Free access code - JCAL special issue on "Learning analytics in massively multi-user virtual environments and courses"

[Lee, Mark]

Dear colleagues,

Following my earlier email about the publication of the the special issue of Journal of Computer Assisted Learning (JCAL) on "Learning analytics in massively multi-user virtual environments and courses", Wiley has been kind enough to provide an access code that will permit free access to the content of the journal for the remainder of the year—but only for the first 300 users.

The code is: JCALLAK16

If you DO NOT have access to JCAL via your institution’s library, we strongly encourage you to make use of this code, as Wiley will be monitoring its uptake to facilitate future decision-making on whether to make this special issue, along with other selected content, permanently free and open access.

To use the access code, please follow these steps:

1. You will need to register for an account on the Wiley website at http://www.onlinelibrary.wiley.com/user-registration if you have not already done so.

2. Log in to Wiley Online Library (http://onlinelibrary.wiley.com) with your email and password.

3. Once you have logged in, go to the trial access page within your profile at http://www.onlinelibrary.wiley.com/myprofile/trials. Enter the access code in the "Trial Access Code" dialog box, then click "Submit Code."

4. You should now have access to *all* JCAL content (not just the special issue) until the end of 2016. Enjoy!

The contents of the special issue are included below again, for your reference.


*** JCAL SPECIAL ISSUE ON LEARNING ANALYTICS IN MASSIVELY MULTIUSER ONLINE ENVIRONMENTS AND COURSES ***

EDITORIAL

Learning analytics in massively multi-user virtual environments and courses
M.J.W. Lee, P.A. Kirschner and L. Kester
http://dx.doi.org/10.1111/jcal.12139

SPECIAL ISSUE ARTICLES

A MOOC based on blended pedagogy
S. Rayyan, C. Fredericks, K.F. Colvin, A. Liu, R. Teodorescu, A. Barrantes, A. Pawl, D.T. Seaton and D.E. Pritchard
http://dx.doi.org/10.1111/jcal.12126

Understanding MOOC students: motivations and behaviours indicative of MOOC completion
B.K. Pursel, L. Zhang, K.W. Jablokow, G.W. Choi and D. Velegol
http://dx.doi.org/10.1111/jcal.12131

The role of students' motivation and participation in predicting performance in a MOOC
P.G. de Barba, G.E. Kennedy and M.D. Ainley
http://dx.doi.org/10.1111/jcal.12130

Who are the top contributors in a MOOC? Relating participants' performance and contributions
C. Alario-Hoyos, P. J. Muñoz-Merino, M. Pérez-Sanagustín, C. Delgado Kloos and H. A. Parada G.
http://dx.doi.org/10.1111/jcal.12127

Connecting performance to social structure and pedagogy as a pathway to scaling learning analytics in MOOCs: an exploratory study
S.P. Goggins, K.D. Galyen and J.M. Laffey
http://dx.doi.org/10.1111/jcal.12129

Towards general models of effective science inquiry in virtual performance assessments
R.S. Baker, J. Clarke-Midura and J. Ocumpaugh
http://dx.doi.org/10.1111/jcal.12128

CLOSING COMMENTARY

The MOOC and learning analytics innovation cycle (MOLAC): a reflective summary of ongoing research and its challenges
H. Drachsler and M. Kalz
http://dx.doi.org/10.1111/jcal.12135


Kind regards,



Mark J.W. Lee, Paul A. Kirschner and Liesbeth Kester
Editors