Resilience of anthropometric data assembly strategies to imposed error

The aim of this study was to examine strategies for selecting a criterion value during anthropometric data assembly and their resilience to imposed error. Sixty-seven women aged 16-60 years were subjected to three separate series of measurements, which included six skinfolds and three girths. A random error term was added to the first of the three series of measurements to produce a pseudo-series containing error, termed the 'erroneous replicated series'. Five strategies were then used to determine the criterion value of each of the replication series: the first measurement, the mean of the first two measurements, the mean of all three measurements, the mean of the closest two measurements and the median of the three measurements. The technical error between the criterion values of the true and the flawed replication series for each of the selection strategies was calculated. We found that, for five of the skinfolds and all of the girths, the median value provided the smallest technical error of measurement between the criterion values for the true and erroneous replication series. We conclude that the strategy of selecting the median of three measurements is the most resilient to imposed error.     

The Nature of Teacher Leadership in Schools as Reciprocal Influences Between Teacher Leaders and Principals

As part of a comprehensive qualitative study of 6 schools noted for teacher leadership 28 respondents were interviewed. It was noted that teacher leadership often involved the mutual influence between teacher leaders and principals. These influences are discussed from the perspectives of each of the 6 schools and respondent status as teacher leader, teacher nominator, and administrator. Further to these influences, the data suggest relationships between teachers, teacher leaders, and principals, in these schools, which are reflective of 3 models of “leadership reciprocity” based on unique features found to be typical of these schools.     

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations.