The model performance is evaluated at JRec - Japanese reading text recommendation tool . 380 articles were used form Japanese news website and these articles were split in 4267 sentence and paragraphs. Then hierarchical structure of the vocabulary was analyzed and afterwards fuzzy partial ordering graph was applied to it . After the sentence appears user should answer whether they understand it or not. Their tool was used by 386 users in 3 days. "In JRec, we tested four different versions: 1) adaptive recommendation (which balances recommendation and assessment as we discussed in the last section4 ) and 2) non-adaptive recommendation (with no assessment incorporated), as well as 3) assessment-only, and 4) random selection as additional baselines" As it was found adding adaptivity increased user performance.