Undergraduate Course: Statistics in Education (MATH10108)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 4 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | This course will explore the use of statistics in the application area of education. The course will involve both developing understanding of the underlying statistical ideas, and engagement with the critical debate in the education literature around these topics. |
| Course description |
The core topics covered in the course include:
- Common experimental designs and analyses used in education studies
- Randomised controlled trials (RCTs)
- Effect sizes and meta-analysis
There will also be a topic-based element, focused on the use of statistical models in a particular application area or method. Possible topics (to be decided each year at the start of the course) include:
- Item-response theory, as used in psychometrics
- Comparative judgement and the Bradley-Terry model, used as an assessment method
- Factor analysis, used in developing scales (e.g., to measure attitudes)
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
Statistical Methodology (MATH10095)
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
Course Delivery Information
|
| Academic year 2024/25, Available to all students (SV1)
|
Quota: 50 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 11,
Supervised Practical/Workshop/Studio Hours 22,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
63 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework: 100%
Exam: 0% |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- apply previously learned statistical techniques to analyse data from an education study and interpret the findings
- learn and apply techniques from a statistical topic based on guided reading of research literature
- engage in critical discussion of statistical analyses
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Reading List
Textbook TBC, but these are some education papers that will definitely feature:
Bisson, M.-J., Gilmore, C., Inglis, M., & Jones, I. (2019). Teaching using contextualised and decontextualised representations: examining the case of differential calculus through a comparative judgement technique. Research in Mathematics Education, 1¿20.
https://doi.org/10.1080/14794802.2019.1692060
Lortie-Forgues, H., & Inglis, M. (2019). Rigorous Large-Scale Educational RCTs Are Often Uninformative: Should We Be Concerned? Educational Researcher, 48(3), 158¿166.
https://doi.org/10.3102/0013189X19832850
Simpson, A. (2019). On the misinterpretation of effect size. Educational Studies in Mathematics.
https://doi.org/10.1007/s10649-019-09924-4 |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | StEd,Statistics,Education |
Contacts
| Course organiser | Dr George Kinnear
Tel: (0131 6)50 5052
Email: G.Kinnear@ed.ac.uk |
Course secretary | Miss Kirstie Paterson
Tel:
Email: Kirstie.Paterson@ed.ac.uk |
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