Christos Katsanos

HC
h-index19
3papers
23citations
Novelty28%
AI Score17

3 Papers

5.6HCMar 20, 2019
Effect of Personality Traits on UX Evaluation Metrics: A Study on Usability Issues, Valence-Arousal and Skin Conductance

Alexandros Liapis, Christos Katsanos, Michalis Xenos et al.

Personality affect the way someone feels or acts. This paper examines the effect of personality traits, as operationalized by the Big-five questionnaire, on the number, type, and severity of the identified usability issues, physiological signals (skin conductance), and subjective emotional ratings (valence-arousal).Twenty-four users interacted with a web service and then participated in a retrospective thinking aloud session. Results revealed that the number of usability issues is significantly affected by the Openness trait. Emotional Stability significantly affects the type of reported usability issues. Problem severity is not affected by any trait. Valence ratings are significantly affected by Conscientiousness, whereas Agreeableness, Emotional Stability and Openness significantly affect arousal ratings. Finally, Openness has a significant effect on the number of detected peaks in user's skin conductance.

5.4HCFeb 12, 2018
Don't Leave Me Alone: Retrospective Think Aloud supported by Real-time Monitoring of Participant's Physiology

Alexandros Liapis, Christos Katsanos, Michalis Xenos

Think aloud protocols are widely applied in user experience studies. In this paper, the effect of two different applications of the Retrospective Think Aloud (RTA) protocol on the number of user-reported usability issues is examined. To this end, 30 users were asked to use the National Cadastre and Mapping Agency web application and complete a set of tasks, such as measuring the land area of a square in their hometown. The order of tasks was randomized per participant. Next, participants were involved in RTA sessions. Each participant was involved in two different RTA modes: (a) the strict guidance, in which the facilitator stayed in the background and prompted participants to keep thinking aloud based on his judgement and experience, and (b) the physiology-supported interventions, in which the facilitator intervened based on real-time monitoring of user's physiological signals. During each session, three participant's physiological signals were recorded: skin conductance, skin temperature and blood volume pulse. Participants were also asked to provide valence-arousal ratings for each self-reported usability issue. Analysis of the collected data showed that participants in the physiology-supported RTA mode reported significantly more usability issues. No significant effect of the RTA mode was found on the va-lence-arousal ratings for the reported usability issues. Participants' physiological signals during the RTA sessions did not also differ significantly between the two modes.

5.4HCFeb 6, 2018
Tool-mediated HCI Modeling Instruction in a Campus_based Software Quality Course

Christos Katsanos, Michalis Xenos, Nikolaos Tselios

The Keystroke Level Model (KLM) and Fitts Law constitute core teaching subjects in most HCI courses, as well as many courses on software design and evaluation. The KLM Form Analyzer (KLM_FA) has been introduced as a practitioner s tool to facilitate web form design and evaluation, based on these established HCI predictive models. It was also hypothesized that KLMFA can also be used for educational purposes, since it provides step by step tracing of the KLM modeling for any web form filling task, according to various interaction strategies or users characteristics. In our previous work, we found that KLM-FA supports teaching and learning of HCI modeling in the context of distance education. This paper reports a study investigating the learning effectiveness of KLM-FA in the context of campus-based higher education. Students of a software quality course completed a knowledge test after the lecture- based instruction (pre-test condition) and after being involved in a KLMFA mediated learning activity (post-test condition). They also provided posttest ratings for their educational experience and the tool s usability. Results showed that KLM-FA can significantly improve learning of the HCI modeling. In addition, participating students rated their perceived educational experience as very satisfactory and the perceived usability of KLM-FA as good to excellent.