Improving Feedback from Automated Reviews of Student Spreadsheets
- URL: http://arxiv.org/abs/2311.10728v1
- Date: Sat, 14 Oct 2023 08:12:39 GMT
- Title: Improving Feedback from Automated Reviews of Student Spreadsheets
- Authors: S\"oren Aguirre Reid, Frank Kammer, Jonas-Ian Kuche, Pia-Doreen
Ritzke, Markus Siepermann, Max Stephan, Armin Wagenknecht
- Abstract summary: We have developed an Intelligent Tutoring System (ITS) to review students' Excel submissions and provide individualized feedback automatically.
Although the lecturer only needs to provide one reference solution, the students' submissions are analyzed automatically.
To take the students' learning level into account, we have developed feedback levels for an ITS that provide gradually more information about the error.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Spreadsheets are one of the most widely used tools for end users. As a
result, spreadsheets such as Excel are now included in many curricula. However,
digital solutions for assessing spreadsheet assignments are still scarce in the
teaching context. Therefore, we have developed an Intelligent Tutoring System
(ITS) to review students' Excel submissions and provide individualized feedback
automatically. Although the lecturer only needs to provide one reference
solution, the students' submissions are analyzed automatically in several ways:
value matching, detailed analysis of the formulas, and quality assessment of
the solution. To take the students' learning level into account, we have
developed feedback levels for an ITS that provide gradually more information
about the error by using one of the different analyses. Feedback at a higher
level has been shown to lead to a higher percentage of correct submissions and
was also perceived as well understandable and helpful by the students.
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