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. 2018 Dec;23(1):1457394.
doi: 10.1080/10872981.2018.1457394.

Knowledge maps: a tool for online assessment with automated feedback

Veronica W Ho  1 , Peter G Harris  2 , Rakesh K Kumar  1 , Gary M Velan  1
Affiliations

Knowledge maps: a tool for online assessment with automated feedback

Veronica W Ho et al. Med Educ Online. 2018 Dec.

Abstract

In higher education, most assessments or examinations comprise either multiple-choice items or open-ended questions such as modified essay questions (MEQs). Online concept and knowledge maps are potential tools for assessment, which might emphasize meaningful, integrated understanding of phenomena. We developed an online knowledge-mapping assessment tool, which provides automated feedback on student-submitted maps. We conducted a pilot study to investigate the potential utility of online knowledge mapping as a tool for automated assessment by comparing the scores generated by the software with manual grading of a MEQ on the same topic for a cohort of first-year medical students. In addition, an online questionnaire was used to gather students' perceptions of the tool. Map items were highly discriminating between students of differing knowledge of the topic overall. Regression analysis showed a significant correlation between map scores and MEQ scores, and responses to the questionnaire regarding use of knowledge maps for assessment were overwhelmingly positive. These results suggest that knowledge maps provide a similar indication of students' understanding of a topic as a MEQ, with the advantage of instant, consistent computer grading and time savings for educators. Online concept and knowledge maps could be a useful addition to the assessment repertoire in higher education.

Keywords: Knowledge maps; assessment; concept maps; feedback; modified essay question; online.

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Figures

Figure 1.
Figure 1.
Teacher view of an assessment map with a pop-up box for writing distractors for a node (and specific feedback for each choice is desired).
Figure 2.
Figure 2.
Student view of the acute inflammation map with dropdown list.
Figure 3.
Figure 3.
Graphical feedback with incorrect nodes highlighted in red.
Figure 4.
Figure 4.
Acute inflammation knowledge map with testable items highlighted in blue; in pink boxes, difficulty (percentage of students who answered correctly) is above and point biserial correlation coefficient is below.
Figure 5.
Figure 5.
Likert-scale questionnaire responses (percentage agreement [i.e., scores >3 on a scale from 0 to 6]; n = 34).
See this image and copyright information in PMC

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