Impact of Slavin's Effective Teaching Model on Procrastination in Nursing Students: a Quasi-Experimental Study

Time management is a critical skill that directly affects success and efficiency in nursing students' educational processes. Procrastination can negatively impact both academic performance and the quality of clinical practice, making understanding and managing this behavior crucial for both students and healthcare services. This study aims to investigate the effects of a time management training program on procrastination behavior among intern nursing students. The training content, developed based on the Effective Teaching Model, will assess how students' time management skills and procrastination tendencies change. The study will be conducted at a private university in Istanbul from November 2024 to March 2025, with the target population being all intern nursing students enrolled at the university during the research period (N=70). No sampling will be done, and the aim is to reach the entire population.

The research aims to provide effective time management training for nursing students and to reduce procrastination behavior through this training. The training program will last for five days, with each day focusing on a specific topic. On the first day, the fundamentals of time management and understanding procrastination behavior will be covered. The second day will address time management strategies and techniques. The third day will focus on managing procrastination behavior and related strategies. On the fourth day, practical workshops will be conducted to create personal time management plans. The fifth day will include training evaluation, student feedback, and motivational activities. The training will utilize Slavin's Effective Teaching Model and will be enriched with presentations, interactive sessions, practical workshops, feedback, and motivational techniques. The program aims to enhance students' time management skills, reduce procrastination behavior, and improve academic performance. By the end of the training, a reduction in stress and anxiety levels, increased motivation, and overall improvement in quality of life are expected.

Data for the study will be collected using a personal information form and a general procrastination scale. Data analysis will be conducted using SPSS (Statistical Package for Social Sciences) for Windows 22.0. To determine if the research data follow a normal distribution, the Kolmogorov-Smirnov Test will be used. If p>0.05, the distribution is considered normal. If p\<0.05, the distribution is not normal, and skewness and kurtosis values will be examined. Changes in repeated measurements will be analyzed using the repeated measures ANOVA test if the data are normally distributed, and the Friedman test if the data are not normally distributed. Initially, descriptive statistics will summarize the general characteristics of the data, and means and distributions of pre-test and post-test scores will be determined. The paired samples t-test will be used to evaluate differences between pre-test and post-test scores within the same group. This analysis will assess the impact of the training program on time management and procrastination behaviors. Additionally, effect size (e.g., Cohen's d) will be calculated to evaluate the magnitude and significance of the training intervention. Variance analysis (ANOVA) may be used to determine if there are significant differences between different groups, but its necessity will be determined based on the specifics of the study. Finally, power analysis will be performed to ensure the study's sample size is adequate. These analyses will collectively allow for meaningful and reliable interpretation of the research findings.