Abstract
ABSTRACTStatistical literacy refers to understanding fundamental statistical concepts. Assessment of statistical literacy can take the forms of tasks that require students to identify, translate, compute, read, and interpret data. In addition, statistical instruction can take many forms encompassing course delivery format such as face-to-face, hybrid, online, video capture, and flipped. In this study, we examined statistical literacy of graduate students using a validated assessment tool (the Comprehensive Assessment of Outcomes in Statistics; CAOS) across two increasingly popular delivery formats—hybrid and online. In addition, we examined condensed (six week) semesters to full (16 week) semesters to determine if course length was related to statistical literacy. Our findings suggest that, holding other factors constant, delivery format is not related to statistical literacy for graduate students. This contradicts some existing research that shows hybrid delivery outperforms online only. Our results have important implications for the teaching of statistics as well as for graduate education overall.
Highlights
EM algorithm for missing data replacement is an iterative process that produces maximum likelihood estimates with missing values estimated in an iterative fashion via a regression-based process with predictors including the variables included in the multilevel model (e.g., Comprehensive Assessment of Outcomes in Statistics (CAOS) pre- and posttest scores, delivery format, course length) as well as additional variables (Graham 2009)
The results revealed that approximately 2.0% of the variance in statistical literacy resided between class sections (ICC D 0.020) and 98.0% of the variance was attributable to the individual
Our results showed that there was no significant difference in statistical literacy of students who are enrolled in hybrid, as compared to online, introductory statistics course when controlling for baseline statistical literacy, graduate level of the student and length
Summary
Constructs such as critical thinking, engagement, motivation, and learning are arguably requisite elements for instruction to be effective and for students to successfully learn (Dziuban 2016). Each of these constructs derives from learning theory. The fact that they are essentially abstract, but making them objective in the assessment process can create issues in that very process (Postman 2011). “we must be cognizant that we are forced to select surrogates to assess the characteristics in which we are interested. Our responsibility is to understand that at best these surrogates only approximate the construct with which we are interested” (Dziuban 2016, p. 160)
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