Introduction to scientific research

Duration

10h Th, 10h Pr, 30h Proj.

Number of credits

Lecturer

Mario Cools

Language(s) of instruction

French language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

• General Research Methodology
• Introduction to Quantitative Research
• Introduction to Qualitative Research
• Use of Academic Databases (Scopus, ProQuest, Google Scholar, etc.)
• Introduction to APA Referencing Standards
• Awareness of Plagiarism
• Exploration of Artificial Intelligence Tools in Research
• Scientific Communication
• Expectations for a master thesis

Learning outcomes of the learning unit

At the end of this course, the student will be able to:

• Effectively use academic research tools to find relevant sources.
• Master APA referencing standards in their academic work.
• Recognize and avoid plagiarism practices.
• Have a critical perspective on the use of artificial intelligence tools in research, evaluating their strengths, weaknesses, and ethical implications.
• Begin working on their final thesis/project. The student will be introduced to the specifics and methods of a scientific approach and will be able to implement them in the context of their thesis.
• Design a clear, well-argued, and convincing pitch to present a thesis topic.

Prerequisite knowledge and skills

This course has no prerequisites or corequisites.

However, a strong proficiency in the following languages is essential:

English:

• Reading comprehension (reading academic documents and using research tools).

• Reading comprehension (reading academic documents and using research tools).
• Written expression, including spelling and grammar, for writing documents and academic work.

Planned learning activities and teaching methods

The course is structured around 2 ECTS, corresponding to 50 hours of work distributed as follows:

10 hours of theoretical lessons in class
The lessons will cover the following topics:

• General research methodology.
• Introduction to quantitative and qualitative research.
• Use of academic databases.
• APA referencing standards.
• Awareness of plagiarism.
• Critical exploration of artificial intelligence tools in research.
• Expectations for a final thesis/project.

• Quizzes and practical exercises to validate understanding of the lessons.
• Library and online research sessions.
• Writing and referencing workshops.
• Group presentations on AI tools.

• Documentary research and the use of academic tools.
• Writing the podcast script.
• Producing the pitch/podcast.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course


Further information:

The course will be delivered in person, mainly in French. Participation in both class sessions and practical work is mandatory. Part of the work must be done independently outside of class, particularly to finalize the productions (script and pitch/podcast).

For the academic year 2024-2025, Prof. Mario Cools' courses will be offered online, in the form of video capsules and/or via live stream. However, attendance in class is still required to allow for interactions and to ensure adequate feedback

Course materials and recommended or required readings

Platform(s) used for course materials:
- eCampus


Further information:

Recommended reading: John Biggam (2008): Succeeding with your Master's dissertation. A step-by-step handbook. Open University Press. Berkshire, England.

A selection of slides presented during the course will be made available via the eCampus platform.

Written work / report


Further information:

The evaluation will be based on:
* Script for a Podcast:

Writing a podcast script presenting the future thesis topic. This script must include a context, a literature review (correctly referenced according to APA standards), a focus on one or more research questions, the proposed methodology, and a reflection on the limitations and perspectives of the topic.

The transformation of the script into a pitch video, which will be posted online. This video will not be graded but will serve as a basis for discussion with the future supervisor. However, failure to submit the video will result in a grade of 0, as it is a mandatory component for course validation.

Quizzes, exercises, and presentations in class are mandatory but not graded. Failure to present these exercises without valid justification will result in a penalty on the student's final grade.

Work placement(s)

Not applicable.

Organisational remarks and main changes to the course

This year, the course places increased emphasis on the critical use of artificial intelligence tools in research, taking into account recent developments in this field. Additionally, special attention is given to the quality of scientific communication and the ability to focus on the essentials, particularly through the creation of the podcast.

Contacts

Mario Cools, Full professor mario.cools@uliege.be

Audrey Mertens, Assistant audrey.mertens@uliege.be

Association of one or more MOOCs

There is no MOOC associated with this course.