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About this paper
Rosana Montes, Cristina Zuheros, Jeovani M. Morales, Noe Zermeño, Jerónimo Duran, Francsico Herrera
A 2-Tuple Fuzzy Linguistic Delphi method is introduced to validate questionnaires, accommodating multi-granular expert input and providing linguistic outputs. This approach successfully validated a 45-item questionnaire for b-learning education in two rounds, raising its overall quality score from 'Very correct' to 'Excellent' and significantly improving expert consensus on problematic items.
Key insights
- The 2-tuple linguistic representation model effectively preserves information during computational aggregation of linguistic terms, enabling precise and continuous representation of expert judgments.
- Allowing experts to express opinions with different linguistic granularities, along with assigning expertise weights per dimension, provides a more accurate and flexible method for integrating diverse expert knowledge.
- The dynamic consensus and reliance indices, combined with linguistic outputs from the DSS, offer actionable feedback that efficiently guides moderators in identifying problematic questionnaire items and facilitating targeted revisions.
Summary by alphaXiv.
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