A Method for Assessing Dogs in a Test Evaluating Dogs’ Suitability for Animal-Assisted Education

Abstract

In objective behavioral rating (BR), dogs are rated for behavior based on the observations made during a behavioral test. However, behavioral definitions can differ between raters, and the definitions proposed by artificial intelligence (AI) can help standardize the applied measures. The aim of this study was to propose a new approach for assessing dogs’ suitability for animal-assisted education (AAE) with the use of the BR method and the definitions of dog behaviors proposed by AI. The analysis relied on video footage of 25 dogs that participated in tests assessing the animals’ suitability for AAE. The dogs were rated by five independent observers. Inter-rater reliability was satisfactory in 7 out of 9 subtests (0.715–0.856) and low in the remaining 2 subtests (0.667 in Subtest 2 and 0.617 in Subtest 5). The results indicate that the BR method based on AI definitions produced satisfactory inter-rater reliability in a test evaluating dog behavior. A comparison of subtest scores in the BR method and the subjective rating method did not reveal significant differences. Thus, it can be concluded that the proposed approach gives promising outcomes and can be used to develop new tests for assessing dogs’ suitability for AAE and, perhaps, other types of work.