2023
Authors
Pinho, D; Aguiar, A; Amaral, V;
Publication
JOURNAL OF COMPUTER LANGUAGES
Abstract
Context: Low-code development is a concept whose presence has grown both in academia and the software industry and is discussed alongside others, such as model-driven engineering and domain-specific languages. Usability is an important concept in low-code contexts since users of these tools often lack a background in programming. Grey literature articles have also stated that low-code tools have high usability.Objective: This paper examines the current literature about low-code and no-code to discover more about them and their relationship with usability, particularly its quality, which factors are the most relevant, and how users view these tools. This focus on usability aims to provide a different point of view from other works on low-code.Method: We performed a systematic literature review based on a formal protocol for this study. The search protocol returned a total of 207 peer-review articles across five databases, which was supplemented with a snowballing process. These were filtered using inclusion and exclusion criteria, resulting in 38 relevant articles that were analysed, synthesised and reported.Conclusion: Despite growing interest and a strong enterprise presence in academia, we did not find a formal definition of low-code, although common characteristics have been specified. We found that users have a heightened awareness of usability regarding low-code tools, with some authors performing feasibility studies on their implementations or listing factors that influence the user experience in a given tool. Researchers are considering usability factors unconsciously, and the low-code field would grow if research on usability increased. This paper also suggests a definition for low-code development.
2023
Authors
Ferreira Ribeiro, JE; Silva, JG; Aguiar, A;
Publication
CoRR
Abstract
2023
Authors
Aguiar, A; Soeiro, A; Jacklin-Jarvis, C; Foster, T;
Publication
EDULEARN Proceedings - EDULEARN23 Proceedings
Abstract
2023
Authors
Fernandes, S; Aguiar, A; Restivo, A;
Publication
CoRR
Abstract
2023
Authors
Morgado, L; Coelho, A; Beck, D; Gutl, C; Cassola, F; Baptista, R; van Zeller, M; Pedrosa, D; Cruzeiro, T; Cota, D; Grilo, R; Schlemmer, E;
Publication
SUSTAINABILITY
Abstract
The objective of this work was to support the sustainable deployment of immersive learning environments, which face varied obstacles, including the lack of support infrastructures for active learning pedagogies. Sustainability from the perspective of the integration of these environments in educational practice entails situational awareness, workload, and the informed assessment ability of participants, which must be supported for such activities to be employed in a widespread manner. We have approached this wicked problem using the Design Science Research paradigm and produced the Inven!RA software architecture. This novel result constitutes a solution for developing software platforms to enable the sustainable deployment of immersive learning environments. The Inven!RA architecture is presented alongside four demonstration scenarios employed in its evaluation, providing a means for the situational awareness of immersive learning activities in support of pedagogic decision making.
2023
Authors
Rodrigues, N; Sousa, A; Reis, LP; Coelho, A;
Publication
ROBOT2022: FIFTH IBERIAN ROBOTICS CONFERENCE: ADVANCES IN ROBOTICS, VOL 2
Abstract
Intelligent wheelchairs aim to improve mobility limitations by providing ingenious mechanisms to control and move the chair. This paper aims to enhance the autonomy level of intelligent wheelchair navigation by applying reinforcement learning algorithms to move the chair to the desired location. Also, as a second objective, add one more chair and move both chairs in pairs to promote group social activities. The experimental setup is based on a simulated environment using gazebo and ROS where a leader chair moves towards a goal, and the follower chair should navigate near the leader chair. The collected metrics (time to complete the task and the trajectories of the chairs) demonstrated that Deep Q-Network (DQN) achieved better results than the Q-Learning algorithm by being the unique algorithm to accomplish the pair navigation behaviour between two chairs.
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