Examinando por Autor "Cechinel, Cristian"

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    Ítem
    A Learning Analytics Framework to Analyze Corporal Postures in Students Presentations
    (MDPI, 2021) Vieira, Felipe; Cechinel, Cristian; Ramos, Vinicius; Riquelme, Fabián; Noel, Rene; Villarroel, Rodolfo; Cornide-Reyes, Hector; Munoz, Roberto
    Communicating in social and public environments are considered professional skills that can strongly influence career development. Therefore, it is important to proper train and evaluate students in this kind of abilities so that they can better interact in their professional relationships, during the resolution of problems, negotiations and conflict management. This is a complex problem as it involves corporal analysis and the assessment of aspects that until recently were almost impossible to quantitatively measure. Nowadays, a number of new technologies and sensors have being developed for the capture of different kinds of contextual and personal information, but these technologies were not yet fully integrated inside learning settings. In this context, this paper presents a framework to facilitate the analysis and detection of patterns of students in oral presentations. Four steps are proposed for the given framework: Data collection, Statistical Analysis, Clustering, and Sequential Pattern Mining. Data Collection step is responsible for the collection of students interactions during presentations and the arrangement of data for further analysis. Statistical Analysis provides a general understanding of the data collected by showing the differences and similarities of the presentations along the semester. The Clustering stage segments students into groups according to well-defined attributes helping to observe different corporal patterns of the students. Finally, Sequential Pattern Mining step complements the previous stages allowing the identification of sequential patterns of postures in the different groups. The framework was tested in a case study with data collected from 222 freshman students of Computer Engineering (CE) course at three different times during two different years. The analysis made it possible to segment the presenters into three distinct groups according to their corporal postures. The statistical analysis helped to assess how the postures of the students evolved throughout each year. The sequential pattern mining provided a complementary perspective for data evaluation and helped to observe the most frequent postural sequences of the students. Results show the framework could be used as a guidance to provide students automated feedback throughout their presentations and can serve as background information for future comparisons of students presentations from different undergraduate courses.
  • Miniatura
    Ítem
    Can Analytics of Speaking Time Serve as Indicators of Effective Team Communication and Collaboration?
    (ACM, 2021) Salinas, Omar; Riquelme, Fabian; Muñoz, Roberto; Cechinel, Cristian; Martinez, Roberto; Monsalves, Diego
    People with effective teamwork skills, such as collaboration or leadership, are highly demanded in the workplace. In turn, educational providers have adopted active learning methodologies, such as collaborative problem-solving. However, the objective evaluation of collaboration at scale still is a challenge. This paper explores the relationship between quantitative measures obtained from automated transcriptions of speech and qualitative indicators of effective collaboration. An omnidirectional microphone and an artificial intelligence algorithm were used to collect speaking data from 20 triads of students discussing and building a concept map. The study focused on validating the potential value of speech recording devices to quantify the dynamics of communication networks by comparing quantitative metrics obtained from them with an established rating scheme for measuring the extent of collaboration. Results showed a relationship between the standard deviations of the speaking times of the participants in each group and the evaluation obtained from the qualitative rubrics of communication and interpersonal relationships. Thus, the extent to which all group members contribute to the discourse can potentially serve as an indicator of effective group work.
  • Miniatura
    Ítem
    Key Skills to Work With Agile Frameworks in Software Engineering: Chilean Perspectives
    (IEEE, 2021) Cornide-Reyes, Héctor; Riquelme, Fabián; Noel, Rene; Villarroel, Rodolfo; Cechinel, Cristian
    Agile frameworks continue to provide positive evidence regarding the benefits of their use in the software products. Since these methods develop professional skills in those who practice them, their knowledge and use will acquire greater demand in areas other than software development. For this reason, it is essential to recognize the key skills for agile team building. The goal of this paper is to identify the agile professional skills that the Chilean industry considers key to conform high-performance agile teams. A survey was applied to agile community professionals in Chile to validate the results of previous work and to identify relevant information regarding learning processes, techniques, and tools for working with agile frameworks. The results allowed to establish three key skills for high-performance teams with their respective levels of achievement.