Intrance: Designing an Interactive Enhancement System for the Development of QA Chatbots

Abstract

User input is essential for the successful development of question-and-answer (QA) chatbots. Therefore, interactive development systems are emerging that allow developers to involve test-users in the QA chatbot development process. Although the feasibility and effectiveness of this approach have been demonstrated, there is a lack of knowledge on how to design interactive QA chatbot development systems to increase test-user engagement as well as data quality in this time-consuming and tedious task. To address this research gap, we propose an interactive system design based on the interactivity effects model. We instantiate the proposed design and introduce Intrance, an interactive enhancement system for QA chatbots. Subsequently, we show in two online experiments that the proposed design significantly increases subjective and objective engagement of test-users and has a positive effect on data quality, conceptualized as data completeness and data accuracy. We discuss design implications for an implementation of the proposed design in commercial chatbot development systems.