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Publicações

Publicações por HumanISE

2020

Managing learning in environments where students move: a panorama of problems and contributions

Autores
Lima, Claudio Cleverson de; Schlemmer, Eliane; Morgado, Leonel;

Publicação
EJML 2020 - 5.º Encontro sobre Jogos e Mobile Learning

Abstract
Educational activities where students do not stay at a fixed, predetermined location, has been growing in research output. The pedagogies and processes for these environments where students move are typically less documented than those of traditional classrooms. We have surveyed the areas of problems addressed by the literature on the field, and the areas of its contributions, to build a panorama of the research foci for managing learning in environments where students move. This was done by means of an exploratory literature review, followed by thematic analysis and triangulation. We established that research focuses on problems and contributions dealing with the design, creation, and deployment of these learning activities, and to a lesser degree, on problems and contributions dealing with the potential of use of technology. However, there is a lack of research focusing on other areas relevant to more widespread implementation across the educational system, namely structural, logistic, and assessment problems and contributions. This points towards a need to develop research in these areas, in order to contribute to more grounded and successful efforts to implement learning activities in environments where students move.

2020

Factors that Influence the Use of Educational Software in Mathematics Teaching

Autores
Nunes, PS; Nascimento, MM; Catarino, P; Martins, P;

Publicação
REICE-REVISTA IBEROAMERICANA SOBRE CALIDAD EFICACIA Y CAMBIO EN EDUCACION

Abstract
This paper aims to explore and describe fundamental factors that influence the knowledge and use of Information and Communication Technologies (ICT), in particular of Educational Software (ES) as a tool, by teachers who teach mathematics in any portuguese teaching cycle. The adopted method has a descriptive and exploratory nature, focusing on a quantitative paradigm. The study participants were 96 teachers who teach mathematics, from various elementary and secondary schools, from different regions of Portugal, as well as from other countries where the portuguese curriculum is inserted. The questionnaire, the chi-square independence test and Cramer's V test were used as instruments. Data analysis was performed using SPSS (version 25) and Excel (Office 2016). The results suggest that the age, gender and length of service of mathematics teachers may be factors that influence the knowledge and use of Kahoot ES and that having training may be an essential condition for the use of Modellus and Scratch ESs. We did not find any relationship of dependence between having training and the use of the rule and compass ES by the respondents.

2020

Innovative Technologies and Learning - Third International Conference, ICITL 2020, Porto, Portugal, November 23-25, 2020, Proceedings

Autores
Huang, TC; Wu, TT; Barroso, J; Sandnes, FE; Martins, P; Huang, YM;

Publicação
ICITL

Abstract

2020

Using Artificial Intelligence to Predict Academic Performance

Autores
Reis, A; Rocha, T; Martins, P; Barroso, J;

Publicação
HCI International 2020 - Late Breaking Papers: Multimodality and Intelligence - 22nd HCI International Conference, HCII 2020, Copenhagen, Denmark, July 19-24, 2020, Proceedings

Abstract
The academic performance of a higher education student can be affected by several factors and in most cases Higher Education Institutions (HEI) have programs to intervene, prevent failure or students dropping out. These include student tutoring, mentoring, recovery classes, summer school, etc. Being able to identify the borderline cases is extremely important for planning and intervening in time. This position paper reports on an ongoing project, being developed at the University of Trás-os-Montes e Alto Douro (UTAD), which uses the students’ data and artificial intelligence algorithms to create models and predict the performance of students and classes. The main objective of the IA.EDU project is to research the usage of data, artificial intelligence and data science to create artificial intelligence solutions, including models and applications, to provide predictive information that can contribute to the increase in students’ academic success and a reduction in the dropout rate, by making it possible to act proactively with the students at risk, course directors and course designers. © 2020, Springer Nature Switzerland AG.

2020

The Use of Kahoot, GeoGebra and Texas Ti-Nspire Educational Software's in the Teaching of Geometry and Measurement

Autores
Nunes, PS; Martins, P; Catarino, P;

Publicação
Technology and Innovation in Learning, Teaching and Education - Second International Conference, TECH-EDU 2020, Vila Real, Portugal, December 2-4, 2020, Proceedings, 3

Abstract
The use of Educational Software (ES) in education has become essential for teachers and students. On the one hand, the effectiveness of its use may facilitate the acquisition of learning and on the other hand, it may enable a better transmission of the contents. In this sense, it is necessary to provide teachers with tools that allow them to develop successful pedagogical actions with appealing and innovative resources, capable of stimulating creativity and motivating students for learning. The aim of this study is to ascertain the knowledge and the use by teachers of ES Kahoot, GeoGebra and Texas Ti-Nspire, in what type of content, activities and what is the impact of their use in the teaching of Geometry and Measurement (GM), whether in teaching practice of teachers, or in the learning of students. The adopted method has a qualitative nature, with characteristics of a case study. Fourteen teachers who teach Mathematics at various schools in Portugal participated. Two questionnaires and a challenge that consisted of the elaboration of tasks were used as instruments. Data analysis was performed using Excel (Office 2016) and content analysis of the answers given, and the tasks developed. The results suggest that of the three ES, Kahoot was the most unknown and was the most chosen by teachers to develop different GM content. The reasons are also described as to why these ES may cause an improvement in the teaching practices of teachers, as well as motivation and student learning. © 2021, Springer Nature Switzerland AG.

2020

Preface

Autores
Huang, YM; Barroso, J; Sandnes, FE; Huang, TC; Martins, P; Wu, TT;

Publicação
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Abstract

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