This talk offers a critical account of methodological challenges facing interdisciplinary researchers seeking to understand learning at scale. Drawing on our research into learning in MOOCs, we argue that big data and small data, computational and qualitative approaches, are not, on their own, sufficient to extract meaningful insights into how people learn interact and learn in crowdbased settings. We offer constructive ways of addressing research challenges, providing concrete examples and strategies. This talk will discuss and argue for the affordances of adopting a pragmatic research paradigms, embracing multi-level exploration of data for furthering the state of the art. Please email email@example.com to register for this event
What is OxCrowd?
The OxCrowd Network brings together academics and students to share and discuss insights on methodological and theoretical challenges related to understanding contemporary crowdbased phenomena facilitated by digital technologies and platforms. From Citizen Science to Massive Open Online Courses (MOOCs) and crowdsourced cultural heritage collections, crowdbased phenomena facilitated by the internet are of increasing scientific interest across academic disciplines, and are gradually beomcing part of everyday life.
Each term, OxCrowd arranges 2-4 events, ranging from seminars with invited speakers to round table discussions of work-in-progress. Members of the network.
Aims & Objectives
The OxCrowd network aims to:
- Foster interdisciplinary research and collaboration.
- Showcase and discuss empirical research focusing on issues related to crowdbased knowledge and learning.
- Contribute to debates on how to combine qualitative methods and data science approaches.
Who should join the network?
OxCrowd creates a shared space for researchers and students across sociology, education, physics, information engineering, digital humanities, medicine and beyond. OxCrowd is for anyone with interst in crowdbased knowledge and learning, including practicioners.
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About the speakers