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Thesis on study habits and math performance

This is an Open Access article distributed under the terms of the Creative Commons Attribution License which permits unrestricted use of work provided the original work is properly cited. Paired t-tests were used to test if the two measurement points differed.

Bivariate correlations and R2s were compared with five other relevant studies. Utilizing the LASSI to provide medical school students with information about their strengths and weaknesses and implementing targeted support in specific study strategies may yield positive academic performance outcomes.

Study strategies, learning strategies, assessment, academic performance Introduction Why do some students perform well academically in medical school while others do not? This question has been explored and investigated in a variety of ways. Many relevant studies of pre-admission aptitude and study skills dealt with broad concepts and exhibited mixed results.

For example, Sleight and Mavis created a Study Aid questionnaire and found high performers were less reliant on study aids.

Predicting Academic Achievement from Study Skills Habits among Upward Bound Students

Even though there were hundreds of articles, thesis on study habits and math performance 19 studies were relevant and were kept for further analyses a comprehensive summary of the 19 studies are provided in the Appendix 1. The excluded articles included qualitative studies, quantitative studies that used advanced methods to investigate more complicated scenarios, or studies that contained the same keywords but were irrelevant. Of the 19 studies, most 3 - 11131416171920 concluded that study strategies have an influence on academic performance as indicated by GPA 314161920 school performance, 5 - 815171822 or standardized exams4, 589 see Appendix 1.

A retrospective review of those results was difficult due to several reasons. For example, converting a continuous variable into a categorical variable e.

Another approach used percentile scores in the multiple regression models. Many methodologists 2627 have suggested caution when utilizing these types of practices because they may damage the nature of the relationship and weaken the conclusions. Second, the discrepancies of analytical methods and models between studies did not facilitate a direct comparison.

Even those who adopted the same methods like multiple regression, used different predictors, 56171822 or predictors with different scales i. Third, most studies failed to report the key components such as correlation matrices and standard deviations as suggested by Zientek and Thompson. Fourth, the narrow definition of learning strategies, such as those which only included the domains measured by LASSI, restricted generalizability of the results.

Similarly, how academic performance was defined such as course grade, GPA, or standardized test scores may have also influenced the results. Last, but not least, most studies only addressed whether or not there was an effect of study strategies on academic performance, but did not address to what extent the study strategies may affect academic performance.

Even if there were many positive conclusions i. The size of the effect is a more important indicator of the potential importance of using the LASSI in medical school.

The relationship between study strategies and academic performance

Due to the listed limitations, we redesigned the study and re-conducted the research project in 2013. There were two primary changes. The SDLRS was selected because it is the most widely used assessment to measure self-directed learning readiness, 32 and we wanted to assess how learning readiness influenced student performance on specific tasks.

The research questions are: If so, is one measure more valuable than another? The authors integrated current study data with published relevant research 56101417 and conducted a secondary analysis of the two thesis on study habits and math performance that contained a bivariate correlation matrix and related descriptive statistics.

The sessions were held at the beginning of their first year of medical school and again at the beginning of their second year. Three other studies 101417 that reported partial information are also included in the summary table.

Immediately upon completion, each participant receives a performance profile including 10 subscales: Data analysis SPSS 22. Descriptive statistics such as means and standard deviations were calculated. Results Table 1 includes means, standard deviations, and bivariate corelation coefficients for all targeted variables.