Abstract:The African Data Initiative started as a crowd-sourced campaign to improve the teaching of statistics in African universities. The analysis of climate data provides one suitable context to illustrate ideas that lead to a radical new form of teaching. The problem within the context comes first, the technicalities are largely reduced – mathematics is supported by meta knowledge and backed up by modelling; calculations are reduced by user-friendly software that is also used by experts. The problems are treated si… Show more
Stereotype threat (ST) has been extensively explored as an explanation for gender disparities in achievement and participation in mathematics. However, there is a lack of research evaluating ST in statistics. The present study evaluated the impact of ST on gender differences in student performance, self-efficacy, and anxiety in statistics using a four-group, quasi-experimental design. Specifically, 102 elementary statistics students at a university in the Southeast United States were randomly assigned to one of four ST conditions including an explicit ST condition, an implicit ST condition, a reverse ST condition, and a nullified ST condition. Results indicated that there were no gender differences by ST condition in statistics self-efficacy, test anxiety, and performance. Analyses of student responses to open-ended questions indicated that females were more likely than males to report that they had fewer opportunities to achieve in statistics. Implications of our findings and suggestions for future research are discussed.
Stereotype threat (ST) has been extensively explored as an explanation for gender disparities in achievement and participation in mathematics. However, there is a lack of research evaluating ST in statistics. The present study evaluated the impact of ST on gender differences in student performance, self-efficacy, and anxiety in statistics using a four-group, quasi-experimental design. Specifically, 102 elementary statistics students at a university in the Southeast United States were randomly assigned to one of four ST conditions including an explicit ST condition, an implicit ST condition, a reverse ST condition, and a nullified ST condition. Results indicated that there were no gender differences by ST condition in statistics self-efficacy, test anxiety, and performance. Analyses of student responses to open-ended questions indicated that females were more likely than males to report that they had fewer opportunities to achieve in statistics. Implications of our findings and suggestions for future research are discussed.
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