skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 11:00 PM ET on Thursday, June 12 until 2:00 AM ET on Friday, June 13 due to maintenance. We apologize for the inconvenience.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: A Model for the Classroom Environment
The Motivational Attitudes in Statistics and Data Science Education Research group is developing a family of validated instruments: two instruments assessing students’ attitudes toward statistics or data science, two instruments assessing instructors’ attitudes toward teaching statistics or data science, and two sets of inventories to measure the learning environment in which the students and instructor interact. The Environment Inventories measure the institutional structures, course characteristics, and enacted classroom behaviors of both the students and instructors, all of which interact with the student and instructor background. This paper will discuss our proposed theoretical framework for the learning environment and its development.  more » « less
Award ID(s):
2013392
PAR ID:
10386400
Author(s) / Creator(s):
; ; ; ; ; ;
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
More Like this
  1. ; ; ; ; ; ; (, Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the 11th International Conference on Teaching Statistics (ICOTS11 2022), Rosario, Argentina.)
    Peters, S. A.; Zapata-Cardona, L.; Bonafini, F.; Fan, A. (Ed.)
    Attitudes matter in statistics and data science education, but previous instruments have been limited in scope, resulting in many unanswered questions. This paper discusses the Surveys of Motivational Attitudes toward Statistics and Data Science, a family of instruments designed to provide a broad understanding of university-level student and instructor attitudes as well as learning environment characteristics. Based on Expectancy Value Theory, a meta-model explains the interrelationships among the instruments, and an iterative design process is followed for survey development. Psychometric results from data collections using instruments developed thus far are presented. This is the first time a cohesive, synergistic set of instruments has been designed to work together to give a broader understanding of the state of statistics and data science education. 
    more » « less
  2. ; ; ; ; ; (, ACM)
    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. 
    more » « less
  3. ; ; ; ; ; ; (, Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the 11th International Conference on Teaching Statistics (ICOTS11 2022), Rosario, Argentina.)
    Peters, S. A.; Zapata-Cardona, L.; Bonafini, F.; Fan, A. (Ed.)
    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. 
    more » « less
  4. ; ; (, Teaching tips: A compendium of conference presentations on teaching)
    Scherschel, H.; Rudmann, D.S. (Ed.)
    Passion-Driven Statistics is a project-based, introductory curriculum implemented as a course in statistics, research methods, data science, a capstone experience, and a summer research boot camp with students from a wide variety of academic settings. Funded by the National Science Foundation, the curriculum engages students in authentic projects with large, real-world data sets. Passion-Driven Statistics students were more likely to report increased confidence in working with data and increased interest in pursuing advanced statistics course work compared to students from the traditional statistics course (Dierker et al., 2018a). This presentation draws on pre/post data from 67 instructors attending a Passion-Driven Statistics faculty development workshop. Analyses evaluate instructor characteristics, attitudes, and experiences that predict its implementation. Findings show that nearly half of the instructors who reported being likely to implement passion-driven statistics and a quarter of the overall sample employed the project-based curriculum by the end of the first full academic year following the workshop. Those showing this fast uptake were more likely to be female than those who had not yet implemented (87.5% vs. 55.3%), were more likely to hold a Ph.D. (94.1% vs. 59.2%), and were more likely to be employed by a private rather than public institution (76.5% vs. 46.0%). Those showing fast uptake were also more likely to have been previously using statistical software (i.e., SAS, JMP, R, Stata, Python, or SPSS) in their target course (70.6% vs. 40.0%) and to have greater prior experience with project-based skills and fewer post workshop concerns about their likely success. Results from these analyses will guide recommendations for 1) engaging instructors ready to implement innovation in learning and teaching and 2) supporting those instructors requiring additional time, training and skills. Instructors are the most important resource for promoting innovations and all materials are open educational resources 
    more » « less
  5. ; ; ; ; ; (, International Journal of STEM Education)
    Abstract Background Capturing measures of students’ attitudes toward science has long been a focus within the field of science education. The resulting interest has led to the development of many instruments over the years. There is considerable disagreement about how attitudes should be measured, and especially whether students’ attitudes toward science can or should be measured unidimensionally, or whether separate attitude dimensions or subscales should be considered. When it is agreed upon that the attitudes toward science construct should be measured along separate subscales, there is no consensus about which subscales should be used. Methods A streamlined version of the modified Attitudes Towards Science Inventory (mATSI), a widely used science measurement instrument, was validated for a more diverse sample as compared to the original study (Weinburgh and Steele in Journal of Women and Minorities in Science and Engineering 6:87–94, 2000). The analytical approach used factor analyses and longitudinal measurement invariance. The study used a sample of 2016 self-reported responses from 6 and 7th grade students. The factor analysis elucidated the factor structure of students’ attitudes toward science, and some modifications were made in accordance with the results. Measurement invariance analysis was used to confirm the stability of the measure. Results Our results support that the subscales, anxiety toward science and value and enjoyment of science , are two factors and stable over time. Conclusions Our results suggest that our proposed modified factor structure for students’ attitudes toward science is reliable, valid, and appropriate for use in longitudinal studies. This study and its resulting streamlined mATSI survey could be of value to those interested in studying student engagement and measuring middle-school students' attitudes toward science. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email