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Background: When students are given a choice of when to take an exam in engineering and computing courses, it has been previously observed that average exam scores generally decline over the exam period. This trend may have implications both for the design of interventions to improve student learning and for data analysis to detect collaborative cheating. Purpose/Hypothesis: We hypothesize that average exam scores decline over the exam period primarily due to self‐selection effects, where weaker students tend to choose exam times later in the exam period, while stronger students are more likely to choose earlier times. Design/Method: We collected 31,673 exam records over four semesters from six undergraduate engineering and computing courses that had both synchronous exams (all students at the same time) and asynchronous exams (students choose a time). We analyzed student exam time choice and asynchronous exam scores, using synchronous exam scores in the same course as a control variable. Results: We find that students with lower scores on synchronous exams generally elect to take asynchronous exams later and that controlling for student ability (via synchronous exams) removes 70% of the decline observed in average asynchronous exam scores over the exam period but does not eliminate the downward trend with time. Conclusions: We conclude that self‐selection effects are primarily responsible for exam score declines over time, that exam time selection is unlikely to be a useful target for interventions to improve performance, and that there is no evidence for widespread collaborative cheating in the dataset used in this research. [ABSTRACT FROM AUTHOR]

Automatically grading essay questions can have advantages for instructors in higher education. Understanding and specifying how grading is done manually, so that there is potential to do it automatically, is a labor-intensive effort in knowledge elicitation, acquisition, and representation. This paper describes how an interdisciplinary team used conceptual graphs to formally specify the model for a good essay response, and then how that expert model was used as the standard by which the student responses were judged. The methodology is then described for creating the expert model for student responses. These were compared using two different approaches. It was found that most students included the most important concepts, but those student answers that were more complete (i.e., also including concepts of lesser importance) received higher grades. The approaches are then evaluated in terms of reliability and validity, and finally, suggestions are made for future work. [ABSTRACT FROM AUTHOR]