Ralph Vanessa R, Scharlott Leah J, Schafer Adam G L, Deshaye Megan Y, Becker Nicole M, Stowe Ryan L
Teaching Engagement Program (Office of the Provost) and Department of Chemistry and Biochemistry, University of Oregon, 1585 E 13th Avenue, Eugene, Oregon 97403, United States.
Department of Chemistry, University of Iowa, 305 Chemistry Building, Iowa City, Iowa 52242, United States.
JACS Au. 2022 Jul 20;2(8):1869-1880. doi: 10.1021/jacsau.2c00221. eCollection 2022 Aug 22.
What we as scientists and educators assess has a tremendous impact on whom we authorize to participate in science careers. Unfortunately, in critical gateway chemistry courses, assessments commonly emphasize and reward recall of disaggregated facts or performance of (often mathematical) skills. Such an emphasis marginalizes students based on their access to pre-college math preparation and misrepresents the intellectual work of chemistry. Here, we explore whether assessing intellectual work more authentic to the practice of chemistry (i.e., mechanistic reasoning) might support more equitable achievement. Mechanistic reasoning involves explaining a phenomenon in terms of interactions between lower scale entities (e.g., atoms and molecules). We collected 352 assessment tasks administered in college-level introductory chemistry courses across two universities. What was required for success on these tasks was rote math skills (165), mechanistic reasoning (36), neither (126), or both (25). Logistic regression models predict that the intellectual work emphasized on in an assessment could impact whether 15-20% of the cohort passes or fails. Whom does assessment emphasis impact most? Predicted pass rates for those often categorized as "at-risk" could be 67 or 93%, depending on whether their success was defined by rote calculation or mechanistic reasoning. Therefore, assessment transformation could provide a path toward advancing the relevance of our courses and educational equity.
作为科学家和教育工作者,我们所评估的内容对我们授权参与科学事业的人员有着巨大影响。不幸的是,在关键的化学入门课程中,评估通常强调并奖励对零散事实的记忆或(通常是数学方面的)技能表现。这种强调使那些没有接受过大学前数学准备的学生处于边缘地位,并且歪曲了化学的智力工作。在此,我们探讨评估更符合化学实践的智力工作(即机理推理)是否可能支持更公平的成就。机理推理涉及根据较低尺度实体(如原子和分子)之间的相互作用来解释一种现象。我们收集了两所大学本科化学入门课程中进行的352项评估任务。这些任务成功所需的是死记硬背的数学技能(165项)、机理推理(36项)、两者都不需要(126项)或两者都需要(25项)。逻辑回归模型预测,评估中强调的智力工作可能会影响该群体中15%至20%的人通过或不及格。评估重点对谁影响最大?那些通常被归类为“有风险”的人的预测通过率可能为67%或93%,这取决于他们的成功是由死记硬背的计算还是机理推理来定义。因此,评估变革可以为提高我们课程的相关性和教育公平性提供一条途径。