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Integration of the Rosetta Stone AI-Powered Platform as a Learning Management System (LMS) for Language Learning in Moroccan Higher Education
Abstract
Grounded in the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), this chapter investigates Moroccan university students' perceptions and attitudes toward the Rosetta Stone platform based on data collected from 1,262 participants. It also investigates the main predictors of the use and acceptance of the Rosetta Stone platform by shedding light on practical implications for policymakers and university educators to optimize the integration of Rosetta Stone within Moroccan higher education. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the findings revealed that Hedonic Motivation and Habit emerged to have a significant impact on shaping Moroccan university students' intentions to utilize the Rosetta Stone Platform. It was also found that Facilitating Conditions did not significantly predict Behavioural Intention. While Effort Expectancy and Social Influence exhibited a moderate impact on Behavioural Intention, the variables of Age, Gender, Experience, and Familiarity had no direct effect on students' acceptance and use of Rosetta Stone.
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