Submitted by Maria Medeiros (maria.dilva1@ufcg.edu.br) on 2018-06-04T15:11:46Z No. of bitstreams: 1 RANILSON OSCAR ARAÚJO PAIVA - TESE (PPGCC) 2017.pdf: 11842712 bytes, checksum: ac3058f290c36c90ab21ce1a9820b601 (MD5) / Made available in DSpace on 2018-06-04T15:11:46Z (GMT). No. of bitstreams: 1 RANILSON OSCAR ARAÚJO PAIVA - TESE (PPGCC) 2017.pdf: 11842712 bytes, checksum: ac3058f290c36c90ab21ce1a9820b601 (MD5) Previous issue date: 2017 / Vivemos uma mudança no paradigma educacional onde se busca prover educação de qualquer lugar, a qualquer momento e para qualquer pessoa, utilizando tecnologias digitais da informação e comunicação. Há um interesse global no ensino à distância, mas não há um aumento equivalente de suporte aos professores e tutores responsáveis por manter tais cursos. Essa deficiência acentua os problemas e desafios existentes na gestão de cursos a distância, pois com o tempo mais estudantes aderem ao ensino a distância, requerendo a criação de novos cursos e turmas, incrementando a quantidade de estudantes sendo sub-servidos em termos de apoio pedagógico. Isso é evidenciado pelo grande número de desistências e falhas em tais cursos, particularmente, nos MOOCs (Cursos Online Massivos e Abertos), que os estudantes justificam como falta de suporte. Esta tese propõe uma solução de autoria para guiar a tomada de decisões pedagógicas em ambientes online de aprendizagem, tendo sido aplicada em um MOOC. A proposta visa auxiliar professores e tutores (1) a descobrir situações de interesse pedagógico ocorrendo em seus cursos; (2) compreender essas situações; (3) tomar decisões para aborda-las e; (4) monitorar e avaliar o impacto da decisão tomada. As interações em tais cursos geram grande quantidade e diversidade de dados, sendo possível extrair informações pedagogicamente relevantes. Entretanto, professores e tutores não dominam a tecnologia necessária para utilizar esses dados, nem é prático ou apropriado solicitar que sejam treinados para tanto. A proposta se fundamenta na tomada de decisões informada por dados educacionais, na visualização de dados e nos sistemas de autoria para promover a cooperação entre a inteligência artificial e a inteligência humana. Realizamos dois experimentos para: (1) avaliar se o processo auxilia professores e tutores a tomar decisões pedagógicas úteis e em tempo de curso; (2) avaliar se a solução de autoria guia a tomada de decisões pedagógicas de professores e tutores. Os resultados sugerem que o processo trouxe benefícios à tomada de decisões pedagógicas e que a solução de autoria foi capaz de guiar a tomada de decisões pedagógicas em tempo de curso e que sua utilidade e facilidade foram percebidas positivamente por professores e tutores. / We are experiencing changes in the educational paradigm. There is a quest to provide education from anywhere, at any time and for anyone, using digital information and communication technologies. There is a global interest in distance learning, but there is no equivalent increase in support for teachers and tutors responsible for maintaining such courses. This difference accentuates the problems and challenges in managing distance courses once that, over time, more students join distance learning, requiring the creation of new courses and classes, increasing the number of distance students being sub-served in terms of pedagogical support. This is evidenced by the large number of dropouts and faiilures in such courses, particularly in MOOCs (Massive Open Online Courses), that students justify as lack of support. This thesis proposes an authoring solution to guide the pedagogical decision making in online learning environments, which was applied in a MOOC. The proposal aims to help teachers and tutors (1) to discover situations of pedagogical interest occurring in their courses; (2) understand these situations; (3) make decisions to address them; (4) monitor and evaluate the impact of the decision made. The interactions in such courses generate considerable quantity and diversity of data,allowing the extraction of pedagogically relevant information. However, teachers and tutors do not master the technology needed to use this data, nor is it practical or appropriate to ask them to be trained to do so. Our proposal is based on informed decision making by educational data, data visualization and authoring systems to promote cooperation between artificial intelligence and human intelligence. We conducted two experiments to: (1) evaluate whether the process helps teachers and tutors to make useful and time-course pedagogical decisions; (2) to evaluate if the authoring solution guides the pedagogical decision making of teachers and tutors. The results suggest that the process brought benefits to pedagogical decision making and that the authoring solution was able to guide the pedagogical decision making in course time and that its usefulness and ease of use were positively perceived by teachers and tutors.

University students learning object-oriented programming (OOP) encounter many complexities. This study undertook empirical research aimed at analysing learners’ interactions with the Alice visual programming environment, which seeks to engage and motivate learners to grasp concepts of OOP, whilst creating animated movies and video games. A mixed-methods approach was employed, using questionnaire surveys and interviews to investigate learners’ experiences with Alice and their understanding of OOP. Findings indicated that learners lacked problem-solving abilities; were unable to grasp programming concepts on an abstract level and spent insufficient time practicing programming exercises. Alice proved to be an effective tool in helping to address these challenges and in improving learners’ grasp of OOP. Learners found Alice to have good usability. Furthermore, test and exam results revealed a statistically significant difference between performances of learners who had been taught Alice in comparison to similar learners who were not exposed to the Alice intervention. / Computing / Information Systems / M. Sc. (Information systems)

