Publications

(2024). A Family of Instruments to Measure Data Science Attitudes. Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 2, 1702-1703.

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(2023). The Developmental Experiences of Exemplary Statistics Teachers. Northwest Journal of Teacher Education, 18(1), Article 2.

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(2023). MASDERing Attitude Research in Statistics and Data Science Education: Instruments for Measuring Students, Instructors, and the Learning Environment. In E.M. Jones (Ed.), Fostering Learning of Statistics and Data Science: Proceedings of the Satellite conference of the International Association for Statistical Education (IASE).

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(2023). Establishing the Validity and Reliability of the LOCUS Assessments. Numeracy, 16(1), Article 5.

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(2022). A New Survey of Student Attitudes toward Statistics: The S-SOMAS. In S.A. Peters, L. Zapata-Cardona, F. Bonafini, & A. Fan (Eds.), Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics (ICOTS11 2022).

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(2022). The Big Picture: A Family of Instruments for Understanding University-Level Statistics and Data Science Attitudes. In S.A. Peters, L. Zapata-Cardona, F. Bonafini, & A. Fan (Eds.), Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics (ICOTS11 2022).

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(2022). S-SOMADS: A new survey to measure student attitudes toward data science. In S.A. Peters, L. Zapata-Cardona, F. Bonafini, & A. Fan (Eds.), Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics (ICOTS11 2022).

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(2022). A model for the classroom environment. In S.A. Peters, L. Zapata-Cardona, F. Bonafini, & A. Fan (Eds.), Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics (ICOTS11 2022).

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(2022). Validity Evidence for Statistics Education Instruments: Findings and Best Practices.. In S.A. Peters, L. Zapata-Cardona, F. Bonafini, & A. Fan (Eds.), Bridging the Gap: Empowering & Educating Today’s Learners in Statistics. Proceedings of the Eleventh International Conference on Teaching Statistics (ICOTS11 2022).

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(2022). The search for validity evidence for instruments in statistics education: Preliminary findings. In R. Helenius & E. Falck (Eds.), Statistics Education in the Era of Data Science. Proceedings of the Satellite Conference of the International Association for Statistical Education (IASE).

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(2022). Challenges associated with measuring attitudes using the SATS family of instruments. Statistics Education Research Journal, 21(1), Article 4.

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(2022). Measuring opportunity cost in statistics using evaluative space grid items: results from a pilot study. Journal of Research in Science Mathematics and Technology Education, 5(1), 1-36.

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(2021). GridItemTools: Grid item tools. R package version 0.0.12.

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(2021). SATSdata: Survey of Attitudes Toward Statistics (SATS) Data Warehouse. R package version 1.0.0.

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(2021). MVQuickGraphs: Quick multivariate graphs. R package version 0.1.6.

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(2021). Nonlinear Modeling: Something Fishy. Statistics Teacher.

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(2020). Epistemic and mathematical beliefs of exemplary statistics teachers. International Journal for Mathematics Teaching and Learning, 21(2), 119–142.

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(2020). Challenges assessing statistics attitudes: opportunities and costs. Proceedings of the 47th Annual Meeting of the Research Council on Mathematics Learning, 43-50.

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(2019). Design and validation arguments for the Student Survey of Motivational Attitudes toward Statistics (S-SOMAS) instrument. Assessment in mathematics education contexts: Theoretical frameworks and new directions (1st ed., pp. 120-146). New York, NY: Routledge.

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(2019). Developing embedded signature assessments for continuous improvement in teacher education. The Teacher Educator, 54(2), 171–192.

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(2018). A framework and survey for measuring students’ motivational attitudes toward statistics. In M. A. Sorto, A. White, & L. Guyot (Eds.), Looking back, looking forward. Proceedings of the Tenth International Conference on Teaching Statistics (ICOTS10, July, 2018). Voorburg, The Netherlands: International Statistical Institute..

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(2017). Students' Understanding of Bar Graphs and Histograms: Results From the LOCUS Assessments. Journal of Statistics Education, 25(2), 90-102.

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(2016). Lexical ambiguities in the vocabulary of statistics. International Journal for Mathematics Teaching and Learning, 17(3).

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(2016). The development of a professional statistics teaching identity. In Wood, M.B., Turner, E.E., Civil, M., & Eli, J.A. (Eds.), Proceedings of the 38th annual meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (pp. 992-999). Tucson, AZ: The University of Arizona.

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(2016). “Maybe That Helps Folks Feel Better About What They're Doing”: Examining Contradictions Between Educator Presumptions, Student Experiences, and Outcomes at an Alternative School. Journal of Education for Students Placed at Risk, 21(4), 230-245.

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(2016). Innocent until Proven Guilty . Mathematics Teacher, 109(9), 686-692.

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(2015). Reducing Mowing Frequency Increases Floral Resource and Butterfly (Lepidoptera: Hesperioidea and Papilionoidea) Abundance in Managed Roadside Margins. Florida Entomologist, 98(4), 1081-1092.

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(2015). A Constructivist Study of Graduate Assistants' Healthcare Experiences in a Research University. The Qualitative Report, 20(7), 482-497.

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(2015). SEAsic: R Package for Score Equity Assessment. Applied Psychological Measurement, 39(6), 496-497.

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(2014). SEAsic: Score equity assessment- summary index computation. R package version 0.1.

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(2014). Middle school (ages 10 – 13) students’ understanding of statistics. In K. Makar & R. Gould (Eds.), Sustainability in statistics education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9, July, 2014), Flagstaff, Arizona. Voorburg, The Netherlands: International Statistical Institute.

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(2014). The LOCUS assessment at the college level: Conceptual understanding in introductory statistics. In K. Makar & R. Gould (Eds.), Sustainability in statistics education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9, July, 2014), Flagstaff, Arizona. Voorburg, The Netherlands: International Statistical Institute.

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(2014). High school (ages 14 – 18) students’ understanding of statistics. In K. Makar & R. Gould (Eds.), Sustainability in statistics education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9, July, 2014), Flagstaff, Arizona. Voorburg, The Netherlands: International Statistical Institute.

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(2014). Establishing the validity of the LOCUS assessments through an evidenced-centered design approach. In K. Makar & R. Gould (Eds.), Sustainability in statistics education. Proceedings of the Ninth International Conference on Teaching Statistics (ICOTS9, July, 2014), Flagstaff, Arizona. Voorburg, The Netherlands: International Statistical Institute.

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(2014). Starch Content of Citrus Leaves Permits Diagnosis of Huanglongbing in the Warm Season but Not Cool Season. HortScience, 49(6), 757-762.

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(2014). Lessons from the LOCUS assessments (part 1): Comparing groups. Statistics Teacher Network, (83), 13-15..

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(2014). clustsig: Similarity profile analysis. R package version 1.1.

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(2013). Starch content in citrus leaves: A test with seasonal accuracy. Proceedings of the Florida State Horticultural Society, 126, 75-83.

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(2013). Motivation for and Benefits from Attending the AP Statistics Reading. Journal of Education and Training Studies, 1(2), 32-37.

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(2010). Effects of Teaching Suprasegmentals on Second Language Learning and Motivation. University of Florida Journal of Undergraduate Research, 12(1), 1-10.

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