Abstract: This work is a report related to the development and assessment of a Concept Inventory to Introductory Programming (CS1) Courses. A Concept Inventory (CI) is a set of multiple-choice questions addressing specific misunderstandings and misconceptions of the students. In previous works, through instructor interviews, exam analysis, online pilot test and interviews with students, we have identified a list of 33 misconceptions related to 7 programming topics in C language. On this report, we present a CI composed of 27 multiple-choice questions in C language. Each possible answer, besides the right one, was mapped to a previously documented misconception. Future work involves the CI submission to CS1 students and the analysis of its internal consistency and educational impact.
Abstract: Emotionally annotated corpora are specially important for training machine learning models for automatic emotion identification, among other applications. However, the task of manually assigning emotions to a corpus carries a high level of subjectivity. In this technical report, we describe the annotation tools and methodology we used for dealing with this challenge when building an emotionally annotated corpus of investor tweets.
Abstract: Computational ontologies refer to formal representation models that characterize domain concepts. These artifacts are relevant to shape the meanings of data in an explicit way for humans and machines. The study of socio-enactive systems demands the understanding of human actions and the adequate system response in a cyclical interaction. Ontologies can play a key role in the development of socio-enactive systems by providing meaning to data entering and leaving the systems. However, this research field still lacks thorough literature studies. This technical report presents the results achieved by a research working group to further develop methods for ontology engineering in the context of socio-enactive systems. We present a literature review, technical solutions, in addition to conceptual and practical outcomes. Our findings include a preliminary modeling of concepts involved in socio-enactive systems, and a software architecture that allows ontology-based interpretation of several types of data. This research has been developed in the socio-enactive systems project, a FAPESP’s thematic project (grant #2015/16528-0).
Abstract: This technical report presents the preliminary results from the work group “GT Hospital”, a subgroup from the Socio-enactive Systems research group. GT Hospital will explore the “socio-enactive” concept within the context of a hospital for craniofacial rehabilitation. In this first year of project, this group has explored the scenario with the lens of Organizational Semiotics via DSC (Socially Aware Design) system; developed preliminary products for proof of concept and a communication protocol. This research is supported by FAPESP, process #2015/165280.
Abstract: This technical report presents preliminary results regarding the museum research scenario developed during the first year of the Socioenactive Systems project. In this report, we first introduce the research scenario, with the research goals and methodology. Then, we present a preliminary literature review by looking at the intersections between the concepts of enactive systems, interactive art and universal design. Next, we show our preliminary results, which include two exploratory artifacts, as well as research projects and publications associated with the research scenario. Lastly, we ponder on how our efforts during this first year are aligned with the project goals, and we also present future steps for the following year.
Resumo: This work is a partial report of the multiannual FAPESP’s thematic project “Socio-Enactive Systems: Investigating New Dimensions in the Design of Interaction Mediated by Information and Communication Technologies”. Specifically, on this report we focus on the study, exploration and assessment of socio-enactive solutions in the educational environment. The methodology used was the bottom-up approach: initially we analyzed the related literature; then we created high-level socio-enactive work scenarios (e.g. inside or outside the classroom, considering K12 or undergraduate students, etc.); then we defined and expanded a more specific work scenario (children in the classroom environment). Finally we created a MVP (Minimum Viable Product) for the work scenario, developing and implementing a prototype through the MakeBlock platform (an arduino based robot vehicle), using Scratch as programming language. In the work scenario we propose the creation of an environment where children must use concepts of logic and computational thinking to position themselves on a stage in order to predict the robot’s movement patterns. The goal is enable the kids, through their own movements, to guide the robot to a predefined location at the center of the stage. Proof of concept experiments indicate the need for prototype adjustments and adaptations. Next steps include the design and performance of workshops with the children, aiming at retrieving inloco information that will support further development of socio-enactive educational systems.
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