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About
About
Logic Learner is an online tool that that provides students with adaptive feedback when solving propositional logic proofs. Designed to differentiate for different skill levels, the application scaffolds to students by separating questions by complexity, and giving students targeted feedback and hints when mistakes are made or if students get stuck on a particular step. A solution sheet toggle allows students to compare their answer to the optimal version.
The tool and its use was proposed by faculty members, Assaf and Nakul, from the computer science department, after they had discovered that in previous semester students performed on average more poorly to this particular unit of their Discrete Mathematics course. After being awarded a grant from Columbia's Office of Teaching, Learning, and Innovation, they worked with my team from the Center for Teaching and Learning to design, develop, implement, and assess the impact of the application.
Learning Goals
Learning Goals
By using the tool students will be able to…
self-correct incorrectly solved proofs given scaffolds and instantaneous feedback.
self-assess their own ability to solve proofs of a certain level.
improve their own confidence in solving proofs.
improve their performance on homework and exam assignments for proof-related questions.
My Work on This Project
My Work on This Project
As the learning designer on this project I accomplished the following:
Led the design effort for the feedback workflow, determining when students should recieve hints, and how to best scaffold out the hints to promote productive struggle.
Collaborated with Teaching Assessment Fellow to design and implement assessment tools to measure the efftiveness of the tool in terms of the the objectives.
Research Backing
Research Backing
Barnes, T., & Stamper, J. (2010). Automatic hint generation for logic proof tutoring using historical data. Journal of Educational Technology & Society, 13(1), 3-12.
Cavalcanti, A. P., Barbosa, A., Carvalho, R., Freitas, F., Tsai, Y. S., Gašević, D., & Mello, R. F. (2021). Automatic feedback in online learning environments: A systematic literature review. Computers and Education: Artificial Intelligence, 2, 100027.
Deeva, G., Bogdanova, D., Serral, E., Snoeck, M., & De Weerdt, J. (2021). A review of automated feedback systems for learners: Classification framework, challenges and opportunities. Computers & Education, 162, 104094.
Heeren, B., & Jeuring, J. (2019). Automated feedback for mathematical learning environments. In ICTMT International Conference on Technology in Mathematics Teaching, to appear.
Xi, X. (2010). Automated scoring and feedback systems: Where are we and where are we heading?. Language Testing, 27(3), 291-300.
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