Survey research and design in psychology/Overview

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This page describes the "Survey research and design in psychology" unit of study for participants.

General overview[edit | edit source]

Survey research and design in psychology is a 3rd year undergraduate university-level unit of study. The unit focuses on designing survey research and social science surveys and the use of correlational statistics including exploratory factor analysis and multiple linear regression.

There are 5 modules which consist in total of 10 lectures and 5 tutorials. Associated learning materials are available on English Wikiversity, along with guidelines for the assessment exercises. Additional unit materials are provided on UCLearn, Google Slides, Youtube, and Echo360.

These learning materials were primarily developed by James Neill, University of Canberra, Australia (2005 - 2018). There were approximately 120 formally enrolled students from University of Canberra in the unit each year (Feb-May).

Unit outline[edit | edit source]

The unit outline contains specific details for formally enrolled students.

Syllabus[edit | edit source]

This is a third-year tertiary-level, 3 credit point (150 hour), semester-long unit of study in applied psychological research methods. Learning content and activities focus on:

  1. Developing knowledge and skills involved in conducting well-designed, ethical, survey-based research in psychology and the social sciences;
  2. Theory and practice of survey-based research, including how to ask a research question, survey design, sampling, multivariate data analysis (descriptives and graphing, linear correlation, exploratory factor analysis, multiple linear regression), and interpreting and communicating results in APA style.

Learning outcomes[edit | edit source]

On completion of the unit, participants should be able to:

  1. Design and conduct ethically- and scientifically-sound survey-based research in the social sciences;
  2. Use statistical software (SPSS and Excel) to manage data and to conduct descriptive statistics, graphing, exploratory factor analysis and reliability analysis, and multiple linear regression;
  3. Communicate the results of survey-based research in APA style.

Prerequisites[edit | edit source]

Since the unit is targeted at third-year tertiary (university) level, it is assumed that participants have already completed the equivalent of:

  1. A first year tertiary education introductory research and statistics unit (preferably in the social sciences)
  2. A second year tertiary education research and statistics unit (preferably in the social sciences)

As a result of successfully completing such a three-year sequence of units, a student should be equipped for supervised post-graduate and professional research work.

Educational approach[edit | edit source]

Three educational themes guide the andragogical design and facilitation of this unit:

  1. Collegiality: Emerging academics participate in facilitated learning events
    1. Emerging academics ("students") and more experienced academics ("teachers") participate in a collegial academic culture which is designed to develop participants' skills and knowledge through facilitated learning events (lectures, tutorials, readings, assessment, and discussion).
  2. Learning attitude: engage + work hard = learn + succeed
    1. Engagement and active participation in the learning events develop the skills and knowledge needed to demonstrate achievement of the learning outcomes. Basically, this means adopting a "learning attitude".
  3. Open education
    1. The unit materials and learning resources are freely available as open educational resources on Wikiversity and UCLearn so as to maximise their utility. These materials were used to supplement face-to-face (f2f), campus-based teaching at the University of Canberra (UC) by James Neill (2005-2018).
    2. Participants are welcome to contribute by editing and/or commenting on unit materials.
    3. The open educational resources include:
      1. Lecture slides
      2. Lecture recordings
      3. Readings
      4. Tutorial notes

Schedule[edit | edit source]

Principal dates (University of Canberra).

There are 10 lectures and 5 tutorials.

For more details, see Timetable.

Timetable[edit | edit source]

There are 10 lectures on Tuesdays 12:30-14:30, in 2B7, Weeks 1 to 7, 9, 10 and 12.

There are 4 tutorials on Wednesdays 09:30-11:30, 12:00-14:00 and 14:30-16:30 in 12B16 and a 18:00-20:00 online tutorial. Tutorials are during Weeks 01, 03, 05, 09 or Weeks 02, 04, 06, and 10 depending on which tutorial group you enroll in. Check your timetable. The online tutorial will be conducted via Blackboard Ultra (access the link via UCLearn).

In addition, there will an all-day drop-in lab report workshop on Wednesday Week 12 to provide assistance with the lab report.

