Made available in DSpace on 2018-08-02T00:03:48Z (GMT). No. of bitstreams: 1 tese_11160_CamilaZacche_dissertacao_final.pdf: 5437260 bytes, checksum: 0c96c6b2cce9c15ea234627fad78ac9a (MD5) Previous issue date: 2017-03-31 / 8 Resumo Os mapas conceituais são ferramentas gráficas para a representação e construção do conhecimento. Conceitos e relações formam a base para o aprendizado e, portanto, os mapas conceituais têm sido amplamente utilizados em diferentes situações e para diferentes propósitos na educação, sendo uma delas a represent ação do texto escrito. Mes mo um gramá tico e complexo texto pode ser representado por um mapa conceitual contendo apenas conceitos e relações que represente m o que foi expresso de uma forma mais complicada. No entanto, a construção manual de um mapa conceit ual exige bastante tempo e esforço na identificação e estruturação do conhecimento, especialmente quando o mapa não deve representar os conceitos da estrutura cognitiva do autor. Em vez disso, o mapa deve representar os conceitos expressos em um texto. Ass im, várias abordagens tecnológicas foram propostas para facilitar o processo de construção de mapas conceituais a partir de textos. Portanto, esta dissertação propõe uma nova abordagem para a construção automática de mapas conceituais como sumarização de t extos científicos. A sumarização pretende produzir um mapa conceitual como uma representação resumida do texto, mantendo suas diversas e mais importantes características. A sumarização pode facilitar a compreensão dos textos, uma vez que os alunos estão te ntando lidar com a sobrecarga cognitiva causada pela crescente quantidade de informação textual disponível atualmente. Este crescimento também pode ser prejudicial à construção do conhecimento. Assim, consideramos a hipótese de que a sumarização de um text o representado por um mapa conceitual pode atribuir características importantes para assimilar o conhecimento do texto, bem como diminuir a sua complexidade e o tempo necessário para processá - lo. Neste contexto, realizamos uma revisão da literatura entre o s anos de 1994 e 2016 sobre as abordagens que visam a construção automática de mapas conceituais a partir de textos. A partir disso, construímos uma categorização para melhor identificar e analisar os recursos e as características dessas abordagens tecnoló gicas. Além disso, buscamos identificar as limitações e reunir as melhores características dos trabalhos relacionados para propor nossa abordagem. 9 Ademais, apresentamos um processo Concept Map Mining elaborado seguindo quatro dimensões : Descrição da Fonte de Dados, Definição do Domínio, Identificação de Elementos e Visualização do Mapa. Com o intuito de desenvolver uma arquitetura computacional para construir automaticamente mapas conceituais como sumarização de textos acadêmicos, esta pesquisa resultou na ferramenta pública CMBuilder , uma ferramenta online para a construção automática de mapas conceituais a partir de textos, bem como uma api java chamada ExtroutNLP , que contém bibliotecas para extração de informações e serviços públicos. Para alcançar o objetivo proposto, direcionados esforços para áreas de processamento de linguagem natural e recuperação de informação. Ressaltamos que a principal tarefa para alcançar nosso objetivo é extrair do texto as proposições do tipo ( conceito, rela ção, conceito ). Sob essa premissa, a pesquisa introduz um pipeline que compreende: regras gramaticais e busca em profundidade para a extração de conceitos e relações a partir do texto; mapeamento de preposição, resolução de anáforas e exploração de entidad es nomeadas para a rotulação de conceitos; ranking de conceitos baseado na análise de frequência de elementos e na topologia do mapa; e sumarização de proposição baseada na topologia do grafo. Além disso, a abordagem também propõe o uso de técnicas de apre ndizagem supervisionada de clusterização e classificação associadas ao uso de um tesauro para a definição do domínio do texto e construção de um vocabulário conceitual de domínios. Finalmente, uma análise objetiva para validar a exatidão da biblioteca Extr outNLP é executada e apresenta 0.65 precision sobre o corpus . Além disso, uma análise subjetiva para validar a qualidade do mapa conceitual construído pela ferramenta CMBuilder é realizada , apresentando 0.75/0.45 para precision / recall de conceitos e 0.57/ 0.23 para precision/ recall de relações em idioma inglês e apresenta ndo 0.68/ 0.38 para precision/ recall de conceitos e 0.41/ 0.19 para precision/ recall de relações em idioma português. Ademais , um experimento para verificar se o mapa conceitual sumarizado pe lo CMBuilder tem influência para a compreensão do assunto abordado em um texto é realizado , atingindo 60% de acertos para mapas extraídos de pequenos textos com questões de múltipla escolha e 77% de acertos para m apas extraídos de textos extensos com quest ões discursivas

