Toward Robust Assessments of Student Knowledge of Occupation.

The American journal of occupational therapy : official publication of the American Occupational Therapy Association(2021)

引用 3|浏览1
暂无评分
摘要
IMPORTANCE:Occupational therapy students must master knowledge of occupation, yet how educators assess such knowledge has not been explored. In this study, we elucidate robust assessment practices that can help students master knowledge of occupation. OBJECTIVE:To examine practices that educators use to assess knowledge of occupation. DESIGN:Basic qualitative research. Using inductive and constant comparative methods, we coded 25 interviews and 82 educational artifacts for assessment practices, categorized practices as direct or indirect, and analyzed their alignments with features of robust assessments. SETTING:Twenty-five randomly selected occupational therapy and occupational therapy assistant academic programs in the United States, stratified by geographic region and institution type. PARTICIPANTS:Twenty-nine educators who represented selected programs. RESULTS:We found occupation at instruction and program levels primarily in relation to practice using indirect more than direct practices. Assignments were often highly creative and experiential, yet varied in their alignments with established criteria of robust assessments. CONCLUSIONS AND RELEVANCE:Knowledge of occupation was often intertwined with practice-oriented learning experiences and skills; hence, it was not assessed as a distinctly indispensable learning outcome. Educators can build on current practices to design robust assessments that require students to demonstrate knowledge of occupation in practice contexts and everyday life. WHAT THIS ARTICLE ADDS:In this study, we elucidate a continuum of prevalent educational practices used to assess knowledge of occupation; we also review best practices for robust assessments of such knowledge not only related to practice but also as a dynamic instrument of individual and societal well-being more broadly.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要