Preliminaries

Where do we meet?

Class times and locations Lectures Day/Time: Tuesday, 1:10-3:00pm
Lecture Location: Easterfield Building EA407

Course Learning Objectives

Ethical Reasoning. Beginning in week 1, we will explore questions that are typically reserved for philosophy courses but are central to the conduct of psychology: why do we need to think about right and wrong in science? What if different people have different ideas about what is right and wrong in science? Is there hope for ethical progress? Can science play a role in ethical progress? We will provide you with a set of strategies for addressing these questions.
Programming in R. Beginning in week 2, we will teach you the basics of programming in the statistical language R. The past several decades have brought extraordinary new tools to psychological scientists, many of which require literacy in computer programming. While some of you may find the thought of programming thrilling, others may find it terrifying or boring! We promise that programming can be fun. This course is designed to help you find that joy.
Understanding measurement. Beginning in week 3 the course will turn its focus to developing skills for constructing and validating measures in cross-cultural research. Again these skills will be invaluable for a wide range of tasks you may face in psychological science and will help you to address problems that will arise in other areas of your research and work. Measurement will occupy our attention through week 6.
Understanding causal inference. Beginning in week 7 and for the following four weeks, the course will impart skills that you require to disentangle causation from correlation. Again our focus will be on the special problems that arise for cultural datasets. Notably, in psychological science, causal inference remains underdeveloped, and the material in this part of the course will position you to make potentially important contributions, whether or not your interests lie in cross-cultural psychology.

Assignments and due dates

Assessment	CLOs	Percent	Due
Class participation	*	10	Weekly
Take-home	3,4	10	March 19 (w3)
Theoretical application	1,2,3	30	9 May (w9)
Pre-reg review	1,2,3,4	10	28 May (w11)
Statistical application	1,2,3	30	11 June (w13)
Letter to the reviewer	1,2,3	10	11 June (w13)

Assessment 1: Class Participation

1. your willingness to ask/answer questions and generally contribute to class discussion; and
1. the quality of your contributions
NOTE: if you’re sick, you shouldn’t come to class. Just let me know in advance. Your participation will not be affected.

Assessment 2: Take Home Research Concepts Workbook

This test will help you revise core statistical and methodological issues. It is a chance to brush up on basic statistical knowledge and will help you re-familiarize yourself with material that we will build on later in this course.
The key focus is the revision of basic terms, including correlation, regression, and on basic R applications.
The test contains a theoretical and a practical component. Therefore, it is essential that you complete these questions since you will need to understand the material for the more advanced techniques and approaches that we cover in this course.
There is no word limit (be reasonable)
You can use any source that you find useful.
Warning: AI chatbots may be used but they make errors confidently.
Generally, it is better practice, to use peer-reviewed publications.
Any resource you use must be cited. Failure to cite your source is a form of academic misconduct.
You may complete the test in your own study time. We ask that you work individually.

Assessment 3:Theoretical Application (5,000 word maximum including references)

Choose one particular psychological concept or variable of interest to you. Provide a brief introduction to the concept or variable. Provide a sketch of the methodology for your study (what analysis will you run: equivalence tests, regressions, etc.) following the provided pre-registration template. Identify and justify your research participants’ cultural background. This assessment is equivalent to the introduction and methods part of an empirical paper.

The word limit for this assignment is 5000 words max (including references), and it must be typed and double spaced with a 12point Times New Roman font (or similar).

Pre-Registration Review (1000 words maximum, including references)

You will be invited to provide a review of one submitted pre-registration from another student. Using what you have learned about cross-cultural research provide feedback on both theory and suggested methods. Make sure to provide concrete and respectful feedback.

Statistical Application (4,000 word maximum excluding tables and any references)

Option 1 Measurement (see outline)

Option 2 Causality (see outline)

Letter to the Reviewer

Using the reviewer letter you received, respond to the points raised by the reviewer. Where did you alter your methods and pre-registration, where do results support your reviewer, where do they not support their claims.

Submission and return of work

Assessments or detailed feedback on your performance will typically be returned to you within 10 working days.

Extensions

If any due date does not suit you, you may negotiate a new due date, in writing, that suits you. Any request for revision must be submitted in writing (by email) to your instructor before class on March 14th, 2023

Penalties

The submission of late assignments is strongly discouraged. A penalty of one grade per day (e.g., B down to B-) from the hand-in date will be deducted from the final grade for any late work.

Unforeseeable events

In general, we require evidence (medical certificate etc.) to grant an extension.

Word limits

Assignments that are over the word limit (see above) will be penalized. All submitted assessments are expected to be your own. You should neither give nor receive any aid on the assessments. Giving or receiving aid on assessments will be considered academic misconduct, resulting in registration in the Academic Misconduct Register (AMR). You may use any source, but the source must be cited. Penalties appropriate for the level of academic misconduct may be applied. Failure to cite your source will be considered academic misconduct and will result in registration in the Academic Misconduct Register (AMR).

Materials and equipment

You should bring paper and a writing utensil or laptop/tablet to seminars. For the data analysis sessions, having your personal laptop with the relevant computer programs (R and RStudio) installed is essential. Most sessions will require data analysis.

Note: If you do not have a laptop, let me know. We will find a solution.

Help

Dr.Inkuk Kim inkuk.kim@vuw.ac.nz

Torven Schalk torven.schalk@vuw.ac.nz

Joseph Bulbulia joseph.bulbulia@vuw.ac.nz

Thanks to Johannes Karl and Ron Fischer

For developing measurement components of the course