Wednesday tutorials
Tutorial Start End Duration Weeks Room
Computer Laboratory 01 09:30 11:30 2:00 01, 03, 05, 09 12B16
Computer Laboratory 02 12:00 14:00 2:00 01, 03, 05, 09 12B16
Computer Laboratory 03 14:30 16:30 2:00 01, 03, 05, 09 12B16
Computer Laboratory 04 09:30 11:30 2:00 02, 04, 06, 10 12B16
Computer Laboratory 05 12:00 14:00 2:00 02, 04, 06, 10 12B16
Online Tutorial 06 18:00 20:00 2:00 02, 04, 06, 10 Online

In addition to lectures and tutorials, drop-in tutorial time is provided in 12D16 on Wednesdays before and after tutorials at 09:00-09:30 and 11:30-12:00 (Weeks 1 to 6 and 9 to 10), 14:00-14:30 and 16:30-17:00 (Weeks 1, 3, 5, 9) and 17:30-18:00 and 20:00-20:30 online (Weeks 2, 4, 6, 10). For more information, see Drop-in tutorials.

Assessment[edit | edit source]

The assessment for this unit consists of online quizzes (45%), a data collection and entry exercise (10%), and a lab report (45%) which focuses on the use of exploratory factor analysis and multiple linear regression.

Workload[edit | edit source]

The amount of study needed for this unit will depend on your prior knowledge and pace of learning. The unit is designed to involve approximately 150 hours of study (including contact time and personal study time) - or an average of 11 hours per week. The following table provides a break-down of the main learning activities and the estimated time involved:

Task/activity Hours
10 x 2 hour lectures 20
4 x 2 hour computer-lab tutorials 8
9 x quizzes 6
Readings and tutorial/SPSS practice 40
Data collection and entry 6
Lab report 70
Total 150

Special needs[edit | edit source]

People who need assistance in undertaking the unit because of disability or other circumstances should inform the Unit Convener as soon as possible so that necessary arrangements can be made.

Participation requirements[edit | edit source]

Attendance at tutorials is strongly recommended but not compulsory.

Tutorials develop hands-on data analysis skills through direct contact with teaching staff.

Tutorial learning activities are closely related to the assessment tasks, particularly the lab report.

Readings[edit | edit source]

Readings are recommended but optional. The amount of reading is ultimately up to each emerging scholar. It is not intended or necessary that you read every single reading word for word. Some may prefer to read one or two readings per topic in-depth, others may prefer a lighter reading of a wider range of sources. Do what works for you - the goal should be to satisfy your desired level of understanding and to acquire sufficient knowledge to succeed at the assessment tasks.

There are recommended readings for each lecture. In addition, the lecture readings are listed in the unit outline. Readings may include textbook chapters, other chapters and articles available via the UCLearn site, and openly available online material. The textbook readings are strongly recommended. You could use any textbook that covers the relevant topics, but suggested chapters from Howitt and Cramer (2014) are listed mainly because that is the textbook that students are most likely to already have access to because it is used in the co/prerequisite 2nd year unit Experimental Psychology.

For more information, see readings.

Required IT skills[edit | edit source]

A moderate level of expertise in using word-processing and spreadsheet software is required.

Previous introductory experience using SPSS software is expected.

Software[edit | edit source]

To complete the tutorials and survey research project for Survey research and design in psychology access will be needed to statistical software, including IBM SPSS and spreadsheet software such as Microsoft Excel (part of Microsoft Office). This software can be accessed on University of Canberra campus computers at no additional cost by those enrolled.

You can also use versions of the software on other computers. Options for accessing SPSS include:

  1. Download and install a 14-day trial version.
  2. Purchase a SPSS Standard Grad Pack 6 or 12 month license via SPSS buy now - see bottom right hand corner for links to student version resellers

Calculator[edit | edit source]

A non-programmable calculator (~$10) is recommended for tutorials and quizzes.

USB flash drive[edit | edit source]

A 2GB or larger USB flash drive (~AU$10) is recommended for file storage whilst working on tutorial exercises and the survey research project. Backups should also be made.

See also[edit | edit source]

External links[edit | edit source]