Cookies Policy
The website need some cookies and similar means to function. If you permit us, we will use those means to collect data on your visits for aggregated statistics to improve our service. Find out More
Accept Reject
  • Menu
About

About

I hold a PhD on Computer Science and 'im an Assistant Professor of Computer Science at the Polytechnic Institute of Porto. I'm also a researcher in the field of e-learning interoperability and programming languages learning at the Center for Research in Advanced Computing Systems (CRACS) research group of INESC TEC Porto. I'm also the author of 5 books regarding Android development and almost 100 scientific publications focused on computer science education.

Interest
Topics
Details

Details

  • Name

    Ricardo Queirós
  • Cluster

    Computer Science
  • Role

    Senior Researcher
  • Since

    01st January 2012
001
Publications

2020

Authoring Game-Based Programming Challenges to Improve Students’ Motivation

Authors
Paiva, JC; Leal, JP; Queirós, R;

Publication
Advances in Intelligent Systems and Computing

Abstract
One of the great challenges in programming education is to keep students motivated while working on their programming assignments. Of the techniques proposed in the literature to engage students, gamification is arguably the most widely spread and effective method. Nevertheless, gamification is not a panacea and can be harmful to students. Challenges comprising intrinsic motivators of games, such as graphical feedback and game-thinking, are more prone to have longterm positive effects on students, but those are typically complex to create or adapt to slightly distinct contexts. This paper presents Asura, a game-based programming assessment environment providing means to minimize the hurdle of building game challenges. These challenges invite the student to code a Software Agent to solve a certain problem, in a way that can defeat every opponent. Moreover, the experiment conducted to assess the difficulty of authoring Asura challenges is described. © 2020, Springer Nature Switzerland AG.

2019

PROud-A Gamification Framework Based on Programming Exercises Usage Data

Authors
Queiros, R;

Publication
INFORMATION

Abstract
Solving programming exercises is the best way to promote practice in computer programming courses and, hence, to learn a programming language. Meanwhile, programming courses continue to have an high rate of failures and dropouts. The main reasons are related with the inherent domain complexity, the teaching methodologies, and the absence of automatic systems with features such as intelligent authoring, profile-based exercise sequencing, content adaptation, and automatic evaluation on the student's resolution. At the same time, gamification is being used as an approach to engage learners' motivations. Despite its success, its implementation is still complex and based on ad-hoc and proprietary solutions. This paper presents PROud as a framework to inject gamification features in computer programming learning environments based on the usage data from programming exercises. This data can be divided into two categories: generic data produced by the learning environmentsuch as, the number of attempts and the duration that the students took to solve a specific exerciseor code-specific data produced by the assessment toolsuch as, code size, use memory, or keyword detection. The data is gathered in cloud storage and can be consumed by the learning environment through the use of a client library that communicates with the server through an established Application Programming Interface (API). With the fetched data, the learning environment can generate new gamification assets (e.g., leaderboards, quests, levels) or enrich content adaptations and recommendations in the inner components such as the sequencing tools. The framework is evaluated on its usefulness in the creation of a gamification asset to present dynamic statistics on specific exercises.

2018

CSS Preprocessing: Tools and Automation Techniques

Authors
Queirós, R;

Publication
Information

Abstract
Cascading Style Sheets (CSS) is a W3C specification for a style sheet language used for describing the presentation of a document written in a markup language, more precisely, for styling Web documents. However, in the last few years, the landscape for CSS development has changed dramatically with the appearance of several languages and tools aiming to help developers build clean, modular and performance-aware CSS. These new approaches give developers mechanisms to preprocess CSS rules through the use of programming constructs, defined as CSS preprocessors, with the ultimate goal to bring those missing constructs to the CSS realm and to foster stylesheets structured programming. At the same time, a new set of tools appeared, defined as postprocessors, for extension and automation purposes covering a broad set of features ranging from identifying unused and duplicate code to applying vendor prefixes. With all these tools and techniques in hands, developers need to provide a consistent workflow to foster CSS modular coding. This paper aims to present an introductory survey on the CSS processors. The survey gathers information on a specific set of processors, categorizes them and compares their features regarding a set of predefined criteria such as: maturity, coverage and performance. Finally, we propose a basic set of best practices in order to setup a simple and pragmatic styling code workflow. © 2018 by the authors.

2018

Fostering Students-Driven Learning of Computer Programming with an Ensemble of E-Learning Tools

Authors
Queirós, R; Leal, JP;

Publication
Trends and Advances in Information Systems and Technologies - Volume 2 [WorldCIST'18, Naples, Italy, March 27-29, 2018]

Abstract
Learning through practice is crucial to acquire a complex skill. Nevertheless, learning is only effective if students have at their disposal a wide range of exercises that cover all the course syllabus and if their solutions are promptly evaluated and given the appropriate feedback. Currently the teaching-learning process in complex domains, such as computer programming, is characterized by an extensive curricula and a high enrolment of students. This poses a great workload for faculty and teaching assistants responsible for the creation, delivering and assessment of student exercises. In order to address these issues, we created an e-learning framework - called Ensemble - as a conceptual tool to organize and facilitate technical interoperability among systems and services in domains that use complex evaluation. These domains need a diversity of tools, from the environments where exercises are solved, to automatic evaluators providing feedback on the attempts of students, not forgetting the authoring, management and sequencing of exercises. This paper presents and analyzes the use of Ensemble for managing the teaching-learning process in an introductory programming course at ESEIG - a school of the Polytechnic of Porto. An experiment was conducted to validate a set of hypotheses regarding the expected gains: increase in number of solved exercises, increase class attendance, improve final grades. They support the conclusion that the use of this e-learning framework for the practice-based learning has a positive impact on the acquisition of complex skills, such as computer programming. © Springer International Publishing AG, part of Springer Nature 2018.

2018

Kaang: A RESTful API Generator for the Modern Web

Authors
Queirós, R;

Publication
7th Symposium on Languages, Applications and Technologies, SLATE 2018, June 21-22, 2018, Guimaraes, Portugal

Abstract
Technology is constantly evolving, as a result, users have become more demanding and the applications more complex. In the realm of Web development, JavaScript is growing in a surprising way, already leaving the boundaries of the browser, mainly due to the advent of Node.js. In fact, JavaScript is constantly being reinvented and, from the ES2015 version, began to include the OO concepts typically found in other programming languages. With Web access being mostly made by mobile devices, developers face now performance challenges and need to perform a plethora of tasks that weren’t necessary a decade ago, such as managing dependencies, bundling files, minifying code, optimizing images and others. Many of these tasks can be achieved by using the right tools for the job. However, developers not only have to know those tools, but they also must know how to access and operate them. This process can be tedious, confusing, time-consuming and error-prone. In this paper, we present Kaang, an automatic generator of RESTFul Web applications. The ultimate goal of Kaang is to minimize the impact of creating a RESTFul service by automating all its workflow (e.g., files structuring, boilerplate code generation, dependencies management, and task building). This kind of generators will benefit two types of users: will help novice developers to decrease their learning curve while facing the new frameworks and libraries commonly found in the modern Web and speed up the work of expert developers avoiding all the repetitive and bureaucratic work. At the same time, Kaang promotes the good development principles by adding automatic testing and documentation generation. For this accomplishment, Kaang generates the main API content based on the user’s input and a set of templates which will help developers to manage and test routes, define resources, store data models and others. In order to provide an addition level of confidence to the generator’s end-users, the generator will be integrated on Travis CI and published on both the npmjs and Yeoman registries. © Ricardo Queirós.