Duration
20h Th, 20h Pr
Number of credits
| Master in education (120 ECTS) | 4 crédits |
Lecturer
Language(s) of instruction
French language
Organisation and examination
Teaching in the first semester, review in January
Units courses prerequisite and corequisite
Prerequisite or corequisite units are presented within each program
Learning unit contents
This lecture aims at initiating students to conduct statitistical analyses with SAS software on databases of international surveys in education on achievement such as the OECD/PISA or IEA/TIMSS & PIRLS programs
Learning outcomes of the learning unit
Students will have to demonstrate their capabilities to :
1. Create and modify data files ;
2. Merge files;
3. Conduct differents types of statistical analyses: linear and non linear regresion, multi-level regression with fix and random effects, logistic regression, correlation, effect size and relative risk analyses ;
4. Estimate the sampling variance with resampling methods
Prerequisite knowledge and skills
Deep understanding of the statistical tools listed in the "Learning outcomes" section
Planned learning activities and teaching methods
Lecture, seminar and groups and individual works
Mode of delivery (face-to-face ; distance-learning)
Face to face required
Recommended or required readings
OECD (2007). PISA Data Analysis Manual, SAS second edition. Paris : OECD.
Assessment methods and criteria
Students will have to conduct statistical analyses that involves data transformations and the use of a macro for the estimation of the sampling variance
Work placement(s)
Organizational remarks
None
Contacts
Christian Monseur
++ 32 4 358 05 84
cmonseur@ulg.ac.be