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Dan Russell: 150K+ online students at a time: How to understand what’s happening in online learning #EDM_2014 @IOE_London

Hi guys...we had this last year. We starting using #EDM_2014 on purpose to let you use EDM or EDM2014. Do you mind using that one?

RT @johnscarney: Educational Data Mining in action. #EDM_2014 #ncstate Non-cognitive factors in improving education outcomes! #mari http:/…

RT @sjgknight: #Edm_2014 @dwshaffer kicking off ENA tutorial @ioe_london

A hint for the banquet on Sunday ;-) #EDM_2014

#EDM_2014 website is down. In the meantime wrkshp/tut schedule and conference one

RT @gsiemens: Full house at #lasi14

RT @Ani_Aghababyan: #lasi14 is also available online. Live streaming:

May 30th 23:59 BST early bird registration 7th Educational Data Mining conference #EDM_2014 @IOE_London Hurry Up!

The 7th International Conference on Educational Data Mining is open: - early bird price is £230 and students pay £150


Organized by the International Educational Data Mining Society (IEDMS).



Carnegie Learning










To discover more about sponsorship contact

Call for Papers


EDM 2014: The Seventh International Conference on Educational Data Mining

4-7 July 2014 in London, UK
We invite submissions to the 7th International Conference on Education Data Mining (EDM2014), to be held under auspices of the International Educational Data Mining Society on 4-7 July 2014 at the Institute of Education, London, UK.

The EDM conference is a leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces that students leave when they interact, either individually or collaboratively, with learning management systems, interactive learning environments, intelligent tutoring systems, educational games or when they participate in a data-rich learning context. The types of data therefore range from raw log files to eye-tracking devices and other sensor data.

Being hosted in London, UK EDM 2014 invites us to thing BIG. The theme of the conference is "Big Data - Big Ben - Education Data Mining for Big Impact in Teaching and Learning". We particularly solicit submissions that look into EDM applications with a measurable impact on the future of teaching and learning. Appreciating this impact, particularly with an eye to scaling up, requires an interdisciplinary approach and the coming together of different stakeholders. EDM 2014 will therefore bring together practitioners, industry representatives, and researchers from cognitive psychology, computer science, education, learning sciences, neuroscience, psychometrics, and statistics.

A selection of accepted papers for the conference will be invited to extend their submission (providing a significant contribution beyond the conference paper) for a special issue in the Journal of Educational Data Mining (JEDM) on Advances and Emerging trends in EDM.

EDM 2014 will precede the 22nd conference on User Modeling, Adaptation, and Personalization - UMAP 2014, 7 - 11 July 2014, in Aalborg, Denmark.

Topics of interest to the conference include, but are not limited to:
  • Closing the loop between education data research and educational outcomes
  • Stealth assessment and evaluating the efficacy of curriculum and interventions
  • Deriving representations of domain knowledge from data
  • Detecting and addressing students' affective and emotional states
  • Integrating data mining and pedagogical theory
  • Data mining with emerging pedagogical environments such as educational games, MOOCs, and exploratory learning
  • Multi-modal learning environments and sensor analysis
  • Providing feedback to teachers and other stakeholders generated from EDM methods
  • Papers that apply a previously used technique to a new domain, or that reanalyze an existing data set with a new technique
  • Best practices for adaptation of state of the art analytic techniques to information retrieval, recommender systems, opinion mining, auto scoring, and learner modeling
  • Collaborative learning
  • Generic frameworks, methods and approaches for EDM

Full Papers 6-8 pages. Should describe original, substantive, mature and unpublished work.
Short Papers 4 pages. Should describe original, unpublished work. This includes early stage, less developed works in progress.
Industry Papers 4-6 pages. Industry papers should describe innovative ways in which data drives system features or processes in a commercial setting.
YRT/Doctoral Consortium 3 pages. Should describe the graduate/postgraduate student’s research topic, proposed contributions, results so far, and aspects of the research on which advice is sought. Should be solely authored by the student.
Posters/Demos 2 pages. Posters describe original and unpublished work in progress and last minute results. Demos describe educational data mining tools and systems, or educational systems that use EDM techniques.

See Important Dates page