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<pdf width="1500px">https://ceur-ws.org/Vol-1967/foreword.pdf</pdf>
<pre>
Foreword by L. Vigentini and Yuan (Elle) Wang.




   As well as attracting millions of learners worldwide, MOOCs have received a lot of
attention from both popular media and the research community. Whilst MOOCs have
opened interesting new lines of research, few of the findings had major implications for
learning and teaching:

   “For MOOC research to advance the science of learning, researchers, course
   developers, and other stakeholders must advance the field along three
   trajectories: from studies of engagement to research about learning, from
   investigations of individual courses to comparisons across contexts, and from a
   reliance on post hoc analyses to greater use of multidisciplinary, experimental
   design.” (Reich, 2015, p.34).

   Reich’s remark was a call to action for researchers across the disciplines to ‘reboot’
the trends and refocus on learning design and improve assessment practice, facilitate
data sharing to expand our understanding beyond the presentation of findings in a single
course or context, and rethink about the types of research implemented, moving away
from the typical experimental designs.
   Two recent reviews expanded Reich’s lines of thinking focusing on methodology
(Raffaghelli, Cucchiara, & Persico, 2015) and criticising existing approaches in
modelling learning at scale and pointing out several areas of research which could be
further (Joksimovic et al., 2017) and demonstrated the gaps in the literature.

  This joint column contains papers from the Workshop on FutureLearn Data
Analytics the Workshop on Integrated Analytics of MOOC Post-Course
Development, co-located with the 7th International Learning analytics and Knowledge
Conference, held March 13th to 17th.

   Although organized independently, the two workshops set to tackle some of the gaps
and share the same commitment to bring scholars and practitioners together to share
their work and advance our understanding of learning (in context), professional
development (across contexts) and learning design (beyond the context) and how these
interact in the open learning occurring in MOOCs.
                                                                                          II




   The first Workshop takes the opportunity offered using a specific MOOC learning
platform (FutureLearn) and showcase a range of studies focusing on the use of near-
real time data to understand learning design, interactions and engagement with learning
activities across multiple institutions. The papers in this workshop include work done
to make the data available and usable by different stakeholders, the application of
analytical methods to understand and improve learners’ engagement and participation
and the use of analytics to support the future pedagogical development.

   The second workshop was conceived to respond to the challenge that MOOC
research is typically limited to evaluations of learner behaviour in the contest of the
learning environment. The papers published in these proceedings represent examples
of recent efforts from learning analytics researchers to examine the relationship
between performance and engagement within the course and learner behaviour and
development beyond the course. The workshop awareness in the community regarding
the importance of research measuring multi-platform activity and long-term success
after taking a MOOC.



References
Joksimovic, S., Poquet, O., Kovanovic, V., Dowell, N., Mills, C., Gasevic, D., … Brooks, C.
         (2017). How do we Model Learning at Scale? A Systematic Review of Research on
         MOOCs. Review of Educational Research, accepted.
Raffaghelli, J. E., Cucchiara, S., & Persico, D. (2015). Methodological approaches in MOOC
         research: Retracing the myth of Proteus. British Journal of Educational Technology,
         46(3), 488–509. https://doi.org/10.1111/bjet.12279
Reich, J. (2015). Rebooting MOOC Research. Science, 347(6217), 34–35.
         https://doi.org/10.1126/science.1261627

</pre>