Deriving from these results, the study highlighted a number of practical implications that benefit developers, designers, service providers, and instructors. The sensitivity analysis results revealed that knowledge application has the most considerable effect on the sustainable use of chatbots with 96.9% normalized importance, followed by perceived usefulness (70.7%), knowledge acquisition (69.3%), satisfaction (61%), and knowledge sharing (19.6%). The hypotheses testing results reinforced all the suggested hypotheses in the developed model.
Contrary to the prior literature that mainly relied on structural equation modeling (SEM) techniques, the empirical data were analyzed using a hybrid SEM-artificial neural network (SEM-ANN) approach. The developed model was then tested based on data collected through an online survey from 448 university students who used chatbots for learning purposes. This research, therefore, develops a theoretical model based on extracting constructs from the expectation confirmation model (ECM) (expectation confirmation, perceived usefulness, and satisfaction), combined with the knowledge management (KM) factors (knowledge sharing, knowledge acquisition, and knowledge application) to understand the sustainable use of chatbots. However, little is known concerning what affects their use for educational purposes. The dependence on immersion subject to external or internal factors and ludic contexts associated with internalization of motivation influenced the effect stability on learning achievement and motivation.Īrtificial intelligence (AI)-based chatbots have received considerable attention during the last few years. The main conclusion was that gamification and game-based learning, as two distinct game-related pedagogies, differently influenced learning achievement, intrinsic motivation, and extrinsic motivation. Game-based learning exerted less significant but more stable effects on extrinsic motivation (ES = 0.56, 95% CI ) than on intrinsic motivation (ES = 0.62, 95% CI ). Gamification exerted less significant but more stable effects on intrinsic motivation (ES = 0.64, 95% CI ) than on extrinsic motivation (ES = 0.92, 95% CI ). The overall effects on motivation were more significant for gamification (ES = 0.77, 95% CI ) than for game-based learning (ES = 0.60, 95% CI ). The effects on learning achievement were more stable and significant for game-based learning (ES = 0.54, 95% CI ) than for gamification (ES = 0.85, 95% CI ). With distinctive features, gamification and game-based learning were hypothesized to exert different effects on learning achievement and motivation. This meta-analysis aimed to investigate and compare the efficiencies of gamification and game-based learning in terms of learning achievement and motivation.
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