Students’ perceptions of the structure of the personality of a Socially Assistive Robot for Learning and Instruction

Manuscript
Published: Dec 27, 2025
DOI: https://doi.org/10.12681/psy_hps.43954
Keywords:
socially assistive robot, learning and instruction, personality, exploratory factor analysis, confirmatory factor analysis
Panagiota Christodoulou
Department of Education, University of Western Macedonia
Dimitrios Pnevmatikos
Department of Education, University of Western Macedonia
Tiina Mäkelä
Finnish Institute for Educational Research, University of Jyväskylä
Nikolaos Fachantidis
Department of Education and Social Policy, University of Macedonia
Abstract

Policymakers in the 21st century consider the application of Socially Assistive Robots (SARs) in the educational context essential to transform instruction and support students in achieving better learning results. However, several questions emerge regarding the conditions of SAR's application in education. The current study aimed to investigate students' perceptions regarding the personality of a SAR involved in learning and instruction, namely the dynamic and unique set of traits and characteristics that shape the SAR's behaviors and interactions with the students. An online questionnaire was administered to 1083 primary (N=390, M=11.23, SD=.72), lower secondary (N=378, M=14.10, SD=.85) and upper secondary (N=315, M=16.82, SD=.77) students from Greece and Finland. The exploratory factor analysis revealed two psychological factors that reflect two types of personality traits of a SAR for learning and instruction: the SAR as a "Regulator" and a "Facilitator" of learning. Then, a Confirmatory Factor Analysis showed that the model in which the two dimensions tap into the same factor that expresses the unity of a SAR's personality for learning and instruction had the best fit to the data. This structure was confirmed across both countries. Still, some age, gender and culture related differences in students’ endorsements of the dimensions of the SAR’s personality were identified. Capturing the dimensions of the personality of a SAR for learning and instruction can inform the design and development of more effective SARs tailored to specific cultural contexts and student preferences. Furthermore, these findings enhance our understanding of Human-Robot Interaction in education.

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