Call for Papers: The First International Workshop on Data Management and Mining on MOOCs

Call for Papers

The First International Workshop on Data Management and Mining on MOOCs (DMMOOC 2017)


Scope and Vision

The MOOCs (Massive Open Online Courses) have significantly increased scale of online education and have brought great opportunities to understand learner behaviors and design intelligent personalized and collaborative learning systems in an unprecedented way. Large datasets collected from online learning platforms enable researchers from data science and learning science as well as educators to work together to answer educational questions in the learning process and improve the overall quality of education. To this end, educational data mining and learning analytics are emerging as interdisciplinary research fields that attract lots of research attention from both academia and industry.

The DMMOOC 2017 workshop addresses issues of data management and mining in a wide range of MOOC related scenarios. The goal of the workshop is to provide a platform for researchers, educators and practitioners from academia and industry to present their latest progress and discovery from the perspective of diverse MOOCs related applications. We intend this workshop to act as a place where people from different disciplines can find a platform to discuss issues of data management and mining in both conventional and emerging MOOCs related scenarios. Potential participants may come from research communities such as data management, data mining, education science, machine learning, information retrieval or any other areas related to the MOOCs.

Workshop Topics (include but not limited to)

l  Automated construction and optimization of MOOCs knowledge graph

l  Automatic feedback and peer grading on MOOCs

l  Big data and learning analytics

l  Data-driven crowdsourcing on MOOCs

l  Data mining and learning metrics

l  Data mining in social and collaborative learning

l  Deriving representations of domain knowledge from MOOCs data

l  Intelligent tutoring

l  Personalized and adaptive learning

l  Text mining and semantic analysis on MOOCs

l  User analytics on MOOCs

Steering Committee

Wei Li, Beihang University, China

Xiaomin Li, Peking University, China

Huaiming Wang, National University of Defense Technology, China

Maosong Sun, Tsinghua University, China

Wei-Tek Tsai, Arizona State University, USA

Program Chairs:

Wenjun Wu, Beihang University, China

Yan Zhang, Peking University, China

Yongxin Tong, Beihang University, China

Important Dates

Submission deadline: Dec. 23rd, 2016

Review notification: Jan. 6th, 2017

Camera ready and registration deadline: Jan. 10th, 2017

Conference: March 27-30, 2017

Paper Submission

The length of camera-ready papers will be limited to 12 pages (also position papers presenting relevant work-in-progress in the area are welcomed, length limitation = 6 pages).

All papers should be prepared using the IEEE format, please see

Each paper will be reviewed by at least three TPC members. Authors must submit their manuscripts using the EasyChair conference system using this link:

Paper Publication

All accepted papers will be published by the IEEE Computer Society Press and included in the IEEE Digital Library.

At least one author of each accepted submission is required to attend the DMMOOC 2017 to present their paper and at least one author must be registered at the full conference rate.



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