli studenti in difficoltà e allertare docenti e tutor per attuare eventuali azioni correttive. Questo lavoro dimostra come le reti neurali artificiali consentano l’analisi delle attività degli studenti anche al di fuori di un Learning Management System e senza aver alcuna cognizione di relazioni algoritmiche tra tali tracciati e le possibili future performance.
Dettagli articolo
Sezione
Articoli - Numero speciale
Questo lavoro è fornito con la licenza Creative Commons Attribuzione - Non commerciale 4.0 Internazionale.
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Riferimenti bibliografici
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Bishop, C. M., (2006). Pattern recognition and Machine Learning. New York, NY, USA: Springer-Verlag.
Brookhart, S. (2013). The use of teacher judgement for summative assessment in the USA. Assessment in Education: Principles, Policy & Practice, 20(1), 69-90. doi: 10.1080/0969594X.2012.703170
Brown, M. (2011). Learning Analytics: The coming third wave. Louisville, CO, USA: EDUCAUSE Learning Initiative.
Chatti, M. A., Dyckhoff, A. L., Schroeder, U., & Thüs, H. (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning, 4(5-6), 318-331. doi: 10.1504/IJTEL.2012.051815
Cooper, A. (2012). What is analytics? Definition and essential characteristics [White paper]. CETIS Analytics series 1(5). Manchester, UK: The University of Bolton.
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Gaeta, M., Marzano, A., Miranda, S., & Sandkuhl, K. (2017). The competence management to improve the learning engagement. Journal of Ambient Intelligence and Humanized Computing, 8(3), 405-417. doi: 10.1007/s12652-016-0399-7
Lal, P. (2016). Designing Online Learning Strategies through Analytics. In F. J. García-Peñalvo & A. M. Seoane Pardo (Eds.), Online Tutor 2.0: Methodologies and Case Studies for Successful Learning (pp. 1-15). Hershey, PA, USA: IGI Global. doi:10.4018/978-1-4666-5832-5.ch001
Marzano, A., & Vegliante, R. (2017). Training to teach: the laboratory experience of General Didactic and Educational Technology at the University of Salerno. Formazione & Insegnamento, 1, 283-303.
Miranda, S., & Ritrovato, P. (2015). Supporting Learning Object Repository by automatic extraction of metadata. Journal of e-Learning and Knowledge Society, 11(1), 43-54.
Pardo, A., & Kloos, C. D. (2011). Stepping out of the box: towards analytics outside the learning management system. In Proceedings of the 1st International Conference on Learning Analytics and Knowledge (LAK '11). ACM, New York, NY, USA, 163-167. doi: 10.1145/2090116.2090142
Persico, D., & Pozzi, F. (2015). Informing learning design with learning analytics to improve teacher inquiry. British Journal of Educational Technology, 46(2), 230-248. doi: 10.1111/bjet.12207
Sampson, D. (2016). Learning Analytics: Analyze your lesson to discover more about your students, ELearning Industry. Retrieved from https://elearningindustry.com/learning-analytics-analyze-lesson
Scriven, M. (1967). The methodology of evaluation. In R. W. Tyler, R. M. Gagné, & M. Scriven (Eds.), Perspectives of curriculum evaluation (pp.39-83). Chicago, IL, USA: Rand-McNally.
Sah, M., & Hall, W. (2009). Building and managing personalized semantic portals. In Proceedings of the 16th International Conference on World Wide Web, 1227-1228.
Sergis, S., & Sampson, D. (2017). Teaching and Learning Analytics to support Teacher Inquiry: A Systematic Literature Review. In A. Peña-Ayala (Ed.), Learning Analytics: Fundaments, Applications, and Trends (pp. 25-63). New York, NY, USA: Springer.
Siemens, G., & Baker, R. (2012). Learning analytics and educational data mining: Towards communication and collaboration. In S. Buckingham Shum, D. Gašević, & R. Ferguson (Eds.), LAK '12 Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 252-254). New York, NY, USA: ACM. doi: 10.1145/2330601.2330661
Trent, R. (June 29, 2015). Microsoft rolls out changes to family safety, renamed to Microsoft family. ITProToday. Retrieved from http://www.itprotoday.com/windows-server/microsoft-rolls-out-changes-family-safety-renamed-microsoft-family
Weurlander, M., Söderberg, M., Scheja, M., Hult, H., & Wernerson, A. (2012). Exploring formative assessment as a tool for learning: students’ experiences of different methods of formative assessment. Assessment & Evaluation in Higher Education, 37(6), 747-760. doi: 10.1080/02602938.2011.572153
Barile, S., Magna L., Marsella, M., & Miranda, S. (1999). A marketing decision problem solved by application of neural networks”, Proceedings of Third International Conference on Computational Intelligence and Multimedia Applications ICIIMA (September 1999).
