[on behalf of Christopher Brooks]
*Note: abstracts requested by June 1, see
http://replicate.education/edm18-workshop/
<http://replicate.education/edm18-workshop/>*
*Call for Participation, in conjunction with Educational Data Mining 2018*
*July 15-18, Buffalo NY*
The big data revolution in education has led to many shifts and advances in
the field, including better prediction of student outcomes and better
modeling of student knowledge and engagement. However, many findings appear
to contradict each other across datasets, differ from each other in subtle
ways, or are hindered by methodological shortcomings (e.g., uncorrected
multiple testing for statistical significance). As such, the issues of
replication and research synthesis across studies facing the community now
loom large, and there is increasing worry about spurious studies being
accepted as true, often referred to as the “replication crisis” in other
areas of science. This issue is particularly critical in the field of
educational data mining, where the sharing of datasets for replication
purposes is restricted by educational privacy laws (e.g., FERPA) and many
studies evaluate novel educational domains with no clear scientific
consensus to guide the interpretation of novel methods and results (e.g.,
MOOCs). This workshop is intended to build working capital up within the
EDM community, focusing on the challenges, opportunities, and best
practices for reproducibility, replication, and generalization of EDM
findings.
The workshop will be organized as a half day event immediately preceding
the main EDM conference. This will include invited discussions on work done
in the field to date, as well as a poster session. Participants interested
in presenting posters are requested to provide a brief (500-1,000 words)
abstract of their interests, work, or positions in the area, and may
include topics broadly about education and replication including:
- methods, procedures, and norms (e.g., pre-registration)
- reproducibility best practices
- generalization efforts
- computational infrastructure and architectures for replication
- data set openness, availability, and privacy
- issues of ecological validity relating to replication and generalization
- replication efforts (both failed and successful) in experimental
randomized
- controlled trials or predictive models in education
- surveys of successful reproducibility and replication methods and efforts
in other related domains (e.g., a survey or case study of how the EDM
community can learn from reproducibility efforts in medical research using
privacy-restricted data)
Important Dates
June 1, 2018 – Submission of Abstracts (send to
replicate.education@xxxxxxxxx)
July 15, 2018 – Workshop
Organizers
Christopher Brooks (University of Michigan)
Ryan Baker (University of Pennsylvania)
Neil Heffernan (Worcester Polytechnic Institute)
Joshua Gardner (University of Michigan)
Juan Miguel Andres (University of Pennsylvania)
--
Christopher Brooks
Research Assistant Professor, School of Information
Director of Learning Analytics & Research, Office of Academic Innovation
E-Mail: brooksch@xxxxxxxxx
Web: http://www.si.umich.edu/people/christopher-brooks
School of Information
University of Michigan
4439 North Quad
105 S. State St.
Ann Arbor, MI 48109-1285