RD7003 Flexible Components

Epigeum Research Integrity Modules (online)

The LearnJCU Higher Degree by Research Organisation contains two suites of Epigeum research integrity modules.  In the first folder, titled Epigeum Research Integrity, you will find the two Fixed Component ethics module that you must complete before Confirmation of Candidature.  The compulsory modules are titled “The Responsible Conduct of Research” and “When Things go Wrong:  Breaches of the Code”.  You must go through these modules and undertake the associated end of course quizzes to satisfy the requirements of the Fixed Component of your professional development.

In addition, you may also undertake other topics in this folder, on a range of material relevant to research ethics and integrity.  You are encouraged to undertake these courses if they are relevant to your research degree program and your career aspirations, and may count them towards the Flexible Component of RD/RM7003. Each individual course will take around three hours, so for each topic successfully-completed you may count three hours towards RE/RM7003 Professional Development. Topics include: planning your research, managing and recording your research, data selection, analysis and presentation, scholarly publication, professional responsibilities, and communication and social responsibility.

The second folder in the HDR Organisation is titled Epigeum Research Integrity Supplementary modules, and contains a variety of modules that you may choose to undertake as part of your Flexible Component.  Topics include:  conflicts of interest, responsible conduct of human participants research, care and use of animals in research, and intellectual property.  Each successfully-completed topic counts for three hours towards RD/RM7003.

Scientific Integrity:  Aboriginal and Torres Strait Islander Research Ethics Module

Historically, Aboriginal and Torres Strait Islander people have been the subject of much research, the vast majority of which was undertaken by non-Indigenous people. Communities were not always aware that they were the subject of a research project, there was little benefit to the communities from the research and in some cases researchers assumed ownership of what was traditional knowledge.

This module has been developed to enable participants to:

• Develop a substantial knowledge of research principles and methods applicable to their field of work
• Develop cognitive skills to demonstrate expert understanding of theoretical knowledge and to reflect critically on that theory and practice
• Develop communication skills to explain and critique theoretic propositions, methodologies and conclusions
• Apply their knowledge and skills with full responsibility and accountability for personal outputs.

How the Modules Work

• The Research Integrity modules made available by GRS provide flexible study areas that enable research candidates to engage in an interactive way with research integrity issues in many different contexts.
• The modules include a short quiz, the results of which are recorded in the LearnJCU Grade Centre, where they can be accessed by the GRS.
• You must obtain at least 80% accuracy in your responses to the quiz to successfully complete it.  If you don’t achieve 80% on your first attempt, you may re-take the quiz.

Graduate Attribute code: [IS]

Epigeum’ Research Methods Modules (online)

The Epigeum modules provide flexible study that enable HDR candidates to engage in an interactive way.  The modules include a pre-course quiz as well as post-course survey and quiz activities.

Access to this and other online modules is via LearnJCU’s Community Group ‘Higher Degree by Research Students’. Click here for a guide to accessing LearnJCU.

Research Methods in the Arts & Humanities Module

This course aims to develop an awareness of the practical and conceptual skills that support effective independent scholarly research in the arts and humanities. The end goal is to help researchers to understand the issues involved in making an informed choice about the methodology and approach most suitable for their own specific project.

Components will include:

• Introducing research methodology in the arts and humanities
• Approaching archives, artefacts and other evidence
• Thinking critically, thinking theoretically
• Understanding disciplinarily and interdisciplinary
• Is it working?

The Arts & Humanities module will take approximately 2.5 hours to complete.

Research Methods in the Sciences Module

This course aims to support doctoral and postdoctoral researchers undertaking independent research in the sciences. The course provides guidance on the different research processes, from the early stages of framing a research question, through conducting the research, to writing up findings and publication.

Components will include:

• What is science?
• Identifying and formulating the research question
• Evaluating research questions
• Designing and planning your research
• Reflection and communication

The Sciences module will take approximately 3 hours to complete.

Research Methods in the Social Sciences Module

This course aims to support doctoral and postdoctoral researchers undertaking independent research in the social sciences. The course provides guidance on the different research processes, from the early stages of framing a research question, through conducting the research, to writing up findings and publication.

Components will include:

• Before you get started
• Framing your research question
• Planning considerations
• Designing your research
• Data collection
• Data analysis
• Starting your research
• Reporting your research

The Social Sciences module will take approximately 3 hours to complete.

