Shepherd Tricia D, Garrett-Roe Sean
Department of Chemistry, University of Pittsburgh, Pittsburgh, Pennsylvania 15260, United States.
J Chem Educ. 2024 Jul 25;101(8):3097-3106. doi: 10.1021/acs.jchemed.3c00993. eCollection 2024 Aug 13.
We formulate an alternative to high-stakes examinations that is designed to help students grow, and we describe its implementation in a large-enrollment General Chemistry 1 class. In our alternative grading approach, students complete weekly assessments. Each assessment has four items that are aligned to explicit learning objectives and a level in Marzano's taxonomy, , , , and , which can be used by students and instructors to gauge the progression of student learning. Proficiency-based grading and multiple attempts reduce the stakes of the assessments. Unique assessments are generated through a computational infrastructure that draws question stems from an item bank and further randomizes quantities, elements, compounds, reactions, spectra, Lewis structures, orbitals, etc. in the questions. Nearly all assessment items require student-generated responses and cover a complete General Chemistry 1 curriculum. We interpret Marzano's taxonomy in the General Chemistry context and outline the structure of the learning objectives, cognitive levels, assessment schedule, and grading scheme. Item response theory (Rasch analysis) validates the theoretical framework and indicates that assessment items are high quality. Students demonstrate improvement through assessment retakes, and they report that the system motivates them to study and learn.
我们制定了一种替代高风险考试的方式，旨在帮助学生成长，并描述了其在一门大招生规模的普通化学1课程中的实施情况。在我们的替代评分方法中，学生要完成每周的评估。每次评估有四个项目，这些项目与明确的学习目标以及马扎诺分类法中的一个水平相对应，学生和教师可以使用该分类法来衡量学生学习的进展情况。基于熟练程度的评分和多次尝试降低了评估的风险。独特的评估是通过一个计算基础设施生成的，该基础设施从题库中提取问题主干，并进一步对问题中的数量、元素、化合物、反应、光谱、路易斯结构、轨道等进行随机化处理。几乎所有的评估项目都要求学生给出自己的答案，并涵盖完整的普通化学1课程。我们在普通化学背景下解读马扎诺分类法，并概述了学习目标、认知水平、评估时间表和评分方案的结构。项目反应理论（拉施分析）验证了理论框架，并表明评估项目质量很高。学生通过重考评估显示出进步，他们报告说这个系统激励他们去学习。
