Description
The course aims to get students acquainted with the practice of empirical research on the level required for their Research Master’s thesis. We will pay attention to both the methodological design and the statistical analysis of results. The course offers tools for assessing the quality of published research results as well as for producing one’s own research report.
During the course we will (re)visit and discuss different analyses and common assumptions. In this course, we extend these assumptions with a strong emphasis on their 1) practical feasibility, 2) interpretation and 3) implications for use in daily academic as well as clinical research practice. In addition, we connect the general concept of some more advanced techniques, such as nonlinear transformations and the bootstrap, to the just-mentioned foundations. In addition, we will introduce some concepts that will later be addressed in more detail in the specialized course Applied Multivariate Data Analysis.
We practice the three aspects regarding assumptions using several real empirical datasets to make a direct connection between research methodology and the practice of education and child studies.
Course objectives
At the end of this course, the student:
Can systematically apply methodological and technical research skills that are most common in Education and Child Studies;
Is able to design and conduct research in one of the research areas of the institute of Education and Child Studies;
Is able to critically evaluate aspects of study design and methodology in empirical research;
Can analyse and critically evaluate scientific literature to establish its practical and theoretical relevance;
Can formulate a consistent line of reasoning, based on scientific arguments;
Can report in writing (in English) on human development in an academic professional context;
Is conscious of ethical considerations involved in performing and describing scientific research.
Timetable
For the timetable of this course please refer to MyTimetable
Mode of instruction
Seven interactive lectures
Seven computer lab sessions (attendance obligatory)
Materials as well as instruction will be in English.
Assessment method
Grades are based on a final research paper (written in English), under the condition that all other obligatory assignments have been successfully completed. The final paper assignment is formulated around an existing empirical dataset, on which two PhD theses and several journal articles have been published.
Based on a description of these data and their context you will write your own proposal for research questions and data analysis, with an emphasis on the methodological aspects as discussed in the course. You will receive feedback on your proposal based on which you will adapt the proposal.
After approval of the proposal, you will execute the proposed analyses, and present the results in a final paper which follows the format of a journal article. This format will be provided on Brightspace. The lecturers will grade your paper using a detailed rubric system. Feedback on the final paper is based on these rubrics, with additional comments. If you receive a failing grade, you will get one opportunity to rewrite your paper based on the feedback.
The workgroups have required attendance. One meeting can be skipped. Absence should be mentioned in advance via email to the teacher. The student will be asked to complete an alternative assignment. If more than one meeting is missed, the learning goals of this course cannot be achieved. This implies that the course cannot be completed with a passing grade in the current academic year. The student will need to retake the course in the next academic year.
Brightspace
During this course Brightspace will be used. The Brightspace site will contain announcements, course documents, information on tutorials and computer labs, lecture notes and discussion boards.
Reading list
A Student Manual will be available on Brightspace prior to the start of the course. Additional materials will be announced and, whenever possible, made available in the Brightspace course module.
Registration
Education
Students must register themselves for all course components (lectures, tutorials and practicals) they wish to follow. You can register via My Studymap up to 5 days prior to the start of the course.
Exams
The exam of this course is a written report. Hence, you do not have to register for an exam in MyStudymap.
Contact information
All necessary information on the course will be provided on Brightspace.;
If, after consulting Brightspace, you still have questions, please:
o Email dr R.C.A. Rippe: for enrolment and organisational issues;
o Pose general questions regarding the end paper on the general Brightspace forum;