Matrix as an Alternative Solution for Evaluating Sentence Reordering Tasks
Although sentence reordering is a popular practice in educational contexts its scoring method has virtually remained ‘all-or-nothing’. The author proposed a more psychologically valid means of partial scoring called MRS (Maximal Relative Sequence) where a point is counted for each ascending run in t...
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| Main Author: | |
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| Format: | Book Chapter |
| Language: | English |
| Published: |
IntechOpen
2022
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| Subjects: | |
| Online Access: | https://www.intechopen.com/chapters/81608 |
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| Summary: | Although sentence reordering is a popular practice in educational contexts its scoring method has virtually remained ‘all-or-nothing’. The author proposed a more psychologically valid means of partial scoring called MRS (Maximal Relative Sequence) where a point is counted for each ascending run in the answer sequence allowing gaps and the final score reflects the length of the longest sequence of ascending elements. This scoring method, together with an additional consideration of recovery distances, was woven into an executable programme, and then transplanted to Excel without having to understand a programming language. However, the use of Excel was severely limited by the number of columns available. This chapter reviews the past practices of evaluating partial scoring of reordering tasks and proposes an alternative solution LM (Linearity Matrix), also executable on Excel, with far smaller consumption of columns and with the idea of calculating the recovery distances as well as MRS scores. Although LM and MRS are different scoring procedures, they both reflect psychological complexity of the task involved. Furthermore, LM is versatile as to the adjustability of adjacency weights as an extended model of Kendall’s tau. Some reflections on practical application are referred to as well as future directions of the study. |
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| ISBN: | 978-1-80355-822-6 |
| DOI: | 10.5772/intechopen.102868 |