PSYCHOL 6504OL - Applying Research Methods in Psychology

Online - Online Teaching 4 - 2025

How do we apply methodological and statistical concepts to real-world problems? This course builds onto the foundation provided by Research Methods, Design and Analysis, exploring research methods for quantitative and qualitative data in more depth. You will think critically about the process of conducting research, apply your knowledge of research methods to a variety of contexts, and further develop your understanding of common analyses.

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Course Details

Course Code	PSYCHOL 6504OL
Course	Applying Research Methods in Psychology
Coordinating Unit	Psychology
Term	Online Teaching 4
Level	Postgraduate Coursework
Location/s	Online
Units	3
Contact	1 to 2 hour online tutorial
Available for Study Abroad and Exchange	N
Prerequisites	PSYCHOL 6500OL and PSYCHOL 6501OL
Restrictions	Graduate Diploma in Psychology or Graduate Certificate in Psychology
Assessment	Online Assessments and Written Assignments

Course Staff

Course Coordinator: Dr Matthew Dry

Course Timetable

The full timetable of all activities for this course can be accessed from .

The course has six modules. Students study one module per week. Modules 1 and 2 focus on qualitative research methods and data analysis, Modules 3 and 4 focus on quantitative data analysis, and Modules 5 and 6 focus on biases and errors in research, as well as how to address them. The modules are:

Module 1: Introduction to qualitative research
Module 2: Qualitative analysis
Module 3: Factorial ANOVA and chi-square
Module 4: Simple and multiple regression
Module 5: Biases and errors in research
Module 6: Contemporary best practice in research

Course Learning Outcomes

Upon completion of this course, students will be able to:

demonstrate advanced knowledge of qualitative research methods in psychology
analyse qualitative data to answer psychological research questions
analyse quantitative data in JASP to answer psychological research questions
demonstrate advanced knowledge of factorial ANOVA, chi-square, and multiple regression
evaluate published research papers in psychology

University Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

University Graduate Attribute	Course Learning Outcome(s)
Attribute 1: Deep discipline knowledge and intellectual breadth Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.	1,2,3,4,5
Attribute 2: Creative and critical thinking, and problem solving Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.	1,2,3,4,5
Attribute 3: Teamwork and communication skills Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.	2,3
Attribute 4: Professionalism and leadership readiness Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.	N/A
Attribute 5: Intercultural and ethical competency Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.	1,2,5
Attribute 6: Australian Aboriginal and Torres Strait Islander cultural competency Graduates have an understanding of, and respect for, Australian Aboriginal and Torres Strait Islander values, culture and knowledge.	1,2
Attribute 7: Digital capabilities Graduates are well prepared for living, learning and working in a digital society.	3
Attribute 8: Self-awareness and emotional intelligence Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.	N/A

Learning Resources
Required Resources
Course Texts

Required readings in Modules 1 and 2 will be taken from:
- Howitt, D., & Cramer, D. (2020). Research methods in psychology. Harlow: Pearson.
Required readings in Modules 3 and 4 will be taken from:
- Coolican, H. (2024). Research methods and statistics in psychology (8th ed.). Routledge.
The required readings in Modules 5 and 6 will be a selection of journal articles. Further details are provided in the modules themselves.

Online copies of both textbooks are available via the 成人大片 library.

Software

For Modules 3 and 4, students need to install a free cross-platform statistical software package called JASP onto their computer. Guidance will be provided in the course on how to do this. This software is the same as what's used in PSYCHOL 6501OL - Research Methods, Design and Analysis. Students who previously studied that course may wish to see if an updated version of JASP is available.
Recommended Resources

N/A

Online Learning

This is a fully online offering. MyUni will be used for all course materials, communication, links to curated resources, online activities, online tutorial support, and assignment submission, feedback and grades
Learning & Teaching Activities
Learning & Teaching Modes

Engagement with course content is facilitated by online presentations, interactive online activities, curated readings and resources, and self directed research and study supported by weekly online tutorial sessions. There are six weekly modules with learning scaffolded across the modules to ensure that students develop deep discipline knowledge as well as the academic literacy, research skills and capacity to apply and communicate their understanding as specified for an AQF8 level offering.

Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
This course is a six week intensive, accelerated learning offering. Students should expect to approximately 25 hours per week engaging with the online content, in private study, attending online tutorials, and completing the coursework assignments.

