Promoting students’ motivation in language education with gamified pedagogical conversational agents

Pedagogical conversational agents (PCAs) like chatbots are a novel approach to technology-mediated language learning with artificial intelligence. They convey learning content interactively and accompany students in their education. However, many users find conversations with PCAs unmotivating. Gamification is a suitable solution to these motivational hurdles due to its playful nature. Given the difficulty of selecting the appropriate game elements and the scarcity of design recommendations for gamified PCAs, we propose the GNPL framework including a cohesive set of four design principles: goal-setting and reflection, novice-expert relationship, performance-related motivation, and learning story narration. In two design cycles, the article shows the application of the design principles in English learning – a domain commonly associated with motivational challenges – by implementing and evaluating a gamified PCA. The results show that the design principles significantly foster learners' motivation and that learners perceive a solid language learning experience, expressed by higher perceived value and social factors. They highlight the relevance of aligning the PCA's social role, the motivational impact of gamification, and the educational goals of the learning context. The design principles guide educators and developers in gamified PCA design. The paper contributes to the theory stream of PCAs by investigating learners' motivation enhancement when using PCAs. In addition, the paper provides new knowledge on meaningful gamification in an unexplored context and practical insights to solve the design challenges of selecting game elements in this context. Furthermore, it shows how language education can be supported by educational technology.