Data and statistical analysis to evaluate the effectiveness of LOs in teaching statistics to nursing
This dataset records the assessment of the effectiveness of learning objects in statistical education within nursing degree programs. It includes observations from 54 students with the following variables: - diagnostico_institucional: Assessment by the educational institution. - pre_test: Knowledge assessment prior to the educational intervention. - post_test: Knowledge assessment following the educational intervention. - edad: Age of the students. - campus: Campus of the institution where education is conducted. - sede: University site grouping several campuses together. - sexo: Gender of the student. - promedio_acumulado: Student's academic average up to the point of intervention. - rda_01 to rda_05: Score obtained in the corresponding evaluation of the learning objects. - rda_average: Average object learning outcome scores. - cat_1: Results of the primary evaluation number 1. - asistencia: Attendance record of the students at educational sessions. - RAA5_pre, RAA6_pre, RAA7_pre: Assessment results for each learning outcome before the intervention. - RAA5_post, RAA6_post, RAA7_post: Assessment results for each learning outcome after the intervention. The dataset includes a Quarto file, which performs various statistical analyses in R and returns a report in MS Word format. This data is crucial for future research in statistical teaching methodologies and is of particular interest to those in the field of nursing education. The tabular format is conducive to analysis with statistical software such as R.
Steps to reproduce
Steps to reproduce statistical analyses in R 1. Open RStudio on your computer. 2. Load the dataset 'data_article_effectiveness_LO.csv' using the appropriate command in the console. Ensure the dataset file is in your current working directory or provide the full path to the file. 3. Open the 'data_analisis_LO_statistics.qmd' Quarto file from the file> Open File menu in RStudio. 4. Each line of code in the Quarto file is commented on for clarity. Review the comments to understand the analysis steps. 5. Click the 'Run' or 'Knit' button to run the Quarto file. This will execute the embedded R code and compile the report into a 'data_analisis_LO_statistics.docx' document. 6. Once the document is compiled, check the output panel or your working directory for the 'data_analisis_LO_statistics.docx' file and review the report. If you run into any issues, check that the Quarto file's dataset file path is correct and that the code comments align with your understanding of the analysis process.
Universidad de Las Américas, Chile