Call for papers - AI4MOOCs: Artificial Intelligence, sensoring, modeling and assessment for MOOCs. A step beyond

International Journal of Artificial Intelligence in Education welcomes submissions to the special issue "AI4MOOCs: Artificial Intelligence, Sensoring, Modeling and Assessment for MOOCs. A Step Beyond"

The demand for Distance Education has been dramatically growing in recent years, also as a consequence of the huge and increasing availability of systems supporting e-learning through the internet. People, geographically and culturally spread across the globe, companies, practitioners, students, and Communities of Practice with thousands of learners, are involved in networked learning programs. Thanks to the Internet, the 21st century seems to be the Century of lifelong learning.

Massive Open Online Courses (MOOCs), are courses characterized by having a very high number (in the thousands, or more) of students. These courses, mostly free, are offered through special web-based platforms, with the provision of video-based teaching materials, interactive assessment tools, and some social interaction or collaboration means. While, on the one hand, these courses help thousands of students, on the other hand they introduce a strong problem for tutors, who can have a hard life at monitoring the learning process of such an extended class of students. This tutoring support presents challenges that relate to cognitive, affective and even psychomotor aspects (in this last case, towards supporting embodied learning in massive online learning contexts).

Artificial Intelligence in general and Machine Learning in particular propose techniques and tools to study, model, and manage such a complex reality.

We encourage in particular the submission of articles where AI techniques and methods are used to provide automated support to the cognitive, affective and even when possible, psychomotor modeling of students and to the assessing of competences in a MOOC scenario that can be enriched with traditional interaction devices and/or emerging sensors, which are available in traditional computerized learning scenarios (such as webcam, keyboard and mouse), in mobile learning context (which in addition to mobile cameras can also collect information from the inertial and physiological sensors available in smart phones) and even in smarter learning scenarios which can also make use of other sensors such as smart bracelets or virtual reality head mounted displays. Such support would be directed to teachers, in order to allow monitoring the learning process; to students, such as in the case of course adaptation, or for the support to individual self-reflection, about own performances, and decision-taking about what learning experience to select; to course managers, or teachers again, to appreciate the MOOC’s inner dynamics, and wisely guide them.

Topics of interest include but are not limited to:

  • Technology-enhanced learning and Peer Assessment in MOOCs
  • Deep learning and MOOCs
  • Learners’ Evaluation in MOOCs
  • MOOCs dynamics and Modeling
  • Recommendation of learning units in MOOCs
  • Technology-Enhanced learning and MOOCs
  • Mobile-based technologies for recommendations and adaptivity in MOOCs
  • Learning Analytics Models for MOOCs
  • Visual presentation of data in MOOCs
  • Design and implementation of adaptive e-learning systems in MOOCs
  • Teacher and student modeling in Technology-enhanced learning for MOOCs
  • Artificial Intelligence and Embodied Learning in MOOCs

Important Dates

First round: extended abstract submission (

Second round: full paper submission (IJAIED editorial manager)

  • File format: Please follow the journal's submission guidelines
  • Submission deadline: January 31th, 2020
  • Acceptance notification: March 31th, 2020
  • Revisions submission: May 15th, 2020
  • Publication: All papers will appear online as soon as they have been accepted

Additional information can be found here.

Guest Editors

Lead Guest editor: Filippo Sciarrone, ROMA TRE University, Engineering Department
Guest Editor: Carla Limongelli, ROMA TRE University, Engineering Department
Guest Editor: Olga C. Santos, aDeNu Research Group. UNED
Guest Editor: Marco Temperini, DIAG-Department of Computer, Control and Management Engineering,  Sapienza University of Rome