TY - GEN
T1 - Benchmarking Partial Credit Grading Algorithms for Proof Blocks Problems
AU - Poulsen, Seth
AU - Kulkarni, Shubhang
AU - Herman, Geoffrey
AU - West, Matthew
N1 - Publisher Copyright:
© 2022, Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - Proof Blocks (proofblocks.org ) is a software tool that allows students to practice writing mathematical proofs by dragging and dropping lines instead of writing proofs from scratch. Because of the large solution space, it is computationally expensive to calculate the difference between an incorrect student solution and some correct solution, restricting the ability to automatically assign students partial credit. We benchmark a novel algorithm for finding the edit distance from an arbitrary student submission to some correct solution of a Proof Blocks problem on thousands of student submissions, showing that our novel algorithm can perform over 100 times better than the naïve algorithm on real data. Our new algorithm has further applications in grading Parson’s Problems, task planning problems, and any other kind of homework or exam problem where the solution space may be modeled as a directed acyclic graph.
AB - Proof Blocks (proofblocks.org ) is a software tool that allows students to practice writing mathematical proofs by dragging and dropping lines instead of writing proofs from scratch. Because of the large solution space, it is computationally expensive to calculate the difference between an incorrect student solution and some correct solution, restricting the ability to automatically assign students partial credit. We benchmark a novel algorithm for finding the edit distance from an arbitrary student submission to some correct solution of a Proof Blocks problem on thousands of student submissions, showing that our novel algorithm can perform over 100 times better than the naïve algorithm on real data. Our new algorithm has further applications in grading Parson’s Problems, task planning problems, and any other kind of homework or exam problem where the solution space may be modeled as a directed acyclic graph.
KW - Automated feedback
KW - Mathematical proofs
KW - Scaffolding
UR - http://www.scopus.com/inward/record.url?scp=85135933260&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85135933260&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-11647-6_34
DO - 10.1007/978-3-031-11647-6_34
M3 - Conference contribution
AN - SCOPUS:85135933260
SN - 9783031116469
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 199
EP - 203
BT - Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium - 23rd International Conference, AIED 2022, Proceedings
A2 - Rodrigo, Maria Mercedes
A2 - Matsuda, Noburu
A2 - Cristea, Alexandra I.
A2 - Dimitrova, Vania
PB - Springer
T2 - 23rd International Conference on Artificial Intelligence in Education, AIED 2022
Y2 - 27 July 2022 through 31 July 2022
ER -