Indicative hours per week:
- 1.5 hours - Tutorial
- 1 hour - Tutorial Preparation
- 9 hours - Assessment related tasks
- 10 hours - Engaging with online content (e.g, video presentations, podcasts, directed research activities, discussions, interactive tasks)
- 3.5 hours - Readings
Learning Activities Summary

The course has six modules. Students study one module per week. Modules 1 and 2 focus on qualitative research methods and data analysis, Modules 3 and 4 focus on quantitative data analysis, and Modules 5 and 6 focus on biases and errors in research, as well as how to address them. The modules, and their indicative content are outlined below:

1. Introduction to Qualitative Research
Qualitative and mixed methods approaches
Preliminary considerations in study design
Methodological rigour in qualitative research

2. Qualitative Analysis
Quantitative versus qualitative research
Beginning your qualitative analysis: coding
Introduction to qualitative analysis: thematic analysis and content analysis
Appraising qualitative research

3. Factorial ANOVA and Chi-Square
Factorial ANOVA
Chi Square Test of Association

4. Simple and Multiple Regression
Regression overview
Simple linear regression
Multiple linear regression

5. Biases and Errors in Research
    Drawing incorrect conclusions from data
    Biases and errors during the research process
    Reproducibility and the replication crisis

6. Contemporary Best Practice in Research
Reconsidering research findings
    Improving research practices
Open science

Specific Course Requirements

N/A

The University's policy on Assessment for Coursework Programs is based on the following four principles:

Assessment must encourage and reinforce learning.
Assessment must enable robust and fair judgements about student performance.
Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
Assessment must maintain academic standards.

Assessment Summary

Assessment Task	Task Type	Due	Weighting (%)	Learning Outcome
Assessment 1: Qualitative Coding and Preliminary Analysis	Summative	Week 2 Sunday 11:59pm	35	1, 2
Assessment 2: Data Analysis	Summative	Week 4 Sunday 11:59pm	35	3, 4
Assessment 3: Evaluation of Published Research	Summative	Week 6 Sunday 11:59pm	30	5

Assessment Related Requirements

Submission via Turnitin. All assignments are due by 11:59pm on the Sunday at the end of the week in which they are due. A penalty of 5% per day applies for late submissions.

Extensions are granted on medical, compassionate or other special circumstances recognised under the University’s Modified Arrangements for Coursework Assessment Policy.

The completed extension application form and any documentation (such as a medical or counsellor's certification) should be emailed to the
course coordinator and submitted before the due date. The course coordinator will consider the request in the light of the case made and
University deadlines, and may grant an extension of up to three days.

Assessment Detail

Assessment 1: Qualitative Coding and Preliminary Analysis (35%, 500 words, due week 2)
In this assessment, you will be conducting qualitative coding and preliminary thematic analysis on provided extracts from interview transcripts. You are required to develop your own coding framework based on the ideas/ concepts and patterns you identify in the data, and answer three short answer questions related to this coding process. This assessment relates and maps onto content from Modules 1 and 2.

Assessment 2: Data Analysis (35%, no word limit, due week 4)
This assessment focusses on factorial ANOVA, chi-squared, and multiple regression. These statistical tests were covered in Modules 3 and 4. The assessment has three sections. Section 1 focusses on factorial ANOVA, Section 2 focusses on chi-squared, and Section 3 focusses on multiple regression. In each section, you will be given an overview of a fictional study that used that section’s test in its analysis. You will run the fictional study’s analysis yourself in JASP. You will then be asked a series of questions about the fictional study’s design, its findings, and / or general questions about the statistical test. Content relevant to this assessment is covered in Modules 3 and 4.

Assessment 3: Evaluation of Published Research (30%, 1000 words, due week 6)
This assessment requires answering several short answer questions that centre on the reproducibility crisis and contemporary best-practice when conducting research. To answer some questions, you will need to read and evaluate several provided research articles. Content relevant to this assessment is covered in Modules 5 and 6.

Submission

Online submission via Turnitin.

Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
Grade	Mark	Description
FNS		Fail No Submission
F	1-49	Fail
P	50-64	Pass
C	65-74	Credit
D	75-84	Distinction
HD	85-100	High Distinction
CN		Continuing
NFE		No Formal Examination
RP		Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through .

Student Feedback

The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
Student Support
Counselling for Fully Online Postgraduate Students

Fully online students can access counselling services here:

Phone: 1800 512 155 (24/7)

SMS service: 0439 449 876 (24/7)

Email: info@assureprograms.com.au

Go to the to learn more, or speak to your Student Success Advisor (SSA) on 1300 296 648 (Monday to Thursday, 8.30am–5pm ACST/ACDT, Friday, 8.30am–4.30pm ACST/ACDT)
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
Fraud Awareness

Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator

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