Lab Learning Analytics and Visual Analytics

Lab Course: Learning Analytics and Visual Analytics (LAVA) (SS 20)

Semester: Summer Semester 2020

Lab language: English

Exam language: English

Exam type: Prototype, Presentation, Report

Maximum number of participants: 20

Notice

The course will officially start on April 20th, 2020 and will take place fully online. More information will be provided in the Moodle courseroom for the registered students. Registration is still possible until April 16th, 2020 (see the registration section below).

About this course

In the Learning Analytics and Visual Analytics (LAVA) project, you will systematically design and implement interactive visualizations of an educational dataset of your choice, following the Human-Centered Design (HCD) process proposed by Norman (2013) and the What-Why-How visualization analysis framework proposed by Munzner (2014).

You will organize yourselves in groups of 4. In the first few weeks of the lab, we will provide a general overview on HCD and visualization libraries (e.g. D3.js). There will be weekly tasks which include:

  • Reading, presenting, and discussing selected chapters from the Visualization Analysis and Design book (Munzner, 2014)
  • Project presentations (ideas/concepts, prototypes, end product, demos)
  • Writing a project report in form of a scientific article

Grading for this lab will be based on the content and quality of the project presentations and report as well as your performance (project management and collaboration, class participation, creativity) during the project.

Target audience

  • Master Applied Computer Science
  • Bachelor Applied Computer Science
  • Master ISE CE
  • Master Komedia
  • Bachelor Komedia

4 places for each study program

Date and location

  • Mon, 16:00 – 18:00
  • LF 125 Online
  • Starts on April 6, 2020 April 20, 2020

Prerequisites

  • Good knowledge of basic Web technologies such as HTML, CSS, JavaScript
  • Past participation in our lecture courses Advanced Web Technologies and Learning Analytics is important, but not mandatory
  • Interest in data science and/or learning technologies
  • High motivation and commitment

Registration

We have 4 places for each of the study programs: Master AI, Bachelor AI, Master ISE CE, Master Komedia, Bachelor Komedia (first come first serve). To register, please send an email to Dr. Arham Muslim by March 30th, 2020 April 16th, 2020 with your matriculation number, study program, and if available your knowledge/experience in Visual Analytics and Learning Technologies. If the maximum number of participants is reached, we will use a waiting list. Komedia Bachelor students should register via the central registration system.

Organization

  • Course material in Moodle
  • Show in course catalog (LSF)

Instructors

For any questions about the class, please contact Dr. Arham Muslim.

Prof. Dr. Mohamed Chatti (Lecturer)

Dr. Arham Muslim (Teaching Assistant)

Literature

  • Munzner, T. (2014). Visualization Analysis and Design. AK Peters/CRC Press.
  • Ward, M. O., Grinstein, G., & Keim, D. (2010). Interactive Data Visualization: Foundations, Techniques, and Application. AK Peters/CRC Press.
  • Ware, C. (2004). Information Visualization: Perception for Design (2nd Edition). Elsevier.
  • Norman, D. (2013). The Design of Everyday Things. New York: Basic Books
  • Dix, A., Finlay, J. E., Abowd, G. D., and Beale, R. (2004). Human-Computer Interaction (4th Edition). Prentice-Hall, Inc., Upper Saddle River, NJ, USA.