Checking date: 19/05/2022


Course: 2022/2023

Educational data analytics
(16659)
Study: Bachelor in Data Science and Engineering (350)


Coordinating teacher: MUÑOZ MERINO, PEDRO JOSE

Department assigned to the subject: Department of Telematic Engineering

Type: Electives
ECTS Credits: 6.0 ECTS

Course:
Semester:




Skills and learning outcomes
Description of contents: programme
1 - Introduction to learning analytics and educational data mining 1.1 Definitions and purpose 1.2 Educational platforms and services 1.3 Reference architectures and frameworks 1.4 Learning analytics life cycle 2 - Collection of educational data 2.1 Types of data 2.2 Storage formats 2.3 Interoperability. CAM, xAPI, IMS Calliper specifications 2.4 Combination of data from different sources in distributed services 3 - Detection of student skills 3.1 Item Response Theory 3.2 Bayesian models 3.3 Knowledge spaces 4 - Detection of student behaviors 4.1 Preferences 4.2 Help-seeking 4.3 Gaming the system 4.4. Others 5 - Visual analytics for the learning process 5.1 Existing tools 5.2 Video and exercise visualizations 5.3 Social interaction visualizations 5.4 Other high-level visualizations 5.5 Analysis and interpreation of visualizations from different situations 5.6 Interventions in the learning process 6 - Prediction of learning outcomes 6.1 Prediction of dropout 6.2 Prediction of learning gains 6.3 Prediction of interactions in services
Assessment System
  • % end-of-term-examination 60
  • % of continuous assessment (assigments, laboratory, practicals...) 40

The course syllabus may change due academic events or other reasons.