TY - GEN
T1 - Comparison of Grade Replacement and Weighted Averages for Second-Chance Exams
AU - Herman, Geoffrey L.
AU - Cai, Zhouxiang
AU - Bretl, Timothy
AU - Zilles, Craig
AU - West, Matthew
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/8/10
Y1 - 2020/8/10
N2 - We explore how course policies affect students' studying and learning when a second-chance exam is offered. High-stakes, one-off exams remain a de facto standard for assessing student knowledge in STEM, despite compelling evidence that other assessment paradigms such as mastery learning can improve student learning. Unfortunately, mastery learning can be costly to implement. We explore the use of optional second-chance testing to sustainably reap the benefits of mastery-based learning at scale. Prior work has shown that course policies affect students' studying and learning but have not compared these effects within the same course context. We conducted a quasi-experimental study in a single course to compare the effect of two grading policies for second-chance exams and the effect of increasing the size of the range of dates for students taking asynchronous exams. The first grading policy, called 90-cap, allowed students to optionally take a second-chance exam that would fully replace their score on a first-chance exam except the second-chance exam would be capped at 90% credit. The second grading policy, called 90-10, combined students' first- and second-chance exam scores as a weighted average (90% max score + 10% min score). The 90-10 policy significantly increased the likelihood that marginally competent students would take the second-chance exam. Further, our data suggests that students learned more under the 90-10 policy, providing improved student learning outcomes at no cost to the instructor. Most students took exams on the last day an exam was available, regardless of how many days the exam was available.
AB - We explore how course policies affect students' studying and learning when a second-chance exam is offered. High-stakes, one-off exams remain a de facto standard for assessing student knowledge in STEM, despite compelling evidence that other assessment paradigms such as mastery learning can improve student learning. Unfortunately, mastery learning can be costly to implement. We explore the use of optional second-chance testing to sustainably reap the benefits of mastery-based learning at scale. Prior work has shown that course policies affect students' studying and learning but have not compared these effects within the same course context. We conducted a quasi-experimental study in a single course to compare the effect of two grading policies for second-chance exams and the effect of increasing the size of the range of dates for students taking asynchronous exams. The first grading policy, called 90-cap, allowed students to optionally take a second-chance exam that would fully replace their score on a first-chance exam except the second-chance exam would be capped at 90% credit. The second grading policy, called 90-10, combined students' first- and second-chance exam scores as a weighted average (90% max score + 10% min score). The 90-10 policy significantly increased the likelihood that marginally competent students would take the second-chance exam. Further, our data suggests that students learned more under the 90-10 policy, providing improved student learning outcomes at no cost to the instructor. Most students took exams on the last day an exam was available, regardless of how many days the exam was available.
KW - assessment
KW - computer education
KW - computer-based exams
KW - mastery
KW - second-chance testing
UR - http://www.scopus.com/inward/record.url?scp=85092173659&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85092173659&partnerID=8YFLogxK
U2 - 10.1145/3372782.3406260
DO - 10.1145/3372782.3406260
M3 - Conference contribution
AN - SCOPUS:85092173659
T3 - ICER 2020 - Proceedings of the 2020 ACM Conference on International Computing Education Research
SP - 56
EP - 66
BT - ICER 2020 - Proceedings of the 2020 ACM Conference on International Computing Education Research
PB - Association for Computing Machinery
T2 - 16th Annual ACM Conference on International Computing Education Research, ICER 2020
Y2 - 10 August 2020 through 12 August 2020
ER -