PSY205 – Introduction to Scientific Programming
Bachelor of Science in Psychology
Core Course
PSY205 – Introduction to Scientific Programming
Course Unit Code: PSY205
Type Of Unit: Compulsory
Level of Course Unit: Undergraduate
Year of Study: Year 2
Semester: Semester 2
Number of ECTS Credits: 7.5
Class Contact Hours: 36
Mode of Delivery
Face to Face
Prerequisites
PSY202, PSY203 & PSY206
Course Objectives
The purpose of this course is to provide psychology students the fundamental programming abilities and resources they need to undertake simulations, experiments, and data analysis more effectively and rigorously. This course intends to enable students to engage in sophisticated data manipulation, analysis, and visualization techniques, promoting a deeper understanding of psychological phenomena and boosting their research capacities. It does this by fusing programming knowledge with psychological research concepts.
Learning Outcomes
Students are expected to:
- Show a grasp of basic programming ideas, such as variables, data types, loops, conditionals, and functions.
- Use programming tools to import, purge, and preprocess psychological data.
- Conduct fundamental to advanced statistical analyses on psychological data.
- Create data visualizations to convey psychological insights clearly.
- Discuss the ethical issues in programming for psychological research, including data privacy and biases.
Course Content
Students should acquire the fundamental programming abilities and resources they need to undertake simulations, experiments, and data analysis more effectively and rigorously. Also, students should engage in sophisticated data manipulation, analysis, and visualization techniques, promoting a deeper understanding of psychological phenomena and boosting their research capacities. It does this by fusing programming knowledge with psychological research concepts.
Week 1: Introduction to Programming and Psychology Research
Week 2: Fundamentals of Programming
Week 3: Data Handling and Manipulation
Week 4: Programming & Statistical Analysis
Week 5: Data Visualization
Week 6: Experimental Simulations
Week 7: Algorithmic Thinking in Psychology
Week 8: Replicability and Open Science
Week 9: Advanced Techniques in Programming for Psychology
Week 10: Ethical Considerations in Programming for Psychology
Week 11: Project-based Learning
Week 12: Collaboration and Communication
Week 13: Critical Thinking and Problem Solving
Week 14: Final Projects and Showcase & Future Directions in Psychological Programming
Course Features
Teaching methodology: Lab-based
Assessment:
- Weekly assignments covering all programming areas taught per module (10 x 5 = 50%)
- Final programming project (40%)
- Presence and Participation (10%): Students should be present and actively participate in in-class discussions.
Readings
Matthes, E. Python Crash Course, 3rd Edition: A Hands-On, Project-Based Introduction to Programming (3rd ed.). No Starch Press.
Github portal
Further material will be determined by the course leader.