In this study we analyzed the curricula of 65 university students to investigate the impact of activities progression on student performances. Clustering curricula based on activity order and type we discovered a significant incidence on performance, validating the predictive power of curricula. Nevertheless, we discovered that the characterization of clusters is mainly due to non mandatory activities, selected by a student to personalize his curriculum, while activity order is very less relevant. This observation rejects the idea that activities progression has impact on performance, resulting rather as a consequence of student choices.
On the predictive power of university curricula / A. Azzini, P. Ceravolo, N. Scarabottolo, E. Damiani - In: Global Engineering Education Conference (EDUCON)[s.l] : IEEE, 2016. - pp. 1-4 (( convegno Global Engineering Education Conference tenutosi a Abu Dhabi nel 2016.
On the predictive power of university curricula
A. AzziniPrimo
;P. CeravoloSecondo
;N. ScarabottoloPenultimo
;E. Damiani
2016
Abstract
In this study we analyzed the curricula of 65 university students to investigate the impact of activities progression on student performances. Clustering curricula based on activity order and type we discovered a significant incidence on performance, validating the predictive power of curricula. Nevertheless, we discovered that the characterization of clusters is mainly due to non mandatory activities, selected by a student to personalize his curriculum, while activity order is very less relevant. This observation rejects the idea that activities progression has impact on performance, resulting rather as a consequence of student choices.Pubblicazioni consigliate
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