The written assignments are reports on small research projects using data from the international large-scale assessments. The participants are assigned research questions in course of the seminar. They develop analytical strategies and select appropriate dataset(s) themselves. They analyze the dataset(s), report central findings, and interpret their results.
The written assignment is passed if the reports fulfill the following formal and quality criteria. If at least one criterion is not met at all, the written assignment is not passed.
Formal Criteria
- Structure: The paper includes a title page, the sections introduction, research question, methods, results, discussion, an APA-conform literature list, and an appendix (complete and properly commented R script).
- Readability: The text is in correct and clear, scientific English. Sections have appropriate headings and all abbreviations are introduced.
- Format: The format follows the APA standard. Format 3cm margins to all sides.
- Tables and figures: Tables and figures are formatted according to APA standards. They can be moved to the appendix to save space.
- Length: The paper encompasses 5-9 pages (only counting the parts introduction, research question, methods, results, and discussion).
- File format: PDF
Quality Criteria
- Introduction:
- This section introduces the topic; giving a brief overview of the background and a precise description of the problem. It is supposed to raise interest and more importantly emphasize that and why this research is relevant.
- References to previous empirical findings and/or theoretical literature are not needed extensively, but a few should be presented.
- Research question:
- This section presents the research question, which argumentatively follows directly and logically from the introduction.
- The research question is clear and concise and grounded hypotheses are stated.
- Methods:
- This section entails all information that other researchers need to be able to replicate the study.
- The international large-scale assessment dataset(s) is/are chosen in accordance with the research question.
- The sample is described, including the original and, if applicable, effective sample sizes and central demographics.
- All used variables are described, including their role in the analysis (e.g., dependent, independent, control). This description includes how and in which instruments the variables were assessed and which values they can have (e.g., Likert scale, continuous plausible values). If variables are summarized in scales (e.g., mean scale, latent factor), the indicators and scaling procedure is described, as well. Details can be summarized in a table.
- It is stated if and how many missing values occurred and how they were handled.
- The statistical methods are chosen according to the research question and described in sufficient detail. The methodological complexity of the large-scale assessments is taken into account in the analysis (sampling weights, if applicable handling of plausible values).
- The data and software packages are properly cited.
- Results:
- This section describes central descriptive and inferential findings in an accessible way. Answering the research question is in the main focus.
- Descriptive statistics of the central analysis variables are provided either in text or table format.
- Central inferential findings are described clearly and, if necessary, accompanied by appropriate tables and/or figures.
- Discussion:
- This section connects the research question and findings of the study. It clearly states if the evidence supported the hypotheses or not. Possible explanations for and implications of the findings are discussed, also against the background of the literature presented in the introduction.
- The findings are interpreted with appropriate scientific caution and central limitations of the study are clearly stated.