Survey research and design in psychology/Overview

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

Unit outline
The unit outline contains specific details for formally enrolled students.

Syllabus
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
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
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
Three educational themes guide the andragogical design and facilitation of this unit:
 * 1) Collegiality : Emerging academics participate in facilitated learning events
 * 2) 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).
 * 3) Learning attitude : engage + work hard = learn + succeed
 * 4) 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".
 * 5) Open education
 * 6) The unit materials and learning resources are freely available as open educational resources on Wikiversity and 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).
 * 7) Participants are welcome to contribute by editing and/or commenting on unit materials.
 * 8) The open educational resources include:
 * 9) Lecture slides
 * 10) Lecture recordings
 * 11) Readings
 * 12) Tutorial notes

Assessment
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
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:

Special needs
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
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.

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

Previous introductory experience using SPSS software is expected.