Linda Burchiellaro
Linda Burchiellaro
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Linda Burchiellaro has a total of 6 co-authors. Here are the top co-authors by number of shared publications:
- Claudia Canali
University of Modena and Reggio Emilia
3 shared publications - Francesco Faenza
University of Modena and Reggio Emilia
3 shared publications - Cecilia Marchetti
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, 41125 Modena, Italy
1 shared publication - Mariane Joseph Anzeda
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, 41125 Modena, Italy
1 shared publication - Martina Casari
Department of Engineering “Enzo Ferrari”, University of Modena and Reggio Emilia, 41125 Modena, Italy
1 shared publication - Riccardo Mescoli
Informatics and Mathematics University of Modena and Reggio Emilia
1 shared publication
Latest Publications
- Open Access
- 6 November 2026
- Published by MDPI AG in Education Sciences
- Vol. 16 (11) , 1888
A Real-Time Collaborative Learning Platform Integrated with a Document Management System
The declining interest in STEM disciplines and the limitations of existing cloud-based collaborative tools, including restricted real-time collaboration, privacy concerns, and limited institutional integration, highlight the need for open-source, on-premises platforms that combine notebook-based computation with document management workflows, support synchronous editing, and preserve institutional control over data, access policies, and software environments without proprietary cloud services. This paper presents NextPyter, an open-source platform integrating Jupyter Notebooks with Nextcloud. Originally designed for research, it was adapted for educational use to enable real-time co-editing of computational notebooks within a familiar, file-centric environment. The platform underwent an exploratory evaluation through two university-level programming activities involving first- and second-year Computer Engineering students. The evaluation used the Perceived Usefulness (PU) construct of the Technology Acceptance Model (TAM), complemented by reflexive thematic analysis of open-ended responses. Quantitative results indicate high internal consistency of the PU scale in both cohorts (Cronbach’s = 0.94 and 0.86) and mean PU scores of 4.09 and 3.53, respectively, on a five-point scale. All participants considered the platform useful for learning. Qualitative findings highlight positive perceptions of peer interaction, collaborative coding, and experiential learning. These exploratory findings suggest that NextPyter may support collaborative notebook-based learning while preserving institutional data governance.- 6 November 2026
- Published by MDPI AG in Education Sciences
- Vol. 16 (11) , 1888
Open AccessA Real-Time Collaborative Learning Platform Integrated with a Document Management System
The declining interest in STEM disciplines and the limitations of existing cloud-based collaborative tools, including restricted real-time collaboration, privacy concerns, and limited institutional integration, highlight the need for open-source, on-premises platforms that combine notebook-based computation with document management workflows, support synchronous editing, and preserve institutional control over data, access policies, and software environments without proprietary cloud services. This paper presents NextPyter, an open-source platform integrating Jupyter Notebooks with Nextcloud. Originally designed for research, it was adapted for educational use to enable real-time co-editing of computational notebooks within a familiar, file-centric environment. The platform underwent an exploratory evaluation through two university-level programming activities involving first- and second-year Computer Engineering students. The evaluation used the Perceived Usefulness (PU) construct of the Technology Acceptance Model (TAM), complemented by reflexive thematic analysis of open-ended responses. Quantitative results indicate high internal consistency of the PU scale in both cohorts (Cronbach’s = 0.94 and 0.86) and mean PU scores of 4.09 and 3.53, respectively, on a five-point scale. All participants considered the platform useful for learning. Qualitative findings highlight positive perceptions of peer interaction, collaborative coding, and experiential learning. These exploratory findings suggest that NextPyter may support collaborative notebook-based learning while preserving institutional data governance. - Open Access
- 15 May 2026
- Published by Taylor & Francis in Computer Science Education
- p. 1-37
Computer science camps to reduce the gender gap: a proposal for effective design and impact evaluation
- 15 May 2026
- Published by Taylor & Francis in Computer Science Education
- p. 1-37
Open AccessComputer science camps to reduce the gender gap: a proposal for effective design and impact evaluation
- 15 October 2025
- Published by Polish Information Processing Society PTI in Annals of Computer Science and Information Systems
- Vol. 43, 499-506
ELEVATE-AI: Evaluation of Learning Environments Via Assessment Tools Enhanced by AI
- 15 October 2025
- Published by Polish Information Processing Society PTI in Annals of Computer Science and Information Systems
- Vol. 43, 499-506
ELEVATE-AI: Evaluation of Learning Environments Via Assessment Tools Enhanced by AI