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HPS911 - Advanced Research Methods

Year:

2022 unit information

Important Update:

Unit delivery will be in line with the most current COVIDSafe health guidelines. We continue to tailor learning experiences for each unit to achieve the best possible mix of online and on-campus activities that successfully blend our approaches to learning, working and research. Please check your unit sites for announcements and updates.

Last updated: 4 March 2022

Enrolment modes:Trimester 1: Online
Trimester 2: Online
Credit point(s):1
EFTSL value:0.125
Unit Chair:Trimester 1: Hua Yong
Trimester 2: Hua Yong
Prerequisite:

Nil

Corequisite:

Nil

Incompatible with:

HPS907 and HPS707

Typical study commitment:

Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit.

Scheduled learning activities - cloud:

Learning experiences are via CloudDeakin 1 x 1 hour weekly class delivered cloud (online) plus 1 x 2 hour weekly blackboard collaborate seminar or equivalent each

Note:

Students should consult with their PhD supervisors with regard to selection of elective topics

Content

This unit will focus on a variety of methodological approaches to research based upon the scientist-practitioner model of evidence-based practice. The course will provide an overview of data management, basic Structural Equation Modeling, and basic qualitative analysis. Students are expected to be familiar with univariate statistical techniques prior to commencing the course, and have some familiarity with multivariate techniques. Students will be required to screen, clean, and prepare data for analysis and to undertake preliminary univariate and multivariate screening assessment.

ULO These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can: Deakin Graduate Learning Outcomes

ULO1

Students will be able to read and follow the basics of a series of multivariate analytic techniques.

GLO1: Discipline-specific knowledge and capabilities
GLO3: Digital literacy
GLO4: Critical thinking
GLO5: Problem solving
GLO6: Self-management

ULO2

Students will be able to assess if a multivariate analytic technique has been validly applied.

GLO3: Digital literacy
GLO4: Critical thinking
GLO5: Problem solving
GLO6: Self-management

ULO3

Students will be able to decide which multivariate technique is the most appropriate for a given problem.

GLO3: Digital literacy
GLO4: Critical thinking
GLO5: Problem solving
GLO6: Self-management

ULO4

Advanced students will be able to understand the relationship between multivariate analytic techniques.

GLO1: Discipline-specific knowledge and capabilities
GLO3: Digital literacy
GLO4: Critical thinking
GLO5: Problem solving
GLO6: Self-management

ULO5

Advanced students will understand the deep meaning of a multivariate analytic technique, and that this reveals the structural relationships between many variables.

GLO1: Discipline-specific knowledge and capabilities
GLO3: Digital literacy
GLO4: Critical thinking
GLO5: Problem solving
GLO6: Self-management

ULO6

Extremely advanced students will understand how to generalise from the techniques studied, and understand new techniques as these arise.

GLO1: Discipline-specific knowledge and capabilities
GLO2: Communication
GLO3: Digital literacy
GLO4: Critical thinking
GLO5: Problem solving
GLO6: Self-management

Assessment

Trimester 1:
Assessment description Student output Grading and weighting
(% total mark for unit)
Indicative due week
Assessment 1: Statistical analysis and written assignment 2000 words 40%
  • Week 7
Assessment 2: Examination 2 hours 60%
  • Examination period

The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.

Learning Resource

There is no prescribed text. Unit materials are provided via the unit site. This includes unit topic readings and references to further information.

Unit Fee Information

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