Graduate Attribute code: [DE]

One of the secrets of a successful research higher degree candidate is being able to work effectively with your advisory team. HDR candidates often feel confused by apparently conflicting advice from different members of their advisory team or that they are acting as a carrier pigeon between their advisors (supervisors). This workshop will provide you with practical strategies to help you to maximise the advantages of having a team of advisors, each of whom will make a different contribution to your research candidature.

Presented by the Emeritus Professor Helene Marsh

Graduate Attribute code: [EI]

Participants will learn what is required to successfully proceed through the process of thesis examination. Also to be discussed are oral examinations for HDR candidates, particularly from the perspective of the candidate in having an oral component in the doctoral thesis examination process.

Presented by Emeritus Professor Helene Marsh

Graduate Attribute code: [DE]

It is becoming increasingly acceptable in many disciplines for the data chapters of a thesis to be based on papers that have been published or prepared for publication. This workshop will explore the research on what thesis examiners think of this approach and provide advice on how to maximise the likelihood of a positive response for examiners.

Presented by Emeritus Professor Helene Marsh

Graduate Attribute code: [DE]

This session focuses on research design for qualitative researchers. Emphasis will be placed on designing a research study that ensures creativity and coherence among all aspects of your qualitative study: the research questions, literature, theoretical foundation, methodology, data collection and analysis. The anticipated outcome of the session is for researchers to have a well-conceptualised and innovative research design that will provide a framework for supporting  and providing coherence to your entire research process. This session is particularly valuable for HDR candidates in the early stages of their research, especially preparing for confirmation of candidature.

Presented by Professor Catherine Manathunga, The University of the Sunshine Coast

Graduate Attribute code: [DE]

Epigeum modules provide flexible study areas that enable HDR candidates to engage in an interactive way.

This module provides foundational information on the important topic of plagiarism in academic work, with particular emphasis on ensuring that you avoid it. The module should be undertaken alongside the compulsory Plagiarism and 'SafeAssign' workshop that is part of the Professional Development Program.

The Avoiding Plagiarism module:

• Defines plagiarism and describes different types of plagiarism
• Recognises and describes key terms relating to plagiarism
• Explains the importance of referencing
• Shows you how to compile accurate citations and references
• Demonstrates how to correctly paraphrase and acknowledge others’ work
• Demonstrates how to make better use of referencing software to manage your citations and references
• Shows you how to develop strategies to avoid plagiarism in your own work

The module contains interviews with students, explains key terms and provides interactive activities and strategies to help you plan to avoid plagiarism pitfalls. It also contains online resources that will help extend your learning, including articles on real-life cases of plagiarism.

You must complete the embedded quizzes, so that your participation in this module can be counted towards your professional development requirements.  The module takes about 3-4 hours to complete.

Access to this and other online modules is via LearnJCU’s Community Group ‘Higher Degree by Research Students’. Click here for a guide to accessing LearnJCU.

Graduate Attribute code: [IS]

This session will help those doing literature reviews to:

• Create or revise your research plan
• Identify key sources
• Organise your literature
• Devise strategies to manage the amount of literature to read

Presented by the JCU Library & Information Services

Graduate Attribute code: [CC]

This interactive seminar invites you to engage with the many ways of communicating the outcomes of scientific research. Increasingly, researchers are judged on their impact rather than output. Whatever your field of research, someone in the media, the political sphere, schools or just out there in the broad community will want to hear about it. How do you make your meaning clear (and fascinating) to non-specialists without “dumbing-down” and compromising meaning? How do you craft a story about your research that will appeal to diverse audiences? This seminar will consider how to you might find your own language, voice and medium to get your message to the right people and in the most effective way. Associate Professor Liz Tynan is a former science journalist and communicator with an interest in the language of science communication – how words can best be used to grab and hold attention. She is also a researcher who writes about the history of atomic weapons testing in books and other outlets.

Note that this workshop is not about peer-to-peer communication with other scientists. Instead, come prepared to find new ways to make your research available to non-scientists.

Presented by Associate Professor Liz Tynan, Co-ordinator HDR Professional Development Program

Graduate Attribute code: [CC]

The course will focus on clear, effective academic writing and editing, for all academic disciplines. We will engage with broadly-applicable ideas around clarity, efficiency, consistency, logic and technical and stylistic correctness. The aim is to provide a forum for discussion about how HDR candidates can achieve their written communication goals, making use of sound communication principles and practical activities.

For more information see the Academic Writing and Editing (AWE) website.

The capacity to write convincing grant proposals is an essential skill for a researcher. HDR candidates need to develop this skill in order to have their candidature confirmed and to attract research funding. Learn from an experienced researcher how to identify appropriate sources of potential funding and how to tailor your proposal to the needs of your audience.

Presented by Emeritus Professor Helene Marsh

Graduate Attribute code: [EI]

This workshop will show you how to become a publishing dynamo, and also how to become “famous” or your research.

Presented by Professor Bill Laurance, College of Science & Engineering

Graduate Attribute code: [EI]

Choose from five discipline-based online modules

The Epigeum modules provide flexible study areas that enable HDR candidates to engage in an interactive way.  The modules include a post-course survey and quiz activities.

Statistical Methods for Research in Biomedical Sciences, Business, Engineering & Technology, Natural Sciences and/or Social Sciences

This course introduces HDR candidates to the concepts and some basic methods of statistical data analysis.  It will not cover all of the techniques that you are likely to need for any particular research project, but provides the basic understanding that all quantitative researchers should possess. Different sections of this course are tailored to different disciplinary areas, and you should select the one that best reflects your interests from the selection available. Each module will take approximately 2-3 hours to complete.

Access to this and other online modules is via LearnJCU’s Community Group ‘Higher Degree by Research Students’. Click here for a guide to accessing LearnJCU.

Graduate Attribute code: [DE]

Data analysis and presentation using R and RStudio comprises a series of modules that are designed to build participants’ capacity to handle, describe, display and analyse research data using the free software R and the environment where R is most often run – RStudio. The first module in the series is an introduction to R and RStudio and how to use them. The second module will cover the kinds of statistical techniques normally covered in an introductory statistics course, and how to execute them in R. The remaining modules will cover a variety of more advanced statistical programming techniques that are frequently required by researchers. These later modules assume familiarity with the material in the first two, but participants can otherwise pick and choose to suit their needs.  More details on these modules will be provided later this year.

R is first and foremost a computer language, and learning to use it well – like learning any language – takes practice. Each module in the series provides a walk-through self-paced tutorial with code, output, and examples that participants are expected to execute for themselves to produce appropriate output, plus exercises that use and reinforce the skills demonstrated in the examples. Each of the “live” tutorials delivered in each module will discuss any difficulties experienced by participants and make sure that people can handle the exercise problems.

This first module in the series, Getting Started with R and RStudio, introduces R and RStudio, and will endeavour to leave participants at a stage where they understand the basics of the language and can comfortably use it to manipulate data and display it graphically in appropriate ways. The course will be delivered through a self-guided workbook that contains multiple exercises; this will be supplemented by tutorial sessions to review student progress and answer questions.

The first version of R was written in 1995 by two New Zealand statisticians – Ross Ihaka and Robert Gentleman – as teaching software. Its popularity quickly exceeded the expectations of its developers and has only continued to grow since then. The ability to use it is now an essential skill for anyone involved in data analysis. Because it is free and open-source, it has become the environment where almost all new analytical methods first appear: if an analysis is possible at all, it will probably be possible in R. The online user community is immense and growing, with many websites dedicated to assisting both novice and experienced users with problems.

But first you need to understand the basics of the language, how it is structured, and how it sees and displays data – that is what this module aims to develop.

Learning outcomes

• Familiarity with the use of RStudio as an environment for the R language.
• Ability to devise and execute commands in the R language.
• Understanding of R functions and data structures.
• Ability to manipulate, transform and summarize data in R.
• Ability to produce high-quality and appropriate graphs in R.

Format

Completion of the module will require approximately 20 hours’ total commitment that may be credited towards RD7003 Professional Development. Participation will involve:

• 6 x tutorial sessions (run over two weeks)
• Independent completion of tutorial chapters and exercises prior to sessions
• Completion and submission within 24 hours of release of a final set of exercises for assessment.

You must attend all 6 sessions Zoom sessions at 12pm - 1:30pm AEST on the dates below.

• Monday 6 March
• Thursday 9 March
• Monday 13 March
• Thursday 16 March
• Monday 20 March
• Thursday 23 March

Eligibility

Getting Started with R and RStudio is open to all JCU Higher Degree by Research candidates regardless of their stage of candidature or organisational unit of enrolment. Candidates wishing to use the module for credit toward RD7003 will need to comply with assessment requirements detailed below.  Please note that a strict limit of 20 participants will apply to this module, and preference will be given to candidates seeking to undertake the entire module for PD credit.

Assessment

Credit towards RD7003 Professional Development is dependent on compliance with requirements set out in the relevant subject outline. All questions regarding RD7003 requirements should be directed to the Graduate Research School ([email protected]).

Completion of the course will require:

1. completion of the assigned workbook chapters;
2. attendance and participation in the tutorial sessions;
3. submission of a final assessment, which will be graded either satisfactory or unsatisfactory.

Participation. Those participants seeking credit toward RD7003 are expected to complete all relevant exercises in the assigned workbook and participate in all tutorials. In the event of circumstances beyond their control participants should contact the subject coordinator as soon as possible to explain the problem.

Final assessment. All participants seeking credit toward RD7003 should complete and submit solutions to a set of assessment exercises provided at the final tutorial session.

Register here: TBA

Graduate Attribute code: [DE]

Data analysis and presentation using R and RStudio comprises a series of modules that are designed to build participants’ capacity to handle, describe, display and analyse research data using the free software R and the environment where R is most often run – RStudio. The first module in the series is an introduction to R and RStudio and how to use them. The second module will cover the kinds of statistical techniques normally covered in an introductory statistics course, and how to execute them in R. The remaining modules will cover a variety of more advanced statistical programming techniques that are frequently required by researchers. These later modules assume familiarity with the material in the first two, but participants can otherwise pick and choose to suit their needs.  More details on these modules will be provided later this year.

R is first and foremost a computer language, and learning to use it well – like learning any language – takes practice. Each module in the series provides a walk-through self-paced tutorial with code, output, and examples that participants are expected to execute for themselves to produce appropriate output, plus exercises that use and reinforce the skills demonstrated in the examples. Each of the “live” tutorials delivered in each module will discuss any difficulties experienced by participants and make sure that people can handle the exercise problems.

This second module in the series, Introduction to Probability and Basic Statistics with R and RStudio, will review the foundations of statistical analysis and describe how commonly-used statistical methods are implemented in the R programming language. The course will be delivered through pre-recorded online lectures and a self-guided workbook which contains multiple exercises. These materials will be supplemented by two weekly online tutorial sessions to review student progress and answer questions. The module includes:

• Descriptive statistics
• Probability and probability distributions
• Hypothesis testing
• X²  tests and their alternatives
• t-tests and Analysis of Variance (ANOVA)
• Non-parametric tests
• Correlation and regression
• Experiment and survey design (including sample size and power).

Learning outcomes

• Familiarity with the use of RStudio as an environment for the R language.
• Understanding of foundational concepts in probability and statistics.
• Ability to identify appropriate statistical tests for scientific data analysis.
• Ability to devise and execute statistical analyses in the R language.
• Understanding of appropriate experimental design to enable statistical inference.

Format

Completion of the module will require approximately 60 hours total commitment that may be credited towards RD7003 Professional Development. Participation will involve:

• Online, twice weekly tutorial sessions (run over 6-8 weeks) using Zoom.
• Independent viewing of pre-recorded lectures and completion of tutorial chapters and exercises prior to sessions.
• Completion and submission within 24 hours of release of a final set of exercises for assessment.

You must attend the Zoom sessions twice a week on Monday's and Thursday's at 12pm - 1:30pm AEST on the following dates.

Dates for 2023: TBA

Eligibility

Basic Statistics with R and RStudio is open to all JCU Higher Degree by Research candidates regardless of their stage of candidature or organisational unit of enrolment. Candidates wishing to use the module for credit toward RD7003 will need to comply with assessment requirements detailed below. Moreover, this course assumes some familiarity with the R programming language and RStudio, with an ability to import, manipulate and describe data and display it graphically in appropriate ways using R or RStudio. As such, we recommend that prior to enrolment that you either (i) have successfully completed the introductory module in this series: Getting Started with R and RStudio; or (ii) directly contact Michael Meehan ([email protected]) or Rhondda Jones ([email protected]) to access and complete the Basic Programming in R and RStudio worksheet to demonstrate R competency.

