UV9258 – Machine Learning in Education

Course content

UV9258 is taught as one (of several) elective module of the master level course MAE4051 Selected Topics in Educational Measurement. The contents of the course, schedule and reading list are the same as for MAE4051.

Please see the course pages for MAE4051 for a general description of the course contents and learning outcomes.

Please see the semester pages for MAE4051 for a more detailed description of this specific module, including reading list.

It is strongly recommended that the students in UV9258 attend all lectures and participate in the group discussions.

Admission

There is a limited number of seats due to joint teaching with the master’s level version of the course.

PhD candidates at the Faculty of Educational Sciences will be given priority, but it is also possible for others to apply for the course.

The deadline for registration is September 6th,  2021.

Candidates admitted to a PhD-program at the Faculty of Educational Sciences (UV) can apply in StudentWeb.

Other applicants can apply by filling out this electronic form.

Prerequisites

Formal prerequisite knowledge

Solid knowledge of basic statistical methods as typically acquired in a master- program in the social sciences (descriptive statistics, statistical inference, correlation, regression analysis, factor analysis, path analysis) is expected. Additionally, a basic command of the statistical software R would be advantageous. The students are expected to bring a laptop with administrator rights and the newest version of R installed.

Teaching

Organizer: CEMO (Centre for Educational Measurement at University of Oslo)

Coordinator/Responsible: Denise Reis Costa

Teaching: Joint teaching with the master level version of the course, MAE4051.

Schedule: Joint teaching with the master level version of the course (13 sessions (2X45 minutes) week 38-42)

Literature: Please refer to the MAE4051 semester pages for autumn 2021

Examination

To obtain 3 credits, 80 % attendance and a successfully completed paper is required.

A more specific description of the paper and a submission deadline will be given in class.

Language of examination

The examination text is given in English, and you submit your response in English.

Grading scale

Grades are awarded on a pass/fail scale. Read more about the grading system.

Facts about this course

Credits
3
Teaching
Every autumn
Examination
Every autumn
Teaching language
English