The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science Course
In this paper we explore motivational structure of students taking a challenging university course. The participants were second-year undergraduate students majoring in Economics, Sociology, Management and Humanities, enrolled in the Data Science minor. Using expectancy-value theory as a framework,...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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National Research University Higher School of Economics (HSE)
2016-12-01
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| Series: | Вопросы образования |
| Subjects: | |
| Online Access: | https://vo.hse.ru/article/view/15568 |
| _version_ | 1797902671128035328 |
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| author | Valeria Ivaniushina Daniil Alexandrov Ilya Musabirov |
| author_facet | Valeria Ivaniushina Daniil Alexandrov Ilya Musabirov |
| author_sort | Valeria Ivaniushina |
| collection | DOAJ |
| description | In this paper we explore motivational structure of students taking a challenging university course. The participants were second-year undergraduate students majoring in Economics, Sociology, Management and Humanities, enrolled in the Data Science minor. Using expectancy-value theory as a framework, we aim (1) to analyze gender differences in motivation; (2) to identify the link between the components of motivation and academic achievement; (3) to estimate the role of the previous academic achievement and educational choices. Two alternative
theoretical models are proposed and tested on empirical data. Structural equation modeling (SEM) in M Plus 7.31 was used for analysis. We found that the course is more popular among males students, who also demonstrate higher level of expectancy for success. However, there is no gender difference in academic performance. Students majoring in Sociology and Economics perceive Data Science as more interesting and useful than Management and Humanities students. SEM analysis empirically validated the model in which expectancy of success directly influences academic achievement, and values influence is mediated by expectancies. The final model that includes motivation, gender, student’s major, and previous achievement explains 34% of variance in academic performance. We discuss the role of different components of student motivation and practical significance of our results. |
| first_indexed | 2024-04-10T09:21:20Z |
| format | Article |
| id | doaj.art-d0c497f158cb44129f2e0db4ae02c311 |
| institution | Directory Open Access Journal |
| issn | 1814-9545 2412-4354 |
| language | English |
| last_indexed | 2024-04-10T09:21:20Z |
| publishDate | 2016-12-01 |
| publisher | National Research University Higher School of Economics (HSE) |
| record_format | Article |
| series | Вопросы образования |
| spelling | doaj.art-d0c497f158cb44129f2e0db4ae02c3112023-02-20T11:33:06ZengNational Research University Higher School of Economics (HSE)Вопросы образования1814-95452412-43542016-12-01422925010.17323/1814-9545-2016-4-229-25015568The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science CourseValeria Ivaniushina0Daniil Alexandrov1Ilya Musabirov2HSE UniversityHSE UniversityHSE UniversityIn this paper we explore motivational structure of students taking a challenging university course. The participants were second-year undergraduate students majoring in Economics, Sociology, Management and Humanities, enrolled in the Data Science minor. Using expectancy-value theory as a framework, we aim (1) to analyze gender differences in motivation; (2) to identify the link between the components of motivation and academic achievement; (3) to estimate the role of the previous academic achievement and educational choices. Two alternative theoretical models are proposed and tested on empirical data. Structural equation modeling (SEM) in M Plus 7.31 was used for analysis. We found that the course is more popular among males students, who also demonstrate higher level of expectancy for success. However, there is no gender difference in academic performance. Students majoring in Sociology and Economics perceive Data Science as more interesting and useful than Management and Humanities students. SEM analysis empirically validated the model in which expectancy of success directly influences academic achievement, and values influence is mediated by expectancies. The final model that includes motivation, gender, student’s major, and previous achievement explains 34% of variance in academic performance. We discuss the role of different components of student motivation and practical significance of our results.https://vo.hse.ru/article/view/15568motivationexpectancy value theorygender differencesstatisticsdata science |
| spellingShingle | Valeria Ivaniushina Daniil Alexandrov Ilya Musabirov The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science Course Вопросы образования motivation expectancy value theory gender differences statistics data science |
| title | The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science Course |
| title_full | The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science Course |
| title_fullStr | The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science Course |
| title_full_unstemmed | The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science Course |
| title_short | The Structure of Students’ Motivation: Expectancies and Values in Taking Data Science Course |
| title_sort | structure of students motivation expectancies and values in taking data science course |
| topic | motivation expectancy value theory gender differences statistics data science |
| url | https://vo.hse.ru/article/view/15568 |
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