Women, Research & Digital Learning

For me, doing research is first and foremost a very concrete thing: to put method, depth and meaning inside innovation.
It's been part of my daily life for years. Working in R&D in digital learning means bringing together multiple dimensions: technological evolution, training processes and – above all – the real experience of people learning.

In my role, I have had the privilege of collaborating with researchers and university professors in very diverse fields: from computer engineering to statistics, from mathematics to physics, all the way to organizational governance and HR processes.

The true value?
Time dedicated to analysis and reflection, which is often missing in daily work. And that's where lasting innovation is born.

The meeting point is a delicate balance.
I come from the design of digital learning and edtech courses, but I've also worked in delivery, tutoring, blended projects, gamification, VR... and complex projects where technology is just "one piece" of the puzzle.

Today I deal with educational innovation with a very clear approach:
🔹 first the learning process
🔹 then the tools

If we reverse the order, the instructional design loses strength… and in the end it doesn't work.

I wonder: “What real problem does it solve?”
And even before that: “Are we defining that problem well?”

Because the most important, and often underestimated, phase is precisely this: defining the need for innovation.
We work hard on the "research problem": understanding what's really needed and comparing it with the scientific state of the art. This is where the foundations for solid innovation are laid.

The fashions.
Innovation requires curiosity, of course, but also clarity. knowledge of training processes to distinguish between the “wow effect” and structural, effective, long-lasting innovations.

In many cases, innovation is a technical job, but it is also a job of:

• process review
• evolution of skills
• change of mindset

And above all: a rethinking of the learning experience of the individual participant.
And that's what makes my work always stimulating.

I would say that my job is to transform curiosity and research into applicable solutions.
I'm the Innovation Manager at Piazza Copernico: a multidisciplinary team of developers and data scientists, working alongside researchers and universities to integrate diverse skills into innovation projects.

Every day means:
📌 read, analyze, compare
📌 design and experiment
📌 check what really works
📌 transform research into systems and tools that have an impact

Definitely dedicating the right amount of time to the research phase. In our area, we read articles, study, and compare the state of the art. Someone once told us: "It feels like you're talking to a university department.. "

Look: for us, that's a compliment. Because that part is the most precious.

And it's not just "taking from research": it's a two-way exchange. We share results with white papers and articles, participate in conferences, contribute to environments like hugging face.

And one thing I'm particularly proud of is that, over the years, we've made our AI tools available to students, graduate students, and university departments for free.
Because true innovation grows when knowledge circulates.

The risk is building systems that “seem innovative” but don’t actually improve learning.
Without method, you lose your way: you chase technology instead of governing it.

And AI, from this point of view, is a huge lever… but it must be managed responsibly.

Research forces you to do one thing: stop and think.
It forces you to define the problem well, to confront evidence, to plan with awareness.
And this helps companies not only innovate… but do so sustainably, with robust and scalable models.

We're working on a lot of things related to enabling learning with AI tools.
Among the hottest topics there is certainly adaptability, and along with it the governance of adaptive projects.
However, I can't reveal too much about this yet: we've been experimenting with a university department since July 2025 and will share the results soon.
What I can say is that the point always remains the same: first the learning process, then the instrument.

In Piazza Copernico we made a precise choice: to develop AI with a setting based on transparency, confidentiality, and compliance with the AI ​​Act.

We want:

• choose the best models for each use case
• without losing control over interactions
• working on validated content
• ensuring system governance

For us, innovating also means protecting, governing, and making sustainable.

More and more central.
Because the industry is becoming more complex: between AI, data, personalization, and new people's expectations, solid skills and vision are needed.

The future is not “more technology”. It is best method.

I would tell you to cultivate two things:
✨ curiosity
✨ penalty

Curiosity opens up new avenues for you, while discipline allows you to build something that lasts.

And above all: there's no need to choose between science and education. Today, in digital learning, these two worlds are constantly intertwining.