Where we come from, where we are going

We need to create an Agorá, a space to discuss this issue, because it has “neither face nor eyes”.

Yes, initially, when following the emerging research literature on the subject; and mainly when reached by several scandals and unclear feelings in the field of artificial intelligence, it became more and more necessary to do something that humans do in front of the problem: to dialogue. Talk, exchange ideas, build knowledge, generate collective intelligence.

But also, to activate us, to act, to be an activist of change, in conditions in which conflicts of interest seem to be played, and also dilemmas.

How far will we let process automation and artificial intelligence go? Where do we have to stop? And how do we deal with this problem in education?

  • Because the lack of reflection leaves us alone. In front of the monster without a face or eyes.
  • Because we end up making mistakes, being techno-enthusiasts or techno-critics, naively embracing technologies that contain risks for our students, or wasting opportunities to improve educational quality.

And here we are, aiming to generate spaces to ask questions and share answers.

Our initial questions have been:

  • What type of data is collected in specific institutional cases and what are the subsequent conceptual and pedagogical foundations needed to process this data?
  • What problems of data usability and data visualizations (ie, learning control panels) have been observed over one or more cycles of authentic evaluation?
  • How do teachers approach pedagogical practices based on available data? How do you navigate the abundance of data, in institutional and social contexts of digital learning?
  • How do students approach their learning processes through data-based devices and resources? How do you navigate the abundance of data, in institutional and social contexts of digital learning?
  • Is there a critical awareness about the visibility and use of institutionalized and social data?
  • What types of skills and abilities are required to search, analyze, adopt and share data related to the teaching and learning processes in Higher Education?
  • How can data and interpretations of data be shared to foster the science of open education and open educational practices?

We do not want anyone to feel limited by these questions. One of the wonderful things about dialogue is the possibility of constantly evolving personal positions and joint knowledge, shaping problems to the point of understanding, designing and developing solutions. And also share those solutions.

Where do we start such an enterprise?

Well, from the establishment of this space and its instruments, a complex ecosystem in which our own learning ecologies will flourish, as collections of resources, implementation of practices and/or cure of relationships to give face and eyes to the social drama and turn it into a positive, creative synergy.

Published by jraffaghelli

Professor at the Faculty of Education and Psychology (Universitat Oberta de Catalunya). PhD in Education and Cognitive Science (Ca' Foscari University of Venice) Master in Adult Education (Ca' Foscari University of Venice) Degree in Psychology (University of Buenos Aires)

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: