Academic Integrity
Academic integrity involves acting honestly, ethically, fairly, and respecting others in teaching, learning, research, and administration. It means producing honest, ethical work and it's one of the key foundations of being a good student.听
Learn more about academic integrity, a key principle at UC through this online .
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Avoiding Plagiarism
Plagiarism means using another author鈥檚 words or ideas without proper acknowledgement. This workshop offered by the Academic Skills Centre covers the different forms of plagiarism and teaches strategies for avoiding it in your academic writing.
- Next date to be confirmed
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Copyright and your Thesis
Copyright is a form of intellectual property. It is a legal right that automatically arises when an original work is created, for example an artwork, literary work, musical work, film or sound recording.听
Find out more about through this resource provided by the library.听
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Demystifying the Ethics Process
Will your research require ethics approval? Not sure whether it does? Come along to this session, in which the co-chair of the Human Research Ethics Committee (HREC) will share insights about the need for research ethics committee review and how the HREC works at UC. There will also be opportunities to discuss ethical issues related to your own project to help enhance your research journey.
- Next date to be confirmed
Risk management
Research Data Management听
Research Data Management is becoming increasingly important. Creating a plan at the beginning of your project enables you to be more efficient with regards to data creation, be compliant with regulations and policies and address who is responsible for what.
Develop your knowledge by using the 九州影院鈥檚 and make use of the eResearch Consultancy service or the weekly .听听
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Data Handling听
Good data organization is the foundation of any research project. Most researchers have data in spreadsheets, so it鈥檚 the place that many research projects start.
In order to use tools that make computation more efficient, such as programming languages like R or Python, we need to structure our data the way that computers need the data. Since this is where most research projects start, this is where we want to start too!
In this lesson, you will learn:
Good data entry practices - formatting data tables in spreadsheets
How to avoid common formatting mistakes
Approaches for handling dates in spreadsheets
Basic quality control and data manipulation in spreadsheets
Exporting data from spreadsheets
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- Next date to be confirmed
