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A challenge instructors face is developing and accurately assessing technical communication skills to ensure students can apply and transfer the skills from the academic context into the context of engineering practice. By intentionally balancing teaching transferrable communication skills relevant to engineering practice and evaluating student understanding, engineering educators can foster competence and prepare students for the expectations of their professional careers. This study addresses two questions: (1) how can chemical engineering instructors reliably and consistently assess student communication skills, and (2) are instructor expectations aligned with those of practicing engineers? The use of well-designed rubrics is important for setting clear expectations for students, providing constructive feedback, and in team taught courses, grading consistently. This study discusses how a rubric for assessing technical communication skills in senior-level chemical engineering laboratory reports was validated and demonstrated reliability across five chemical engineering instructors. Additionally, five industry partners evaluated student reports for comparison to instructor rubric scores. Expectations and perceptions of the quality of student work align between instructors and practicing engineers, but practicing engineers prioritized safety and abstract clarity, while instructors prioritized the students’ abilities to interpret results and draw conclusions. 

The use of writing-based exercises in a circuit analysis course has shown promise in aiding students likely to struggle in the course by enhancing their conceptual understanding of topics related to DC circuit analysis [1]. As grading of writing samples and providing personalized feedback can be time-intensive, automating the evaluation and feedback processes through use of emerging techniques in natural language processing (NLP) could open the door for more widespread use of such writing exercises across STEM courses, thus benefiting students in most need of assistance. In this paper, the development and initial testing of two web-based writing activities that leverage a basic NLP technique to probe student writing related to DC circuits are described. The first writing exercise has students describe what happens to the power of various elements in a resistive circuit as the value of one of the resistors decreases. The second exercise has students consider situations in which the ideal independent voltage and current source models might fail. Both writing exercises are built from a template that includes several metacognitive prompts to spur self-reflection on the part of the user. A rule-based approach was taken to detect evidence of common misconceptions [2] and errors in student responses, as well as to identify sentences that revealed the student was correctly addressing the problems. Based on identified misconceptions or correct concepts in a student’s writing, the web-based application selects appropriate directed line of reasoning (DLR) feedback paths to attempt to lead the writer to an accurate understanding of the behavior of the circuits in question. Key features of the web-based application template as well as details regarding misconception detection and personalized feedback are described. Student impressions of the value of the DLR feedback is assessed using comments provided by the student within the applications. Planned modifications of the web-based writing exercise template based on this formative assessment will be given and address a broader goal of this work – to develop a web-based template that instructors across STEM disciplines, even those without a background in coding, could use to implement their own conceptual writing exercises.