The project "Algorithmically: from problem-solving to computer science" is a research-action project funded and carried out in the academic year 2022-23 by the Scientific High School “Leonardo da Vinci” (Trento, Italy), in collaboration with the University of Trento. The goal of the project was to validate the PRIMM (Predict, Run, Investigate, Modify, Make) methodology for teaching programming, which subverts the traditional approach based on early program writing. Instead, students are encouraged to read and understand segments of code before writing their own, emphasising a "reading before writing" approach. The teaching experimentation was applied in 5 second classes of the high school, with 4 control group classrooms (190 students and 9 classes). To understand the effectiveness of this new methodology, the design was a Pre-Test and Post-Test, with a test aiming at understanding skills and knowledge and another based on the Intrinsic Motivation Inventory (IMI). The first iteration of this experimental teaching approach provides promising results but also indicates the need for refining the sample and some methods and procedures. However, there are significant findings: 1 PRIMM methodology proved to be slightly more effective than traditional teaching methods in terms of learning. 2 PRIMM methodology promotes Competence Perception, and its relationship with Competence Perception is confirmed, positive, and significant. 3 Competence Perception correlates with better computer science grades, so PRIMM might bring higher marks in Computer Sciences. The PRIMM approach’s integration into computer science teaching thus appears promising, but additional research and iterations are needed to optimise its effectiveness.
THE PRIMM METHOD FOR TEACHING PROGRAMMING: EXPERIMENTATION AND VALIDATION / Peserico, Giulia; Serafini, Maria; Voltolini, Francesca; Picasso, Federica; Agostini, Daniele; Fiore, Francesca; Serbati, Anna; Montresor, Alberto.. - ELETTRONICO. - (2023), pp. 7278-7282. (Intervento presentato al convegno ICERI 16th annual International Conference of Education, Research and Innovation tenutosi a Sevilla nel 13-15 novembre 2023) [10.21125/iceri.2023.1810].
THE PRIMM METHOD FOR TEACHING PROGRAMMING: EXPERIMENTATION AND VALIDATION
Peserico, Giulia;Serafini, Maria;Voltolini, Francesca;Picasso, Federica;Agostini, Daniele;Fiore, Francesca;Serbati, Anna;Montresor, Alberto.
2023-01-01
Abstract
The project "Algorithmically: from problem-solving to computer science" is a research-action project funded and carried out in the academic year 2022-23 by the Scientific High School “Leonardo da Vinci” (Trento, Italy), in collaboration with the University of Trento. The goal of the project was to validate the PRIMM (Predict, Run, Investigate, Modify, Make) methodology for teaching programming, which subverts the traditional approach based on early program writing. Instead, students are encouraged to read and understand segments of code before writing their own, emphasising a "reading before writing" approach. The teaching experimentation was applied in 5 second classes of the high school, with 4 control group classrooms (190 students and 9 classes). To understand the effectiveness of this new methodology, the design was a Pre-Test and Post-Test, with a test aiming at understanding skills and knowledge and another based on the Intrinsic Motivation Inventory (IMI). The first iteration of this experimental teaching approach provides promising results but also indicates the need for refining the sample and some methods and procedures. However, there are significant findings: 1 PRIMM methodology proved to be slightly more effective than traditional teaching methods in terms of learning. 2 PRIMM methodology promotes Competence Perception, and its relationship with Competence Perception is confirmed, positive, and significant. 3 Competence Perception correlates with better computer science grades, so PRIMM might bring higher marks in Computer Sciences. The PRIMM approach’s integration into computer science teaching thus appears promising, but additional research and iterations are needed to optimise its effectiveness.File | Dimensione | Formato | |
---|---|---|---|
PESERICO2023PRI.pdf
Solo gestori archivio
Descrizione: Peserico, G., Serafini, M., Voltolini, F., Picasso, F., Agostini, D., Fiore, F., Serbati, A, & Montresor, A. (2023). THE PRIMM METHOD FOR TEACHING PROGRAMMING: EXPERIMENTATION AND VALIDATION. In ICERI2023 Proceedings (pp. 7278-7282). IATED.
Tipologia:
Versione editoriale (Publisher’s layout)
Licenza:
Tutti i diritti riservati (All rights reserved)
Dimensione
148.64 kB
Formato
Adobe PDF
|
148.64 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione