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Chatbot as a learning assistant: Factors influencing adoption and recommendation
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Resumo(s)
Soon, it is expected that artificial intelligence (AI) may replace many jobs whose work is based in repetitive tasks. Considering the role that this technology will play in our lives over the next few years, it would be interesting to take advantage of its potential now and use it as a transformation agent in the educational system. This study aims to evaluate the main drivers for adoption and recommendation of chatbots as a learning assistant to students in higher education. The research uses an innovative model based on gamification affordance, support construct from the students control model, and performance expectance, hedonic motivation, and behavioural intention to adopt constructs from the well-known UTAUT2 model. The model was empirically assessed using structural equation modelling (SEM) based on 302 responses from an online survey conducted in a South American country, Brazil. Support and hedonic motivation were found to be the most significant drivers for behaviour intention to adopt a chatbot. To explain the antecedents of the intention to recommend a chatbot, support and behavioural intention to adopt were the most important drivers found. For scholars, this research brings new material for further exploration of individual drivers for technology adoption and recommendation. For practitioners, knowing the main drivers for adoption and recommendation of a chatbot enables them to develop a technology with higher chances of absorption in the market.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Marketing Intelligence
Palavras-chave
Chatbot Gamification Mobile learning Personal Learning Environment SDG 4 - Quality education