The author’s Python course is being delivered by two academic providers in New Zealand and uses CodeRunner for marking all lab work and assessments. Students receive feedback and marks on the code they write within seconds. Installing CodeRunner, creating labs and code/live demos will be covered.
This session covers how to facilitate near immediate marking and feedback of student submitted code. I have been using this mechanism for teaching Python for almost 3 years and the feedback from the students is positive. Moodle, CodeRunner and JobEngine are not restricted to Python although Python is my preference, other coding areas will be mentioned.
I will show how questions created in Moodle covering a variety of topics interact with CodeRunner and ultimately how the student code and question test data is submitted to a JobEngine VM and the results returned to Moodle for the student to see. Based on the response time of both Moodle and JobEngine, this can be between 200 msec and 2 seconds, typically it is less than 1 second. While Moodle is used for hosting the questions, these are not multi-choice based lab questions.
I am keen on providing immediate feedback to the students for their code based solutions, the immediacy of feedback is seen as a success point for this course. I would like to encourage others to explore this.
Instructions will be provided which will encourage the audience to look at creating their own service or making use of shared resources.
I prefer the logic analyser or packet trace end of the computing spectrum and have a passion for embedded computing or IoT as it is now.
Watch 'Automagically marking Python course work and assessments in seconds!' on PyCon AU's YouTube account
Senior Lecturer in the Department of Computing at Ara (formally CPIT) in Ōtautahi, Aotearoa. A maker, coder, networker and educator.