Truth in edutainment: What you get is what you see

Discussion of “Visualizing statistical edutainment: What you see is what you get” by Lesser and Pearl.     

Statistical edutainment: An experimental way to teach for good measure

Concepts of experimentation and measurement are explored using statistics educational fun items and illustrated by sharing our process in conducting an experiment on cartoon captions.     

What you see is what you get: The role of early adolescents’ perceptions in the intergenerational transmission of academic values

The present research addresses processes involved in academic value transmission within family. Drawing on expectancy x value and social learning theory, a two-wave longitudinal study based on data from 1014 students, 878 mothers, and 748 fathers was conducted to examine the mechanisms of parental influence. Structural equation modeling provided evidence for a multi-step mediation process. Predictions of the parents’ academic values on students’ values were shown to be mediated through parents’ actual and student-perceived parental school involvement. Students’ perceptions of the parents’ academic values, inferred from the perceived involvement, in turn, predicted students’ own values. In the discussion, the central role of students’ perceptions in these processes is emphasized.     

Multi-method assessment of metacognitive skills in elementary school children: how you test is what you get

Third grade elementary school children solved tests on mathematical reasoning and numerical facility. Metacognitive skillfulness was assessed through think aloud protocols, prospective and retrospective child ratings, teacher questionnaires, calibration measures and EPA2000. In our dataset metacognition has a lot in common with intelligence, but planning measured with teacher ratings plays a role above and beyond IQ. Moreover, we found that skills are generally related, but that it is more appropriate to assess them separately. In addition, results show the value of an experienced teacher as actual measure of metacognitive planning skills. Our dataset suggests convergent validity for prospective and retrospective child ratings, but no significant relationship with the other metacognitive measures. Metacognitive skillfulness combined with intelligence accounts for between 52.9% and 76.5% of the mathematics performances. The choice of diagnostic instruments highly determines the predicted percentage. Consequences for the assessment of metacognitive skills are discussed.     

Making students part of the dataset: a model for statistical enquiry in social issues

This article reviews a flexible model for engaging students in statistical enquiry. Data from a student survey are first used to stimulate interest and introduce statistical concepts, while easing the transition to working with larger ‘real world’ secondary data.