Predictors of Academic Success of Students: Motivational Factors, Standardised Test Results, and School Grades

Student: Gorobtsova Anna

Faculty: Saint-Petersburg School of Social Sciences

Educational Programme: Sociology and Social Informatics (Bachelor)

Year of Graduation: 2021

The main focus of this research paper are factors that are related to academic achievement of college students. The factors of interest to this study include the results of the standardized test which is taken by school graduates in order to get their school diplomas (Russian Unified State Exam), high school diploma marks for core subjects relevant for certain educational programs a student is applying to and also a set of motivational factors which include self-efficacy beliefs, goal orientations, interest and anxiety. There are several main reasons for studying these factors. Firstly, it will help students who want to perform better figure out the ways to do so. Secondly, it will allow universities to organize the educational environment in a more effective way. And, finally, deeper understanding of the effects of standardized tests (such as SAT/ACT or Russian Unified State Exam) and high school grades will allow universities to make well-reasoned decisions regarding their applicants at the stage of the selection of future students. This aspect is especially relevant for Russia since Unified state exam is in most cases the only admission criteria used by universities. Thus, three main aims for this research paper are identified. The first one is to check whether USE is actually a valid student selection criterion by looking at the performance of college students with different scores. Secondly, the effects of USE results and school grades will be compared. And finally structural relationships between variables will be investigated. For these purposes a sample of undergraduate university students majoring in Economics in the Saint-Petersburg campus of Higher School of economics will be used. The minimum expected number of respondents is approximately 200. And methods that are going to be used for the analysis include structural equation modelling, regression analysis, descriptive data analysis techniques, correlation tests.

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