Register: TBA

Assessment

Credit towards RD7003 Professional Development is dependent on compliance with requirements set out in the relevant subject outline. All questions regarding RD7003 requirements should be directed to the Graduate Research School ([email protected]).

Completion of the course will require: (1) familiarity with the content of the pre-recorded lectures; (2) completion of the assigned workbook chapters; (3) attendance and participation in the tutorial sessions; (4) submission of a final assessment, which will be graded either satisfactory or unsatisfactory.

• Participation. Those participants seeking credit toward RD7003 are expected to complete all relevant exercises in the assigned workbook and participate in all tutorials. In the event of circumstances beyond their control participants should contact the subject coordinator as soon as possible to explain the problem.
• Final assessment. All participants seeking credit toward RD7003 should complete and submit solutions to a set of assessment exercises provided at the final tutorial session.

Graduate Attribute code: [DE]

This workshop is not another lecture on research design or research methods. It is about looking at ‘research’ with a different lens and developing confidence in answering the following questions

• How can I turn a good idea into a research project worthy of doing?
• Is this a good research project into which I should invest time and energy?
• Why is it important to build linkages between research, our daily work/life and our career goals?
• Have I taken the necessary steps to choose the right method(s) to answer the research questions?
• What steps should I take to ensure all benefits of conducting the particular research project can be realised?

With research impact in mind – and how research impact should be considered in relation to project key stakeholders– this workshop will also explore how participants can draw on prior research to guide the choice of design and methods that are right for the research questions and expected outcomes. This workshop is suitable for all HDR candidates who would like to ensure that their research design will lead to the desired research impacts.

Presented by: Dr Zhanming Liang, Associate Professor, Health Systems Management and Policy, JCU College of Public Health, Medical and Veterinary Sciences

Graduate Attribute code: [DE]

Trainer: Sue Bullen

This workshop will be conducted online and run over 3 x two-hour sessions. You should attend each session to complete the workshop.

The workshop is a basic introduction to NVivo for Windows.  If you are using NVivo for Mac, you are welcome to attend but should understand that there are many differences between platforms and it won’t be possible to show both environments.

The objective is to provide you with the information and practice you need to get started with your own project.

What’s covered?

• A ‘big picture’ tour of NVivo, using a sample project.
• Creating a new project. Understanding the NVivo Workspace and file structure.
• Importing Word documents and PDF files. Reading and reflecting with annotations and memos. Making some connections via See Also Links.
• Creating and defining codes. Coding, viewing coding, uncoding, moving and merging codes. Coding on. Understanding the power of an efficient coding structure.
• Classifications, attributes (variables), values, cases. Importing classification sheets.
• Word frequency and text search queries.

Participants can count 6 hours towards RD7003 Professional Development as long as all 3 sessions are attended

Graduate Attribute code: [DE]

Trainer: Sue Bullen

*** Registrants must have attended the Fundamentals in NVivo course prior to attending this course or be very familiar with the topics covered in the Fundamentals course.  The Moving On course is for those who are familiar with the basics and are ready to learn some of the more advanced features.

Overview

This workshop will be conducted online and run over 3 x two-hour sessions. You should attend each session to complete the workshop.

The workshop explores features of the software not covered in the Fundamentals course. We will look at other kinds of data, with a particular focus on survey data (datasets), media, images and web data. In addition, you’ll be introduced to the coding queries and many of the visualisations available in the software.

What’s covered?

• Preparing survey data for import. Using the Survey Wizard to setup the datasets for analysis.
  Importing media, images and web data.
• Coding, Matrix coding and Cross-Tab queries. Working with attribute values and nodes to make comparisons.
• Visualising the matrix and cross tab query result.
• Other visualisations such as Charts, Comparison Diagrams.
• Advanced find, sets and search folders for more advanced comparisons.
• Mind map, project map and concept map; when to use them and how they can help with analysis

Participants can count 6 hours towards RD7003 Professional Development as long as all 3 sessions are attended

Graduate Attribute code: [DE]