TITLE: Concept maps as an assessment tool in education SUMMARY: This thesis thesis is concerned with the types of assessment of concept maps, creation on the bases of studying professional literature. It points out different views and perceptions of assessment methods and offers its own assessment methods. By way of research evaluates its own methods for assessing concept maps, and then explores the possibilities of evaluation of concept maps (in contrast with the written exam, objectivity of assessing methods) for students of upper primary school in the three selected subjects: geography, citizenship education,science. KEYWORDS: Concept map, assessment

¡@¡@e-Learning is becoming more and more important for many educational institutions, and many educators believe that there is a good potential for providing adaptive learning in e-learning environment. In order to support the design of adaptive learning materials, teachers need to refer to the ontology of the subject domain to be taught. Moreover, ontology can show the whole picture and the core knowledge of a subject domain. Literature reviews also pointed out that graphical representation of ontology can reduce the problems of information overloading and learning disorientation for learners. However, ontology constructions all rely on domain experts in the past; it is a time consuming and high cost task. It would be more challenge for those emerging new domains like e-Learning. ¡@¡@e-Learning is a new and fast developing domain, how to automatic constructing its ontology is a very important topic. In this research, we use some relevant e-Learning journals and conferences papers as input data sources, and apply data mining techniques to automatically construct the concept maps for e-learning. We also analyzed the evolution in e-Learning domain according to the concept maps constructed at different time periods. ¡@¡@The contribution of this research is automatic constructing the concept maps of e-Learning domain using text-mining techniques. It can provide a comprehensive and useful reference for researchers to do research, for teachers to do adaptive course design and for learners to understand the related knowledge in e-Learning.

The purpose of this study was to explore the use of concept map assessments in freshman level general chemistry courses. Two strategies were employed in this study. The first strategy involved the creation of a web based concept mapping program capable of scoring concept maps drawn by students. The second strategy involved comparing different methods of scoring concept maps. Students enrolled in web based general chemistry course drew concept maps using the web based Concept Map Assessment Tool, CMAT. The reliability of the automated scoring in the CMAT program was tested by scoring the concept maps created in the CMAT program by hand. The results of the study indicated that scoring concept maps by hand was the same as the automated scoring of concept maps in the CMAT program. Two characteristics of concept maps serve as the basis for scoring methods. The relational character of a concept map is defined as the correctness of the propositions in the concept map. The structural character of a concept map is defined as the key features of the map, such as branches, long chains or intersecting points. The scoring method used in the CMAT program scores the relational aspects of a concept map. In this study, a second relational scoring method was used to score the concept maps drawn by students using the CMAT program, and the two sets of scores were compared. A novel structural scoring method, the Structural Complexity Index (SCI), was developed compared to the relational scoring approach of the CMAT program. The results of this study found the two relational scoring methods to score concept maps similarly under certain conditions. The SCI was found to produce a different score for concept maps than the relational scoring method employed by CMAT. / text

The problems existent within the built environment are inherently complex due to the interactions between different stakeholders, structures, and systems. The reductionist approach vastly utilized by engineers is not appropriate for dealing with this complexity. Engineers need to be trained to think in systems in order to fully explore the design problem space and therefore identify appropriate design solutions. The study here presented investigates the possibility of the use of concept mapping as an intervention to prime engineering students to think in systems. In the study, 66 engineering students were given two problem framing tasks. Half of the sample received the priming intervention before each task. The control and the intervention group were compared across different metrics. The time spent on the task and length of responses were used as measures of cognitive effort. The number of systems mentioned and the semantic distance between words used in each response were the metrics used for exploration of the design space. Results of the analysis for one of the tasks were significant. The findings suggest that the participants who received the concept mapping priming intervention were able to sustain cognitive effort longer and explore a wider design problem space. / Master of Science / The problems existent within the built environment present interdependencies that need to be identified before suitable solutions can be designed. Engineers need to be able to identify and understand these complex relationships. However, engineers are instead trained and prompted to apply a reductionist approach to problem solving, which isolates parts of a system in order to reduce complexity and facilitate the design process. Concept maps, a graphical tool utilized to display the relationships between concepts and ideas in a hierarchical form, could be used to assist engineers on applying a more holistic approach to problem solving. This research investigates if concept mapping activities can affect engineering students' ability to think in systems and consider all the variables behind a design problem. Participants in the study had to identify and describe everything that could be improved about two different systems familiar to Virginia Tech students. Half of the participants were asked to draw a concept map about each system before each task. All responses were compared between the group that did the concept mapping activity and the group that did not do it. The length in time and words of the responses, the number of systems mentioned, and the originality of the words used by each participant were the metrics utilized to compare the groups. Results suggest that concept mapping can be used as a tool to assist engineering students explore the design problem space more fully.

