Supervision of academic projects
I supervise academic projects of students enrolled in Bachelor, Master and PhD programmes.
The topics in which I offer supervision include
- Applied Linguistics
- Language attitudes
- Psychology of Language Learner
- Second language acquisition
- Sociolingustics
- World Englishes
Plagiarisms: what is is and how to avoid them?
Plagiarism is using someone else’s ideas, words, or work without giving proper credit.
It can be:
-
Direct copying (copy–paste from websites, books, or AI tools)
-
Poor paraphrasing (changing only a few words)
-
Using ideas without citing
-
Re-using your own previous work without permission (self-plagiarism)
-
Submitting work you didn’t write
Plagiarism can be intentional or unintentional, but the consequences are the same — so it’s important to learn how to avoid it.
How to Avoid Plagiarism
1. Keep track of your sources
- Write down where every idea, quote, or statistic came from.
2. Paraphrase properly
- Good paraphrasing means rewriting ideas fully in your own words and structure, not just swapping words.
3. Use quotation marks
- If you use someone’s exact words → put them in quotation marks and cite the source.
4. Cite everything that is not common knowledge
- If you had to look it up, you should probably cite it.
5. Use a reference style consistently
- Common styles: APA, MLA, Chicago.
Pick one and use it the same way throughout the text.
6. Plan your writing early
- Most plagiarism happens when students feel rushed.
7. Use plagiarism-detection tools responsibly
- They help you check your work — they do not replace proper writing and citation.
For Learning How to Avoid Plagiarism
-
Purdue Online Writing Lab (OWL)
Excellent tutorials on paraphrasing, quoting, and citation. -
Scribbr – Academic Writing Guides
Clear examples, quizzes, and step-by-step explanations. -
Copyleaks – Plagiarism Resources
Tips for correct referencing and avoiding accidental plagiarism. -
University of Siegen – Plagiate vermeiden
German-language explanations of plagiarism & good academic practice
Useful resources
1. Free software for statistical analysis of data:
JASP: https://jasp-stats.org/
- Free and open-source, runs on Windows, macOS, Linux
- Intuitive GUI, similar to what you might know from commercial packages like SPSS
2. Introductions into statistical analysis of data:
Statistics with LAERD: https://statistics.laerd.com/
- This site offers very clear introductions into the whats and hows of many statistical procedures
- It is not a free source but the prices are very moderate
- From my personal experience, you can learn very fast with this resource within a short period of time