Teacher(s)
Hardwick Robert; Lefebvre Arthur (coordinator);
Language
French
Main themes
- Types of data sources (primary and secondary)
- Types of empirical data (qualitative and quantitative)
- Types of data collection methods (experiments, case studies, surveys, interviews, documents, focus groups, observations)
- Research ethics with regard to data collection: anonymity, confidentiality, etc.
- RGPD
- Bias and validity of data collection methods
- Choice of variables: link between variable, hypotheses, scales and data collection
- Basis for structuring a database
Learning outcomes
At the end of this learning unit, the student is able to : | |
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Content
During this teaching unit, students explore the fundamental principles of data collection in the field of sport sciences. The course introduces the types of sources (primary and secondary), the types of empirical data (qualitative and quantitative), and the main data collection methods: experiments, case studies, surveys, interviews, document analysis, focus groups, and observations. It also addresses research ethics related to data collection, including anonymity, confidentiality, and compliance with GDPR, as well as biases and the validity of methods. Finally, attention is given to the selection of variables, in connection with hypotheses, scales, and data collection, as well as the basic principles for structuring a database.
By the end of the unit, students will be able to describe the basic principles and steps of data collection in sport sciences, as well as the different types of data and collection methods. They will be able to identify biases present in data collection and in scientific articles by using appropriate scales.
By the end of the unit, students will be able to describe the basic principles and steps of data collection in sport sciences, as well as the different types of data and collection methods. They will be able to identify biases present in data collection and in scientific articles by using appropriate scales.
Teaching methods
Lectures and reverse classrooms.
Students are informed that the course requires regular reading and preparation for teaching sessions.
Students are informed that the course requires regular reading and preparation for teaching sessions.
Evaluation methods
☒ The course assessment is based on a written exam during the session.
☐ Exam format: ☒ Multiple Choice Questions (MCQ) consisting of 30 questions.
☒ Calculation rules:
☒ With adjustment: The evaluation of the theoretical part by MCQ will include N questions, each with only one correct answer. The minimum mastery threshold for learning outcomes (corresponding to a score of 10/20) for this exam is set by the following formula, which allows calculating the "minimum passing threshold": c = ((n+1)/2n) x 100. Where
"c" corresponds to the "minimum passing threshold" (you must answer correctly to (c x 100)% of the N questions to obtain a score of 10/20)
"n": represents the number of options per question (for example, n = 5 means 5 answer choices per question)
This formula assumes that to achieve a score of 10/20, you need to have answered correctly:
62.5% of the N questions if there are 4 options
60% of the N questions if there are 5 options
☒ Rounding: the scores obtained will be rounded down to the nearest whole number.
This threshold helps to mitigate the effect of chance associated with strategies of answering all questions, including those where the student does not know the answer, since there are no negative points. Students are informed that under these conditions, they have a strong incentive to answer all questions.
☒ The evaluation procedures for the first session apply to the second session.
☐ Exam format: ☒ Multiple Choice Questions (MCQ) consisting of 30 questions.
☒ Calculation rules:
☒ With adjustment: The evaluation of the theoretical part by MCQ will include N questions, each with only one correct answer. The minimum mastery threshold for learning outcomes (corresponding to a score of 10/20) for this exam is set by the following formula, which allows calculating the "minimum passing threshold": c = ((n+1)/2n) x 100. Where
"c" corresponds to the "minimum passing threshold" (you must answer correctly to (c x 100)% of the N questions to obtain a score of 10/20)
"n": represents the number of options per question (for example, n = 5 means 5 answer choices per question)
This formula assumes that to achieve a score of 10/20, you need to have answered correctly:
62.5% of the N questions if there are 4 options
60% of the N questions if there are 5 options
☒ Rounding: the scores obtained will be rounded down to the nearest whole number.
This threshold helps to mitigate the effect of chance associated with strategies of answering all questions, including those where the student does not know the answer, since there are no negative points. Students are informed that under these conditions, they have a strong incentive to answer all questions.
☒ The evaluation procedures for the first session apply to the second session.
Other information
This course is strictly reserved for FSM students. It is not open to other UCLouvain students.
Faculty or entity
