Recent studies have proposed new ways of providing learning experiences and measuring students’ achievement of learning goals, grounded on the principles of growth mindset, mastery learning, and specifications grading. In one initiative called “A’s for All (as time and interest allow)”, students are given the support to achieve the proficiency they want (not necessarily an A) as long as they are willing to put in the time and effort, thus providing students more control over their learning. One mechanism to support proficiency at different paces is to soften some of the assignment deadlines.
This study examined two flexible deadline policies while keeping exam dates fixed in my Numerical Methods course. Under both policies, students could earn full credit for completing homework and pre-lectures (formative assessments) within one week of release. In the Lenient schedule, homework could be submitted until the end of the semester for 96% credit. In the Strict schedule, the 96% credit deadline was moved to the corresponding exam date.
Both policies led to fewer than 25% of students completing homeworks by the 100% deadline (see figure below). However, the Strict schedule encouraged more timely submissions before exams due to the partial credit incentive when compared with the Lenient schedule (46% vs 27% respectively). There was a signficant performance advantage for students who completed the homeworks by the exam date in both schedules (around 15%), but a smaller increment when completed before the 100% deadline (3-4%). Based on these findings, my course has adopted the Strict schedule as its standard practice.
Zhao C., West M., Silva M., “How much deadline flexibility on formative assessments should we be giving to our students?”, Proceedings of the 2023 American Society for Engineering Education Conference (ASEE 2023), 2023.
Garcia D., Fox A., Zilles C., West M., Silva M., Terrell N., Russell S., Ambrosio E., Shakir F., “A’s for All (as Time and Interest Allow)”, Proceedings of the 54th ACM Technical Symposium on Computer Science Education (SIGCSE 2023), 2023.