Let's talk about R&I

Juliana Raffaghelli, Education and ICT researcher: "We need to learn how to deal with the use and abuse of our data"

Rubn Permuy
Edul@b researcher

What is your academic background?

I studied psychology at the University of Buenos Aires and became involved in the communication sciences field, more specifically in psychological intervention in organizational learning contexts and in transformation processes in social settings. I’m interested in individual learning as a fundamental aspect of emancipation and as an ability to acquire greater levels of freedom through knowledge.

I went to Ca’ Foscari University in Venice in 2003 with a research group working in education sciences and training processes for adults. I completed a master’s degree in capacity building and organizational development processes before later working on an international project in Latin America. I also then started working towards a PhD on the processes of creating a professional identity in a global context and the influence of technology. During this time, I discovered e-learning as a useful tool for training adults in both professional and social contexts, beginning a labour of love.

What has your research background involved?

As a researcher I focused on processes of constructing identity in digital environments, exploring education technologies in the contexts of training and adult learning. Back when I was starting out as a researcher, concepts such as personalization of learning environments, online communities of practice and e-learning were a common topic. They began experimenting with a series of devices to help analyse their impact on training processes, using learning management systems and Web 2.0 platforms, a set of open-source tools. Later, social networks came into play.

Those were utopian years when digital and educational technologies were seen as an instrument for access, emancipation, collaboration and development of unprecedented human potential. However, people are now talking about data slavery, arguing that a lack of literacy when it comes to these data can prevent us from using the data that we create digitally as individuals. These data range include those generated by technologies that intervene in our daily lives and services we use in the workplace. This intervention increases with artificial intelligence, such as algorithms, which guide our life choices.

Why did you choose the UOC?

I was interested in the UOC because my work has always followed two paths: adult learning processes in digital literacy and methodological reflection on education technologies and education sciences. While I was working at the University of Trento I met Albert Sangr, and I later joined the Edul@b research group with him. I was attracted to the UOC as it’s a fully online university with a highly innovative and open approach, and because of its track record in inclusion and adult education. It seemed like a giant laboratory where I could further develop my research interests.

You are currently working on a research project that is funded by the Ramn y Cajal programme, an initiative by the Ministry of Science, Innovation and Universities. What does this work involve?

Albert and I want to focus this project on academics and on datafication as an emerging phenomenon. The work of academics has a profound impact on society in terms of using open data to disseminate information and reflect on the use of data in their students’ learning processes. The project will last five years, and the first exploratory phase will look at how data is used in academic work. The second phase will offer us a deeper understanding of the practices that enable academics to transform and become empowered as subjects of change in their relations with students. Lastly, a third phase will involve developing ongoing learning and training tools, which in technical terms is called faculty development.

What can we do about the data slavery you mentioned earlier?

The data phenomenon requires a new literacy process which starts in primary school. If we ask ourselves questions like what is an algorithm, we realize that before understanding the mathematics of the algorithm we must also understand its social background. When algorithms are used to guide social services, someone decides who to prioritize for these services. The same thing happens with learning analytics: when I develop a dashboard, which is a system for visualizing the data on a learning process, I am a priori making a pedagogical decision about what data this student or teacher can see. This is why datafication concepts need to be understood, taking into account the impact they have from as early as primary school. Within these concepts there is a technical element to do with statistics, preparation and visualization. There is also the graphic element of data storytelling, which refers to the creativity related to data use and data journalism. But most important is the critical aspect, which traces back to studies carried out in the 1960s. The technological processes are not natural; there is always a social basis, of control and power, which is shaping the technological materiality of data. This is the critical aspect I’m researching, which is why we proposed beginning with academics, as they are the ones who influence students and can create cascading activation processes that will reach various levels of society.

In other words, we have to be more aware of how our data is used.

We have to raise awareness through education. It’s the only social discipline focused on engineering the processes of change, as it considers aspects ranging from individual learning psychology and institutional processes, to the objectives of social transformation. All these aspects converge through design, choosing the best methods for the student’s progress. Education is a complex, multidisciplinary science that is still being developed, so I propose that it should be a fundamental part of the datafication processes.

Learning analytics is an emerging phenomenon for applying algorithms to selected data collected from learning platforms. Social networks are another example, which also use algorithms to create visualizations.

We have to make the population literate in data analysis. The University of Edinburgh has a great initiative, which opened a space for reflecting on the types of data used to make decisions and, through a participatory process, deciding how they are used and why.

In other words, there should be more emphasis on the technological rather than the social issue.

Exactly. There is a European Commission report from 2016 on learning analytics that reveals that there are diverse proposals for visualization system models for reading algorithms and data created in learning processes, but little reflection on the critical aspects of technologies and few policies at institutional level, especially at the school and university level. An example of the impact of datafication on education is the prediction of a student’s failure, which is not just a statistic, but also a pedagogical decision about how the teacher will support him or her. Technology also identifies which behaviours will translate to the student’s success based on the data.

What book would you recommend to help us better understand this field?

I would suggest Jorge Luis Borges’s works The Garden of Forking Paths and The Library of Babel, because he argues that we are navigating, making decisions and constructing meaning along this journey, as is happening with datafication in education. I’m also inspired by Blue’s street art, static graffiti that creates dynamic processes and very striking videos in which we can see how the work develops beyond the materiality of a wall. It exists in the digital, the intangible, and the wall is just the material foundation. This is a big metaphor for digitalization and how we relate to it. Through the film The Matrix we can see parallels with the theme of datafication. The pioneers who travel and become aware of a manipulation of the matrix could be understood as the educators or activists that are trying to raise awareness of the materiality of data and their possible manipulation.