Seminar on Educational Data Mining and Learning Analytics

Algorithms and machine learning
Advanced studies
Educational Data Mining (EDM) and Learning Analytics (LA) are research fields that focus on developing methodologies and tools to explore and analyze data gathered from educational settings. The roots of EDM are in constructing, studying and improving intelligent tutoring systems that guide and teach students, while LA has roots in the analysis of data originating from different types of learning management systems with the goal of improving offered education. Methods and practices in both fields are very similar, and various forms of machine learning and data mining practices are in the very core of both fields.
Year Semester Date Period Language In charge
2016 spring 22.01-06.05. 3-4 English Arto Hellas


Time Room Lecturer Date
Fri 10-12 C221 Arto Vihavainen 22.01.2016-04.03.2016
Fri 10-12 C221 Arto Vihavainen 18.03.2016-06.05.2016

Information for international students

This seminar will be held in English.


We focus on both research and practice papers in recent EDM and LA conferences and relevant journals.
Learning objectives
  • Improve scientific and technical writing skills
  • Improve scientific and technical presentation skills
  • Learn about educational data mining and learning analytics
Course schedule:

Completing the course

Participants must have completed the course Scientific writing or have equivalent skills. Students complete this seminar by actively participating in its work: the work methods include studying scientific sources, writing reports and giving presentations, reading the reports of other participants and evaluating them, and actively following presentations.
The grading will be based on each student's own written work (1/2), oral presentations (1/4), and commentary on the reports of others as well as activeness in general (1/4). To pass the seminar, each of these components must be passed. Active attendance of seminar meetings is mandatory.
During the course, you will (1) write an abstract describing your topic, (2) give a short "elevator pitch"-type presentation based on the abstract, (3) participate in discussions on relevant papers in the course, (4) write a seminar report, and (5) give a "conference-style" presentation that is based on your report.
The seminar meets for the first time on Jan. 22nd at 10 AM. During the meeting, we will discuss the primer articles, the seminar schedule (bi-weekly meetings, seminar day for conference presentations), and outline possible seminar report topics.
There is an IRC channel for course participants on IRCnet -- #edmla
There are also a few journals and special issues which may be of interest -- perhaps JEDM can be a starting point.

Possible topics and keywords to search for

Literature and material

As a primer, read the articles "Penetrating the Fog: Analytics in Learning and Education" by Phil Long and George Siemens (link) and "Educational Data Mining and Learning Analytics" by Ryan S.J. Baker and George Siemens (link).