Transforming Engineering Education with Blended Learning at Università Politecnica delle Marche
MATLAB Grader and Live Editor Elevate Student Outcomes
“The resources helped shift their mindset from ‘completing the course’ to actively engaging with the subject. For us, this transformation is one of the most meaningful indicators of success.”
Key Outcomes
- Students show increased motivation, perceived usefulness of resources, and self-efficacy when digital tools are meaningfully integrated into course design with clear learning goals.
- A blended learning approach using MATLAB transforms engineering education by creating a dynamic environment where theory and practice continuously reinforce each other.
- MATLAB Grader and self-paced learning courses serve as catalysts for active learning, collaboration, and self-reflection, contributing to stronger engagement and better learning outcomes.
Professors at Università Politecnica delle Marche bridge theory and practice in a blended learning environment, improving learning outcomes.
At Università Politecnica delle Marche (UNIVPM) in Ancona, Italy, engineering education is undergoing a significant transformation. Faculty members have redesigned their approach to teaching the undergrad System Identification and Modeling course, creating a learning ecosystem where theory and practice continuously reinforce each other. The goal of their recent changes was driven by the desire to improve learning outcomes, foster deeper engagement, and better prepare students for the challenges of modern engineering.
The evolving expectations of students, who now expect seamless integration between digital and face-to-face environments, inspired the university to redesign the course from passive lectures to an engaging, interactive experience where digital tools serve as core learning components rather than mere add-ons.
“We chose MATLAB to create a learning ecosystem where theory and practice continuously reinforce each other,” explained Professors David Scaradozzi and Laura Screpanti. This blended methodology supports flexibility, strengthens conceptual understanding, enhances practical competence, and enables more personalized feedback.
MATLAB at the Core
Professors David Scaradozzi and Laura Screpanti integrated several tools to support the course's learning goals, including:
- MATLAB, installed on all lab computers through the university's campus-wide license, giving students full access for regular practice and exploration.
- Key toolboxes such as Statistics and Machine Learning Toolbox™, Control System Toolbox™, and System Identification Toolbox™. All of these were integrated into both the in-class and online components, providing students with the tools to perform analysis, build models, and run simulations.
- MATLAB Grader™ for monitoring progress and providing immediate feedback on coding exercises. Professor Screpanti said that the new course “extensively used MATLAB Grader to monitor progress and support formative assessment. It offered immediate feedback on coding exercises, helped instructors gauge class understanding, and provided a starting point for peer discussions and post-submission reviews.”
- MATLAB Live Editor for final lab assignments in the form of interactive Live Scripts, allowing students to combine code, visual outputs, and explanatory text.
Additionally, self-paced learning courses were incorporated directly into the university’s Moodle platform, enabling students to build foundational knowledge independently before class. According to Professor Scaradozzi, MATLAB Onramp helped students quickly gain programming basics, allowing in-class time to be used for reviewing prerequisite concepts like algebra and control theory.
This comprehensive suite of tools supported the course’s new learning strategies, where students encountered core concepts online first, then applied this knowledge through in-class discussions, problem-solving, simulations, and lab activities.
Measuring Success and Impact
Pre- and post-course questionnaires revealed significant improvements in students’ perceptions, showing increased appreciation for the blended methodology, greater motivation due to authentic assessment methods, and higher self-efficacy as students felt more competent and confident.
During final exams and oral discussions, students specifically highlighted their appreciation for how the course brought together theory, MATLAB Grader exercises, and lab experience.
Professor Screpanti added that after the course was overhauled, students were “spending more time than required on solving exercises, not out of obligation, but out of genuine interest. The resources helped shift their mindset from ‘completing the course’ to actively engaging with the subject. For us, this transformation is one of the most meaningful indicators of success.”
Readers seeking a more in-depth look at the technical content of the course can review Professors Scaradozzi and Screpanti’s recently published conference paper.
