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Canvas (LMS) as a means for effective student learning assessment across an institution of higher education
Author(s) -
Frederick Burrack,
Dorothy Burr Thompson
Publication year - 2021
Publication title -
the journal of assessment in higher education
Language(s) - English
Resource type - Journals
ISSN - 2642-0694
DOI - 10.32473/jahe.v2i1.125129
Subject(s) - coursework , set (abstract data type) , process (computing) , automaticity , institution , dissemination , higher education , quality (philosophy) , medical education , computer science , mathematics education , psychology , political science , medicine , cognition , telecommunications , philosophy , epistemology , neuroscience , law , programming language , operating system
Programmatic and institutional assessment initiatives have emerged and continuously evolved across higher education institutions through the early part of the twenty-first century. These initiatives have stemmed from a growing emphasis on assessing the quality of learning that occurs throughout the collegiate education. An assessment process that involves faculty and staff collecting, analyzing and discussing the data over time to guide improvement decisions sounds like a reasonable pursuit. Unfortunately, such a process sometimes results in apathy and dissention.  Technology has provided solutions that can remove the tedium and time-consumption from student learning assessment. The purpose of this article is to provide a thorough understanding of the assessment capabilities and data-collecting automaticity processes of Canvas. Provided are examples of ways to extract and disseminate Canvas data to be used for decisions making. The article includes (a) the structure of Canvas, (b) steps for how to set up Canvas for collecting student achievement data directly from coursework and sortable by outcomes and associated criteria, (c) strategies to export data from Canvas, and (d) ideas for visualizing outcome data.

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