Dataset Information

Teaching Assistant Professional Development in Biology: Designed for and Driven by Multidimensional Data.

ABSTRACT: Graduate teaching assistants (TAs) are increasingly responsible for instruction in undergraduate science, technology, engineering, and mathematics (STEM) courses. Various professional development (PD) programs have been developed and implemented to prepare TAs for this role, but data about effectiveness are lacking and are derived almost exclusively from self-reported surveys. In this study, we describe the design of a reformed PD (RPD) model and apply Kirkpatrick's Evaluation Framework to evaluate multiple outcomes of TA PD before, during, and after implementing RPD. This framework allows evaluation that includes both direct measures and self-reported data. In RPD, TAs created and aligned learning objectives and assessments and incorporated more learner-centered instructional practices in their teaching. However, these data are inconsistent with TAs' self-reported perceptions about RPD and suggest that single measures are insufficient to evaluate TA PD programs.

SUBMITTER: Wyse SA

PROVIDER: S-EPMC4041500 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Teaching Assistant Professional Development in Biology: Designed for and Driven by Multidimensional Data.

Wyse Sara A SA Long Tammy M TM Ebert-May Diane D

CBE life sciences education 20140101 2

Graduate teaching assistants (TAs) are increasingly responsible for instruction in undergraduate science, technology, engineering, and mathematics (STEM) courses. Various professional development (PD) programs have been developed and implemented to prepare TAs for this role, but data about effectiveness are lacking and are derived almost exclusively from self-reported surveys. In this study, we describe the design of a reformed PD (RPD) model and apply Kirkpatrick's Evaluation Framework to evalu ...[more]

PMID: 26086654

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Project description:BackgroundPain is part of the everyday life of professional dancers. It can indicate health risks and impair the ability to work. Suitable screening tools can be used to identify pain and its risk potential. A comprehensive, multidimensional, differentiated assessment tool for pain in professional dance does not currently exist.MethodsAn initial questionnaire was developed in German and English and was assessed in a qualitative pretest. In a field study with a cross-sectional design including n = 72 dancers from Germany (n = 36 responses each in the English and German language versions), the questionnaire was optimized by item analysis, its psychometric properties (dimensionality, construct validity, reliability) were examined and the ability of the pain dimensions to classify the subjective ability to work in training was analyzed (ROC analysis).ResultsThe developed Multidimensional Pain Questionnaire in Professional Dance (MPQDA) was reduced and optimized in its psychometric properties. Following questions were reduced in their items or answer categories: pain localizations (from 20 to 15 regions), accompanying symptoms (from 6 to 3 items), sensory and affective pain quality (from 20 to 10 items), pain frequency (from 4 to 3 answer categories), and the motives of working with pain (from 14 to 12 items). Regarding the subjective ability to work in training, the variables of the ability to work in rehearsals and in performances, as well as the accompanying symptoms of tension and mobility restrictions, showed a relatively good classification ability (Area under the Curve (AUC) ≥ 0.7 in the 95% confidence interval) and significant, moderate to strong correlations (Somers' D > 0.25, p < 0.05). The classification ability of the other pain dimensions was largely absent or poor.ConclusionThe MPQDA differentiates various pain dimensions in professional dancers and is available in a compatible manner in German and English. The clinical relevance needs to be explored further in the future.

Dataset Information

Teaching Assistant Professional Development in Biology: Designed for and Driven by Multidimensional Data.

Publications

Teaching Assistant Professional Development in Biology: Designed for and Driven by Multidimensional Data.

Similar Datasets

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