Learning To Read Each Other: Black Female Graduate Students Share Their Experiences at a White Research I Institution

This paper uses Black Feminist Thought to explain the lived experiences of three Black female graduate students at a White Research I institution. Through mentoring from Black female professors, the students received instrumental and psychosocial support that helped them to navigate through their graduate level work. Common themes of identity, community service missions, and empowerment provides a thread that ties the student’s narratives together. We close by offering some suggestions for further research on the Black graduate experience and mentoring Black graduate students. Meca R. Williams, Denise N. Brewley, R. Judith Reed and Dorothy Y. White are affiliated with University of Georgia. Rachel T. Davis-Haley is affiliated with University of New Orleans.     

The Use of Serial Correlation in the Analysis of Data from Interrupted Time Series Trials with Single Subjects in Educational Research

There is need in educational psychology and elsewhere for a simple but reliable technique for analysing data from baseline/intervention type studies with single subjects. The serial‐correlation approach is suitable for this purpose and provides not just a test of statistical significance but also an index of the strength of relationship between intervention and any change, as well as an indication of the proportion of the total variance accounted for by the relationship.     

Stability of Individual Differences in Multiwave Panel Studies: Comparison of Simplex Models and One-Factor Models

The purpose of this investigation is to evaluate structural equation models (SEMs) for measures of the same construct collected on multiple occasions (one-variable, multiwave panel studies). Simplex models hypothesize that a measure at any one wave is substantially influenced by the measure at the 0immediately preceding wave; correlations between the same construct measured on different occasions are predicted to decline systematically as the number of intervening occasions increases. Alternatively, a one-factor model posits that a person's score at any one time is a function of some underlying "true" score and a random disturbance that is idiosyncratic to the time; no temporal ordering of correlations is assumed. Both the simplex and one-factor models can befit when there is only a single indicator of each construct at each wave (e.g., scale scores), but there are serious limitations to such models. Stronger models are possible when the same set of multiple indicators (e.g., the items that make up the scale) is measured at each wave. In Study 1, based on students' evaluations of teaching effectiveness collected over an 8-year period, one-factor models fit the data well, whereas simplex models did not. In Study 2, based on personality variables collected over a 4-year period during adolescence, one-factor models again provided an excellent fit to the data, whereas the simplex model did marginally poorer. The results challenge an overreliance on simplex models and demonstrate that a one-factor model is a potentially useful alternative that should be considered in multiwave studies.     

Questions from our readers: commentary on "lamaze in the 21st century"

In response to Lamaze International's latest position paper, "Lamaze in the 21st Century," the author discusses the concept of normal birth and identifies the need for an advocacy effort in support of normal birth as the standard procedure.     

Exploring sex differences in science enrolment intentions: An application of the General Model of Academic Choice

In many countries there remain substantial sex differences in enrolments in elective science courses, despite concerted efforts in recent years to alleviate them. This paper explores the reasons for these differences by comparing models of male and female enrolment intentions in elective courses in biology, chemistry and physics. The models are based on responses from approximately 450 students from 5 Australian high schools. First, a theoretical model, the Science Enrolment Model, was derived from Eccles and colleagues’ General Model of Academic Choice. Students’ responses were then used to develop empirical models of enrolment intentions in the three elective courses. Analyses for the models were conducted using the LISREL “mean structures” extension. Sex differences in the dependent variables in the models were then attributed to the relevant sets of independent variables. Substantial sex differences were identified in measures of perceived career value, interest and performance expectations in all three models which explained between 70% and 82% of the sex differences in enrolment intentions.