PSYCHOL 6602OL - Applied Quantitative and Qualitative Methods

Online - Online Teaching 2 - 2022

This applied methodology course will equip you with the knowledge, skills, and abilities required for understanding and conducting data analysis in psychology. With a guided step-by-step approach, this course will explore how to use, report, and apply both quantitative and qualitative research methodologies, utilising a range of industry-relevant software packages.

  • General Course Information
    Course Details
    Course Code PSYCHOL 6602OL
    Course Applied Quantitative and Qualitative Methods
    Coordinating Unit Psychology
    Term Online Teaching 2
    Level Postgraduate Coursework
    Location/s Online
    Units 3
    Contact Up to 2 hours per week
    Available for Study Abroad and Exchange N
    Restrictions Available to Graduate Diploma in Psychology (Advanced) (OL) students only
    Course Description This applied methodology course will equip you with the knowledge, skills, and abilities required for understanding and conducting data analysis in psychology. With a guided step-by-step approach, this course will explore how to use, report, and apply both quantitative and qualitative research methodologies, utilising a range of industry-relevant software packages.
    Course Staff

    Course Coordinator: Dr Josiah Krieg

    E-mail: josiah.krieg@adelaide.edu.au
    Course Timetable

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

    Full details of each week's activities can be found in MyUni.
  • Learning Outcomes
    Course Learning Outcomes
    1 Adapt quantitative analysis and data management skills to different software packages
    2 Formulate principled arguments for the use of various methods when conducting qualitative analysis
    3 Formulate principled arguments for the use of various methods when conducting advanced regression and ANOVA techniques
    4 Analyse quantitative data to answer advanced psychological research questions
    5 Communicate the results of quantitative and qualitative analyses using APA guidelines.
    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

    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.

    4

    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.

    5

    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.

    N/A

    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.

    N/A

    Attribute 7: Digital capabilities

    Graduates are well prepared for living, learning and working in a digital society.

    1

    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.

    2, 3
  • Learning Resources
    Required Resources
    This is a fully online offering. Students will require access to the internet to access course content and to engage in online tutorials. Students will need to install free, open-source, cross-platform packages for statistical analysis (JASP, https://jasp-stats.org/; R, https://cran.r-project.org/; RStudio, https://www.rstudio.com/products/rstudio/) on their computer. Required readings will be available through MyUni.
    Recommended Resources
    Detailed reading lists will be provided within course modules on Myuni; all readings will be accessible online.
    Online Learning
    This is a fully online offering. Myuni will be used for all course materials, communication, links to curated resources, online tutorial support and assignments including submissions, feedback and grades.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    Engagement with course content is facilitated by online videos, interactive online activities, curated readings and resources, and self-directed study supported by weekly online 90 minute tutorial sessions.

    There are 6 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 6-week intensive, accelerated learning offering. Students should expect to spend around 25 hours per week on this course.

    Hours per Week
    Tutorials: 1.5 hours
    Tutorial preparation: 1 hour
    Assessment-related tasks: 8.5 hours
    Engaging with online activities: 9 hours
    Weekly reading/study: 5 hours
    Learning Activities Summary
    The course is presented over six weeks, with one module per week:

    1. Introduction to R
    R Basics
    Importing and Describing Data
    Managing Data in R

    2. Statistics and Graphing in R
    Statistics in R
    R Markdown
    Graphing in R

    3. Advanced Regression
    Entering Variables
    Mediation
    Moderation
    Logistic Regression

    4. Advanced ANOVA
    Factorial ANOVA
    ANCOVA
    MANOVA

    5. Applied Qualitative Methods
    Defining Qualitative Research
    Qualitative Interviewing and Transcription
    Textual Data
    Thematic Analysis

    6. Content Analysis and Mixed Methods
    Content Analysis
    Mixed Methods
    Specific Course Requirements
    N/A
  • Assessment

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

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

    Assessment Summary
    Assessment Task Task Type Weighting (%) Hurdle requirement Learning Outcome
    1. Working with R Summative 20 No 1
    2. Quantitative Data Analysis Summative 40 No 3,4,5
    3A. Thematic Analysis Summative 30 No 2,5
    3B. Quiz Summative 10 No 2,5
    Assessment Related Requirements
    Submission via Turnitin. All assignments are due by 11:59pm ACST/ACDT 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: Working with R (20%, due end of week 2)
    The purpose of this assessment is to evaluate your understanding of how to manage, analyse, and graph data in a reproducible manner using R. For this assessment, you will take the role of a research assistant who has been asked to finish tidying a dataset and perform some initial demographic analyses using R. You will be required to respond to the short-answer questions listed in the assessment brief, using the template provided.

    Assessment 2: Quantitative Data Analysis (40%, due end of week 4)
    The purpose of this assessment is to evaluate your understanding of how to conduct regression and ANOVA analyses in JASP to answer psychological research questions, and report the results according to APA guidelines. For this assessment, you will take the role of a researcher who has conducted a study exploring the association between adult attachment style and reaction time, performing preliminary analyses on some of the study’s key research questions. You will be required to respond to the short-answer questions listed in the assessment brief, using the template provided. These exercises will require you to select appropriate tests to address each question posed.

    Assessment 3A: Thematic Analysis (30%, due end of week 6, 2250 words +/- 10%)
    The purpose of this assessment is to demonstrate that you can conduct and report a common type of qualitative analysis—thematic analysis. For this assessment, you will take the role of a researcher at a not-for-profit organisation. You have been tasked with conducting a thematic analysis, and reporting your research-question justification and findings within a draft article that has been partially populated by the research team. You will be required to conduct a thematic analysis and prepare a report, using the template provided.

    Assessment 3B: Quiz (10%, due end of week 6)
    In this assessment, you will complete seven multiple-choice and three short-answer questions to demonstrate your understanding of content analysis and mixed methods. Questions will concern the key principles of these approaches and recent studies in which these approaches have been applied.
    Submission
    Fully online course - e-submission and marking
    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 Access Adelaide.

  • 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 Study Smart Hub 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
  • 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’s disciplinary procedures.

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