Asynchronous online discussion forums are common in blended learning models and are popular with students. A previous report has suggested that participation in these forums may assist student learning in a gross anatomy subject but it was unclear as to whether more academically able students post more often or whether participation led to improved learning outcomes. This study used a path model to analyze the contribution of forum participation, previous academic ability, and student campus of enrolment to final marks in a multicampus gross anatomy course for physiotherapy students. The course has a substantial online learning management system (LMS) that incorporates asynchronous forums as a learning tool, particularly to answer learning objectives. Students were encouraged to post new threads and answer queries in threads started by others. The forums were moderated weekly by staff. Discussion forums were the most used feature of the LMS site with 31,920 hits. Forty-eight percent of the students posted at least once with 186 threads initiated by students and a total of 608 posts. The total number of posts made a significant direct contribution to final mark (P = 0.008) as did previous academic ability (P = 0.002). Although campus did not contribute to final mark, there was a trend for students at the campus where the course coordinator was situated to post more often than those at the other campus (P = 0.073). These results indicate that asynchronous online discussion forums can be an effective tool for improving student learning outcomes as evidenced by final marks in gross anatomy teaching.
Summary In the analysis of panel data that includes a time-varying covariate, a Hausman pretest is commonly used to decide whether subsequent inference is made using the random effects model or the fixed effects model. We consider the effect of this pretest on the coverage probability of a confidence interval for the slope parameter. We prove three new finite sample theorems that make it easy to assess, for a wide variety of circumstances, the effect of the Hausman pretest on the minimum coverage probability of this confidence interval. Our results show that for the small levels of significance of the Hausman pretest commonly used in applications, the minimum coverage probability of the confidence interval for the slope parameter can be far below nominal.
Increasing numbers of lesbian, gay and bisexual (LGB) adults are entering into parenthood. Previous studies indicate many of these parents receive little or no support from their families of origin due to family members' negative attitudes toward homosexuality. This study looks at the extent to which LGB parents report a lower sense of connectedness to family of origin and friendship networks than heterosexual parents and whether this has an impact on psychological wellbeing in either of these groups. Data were derived from two studies of parents: Work, Love, Play, a study of Australian and New Zealand LGB parents (n=324); and the Longitudinal Study of Australian Children, a population‐based study of young children and parents (n=6460). Structural equation modelling was used to explore the relationships between: parent sexuality and family/friendship connectedness, family/friendship connectedness and psychological wellbeing, parent sexuality and psychological wellbeing. LGB parents reported feeling less connected to their families of origin but more connected to their friendship groups than heterosexual parents. Counter to previous studies, we found no difference in the psychological wellbeing of LGB parents compared to heterosexual parents when examining the direct effect of sexuality on psychological wellbeing. Clinical implications for counsellors and family therapists are discussed.
We assess the impact of a Hausman pretest, applied to panel data, on a confidence interval for the slope, conditional on the observed values of the time-varying covariate. This assessment has the advantages that it (a) relates to the values of this covariate at hand, (b) is valid irrespective of how this covariate is generated, (c) uses finite sample results and (d) results in an assessment that is determined by the values of this covariate and only 2 unknown parameters. Our conditional analysis shows that the confidence interval constructed after a Hausman pretest should not be used.2
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