I am broadly interested in what I call

the foundations of learning about learning

and how they relate to

the design of socio-technical systems that improve learning.

Let’s break that up…

learning about learning can come in a number of forms:

• • A researcher learning about how people learn (i.e., learning sciences)

  • A machine learning algorithm that makes inferences about how people learn (i.e., student modeling)

  • A teacher drawing insights about how students in their classroom are learning (e.g., via learning analytics)

foundations refer to the philosophical, historical, sociological, ethical, and critical perspectives that underlie a field

…so foundations of learning about learning can include studying:

• • the equitability of student modeling and learning analytics algorithms [see this paper]

  • the history of the development of learning theories in the learning sciences and artificial intelligence [see this paper]

  • how beliefs about learning and knowledge influence different approaches to learning sciences research [see this paper and this paper]

  • the epistemologies and beliefs that underlie student models [see this paper]

  • the theoretical limits of student modeling [see this paper]

this interrelates with my interest in the design of socio-technical systems that improve learning, which includes designing algorithms and technologies that:

• • combine insights from people (e.g., students, teachers, researchers) and machines [see my thesis]

  • are equitable

  • are informed by critical perspectives on (human and machine) learning

  • are informed by the history of educational technology [see this blog post]

If you are interested in any of these areas, feel free to contact me at doroudis@uci.edu!