摘要：This study explores the factors that influence experts’ regular contribution to educational community question-answering (CQA) platforms. Providing answers is essential for sharing knowledge on CQA platforms, but it also affects learners’ progressive inquiry. Therefore, the purpose of this study is to develop and test a theoretical model that aims to explain which factors influence whether experts answer questions on educational CQA platforms and how these factors correlate with each other to form a “map” of experts’ respective behavior. We examined experts’ perceptions of three dimensions: the CQA platform’s usability, the quality of questions asked, and the added value of answering these questions. We examined the factors involved in these dimensions from the perspective of the Theory of Planned Behavior to connect them with the experts’ perceptions, intentions, and actions on a CQA platform. As our case study, we took the 100mentors web and mobile app, a small-scale platform that addresses learning communities around the world, and we conducted a survey for their registered experts (N=126). The factorial structure indicated that experts first perceived the question quality mostly based on its relevance to their expertise or experience (question quality); secondly, that their intention to answer was mainly set by their motives to make a difference for the learner and partially by the user-friendliness of the platform (added value of answering and CQA platform’s usability); and finally, that their actions were connected to the regular use of the platform for answer-sharing (CQA platform’s usability). A future research challenge is to test the factorial structure in large-scale educational CQA platforms. The further confirmation of the expert behavior pattern can have a practical implication for the platforms to guide their expert community more efficiently and for the learners to pursue their learning through progressive inquiry.
关键词：Educational platform;expert contribution;theory of planned behavior;student questioning;expert motives;structural model
