Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/9244
Title: Towards Developing Scalable Assessments of Higher-Order Learning
Authors: Sealfon, Carolyn D.
Keywords: CSCL
Issue Date: 2023
Publisher: International Society of the Learning Sciences
Citation: Sealfon, C. D. (2023). Towards developing scalable assessments of higher-order learning. In Damșa, C., Borge, M., Koh, E., & Worsley, M. (Eds.), Proceedings of the 16th International Conference on Computer-Supported Collaborative Learning - CSCL 2023 (pp. 386-387). International Society of the Learning Sciences.
Abstract: To improve and broaden participation in science, technology, engineering and math (STEM) requires assessments of learning that are created within a compassionate learner-centered philosophy with heightened attention to ethics and bias. This poster proposes a path towards scalable, learner-mediated assessment instruments of higher-order cognitive abilities that would be convenient to implement at large scales or in any university class.
Description: Poster
URI: https://doi.org/10.22318/cscl2023.978554
https://repository.isls.org//handle/1/9244
Appears in Collections:ISLS Annual Meeting 2023

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