Grand challenges in engineering are complex and require engineers to be cognizant of different systems associated with each problem. The approach to think about these systems is called systems thinking. Systems thinking provides engineers with a lens to identify relationships between multiple components which helps them develop new ideas about the problem. Concept maps are a tool that enables systems thinking by helping engineers organize ideas and the relationship between ideas, graphically. The research presented in this thesis uses concept maps, as an intervention to help engineering students think in systems and, in turn, shape how they frame their design problem. The aim of the research was to understand the neurocognitive effects of engineering students thinking in systems. The effects of systems thinking on neurocognition is not well understood. Sixty-six engineering students were randomly chosen to either draw concept maps about a design problem or not. They were then asked to develop design problem statements for two design problems. Functional near-infrared spectroscopy (fNIRS) was used to measure changes in oxy-hemoglobin (oxy-Hb) in the prefrontal cortex (PFC) of students while they developed their design problem statements. A lower average oxy-Hb was observed in the group that was first asked to develop concept maps. The lower activation was observed in their left PFC. The group of students who first developed concept maps also demonstrated lower network connections between brain regions in the prefrontal cortex, which is a proxy for functional coordination. Using concept maps changed activation in students' brains, reducing the average neuro-cognition in the left PFC and reducing the need for functional coordination between brain regions. / Master of Science / Engineering challenges require engineers to think "outside the box". Concept mapping is a tool that encourages out of the box thinking. Concept mapping is the process of representing components of the problem and the relationship between components graphically. How the process of concept mapping changes the way engineers think is not well understood. Exploring various interconnected system components and their relationships may give rise to new ideas and this may be expressed differently in the brain. The research presented in this thesis explores how concept maps change engineering students' brain behavior. Sixty-six students participated in the study. Half of the participants (the intervention group) were required to draw concept maps before developing two engineering problem statements. The other half (the control group) were given the same two tasks to develop engineering problem statements but without being asked to first develop concept maps. A neuroimaging tool, called functional near-infrared spectroscopy, was used to measure change in the engineering students' prefrontal cortex (PFC) when they were developing problem statements. The PFC is generally associated with executive functions like planning, design, and creative thinking. The results indicate that concept mapping significantly changed brain behavior when developing problem statements. It reduced brain activation in the left PFC, a region generally associated with making analytical judgments and goal-directed planning. It also reduced the network complexity in the PFC, which is a proxy for functional connectivity. These results demonstrate how concept mapping can shape brain behavior when designing and lays the groundwork for future studies to explore how other interventions similar to concept mapping can help shape design thinking.

The purpose of this study was to examine two scaffolding methods on the performance of students in computer-based concept linking and retention of comprehension. After training and practice in concept mapping and CmapTools--a computer-based concept mapping program, 116 undergraduate students were randomly assigned to one of four treatment groups to work on a computer-based concept mapping task. Students in the no scaffolding (NS) group did not receive any scaffolding. Students in the linking phrase scaffolding (PS) group received linking words or phrases as scaffolding. Students in the articulation hint scaffolding (AS) group received a hint question as scaffolding, which asked them to elaborate on relationships between concepts in full sentences. Students in the linking phrase and articulation hint scaffolding (PAS) group received both scaffolding while working on the computer-based concept mapping task. One week after the treatment, students took a concept linking posttest, in which they constructed a concept map in CmapTools based on a web-based instruction on the human heart. After another week, they took another posttest on retention of comprehension about the heart. Two 2 X 2 factorial Analysis of Variance (ANOVA) were conducted to examine the main effects of linking phrase scaffolding and articulation hint scaffolding and any interaction effect between them on the performance of students in computer-based concept linking and retention of comprehension. The results showed no significant difference in the performance of students in both tests. However, the Pearson's correlation analysis showed that there was a positive correlation between students' performance in computer-based concept linking and retention of comprehension (γ = 0.447, p < 0.01). / Ph. D.

The development of spatial thinking proficiency has been increasingly demanded in Geographic Information System (GIS) education. Despite this educational trend, there is little empirical research on college students' spatial concept knowledge, which critically affects the quality of spatial thinking. This study addressed the following three research questions: 1) What differences exist between students' understandings of spatial concepts at the beginning, middle, and end of an introductory-level GIS course?, 2) What spatial misconceptions students may possess while taking an introductory-level GIS course?, and 3) Which spatial concepts are easy or hard for undergraduate students to understand? The researcher asked twelve participants who were taking an introductory-level GIS course to create concept maps about space and revised their concept maps in three experiment sessions. For the first question, the researcher scored the sixty obtained concept maps and statistically analyzed those scores to examine if there is any significant difference among the scores of the three experiment sessions. For the second question, the researcher examined participants' misconceptions by analyzing the incorrect statements of distortion, map projection, and scale. For the third question, the researcher statistically analyzed concept-based scores to examine if there is any significant difference among the scores of three different complexity levels. A main finding for the first question was that there was a significant difference among the scores of the concept maps created in the first session and the scores of the concept maps revised in the second and third sessions. This implied that participants could successfully revise their own original concept maps in the middle of a semester. The result of the study of the second question indicated that a half of participants misunderstood the concepts of map projections and scale. This result suggested that some undergraduate students may have difficulty shifting from scientifically inappropriate spatial concept knowledge to appropriate knowledge. Analysis of the third question resulted that the concept-based scores of simple spatial concepts are significantly higher than the scores of complicated spatial concepts. This result inferred that participants' scores decreased as the complexity of the concepts increased.

