Special Issue "Understanding UX through Implicit and Explicit Feedback"
A special issue of Multimodal Technologies and Interaction (ISSN 2414-4088).
Deadline for manuscript submissions: closed (15 July 2020).
Interests: Psychological modeling; User modeling; Personalization; Recommender Systems
Interests: predictive modeling; user modeling; recommender systems; intelligent systems
This special issue aims to explore the opportunities and challenges of combining implicit and explicit feedback to understand and design user experience (UX) in Human-Computer Interaction (HCI).
Measuring UX is important to understand how successful applications and systems are in reaching their goals. In general, there are two main approaches to measure UX: 1) explicit feedback (i.e., using data measured through surveys, interviews and focus groups) and 2) implicit feedback (i.e., using data describing users’ observable interaction behavior measured through, for example, telemetry). Measuring explicit feedback is costlier, requires user input, and thus relies on smaller scale studies. However, it allows to gain deeper information and understanding about the relationship between user characteristics, their needs and preferences, their behavior and their experience. Although, implicit feedback can be collected automatically, it allows for limited understanding of the relationship between user behavior, user traits and user experience.
Implicit and explicit feedback can be combined to effectively measure and understand UX factors; implicit feedback can facilitate the breadth (by quantitatively indicating how designs influence UX) while explicit feedback can facilitate the depth (by providing insight how user behavior, user characteristics and user experience are related). The combination of these two approaches result in an understanding with a high level of detail with the cost efficiency of quantitative research.
Specific areas in which the combination of implicit and explicit feedback is valuable is in personalized and adaptive systems: systems that adapt itself based on users’ interaction behavior to match their preferences or needs. A prominent direction using this approach is the field of recommender systems in which historical behavioral data (implicit feedback) is used to alter the order of items in a catalog (from highest predicted relevance to lowest predicted relevance), with the goal of helping users to find relevant items more easily or making them consume more items. In this case, implicit feedback (behavior) is used to make inferences about concepts that normally can only be measured through explicit feedback (preferences).
We encourage authors to submit original research articles, case studies, reviews, theoretical and critical perspectives, and viewpoint articles within the domain of HCI on topics including but not limited to:
- Deriving metrics for measuring UX from qualitative research
- The interplay between user characteristics/user behavior and UX
- Combining explicit and implicit feedback for UX Research
- Empirical studies incorporating UX factors, user behavior and/or user characteristics (e.g., A/B testing)
- Explicit and implicit feedback in personalized/adaptive systems
- Implicit feedback for UX design (e.g., data-driven design)
- Explicit feedback for UX design (e.g., theory-driven design)
Dr. Bruce Ferwerda
Dr. Mark Graus
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Multimodal Technologies and Interaction is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- User Experience
- Human-Computer Interaction
- Implicit Feedback
- Explicit Feedback
- Qualitative UX Research
- Quantitative UX Research
- Adaptive Systems
- Personalized Systems