This paper presents the initial findings of the iQJournalism system's prototype, an effort to create an intelligent advisor for predicting the perceived quality of news articles. Accordingly, artificial intelligence methodologies are utilized, with the purpose of providing real-time recommendations to journalists looking to improve the overall quality and engagement of their articles. The iQJournalism is designed using a user-centered design approach, in order to facilitate the specific needs of the journalists and editors using it. In this paper we discuss preliminary results of a study that was conducted with 20 users. Following an extensive literature review and the insights of a focus group with 10 professional journalists and MSc students, we created an interactive prototype of the iQJournalism system. The main aim is to facilitate the interaction of the users with the computational layer of the system for estimating the perceived quality of an article before its release. We organized a moderated desirability (light usability) study, in order to capture the users' feedback. We used user experience and usability measurement tools like UEQ, SUS, Product reaction cards, perceived satisfaction and system adoption items, and open-ended questions to collect more comprehensive insights around the acceptance and usefulness of our prototype. Initial results show an overall favorable user experience, effective and efficient interaction when users engage with a series of situation-specific tasks.