Learning Outcomes:
When students have completed this module they will be:
- Able to demonstrate skill in quantitative analysis, interpretation and presentation of data.
Indicative Module Content:
Advanced quantitative design and analysis
Curricular information is subject to change.
This module is designed for postgraduate students completing the Masters in Behavioural Neuroscience, and aims to support them to develop their quantitative research skills to an advanced level. The focus of the module will be on acquiring the methodological and analytical skills necessary to complete a research project of publishable quality. The topics covered include quantitative design analysis techniques. Teaching methods will include classroom seminars and advanced methodology laboratories, and students will be expected to complete set tasks and reading in between sessions. In addition, this module contains a series of practical workshops in R, a statistical programming package. Students will learn how to use R to analyse and visualise quantitative data.
About this Module
Student Effort Hours:
| Student Effort Type | Hours |
|---|---|
| Specified Learning Activities | 21 |
| Autonomous Student Learning | 70 |
| Seminar (or Webinar) | 18 |
| Practical | 9 |
| Computer Aided Lab | 6 |
| Total | 124 |
Approaches to Teaching and Learning:
The module includes both lectures (morning session) and hands-on lab activities (afternoon session). The lab activities focus on task based learning in pairs/groups. Students are also encouraged to reflect on the nature of debates in research design and consider how they might apply to their previous experience and planned research activity.Students will attend three Introduction to Statistics in R morning workshops and via active-task-based sessions learn how to use R to analyse and visualise quantitative data sets.
Requirements, Exclusions and Recommendations
Learning Recommendations:This is an advanced research methods module and is only suitable for students who have taken research methods and
statistics modules in the behavioural sciences at an undergraduate level.
Module Requisites and Incompatibles
Incompatibles:PSY40440 - Adv. Research Methods & Stats
Assessment Strategy
| Description | Timing | Component Scale | % of Final Grade | ||
|---|---|---|---|---|---|
| Report(s): This assessment requires students to complete a series of analyses in SPSS and then write a detailed report on the findings to APA standards. |
Week 12 | Standard conversion grade scale 40% | No | 70 |
No |
| Participation in Learning Activities: Participate in R workshops and submit in-class coding and data analysis tasks. | Week 3, Week 5, Week 7 | Pass/Fail Grade Scale | No | 30 |
No |
| Resit In | Terminal Exam |
|---|---|
| Spring | No |
Feedback Strategy/Strategies
• Feedback individually to students, post-assessment
• Group/class feedback, post-assessment
How will my Feedback be Delivered?
Group feedback on key areas for development relevant to upcoming activities assignment given in class. Students receive individual written feedback on end of trimester portfolio.
| Name | Role |
|---|---|
| Assoc Professor Nuala Brady | Lecturer / Co-Lecturer |
| Monika Pilch | Lecturer / Co-Lecturer |
Timetabling information is displayed only for guidance purposes, relates to the current Academic Year only and is subject to change.
| Autumn | Small Group | Offering 1 | Week(s) - 10, 11 | Wed 09:00 - 12:50 |
| Autumn | Small Group | Offering 1 | Week(s) - 3, 5, 7 | Wed 09:00 - 12:50 |
| Autumn | Small Group | Offering 1 | Week(s) - 9 | Wed 09:00 - 12:50 |
| Autumn | Small Group | Offering 1 | Week(s) - 9, 10, 11 | Wed 13:00 - 16:50 |