Data‐driven assessment techniques to catalyze student learning (618.19)

Abstract

As we rearticulate the undergraduate biochemistry curriculum to emphasize deep foundations in core biochemical principles and skills, we must also reconsider the assessment of student learning. Assessment is perhaps an instructor’s most powerful tool for affecting student learning, particularly when it is used to diagnose student understanding and to subsequently adjust activities to address learning difficulties. Yet, in undergraduate science teaching, assessment is largely employed as a summative activity, reducing its effectiveness as a tool for developing student understanding. While extensive research at the K‐12 level provides several insights into best practices for assessment, there is less research at the undergraduate level in general, and undergraduate science in particular.The purpose of the research presented here is to contribute to the growing literature base on effective assessments for undergraduate learning in the molecular life sciences. We designed and tested the efficacy of two formative assessment tools in large‐enrollment, introductory biochemistry courses for majors. Both tools make use of Learning Management Systems (e.g. Desire2Learn, Blackboard, WebCT) to formatively assess and diagnose student understanding and provide responsive feedback for instructors and students to inform learning. Data collected for analysis include: student clickstream data from Learning Management System usage, student open‐response items, student achievement data, and self‐report data. We will present results demonstrating the effectiveness of these tools in terms of (1) ability to uncover the range and extent of student reasoning difficulties, (2) ease and use by instructors, (3) utility to predict student performance and enact early warning systems for at‐risk students, and (4) impact on student learning.Grant Funding Source: Supported by the National Science Foundation, HRD‐0811239