Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them. Project number: 2023-1-NL01-KA220-HED-000155675. - Chatbot-Human Interaction Satisfaction Model (CHISM) to assess linguistic elements, design, and user experience. - Qualitative analysis of student reports for insights on AIC benefits and drawbacks. Lessons learned AIC potential: - Can offer immediate feedback and a supportive learning environment. - Need improvement in speech technologies (recognition and synthesis). - Must better adapt to different learner proficiency levels. Design significance: User-friendly interfaces, multimedia, and the potential of emerging tech (AR/VR) are crucial for engagement. CHISM's value: The model provides a comprehensive framework for AIC assessment within language learning contexts. Implications for practice Personalisation is key: AICs need to tailor experiences more effectively to sustain learner interest. Case Study 34: Experiences in the use of an adaptive intelligent system to enhance online learners’ performance: a case study in Economics and Business courses General information Reference/Source: Guerrero-Roldán, A. E., Rodríguez-González, M. E., Bañeres, D., Elasri-Ejjaberi, A., & Cortadas, P. (2021). Experiences in the use of an adaptive intelligent system to enhance online learners’ performance: a case study in Economics and Business courses. International Journal of Educational Technology in Higher Education, 18(1). https://doi.org/10.1186/s41239-021-00271-0 Institution: Universitat Oberta de Catalunya, Spain (fully online, public institution). Course/subject: Two first-year courses in the BSc of Economics and Business program: Introduction to Enterprise and Markets and Behavior Aim: Researchers are developing an Early Warning System (EWS) called the Learning Intelligent System (LIS) to address the issue of student dropout and improve overall performance in online courses. Target group: Undergraduate students enrolled in the specified courses.
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