多選題測驗試題已證明能有效地評估學生的學習成效，然而，以人為方式建立題庫是一件耗時費力的工作。藉由電腦高速運算的能力，電腦輔助產生試題系統能有效率地建置大規模的題庫，同時減少人為的干預而得以保持試題的隱密性。受惠於網路上充裕的文字資源，本研究發展一套克漏詞試題出題系統，利用既有的語料自動產生涵蓋各種不同主題的克漏詞試題。藉由分析歷屆大學入學考試的資料，系統可產生類似難度的模擬試題，並且得到出題人員在遴選測驗標的方面的規律性。在產生試題的過程中導入詞義辨析的演算法，利用詞典與selectional preference模型的輔助，分析句子中特定詞彙的語義，以擷取包含測驗編撰者所要測驗的詞義的句子，並以collocation為基礎的方法篩選誘答選項。實驗結果顯示系統可在每產生1.6道試題中，得到1道可用的試題。我們嘗試產生不同類型的試題，並將這套系統融入網路線上英文測驗的環境中，依學生的作答情形分析試題的鑑別度。 / Multiple-choice tests have proved to be an efficient tool for measuring students’ achievement. Manually constructing tests items, however, is a time- consuming and labor-intensive task. Harnessing the computing power of computers, computer-assisted item generation offers the possibility of creating large amount of items, thereby alleviating the problem of keeping the items secure. With the abundant text resource on the Web, this study develops a system capable of generating cloze items that cover a wide range of topics based on existing corpra. By analyzing training data from the College Entrance Examinations in Taiwan, we identify special regularities of the test items, and our system can generate items of similar style based on results of the analysis. We propose a word sense disambiguation-based method for locating sentences in which designated words carry specific senses, and apply collocation-based methods for selecting distractors. Experimental results indicate that our system was able to produce a usable item for every 1.6 items it returned. We try to create different types of items and integrate the reported item generator in a Web-based system for learning English. The outcome of on-line examinations is analyzed in order to estimate the item discrimination of the test items generated by our system.

Submitted by Mariana Dornelles Vargas (marianadv) on 2015-05-25T12:29:15Z No. of bitstreams: 1 AutoEduMat.pdf: 1060362 bytes, checksum: 25b8156de4b9c2c2c5b9dc0f69aea011 (MD5) / Made available in DSpace on 2015-05-25T12:29:15Z (GMT). No. of bitstreams: 1 AutoEduMat.pdf: 1060362 bytes, checksum: 25b8156de4b9c2c2c5b9dc0f69aea011 (MD5) Previous issue date: 2010 / Nenhuma / Esta dissertação apresenta uma pesquisa relacionada as ferramentas que dão suporte a utilização de objetos de aprendizagem em plataformas digitais. Mais especificamente, a pesquisa se direciona para as ferramentas de apoio a autoria destes objetos, em particular dos seus metadados. Inicialmente é apresentada a contextualização do problema de pesquisa, sua fundamentação teórica e os trabalhos relacionados ao tema. Em seguida são apresentadas as principais características do sistema proposto, o AutoEduMat - Ferramenta de Apoio a Autoria de Metadados de Objetos de Aprendizagem para o Domínio de Ensino de Matemática. A ferramenta AutoEduMat dá apoio a autoria de objetos de aprendizagem, oferecendo assistência ao projetista (designer) de objetos na criação e edição de metadados destes objetos. A principal inovação do trabalho é a combinação das tecnologias de Engenharia de Software de Agentes e de Engenharia de Ontologias para construir um sistema multiagente que oferece suporte inteligente para a geração dos metadados dos objetos de aprendizagem, sendo capaz de interagir com o usuário com termos de seu próprio contexto profissional e educacional. No trabalho é proposta a ontologia Onto-EduMat que incorpora os conhecimentos sobre o domínio de ensino de matemática, incluindo aspectos pedagógicos, necessários para o auxílio a geração dos metadados. Tanto a ferramenta quanto seu modelo ontológico são validados através de experimentos descritos no final do trabalho. / This dissertation presents a research related to the tools that support the utilization of learning objects in digital platforms. More precisely, the research is directed to the tools that support the authoring process of these objects, in particular of their metadata. Initially are presented the characterization of the problem, its theoretical foundations and related works. Then are presented the main characteristics of the proposed system, the AutoEduMat - Metadata Authoring Tool for Mathematics Learning Objects. The AutoEduMat system will provide assistance to the object designer in the metadata creation and edition of these objects. The main innovation of this work is the combination of Agent Oriented Software Engineering and Ontology Engineering technologies to built a multiagent system able to offer intelligent support for metadata creation, interacting with users using terms related to their professional and educational context. This work proposes the Onto-EduMat ontology, which incorporates the mathematical and pedagogical knowledge necessary to generate the metadata. The authoring tool and its ontological model are validated through experiments described in the end of the work.

University students learning object-oriented programming (OOP) encounter many complexities. This study undertook empirical research aimed at analysing learners’ interactions with the Alice visual programming environment, which seeks to engage and motivate learners to grasp concepts of OOP, whilst creating animated movies and video games. A mixed-methods approach was employed, using questionnaire surveys and interviews to investigate learners’ experiences with Alice and their understanding of OOP. Findings indicated that learners lacked problem-solving abilities; were unable to grasp programming concepts on an abstract level and spent insufficient time practicing programming exercises. Alice proved to be an effective tool in helping to address these challenges and in improving learners’ grasp of OOP. Learners found Alice to have good usability. Furthermore, test and exam results revealed a statistically significant difference between performances of learners who had been taught Alice in comparison to similar learners who were not exposed to the Alice intervention. / Computing / Information Systems / M. Sc. (Information systems)