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During the Covid pandemic, we gave a Java assignment that exercised threads, synchronization, and coordination and wrote tests to check each concurrency aspect of the assignment. We used four different technologies to record events related to work on this assignment: the Piazza discussion forum, the Zoom conferencing system, an Eclipse plugin, and a testing framework. The recorded data have given the instructors of the course broad awareness of several aspects of student work: How much time did a student spend on an assignment? How many attempts students made on thread, synchronization, and coordination tests before they reached their final scores? How many times did they go to Piazza or use Zoom-supported office-hour visits to fix concurrency problems, and what was the nature of these problems? How effective was Zoom transcription to classify the office hour problems? How long and effective were the office hour visits, and to what extent was screen sharing used during these visits? To what extent did students use the tests to determine if they had met assignment requirements? These data, in turn, have provided us with preliminary answers to a variety of questions we had about unseen work and the concurrency aspects of the assignment. While the answers may be specific to our assignment, the questions answered by these mechanisms can be expected to apply to other settings. 

Existing techniques for automating the testing of sequential programming assignments are fundamentally at odds with concurrent programming as they are oblivious to the algorithm used to implement the assignments. We have developed a framework that addresses this limitation for those object-based concurrent assignments whose user-interface (a) is implemented using the observer pattern and (b) makes apparent whether concurrency requirements are met. It has two components. The first component reduces the number of steps a human grader needs to take to interact with and score the user-interfaces of the submitted programs. The second component completely automates assessment by observing the events sent by the student-implemented observable objects. Both components are used to score the final submission and log interaction. The second component is also used to provide feedback during assignment implementation. Our experience shows that the framework is used extensively by students, leads to more partial credit, reduces grading time, and gives statistics about incremental student progress