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Attitudes play an important role in students’ academic achievement and retention, yet quality tools to measure them are not readily available in the new field of data science. Through funding from the National Science Foundation, we are developing a family of instruments that measure attitudes toward data science in the context of an introductory, college-level course. This poster will showcase preliminary results discussing pilot instruments to assess instructors’ attitudes toward teaching data science and an inventory which captures classroom characteristics. These instruments, based on Expectancy-Value Theory, will enable data science education researchers to evaluate pedagogical innovations and measure instructional effectiveness relating to student attitudes. We invite instructors of data science courses to join in this discussion and to use these instruments for their own data science education research projects.
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S-SOMADS: A New Survey to Measure Student Attitudes Toward Data Science
Attitudes play an important role in students’ academic achievement and retention, yet we lack quality attitude measurement instruments in the new field of data science. This paper explains the process of creating Expectancy Value Theory-based instruments for introductory, college-level data science courses, including construct development, item creation, and refinement involving content experts. The family of instruments consist of surveys measuring student attitudes, instructor attitudes, and instructor and course characteristics. These instruments will enable data science education researchers to evaluate pedagogical innovations, create course assessments, and measure instructional effectiveness relating to student attitudes. We also present plans for pilot data collection and analyses to verify the categorization of items to constructs, as well as ways in which faculty who teach introductory data science courses can be involved.
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- Award ID(s):
- 2013392
- PAR ID:
- 10386398
- Editor(s):
- Peters, S. A.; Zapata-Cardona, L.; Bonafini, F.; Fan, A.
- Date Published:
- Journal Name:
- Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the 11th International Conference on Teaching Statistics (ICOTS11 2022), Rosario, Argentina.
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.52041/iase.icots11.T8A2