Epidemiological studies are rich in information that could improve the understanding of concept complexity of a health problem, and are important sources for evidence based medicine. However, epidemiologists experience difficulties in recognising and aggregating key characteristics in related research due to an increasing number of published articles. The main aim of this dissertation is to explore how text mining techniques can assist epidemiologists to identify important pieces of information and detect and integrate key knowledge for further research and exploration via concept maps. Concept maps are widely used in medicine for exploration and representation as a relatively formal, easy to design and understand knowledge representation model. To support this aim, we have developed a methodology for the extraction of key epidemiological characteristics from all types of epidemiological research articles in order to visualise, explore and aggregate concepts related to a health care problem. A generic rule-based approach was designed and implemented for the identification of mentions of six key characteristics, including study design, population, exposure, outcome, covariate and effect size. The system also relies on automatic term recognition and biomedical dictionaries to identify concepts of interests. In order to facilitate knowledge integration and aggregation, extracted characteristics are further normalized and mapped to existing resources. Study design mentions are mapped to an expanded version of the Ontology of Clinical Research (OCRe), whereas exposure, outcome and covariate mentions are mapped to Unified Medical Language System (UMLS) semantic groups and categories. Population mentions are mapped to age groups, gender and nationality/ethnicity, and effect size mentions are normalised with the regards to the used metric and confidence interval and related concept. The evaluation has shown reliable results, with an average micro F-score of 87% for recognition of epidemiological mentions and 91% for normalisation. Normalised concepts are further organised in an automatically generated concept map, which has three sections for exposures, outcomes and covariates. To demonstrate the potential of the developed methodology, it was applied to a large-scale corpus of epidemiological research abstracts related to obesity. Obesity was chosen as a case study since it has emerged as one of the most important global health problems of the 21st century. Using the concepts extracted from the corpus, we have built a searchable database of key epidemiological characteristics explored in obesity and an automatically generated concept map represented the normalized exposures, outcomes and covariates. An epidemiological workbench (EpiTeM) was designed to enable further exploration and inspection of the normalized extracted data, with direct links to the literature. The generated results also allow exploration of trends in obesity research and can facilitate understanding of its concept complexity. For example, we have noted the most frequent concepts and the most common pairs of characteristics that have been studied in obesity epidemiology. Finally, this thesis also discusses a number of challenges for text mining of epidemiological literature and suggests various opportunities for future work.

With increasing challenges from international competition and domestic demands for a technologically literate workforce, pressure is growing on the educational system to produce students that are literate in science, technology, engineering, and mathematics (STEM). Integrative STEM education utilizes design-based pedagogical approaches to teach science/math content and practices concurrently with technology/engineering content and practices (Wells & Ernst, 2012, para. 2). The discipline of technology education has traditionally implemented design-based pedagogical approaches. However, the discipline has not demonstrated through empirical research that its existence and pedagogies are beneficial to student learning and cognition (Lewis, 1999, 2006; Petrina, 1998; Wells, 2008, 2010; Zuga, 1994, 1997, 2001). The purpose of this study was to demonstrate that the technological design-based approach to teaching biotechnology literacy supports students' connections of science and technology concepts. Grounded in Ausubel's (1968) theory on meaningful learning and Novak's (1980) advanced organizer of concept mapping, this study examined evidence of high school students' cognitive structural change throughout the technological design-based approach to instruction. At three key intervals throughout the technological design process, students developed concept maps to document their understanding of the biology and technology concepts presented within the instructional materials. Data for this study included the students' constructed concept maps. To analyze the concept maps, the researcher used Hay et al.'s (2008) three-method analysis for measuring the quality of students' learning, and a qualitative analysis. Data analysis across all four methods indicated that all participants experienced a varying degree of growth in biology, technology, and integrative concepts and connections. Collectively this study supports the notion that the technological design-based approach to instruction does indeed (1) encourage meaningful learning, and (2) increase students' use of higher order thinking indicated by their abilities to demonstrate their use of schematic and strategic knowledge within their concept maps. The results of this study have direct implications within the areas of Technology Education, Science Education, classroom practice, and concept mapping. The discussion and implications suggest the need to expand the research conducted within this study, and to improve the methods for concept mapping analysis. / Ph. D.