Misconduct at the Lab? A Performance Task Case Study for Teaching Data Analysis and Critical Thinking

A distractor-rich performance task case study was developed to teach undergraduate analytical chemistry students about standard addition while reinforcing their grasp of data analysis and quality control principles. The performance ance task presents students with an e-mail from a fictional district attorney that asks them to investigate allegations of data falsification in a crime lab and determine whether fabricated, falsified, or faulty analyses may have impacted one particular court case. It also asks students to suggest changes to the lab's quality assurance practices. Correct analysis of the task scenario requires students to recognize that the accused analyst systematically overestimated analyte levels when they incorrectly assumed that their standard addition data fell within the linear region of their method's signal-response curve. The task is also designed to help students to grow in their professional awareness as chemists, critical thinking, and communication skills. This is because students are expected to apply their understanding of data analysis concepts and typical signal response curve behavior to a complex problem; develop an understanding of how standard addition works from the analyst's trial testimony; avoid numerous distractors embedded in the documents that detail the scenario; and present their findings in a written report. Because these features of the task require students to decide how much to focus on possible motives instead of analysis of the analytical data, they raise questions about the degree to which chemists should comment on nontechnical matters when speaking as a chemical professional. Since the prompt deliberately avoids specifying the length and other characteristics of the report, the students must make choices about how to present their findings. Consequently, the assignment concludes with instructor-led discussion and self-evaluation exercises aimed at helping students learn to assess and prioritize information, use statistics to assess analytical data, draw warranted conclusions, and communicate those conclusions appropriately.