Bishop, C. M., (2006). Pattern recognition and Machine Learning. New York, NY, USA: Springer-Verlag.
Brookhart, S. (2013). The use of teacher judgement for summative assessment in the USA. Assessment in Education: Principles, Policy & Practice, 20(1), 69-90. doi: 10.1080/0969594X.2012.703170
Brown, M. (2011). Learning Analytics: The coming third wave. Louisville, CO, USA: EDUCAUSE Learning Initiative.
Chatti, M. A., Dyckhoff, A. L., Schroeder, U., & Thüs, H. (2012). A reference model for learning analytics. International Journal of Technology Enhanced Learning, 4(5-6), 318-331. doi: 10.1504/IJTEL.2012.051815
Cooper, A. (2012). What is analytics? Definition and essential characteristics [White paper]. CETIS Analytics series 1(5). Manchester, UK: The University of Bolton.
De-la-Fuente-Valentìn, L., Corbi, A., Crespo, R. G., & Burgos, D. (2015). Learning Analytics. In M. Khosrow-Pour (Ed.), Encyclopedia of Information Science and Technology, Third Edition (pp. 2379-2387). Hershey, PA: Information Science Reference. doi: 10.4018/978-1-4666-5888-2.ch231
Gaeta, M., Marzano, A., Miranda, S., & Sandkuhl, K. (2017). The competence management to improve the learning engagement. Journal of Ambient Intelligence and Humanized Computing, 8(3), 405-417. doi: 10.1007/s12652-016-0399-7
Lal, P. (2016). Designing Online Learning Strategies through Analytics. In F. J. García-Peñalvo & A. M. Seoane Pardo (Eds.), Online Tutor 2.0: Methodologies and Case Studies for Successful Learning (pp. 1-15). Hershey, PA, USA: IGI Global. doi:10.4018/978-1-4666-5832-5.ch001
Marzano, A., & Vegliante, R. (2017). Training to teach: the laboratory experience of General Didactic and Educational Technology at the University of Salerno. Formazione & Insegnamento, 1, 283-303.
Miranda, S., & Ritrovato, P. (2015). Supporting Learning Object Repository by automatic extraction of metadata. Journal of e-Learning and Knowledge Society, 11(1), 43-54.
Pardo, A., & Kloos, C. D. (2011). Stepping out of the box: towards analytics outside the learning management system. In Proceedings of the 1st International Conference on Learning Analytics and Knowledge (LAK '11). ACM, New York, NY, USA, 163-167. doi: 10.1145/2090116.2090142
Persico, D., & Pozzi, F. (2015). Informing learning design with learning analytics to improve teacher inquiry. British Journal of Educational Technology, 46(2), 230-248. doi: 10.1111/bjet.12207
Sampson, D. (2016). Learning Analytics: Analyze your lesson to discover more about your students, ELearning Industry. Retrieved from https://elearningindustry.com/learning-analytics-analyze-lesson
Scriven, M. (1967). The methodology of evaluation. In R. W. Tyler, R. M. Gagné, & M. Scriven (Eds.), Perspectives of curriculum evaluation (pp.39-83). Chicago, IL, USA: Rand-McNally.
Sah, M., & Hall, W. (2009). Building and managing personalized semantic portals. In Proceedings of the 16th International Conference on World Wide Web, 1227-1228.
Sergis, S., & Sampson, D. (2017). Teaching and Learning Analytics to support Teacher Inquiry: A Systematic Literature Review. In A. Peña-Ayala (Ed.), Learning Analytics: Fundaments, Applications, and Trends (pp. 25-63). New York, NY, USA: Springer.
Siemens, G., & Baker, R. (2012). Learning analytics and educational data mining: Towards communication and collaboration. In S. Buckingham Shum, D. Gašević, & R. Ferguson (Eds.), LAK '12 Proceedings of the 2nd International Conference on Learning Analytics and Knowledge (pp. 252-254). New York, NY, USA: ACM. doi: 10.1145/2330601.2330661
Trent, R. (June 29, 2015). Microsoft rolls out changes to family safety, renamed to Microsoft family. ITProToday. Retrieved from http://www.itprotoday.com/windows-server/microsoft-rolls-out-changes-family-safety-renamed-microsoft-family
Weurlander, M., Söderberg, M., Scheja, M., Hult, H., & Wernerson, A. (2012). Exploring formative assessment as a tool for learning: students’ experiences of different methods of formative assessment. Assessment & Evaluation in Higher Education, 37(6), 747-760. doi: 10.1080/02602938.2011.572153