[Air-L] RIED — CFP: Learning Analytics & Data-driven Education

[Dani Domínguez]

Dear Colleagues,

I would like to invite you to contribute to the following special issue of
RIED — Iberoamerican Journal of Distance Education (RIED — Revista
Iberoamericana de Educación a Distancia),
http://revistas.uned.es/index.php/ried/

Title: Learning Analytics & Data-driven Education

Editor(s):
Daniel Domínguez Figaredo (UNED, Spain)
Justin Reich (MIT, USA)
José A. Ruipérez-Valiente (MIT, USA)

Timeline:
Submission of full papers: November, 15 - December, 15 2019 (upload the
papers to the journal's website)
Decisions and comments sent to authors: March 2020
Publication of the Issue: June 2020

Information:
With the accelerated advance of data science and learning analytics, there
has been a proliferation of research focused on the information generated
by student activity in digital spaces. In distance education it is
essential to use digital mediation systems in order to establish contact
between students, teachers and resources, which makes this field very
conducive to incorporating methods of learning analysis. Based on these
evidences, this special issue aims to strengthen the connections between
data-based educational research and the field of digital learning, with the
aim of enriching knowledge about learning processes and the management of
teaching in non-presential and digitally mediated spaces.
The phenomenon of data-driven education has led to different types of
studies. There is a great deal of research using educational data mining
that seeks to analyze student behavior patterns and to establish
relationships between the variables involved in the learning process and
learning outcomes. A second trend refers to studies with a pedagogical
approach, which use the aggregated information resulting from the analysis
of the data with the aim of improving instructional design, enriching
didactic methods and better understanding the role of educational agents.
Finally, there is also a significant amount of research that focuses on the
institutional derivatives of the use of digital data and seeks to develop
frameworks for improving strategic decision-making, organizational design,
and curricular policies.
Contributions to this special issue may consist of both theoretical and
applied approaches: they may be survey studies on the state of the art of
data-driven education, or research papers presenting evidence of interest
in this field of study. They may also employ quantitative or qualitative
approaches from data science and educational data mining, as well as from
the field of pedagogy and educational sciences. In the case of empirical
research, contributions that go beyond documenting student activity in a
course emphasizing the application in practice are particularly welcome. We
invite case studies from traditional distance education settings (e.g.
learning management systems) but also more specialized and contemporary
environments like games for learning or intelligent tutoring systems.
Research that provides a deeper insight into different learning processes,
such as those that help to measure the skills that students acquire in
online courses, how those skills change throughout a course or in lifelong
learning situations, and, in general, that proposes causal reasoning to
understand how the behaviour of students in digitally mediated spaces
affects their learning, will also be welcome.
We propose to organize the special issue around the following themes:
— Implications of analytics in the improvement of learning processes,
teaching practices and instructional design.
— New research on exploratory, predictive or causal analytics to improve
learning success.
— Pilot studies or policy frameworks for the implementation of learning
analytics at an institutional level.
— Analytics in open and connected learning spaces.
— Innovative approaches to data-driven education.

Instructions for Authors:
Articles should be submitted online via the RIED web-portal (
http://revistas.uned.es/index.php/ried/index). We welcome full manuscripts
of up to 7,000 words maximum, including abstract, notes and bibliography.
Each paper will be reviewed by two referees. Papers may be published in
English, Spanish and Portuguese. Publication and access are free and open.
For more information on the submission process, see the authors guidelines
section (
http://revistas.uned.es/index.php/ried/about/submissions#authorGuidelines)
and especially consider the requirements and criteria demanded by RIED (
http://revistas.uned.es/index.php/ried/about/editorialPolicies#peerReviewProcess
).

Open Access Policy:
RIED is an open access journal. Further information about the  open access
policy can be found here,
http://revistas.uned.es/index.php/ried/about/editorialPolicies#openAccessPolicy

Contact Information:
For questions regarding the special issue please contact the coordinators:
ddominguez at edu.uned.es, jruipere at mit.edu or jreich at mit.edu

Many thanks,

-- 
Daniel Domínguez

UNED
daniel-dominguez.com <http://www.daniel-dominguez.com/>
@danidominguez <http://twitter.com/danidominguez>