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Item Escolas como organizações que aprendem: a autoavaliação como moduladora da aprendizagem da escola(Instituto Federal de Educação Ciência e Tecnologia de Alagoas, 2021-08-26) Moura, Elton Oliveira de; Bispo, Marcelo de Souza; http://lattes.cnpq.br/0046249640629512; Silva, Anielson Barbosa da; http://lattes.cnpq.br/3405428972303042; Guerra, Maria das Graças Gonçalves Vieira; http://lattes.cnpq.br/7195833831322050; Vieira, Almir Martins; http://lattes.cnpq.br/4298642111341453; Brito, Simone Magalhães,; http://lattes.cnpq.br/1833114674355841This thesis dissertation aimed to analyze how the practice of school self-assessment acts as a modulating element of school learning. The onto-epistemology of the Theories of Practice was adopted from the sociological perspective of Learning Organizations. The argument of this thesis is based on two assumptions: (1) the school is an organization that learns from its daily practices, and (2) that self-assessment can be a way to the development of school learning. The empirical study had a first exploratory phase, where some specialists and professionals in educational management were interviewed to foster reflections on the evaluation and learning processes of the school. In the second moment, empirical research was conducted in a public elementary and high school in the city of João Pessoa (PB) in northeastern Brazil. Data collection was driven through online interviews with participants from the school community, remote observations, and documents. Because the research was conducted during the Covid-19 pandemic, digital technologies such as video conferencing and messaging applications mediated the data collection process. The data analysis process adopted the framework proposed by Bispo (2015) to analyze research based on practice. The study's main results indicate that school learning occurs from three practices: self-assessment learning, engagement in practice, and translating policies and context. In addition, it was possible to verify that selfassessment acts as a modulating element of school learning to the point that it balances the relationship between concept ("what") and instrument ("how"). School self-assessment as a modulator of learning is based on the idea that reflection on the practices allows the school to direct more appropriate actions to its specific needs. This research contributes to approximate fields of Administration and Education to develop an expanded understanding of studies on school management and educational management. Also, in building the development of an alternative approach to the study of Schools as Learning Organizations from social learning. Last, in thinking possibilities of evaluation less classificatory, less focused on accountability, and more focused on school learning.Item Estimativa de esforço em story point a partir do texto da user story com aprendizagem de máquina e LLM(UNIVERSIDADE FEDERAL DE CAMPINA GRANDE - UFCG, 2025-09-16) Néo, Giseldo da Silva; Moura, José Antão Beltrão Moura; http://lattes.cnpq.br/3572375884177951; Morais, Fábio Jorge Almeida; http://lattes.cnpq.br/0987042606840444; Costa, Evandro de Barros; https://orcid.org/0000-0003-4663-8715; http://lattes.cnpq.br/5760364940162939; Vieira, Thales Miranda de Almeida; https://orcid.org/0000-0001-7775-5258; http://lattes.cnpq.br/8181104476035846; Bezerra, Tarcio Rodrigues; http://lattes.cnpq.br/5285201763618981Effort estimation in agile software projects remains a persistent challenge in the industry, especially when using textual artifacts such as User Stories to predict Story Points. This thesis investigates the use of Natural Language Processing (NLP) and Machine Learning (ML) techniques in effort prediction, considering the textual description of User Stories as the main source of information. Initially, a systematic literature review identified prevalent techniques for the said estimation, such as Term Frequency – Inverse Document Frequency (TF-IDF) combined with Support Vector Machine (SVM), and highlighted gaps related to the use of readability, sentiment, and subjectivity attributes, as well as the sacant of application of Large-Scale Language Models (LLMs) for this task. The research proposed and evaluated three main approaches: (i) the Neo Legibility Effort Model, which uses attributes automatically extracted from User Story text to predict effort; (ii) the Neo User Story Tutor, an LLM-based application that suggests improvements in User Story writing to improve estimation accuracy; and (iii) the Neo LLM Predictor, which uses LLMs to directly estimate Story Points using different strategies (few-shot, zero-shot, and fine-tuning). To support the experiments a new dataset collected from real projects hosted on GitLab, was built (aka NeoDataset). The proposed models were evaluated using metrics such as MAE and compared with established baselines in the literature. The results demonstrated that both readability attributes and LLMs can significantly contribute to improving effort estimates in agile environments. The thesis presents evidence that it is possible to increase estimate accuracy through the combination of textual analysis and machine learning, in addition to highlighting the relevance of linguistic aspects in the quality of User Stories.Item Governança corporativa na perspectiva do conselho de administração e desempenho das empresas: avaliação do colegiado, composição da estrutura e comitês financeiros(FACULDADE FUCAPE - FUCAPE, 2024-12-16) Santos, José Éliton dos; Cruz, Poliano Bastos da; https://orcid.org/0000-0002-0074-7193; http://lattes.cnpq.br/5544566158794849; Cruz, Poliano Bastos da; https://orcid.org/0000-0002-0074-7193; http://lattes.cnpq.br/4414322289653973; Novaes, Paulo Victor Gomes; http://lattes.cnpq.br/0361983404159254; Santana Júnior, Jorge Luiz de; https://orcid.org/0000-0001-7423-2566; http://lattes.cnpq.br/7935012360141664; Marques, Vagner Antonio; https://orcid.org/0000-0001-7210-4552; http://lattes.cnpq.br/8704491263853222; Viana Junior, Dante Baiardo Cavalcante; http://lattes.cnpq.br/8595633927891889This thesis is structured into three articles. The technical article in chapter 2 presents a structure for developing the performance assessment process for boards of directors based on the assumption that companies are not isolated agents in the market and need to define the materiality of topics based on consultation with their main stakeholders. The research aims to contribute to entities in the development of board evaluation processes and encourage companies to consider the efficiency of boards of directors as important for company performance, given that they must be committed to generating value and business continuity. The second article in chapter 3 uses qualitative comparative analysis to verify which combinations of board characteristics contribute or not to high business performance. The results showed that there are no isolated characteristics of boards of directors that cause high (low) performance, but rather that there are several complex combinations that cause both high and low performance. Thus, the evidence shows that boards should be shaped according to the characteristics of companies and do not always need to follow strict regulatory standards, since certain characteristics can be important or irrelevant to business performance at the same time. The third article in chapter 4 analyzes the relationship between the financial committee and investment efficiency. The results showed that the existence of a financial committee has a direct impact on investment efficiency, in addition to maximizing investment efficiency when related to corporate governance characteristics. Thus, the results demonstrate that the formation of financial committees is relevant to maximize the quality and adequacy of investment levels.