2018 - Present
OSIS (Open Student Information System) is a system to manage the core business of higher education institutions. It is free and open source under the terms of GPL v3 public license.
The tasks assigned to the role of programmer analyst are:
2012 - 2018
The tasks assigned to the role of assistant were:
June 2013 -Show Abstract
Many factors contribute to ensuring User eXperience (UX)of Graphical User Interfaces, such as, but not limited to: usability, fun, engagement, subjective satisfaction. Aesthetics is a potential element that could also significantly contribute to this user experience. Although aesthetics have been extensively discussed, there is a need to rely on a sound, empirically validated methodology in order to properly evaluate how aesthetics could be measured, namely through metrics. Two main issues need to be addressed: the representativeness and the relevance of aesthetics metrics. In order to address these challenges, this paper introduces a methodology for metric-based evaluation of a graphical user interface of any type. This methodology is based on an underlying model that captures aesthetics aspects and related metrics, a method for computing them based on the underlying model, and software that supports enacting this method on any type of graphical user interface.
June 2013 -Show Abstract
The recent popularization of touch screen devices have brought to users the opportunity to use different devices to interact and to share content, while current advances in the mobile context brought new capabilities for systems to run on many devices while maintaining the system’s consistency. Those two factors combined pose new opportunities for researchers to explore how users can collaborate using an heterogeneous set of devices, that can include large tabletops, smartphones or e-readers. This paper starts the discussion on four challenges related to this context.
May 2014 -Show Abstract
The graphical user interface (GUI) of an interactive system is nowadays the most frequently used interaction modality. While the contents are of high importance, the Look and Feel is an equally essential factor determining the GUI quality that is impacted by several determinants such as but not limited to aesthetics, pleasurability, fun, etc. Therefore, GUIs aesthetics is a potential element to focus on in order to facilitate communication between device and user. On that basis, one question that comes up is: “Is it possible to evaluate the quality of a GUI by estimating its aesthetics through a series of measurable geometric metrics?”. This paper suggests possible directions to address the previous question by, first, introducing a simplifying model of GUIs aesthetics that captures aesthetics aspects and regions-related metrics. In a second phase, a methodology for the evaluation of GUIs aesthetics is deﬁned based on the underlying model. The paper finally puts forwards a model-based implementation of the aforementioned methodology in the form of a web service tool for metrics-based evaluation of GUIs and discuss the results of a survey on users aesthetics perceptions.
May 2014 -Show Abstract
An effective User Interface (UI) is a key success factor for interactive systems. Hence, particular attention should be paid to the UI design during the Requirement Engineering process (RE). Several RE tools have been proposed in order to support the UI design. However, these tools have limitations in terms of requirements completeness, requirements quality analysis and UI generation from requirements. In this paper, we present a new RE toolkit called QualIHM, that deals with the limitations of the existing RE. The toolkit supports the description of requirements in different formats. In addition, QualiHM facilitates the UI design by transforming requirement formats from one to another, generating the UI code and providing feedback about the aesthetic of the UI.
July 2016 -Show Abstract
'How to assess user interface aesthetics?' remains a question faced by many user interface researchers and designers during the user interface development life cycle since aesthetics positively influence usability, user experience, pleasureability, and trust. Visual techniques borrowed from visual design suggest that the graphical user interface layout could be assessed by aesthetic metrics such as balance, symmetry, proportion, regularity, and simplicity, to name a few. Whereas different formulas exist for computing each aesthetic metric and different interpretations to sum up their results, no consensus exists today on how to consistently evaluate these metrics in a way that is aligned with human judgement, which is intrinsically subjective. In order to address the challenging alignment of human subjectivity with machine objectivity, this paper reports on an experiment comparing the results issued from the inter-subjectivity of judgment of fifteen participants evaluating four main aesthetic metrics on a sample of ten graphical user interfaces and the values of these metrics calculated semi-automatically by a web-based application. The experiment suggests that some metrics, e.g. symmetry, proportion, simplicity, as computed from the formula are actually positively correlated with human judgment, while some other metrics, such as balance, are surprisingly not correlated with the formula computed, thus indicating that another formula or another interpretation should be determined. Therefore, a new formula for computing balance is defined that decomposes balance into horizontal and vertical balances which re-establish a correlation. This paper then provides some new insights on how to rely on these aesthetic metrics and other related metrics, whether they are interpreted manually or computed automatically.
June 2019 -Show Abstract
We introduce AB4Web, a web-based engine that implements a balanced randomized version of the multivariate A/B testing, specifically designed for practitioners to readily compare end-users' preferences for user interface alternatives, such as menu layouts, widgets, controls, forms, or visual input commands. AB4Web automatically generates a balanced set of randomized pairs from a pool of user interface design alternatives, presents them to participants, collects their preferences, and reports results from the perspective of four quantitative measures: the number of presentations, the preference percentage, the latent score of preference, and the matrix of preferences. In this paper, we exemplify the AB4Web tester with a user study for which N=108 participants expressed their preferences regarding the visual design of 49 distinct graphical adaptive menus, with a total number of 5,400 preference votes. We compare the results obtained from our quantitative measures with four alternative methods: Condorcet, de Borda count starting at one and zero, and the Dowdall scoring system. We plan to release AB4Web as a public tool for practitioners to create their own A/B testing experiments.
2012 - 2017
2007 - 2012