CALL FOR PAPER

Vol. 15, n.3, 2019

LEARNING ANALYTICS: FOR A DIALOGUE BETWEEN TEACHING PRACTICES AND EDUCATIONAL RESEARCH

Guest Editors

Antonio Marzano,University of Salerno, Italy
Antonelle Poce
, University of Rome TRE, Italy

Important dates
Initial manuscripts due July, 20th, 2019
Notification and Review Comments September, 3rd, 2019
Camera Ready manuscript due September, 20th, 2019
Special Issue published September, 2019 

This call for papers is related to a special issue intended to collect theoretical, empirical and comparative contributions of educational and didactic research on the main topics covered in the conference on “Learning Analytics, for a dialogue between teaching practices and educational research” held in Rome 10 and 11 May 2019.
To better address the preparation of the papers, we refer to the definitions provided in (Chatti, Dyckhoff, Schroeder, & Thüs, 2012). In particular, Learning Analytics focuses on converting data from educational activities into actions that improve learning.
All aspects concerning institutional, academic and political issues are included in the topic of Academic Analytics. Among these, for example, the identification of students at risk, strategies to improve learning opportunities and educational outcomes; decisions on ethics, privacy or regulatory aspects; decisions that have an economic impact on the organization involved.
Finally, Educational Data Mining deals with how to analyse large sets of data related to learning and take value from them, i.e. the application of data mining techniques (such as clustering, classification, associative rules) on data from learning environments.
In the specific of the Learning Analytics, moreover, the call recalls the reference model and therefore invites the authors of the contributions to touch one or more of the dimensions indicated in it:
What: which environments and what types of data collect, manage and use for analysis;
Who: for which types of users to address the analysis;
Why: the purposes for which the data is analysed;
How: the methods and techniques with which data are analysed.

Topics of interest include but are not limited to:
  • Educational Data Mining: experiences, surveys and initiatives
  • Academic Analytics: experiences, surveys and initiatives
  • Learning Analytics: experiences, surveys and initiatives
  • Learning Experiences in the Smart City
  • Learning Experiences based on Virtual, Mixed and Augmented Reality
  • Online learning environments (LMS, MOOCs): experiences, surveys and
  • initiatives
  • Techniques and data collection methods in Blended learning experiences
  • Initiatives and surveys aimed at improving evaluation systems and tools in online systems
  • Initiatives and surveys aimed at increasing the success of teaching and learning activities.Review of the state of art in Robotics systems for education

References
Chatti, M., Dyckhoff, A., Schroeder, U., & Thüs, H. (2012). Learning analytics: a review of the state of the art and future challenges. International Journal of Technology Enhanced Learning, 4(5/6).

Types of papers
It is possible to submit proposals in the following three sections:

  • Researches (max. 40,000 characters, spaces included);
  • Experiences (max. 30,000 characters, spaces included);
  • Studies (max. 30,000 characters, spaces included).

Language: all contributions/papers must be written in English
Author Guidelines: http://www.je-lks.org/ojs/index.php/Je-LKS_EN/about/submissions

The Journal of e-Learning and Knowledge Society (Je-LKS) (eISSN 1971-8829) is published by the Italian Society of e-Learning since 2005 and in 2018 has published its fourteenth volume, consisting of three issues. Je-LKS is indexed, among other things, on on AACE-EdITLib, Web of Science Content Expansion (Thompson Reuters) Scopus, Elsevier, DOAJ, IET Inspec, CiteFactor and in 2018 reached a h-index of 17 (Publish or Perish based on Google Scholar database). ANVUR Ranking: A-Class for Sector 10, 11-D1 and 11-D2