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Analysing students' behavioural strategies navigating exploratory learning environments

Venue: Birkbeck Main Building

At the core of Piaget’s constructivism theory sits the idea that knowledge is created from learning experiences which are contextualised and personally meaningful. Exploratory learning environments provide the freedom necessary for individuals to better identify what they already know in order to construct on top of it using the resources around them - tools, people and learning goals. Vygotsky's zone of proximal development theory as well as our current understanding of the workings of the short and long term memory functions require us to support the learners with scaffolded feedback through the exploratory learning activities. In such a context, how can we best enhance each individual’s freedom of exploration, balancing it out with relevant guidance towards the learning goals? Providing adaptive support in such exploratory, often dynamic and interactive environments is challenging yet doing it successfully would enable a much more intuitive way of learning.

Using learning analytics, this talk presents a case study based on data collected through video and audio recordings, as well as physical computing devices’ activity log data, which will explore the following issues:

  1. What are the strategies students employ in navigating these exploratory learning experiences from an individual perspective?
  2. What are the parameters which impact the student's ability to effectively operate and learn in such environments?
  3. Can these parameters inform a criteria for well-designed exploratory environments based on which these can be evaluated by and iterated on?
  4. What specific data visualisations can be generated in order to assist teachers help their students be effective exploratory learners?
  5. To what extent can learners be guided towards maximising the benefits of exploratory environments, mould these to their advantage and push the boundaries of their learnings?


I am Ph.D. student funded by a Bloombury Consortium Studentship between University College London (lead institution) and Birkbeck, supervised by Professors Rose Luckin and Alex Poulovassilis. My research is centered around learning analytics - applying various data analytics methods including machine learning to data collected from educational software and learning environments. I focus on collecting data and analyzing students' behaviours navigating exploratory learning spaces, strategies of overcoming challenges in dynamic and interactive environments and the degree to which students are able to interact with their surroundings (tools, peers, context) to guide their own learning.

For part of my research I collaborate with SAM Labs, who produce app-enabled construction kits, designed for people of all ages to learn STEM, play, and create with technology and the Internet of Things. For my data analysis I combine SAM data with video and audio recordings and integrate educational theory to extract relevant features and measurements which help teachers and students maximise the efficacy of learning projects.

I also run the 'AI in Education' the UCL Knowledge Lab reading group, and co-founded the UCL School Research Competition with a fellow researcher.

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