Postgraduate Course: Research Methods for Developmental Cognitive Science (PSYL11087)
Course Outline
School | School of Philosophy, Psychology and Language Sciences |
College | College of Arts, Humanities and Social Sciences |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | This semester long course is taught using a combination of lab and lecture sessions. The aim is to help students master the techniques and tools needed to conduct research in developmental science, including collecting and analysing data from children. |
Course description |
This course will teach students how to obtain high-quality research data from children, and how to effectively process and analyse that data.
We will cover
- Research ethics for working with children.
- How to design experiments for children, drawing on the research methods and statistics literature.
- How to implement different types of experiment, including coding simple experiments in languages such as JavaScript.
- How to collect developmental data, including an opportunity for 'live' data collection.
- Best practice for data storage and data processing (e.g., git, OSF, dplyr).
- Techniques for analysing timecourse data (e.g., longitudinal data, eye-tracking data).
- How to evaluate a research literature (e.g., through meta-analysis).
Students will complete regular short exercises, as well as a semester-long 'replication' project, where they work in small groups to replicate important recent findings in developmental psychology.
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
Not being delivered |
Learning Outcomes
On completion of this course, the student will be able to:
- understand the key components of research methods for working with children, and their ethical implications
- understand how to create and analyse developmental experiments for working with children
- understand how to evaluate and (meta)-analyse large sets of experiments and research studies
- learn best practices for collecting and analysing data
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Reading List
Gelman, A. & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge University Press.
Rosenthal, R., & Rosnow, R. L. (2008). Essentials of behavioral research: Methods and data analysis (3rd ed.). McGraw-Hill.
Frank, M. C., & Saxe, R. (2012). Teaching replication. Perspectives on Psychological Science, 7(6), 600-604.
Simmons, J. P., Nelson, L. D., & Simonsohn, U. (2011). False-positive psychology: Undisclosed flexibility in data collection and analysis allows presenting anything as significant. Psychological Science, 22(11), 1359-1366.
Simonsohn, U., Nelson, L. D., & Simmons, J. P. (2014). P-curve: a key to the file-drawer. Journal of Experimental Psychology: General, 143(2), 534. |
Additional Information
Graduate Attributes and Skills |
Research and enquiry skills e.g. independent research, problem solving, critical thinking, digital literacy, numeracy, handling complexity
Personal and intellectual autonomy e.g. developing reflective awareness of ethical dimensions
Personal effectiveness e.g. team working; effectively using resources to achieve goals
Communication skills e.g. engaging effectively in discussions; written communication skills, including scientific writing; interpersonal skills, including child-centred communication |
Additional Class Delivery Information |
This course is primarily for students on the MSc in Developmental Cognitive Science. Students on related MSc programmes who are interested in taking the course should contact the course organiser and may be permitted to take the course subject to constraints on lab capacity etc. |
Keywords | developmental cognitive science; research methods; statistics |
Contacts
Course organiser | Dr Hugh Rabagliati
Tel: (0131 6)50 3454
Email: Hugh.Rabagliati@ed.ac.uk |
Course secretary | Miss Toni Noble
Tel: (0131 6)51 3188
Email: Toni.noble@ed.ac.uk |
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