Academic literature on the topic 'Rating concept maps propositions'

Whereas knowledge management relies on processes of knowledge elicitation, there is also a process in which knowledge is “recovered,” typically from archived documents. We conducted a knowledge recovery (KR) effort, going from documents to a structured set of propositions concerning expert knowledge about terrain analysis, discussing landforms, soils, rock types, etc. Assertions and feature associations were recast as over 3,000 propositions. When contrasted with results from previous evaluations of methods of knowledge elicitation, KR was costly in terms of time and effort, suggesting that knowledge-based organizations should make knowledge capture an on-going aspect of work, rather than finding themselves in the “catch-up mode” to recover lost expertise. For both knowledge elicitation and recovery, the knowledge has to be represented in a form that is usable and useful (e.g., instantiation in knowledge bases). We created from the propositions a navigable knowledge model based on over 150 Concept Maps, which were hyperlinked together and to dozens of resources (aerial photos, maps, diagrams, etc.). Such knowledge models are intended to make the “expertise of the past” more useful and usable in training and in performance support.

The television audience rating is an important indicator of the quality of television programs and important reference for decision-television operator. As many factors that affect the ratings and the trends are complex, the article proposes a television rating mining predictive model based on fuzzy cognitive maps (FCMs) with forward stepwise regression. The FCMs use the causal relationship among various concept nodes to simulate the fuzzy reasoning, and enhance the dynamic behavior of the simulation system with its feedback mechanism, which is suitable for system to predict the trend of television audience rating. A FCM-based model for predicting television audience rating is proposed in this paper. The forward stepwise regression algorithm is used to obtain concept nodes of coarse weight matrix for FCMs, and then a training weight algorithm is used to refine the coarse weight matrix model. The FCM model is applied to mine the television audience rating, realizing to predict the television playback volume. The experimental result shows that the modeling method is effective.

This study aims to increase students' interest and mathematics learning achievements on the subject of rank numbers, root shapes and logarithms. In this study I used a concept map. Concept maps are a tool in the form of a scheme that states the relationship between concepts starting from the general to the specific ones which are connected through arrows in the form of propositions. Proposition is two or more statements about a concept that are related to words or arrows. Concept maps play an important role in meaningful learning, with concept maps of students being trained to think, in students being asked to think about concepts or events they already know. Meaningful learning is easier to take place if new concepts are linked to concepts that are inclusive, inclusive concepts that are basic concepts that are more general in nature. Concept maps must be arranged in a hierarchical manner, which means that a more inclusive concept is at the top of the map, the concepts below are sorted into less inclusive ones.

Using visual models is common in science and should become more common in classrooms. Our research group has developed and completed studies on the use of a visual modeling tool, the Concept Connector. This modeling tool consists of an online concept mapping Java applet that has automatic scoring functions we refer to as Robograder. The Concept Connector enables students in large introductory science courses to visualize their thinking through online model building. The Concept Connector's flexible scoring system, based on tested grading schemes as well as instructor input, has enabled >1,000 physiology students to build maps of their ideas about plant and animal physiology with the guidance of automatic and immediate online scoring of homework. Criterion concept maps developed by instructors in this project contain numerous expert-generated or “correct” propositions connecting two concept words together with a linking phrase. In this study, holistic algorithms were used to test automated methods of scoring concept maps that might work as well as a human grader.

Concept maps are graphical tools for representation and construction of knowledge. The manual construction of a concept map requires time and cognitive effort, this being increased when the map should not represent the cognitive structure of the author, but rather, the information expressed in a text written by another author. Therefore, we propose a computational approach for concept map mining from texts in Portuguese that aims to represent the text in summary form through concepts and relationships. To this end, we define a technological architecture that includes the services of: (i) text formatting, removing characters and designing of the text; (ii) domain identification, information retrieval techniques to identify the domain to which refers the text; (iii) elements extractor, natural language processing techniques on the text to extract concept-relation-concept propositions; (iv) element summarizer, supported by graph analysis to identify the relevant concepts on the map; and (v) map visualization, presentation of the propositions in graphic form. The approach developed presents satisfactory results and contributes exceptionally to the summarization of texts to identify the relevant concepts of the text while maintaining its several and most important characteristics. Furthermore, this research introduces the specification of a project to provide computational resources for processing, handling and extraction of conceptual maps.

10506 Background: Proliferating knowledge domains have prompted medical schools to reconsider how best to facilitate multidisciplinary learning. Concept maps promote knowledge retention and integration; however, the feasibility and utility of integrating concept maps into a medical student oncology curriculum as a learning and assessment tool have not previously been described. Methods: In 2015-2016, all 152 second-year University of California, San Francisco (UCSF) medical students in a hematology/oncology course produced a concept map about a single cancer type over four weeks. Two of three graders independently scored each map using a standard rubric. We used linear regression to calculate the Pearson correlation coefficient between graders and between concept map scores and preclinical examination scores, USMLE Step 1 scores, and clerkship grades. We sent course evaluations to 50 randomly selected students (as is typical in the UCSF curriculum) and performed an inductive content analysis of open-ended comments about concept mapping. Results: We graded all 152 concept maps. Inter-rater reliability was excellent ( r = 0.95 or greater between the graders). Concept map scores did not correlate with preclinical or clinical performance. 43 of 50 students (86%) rated the helpfulness of concept mapping on a 5-point agreement scale (1=strongly disagree; 5=strongly agree). The median rating was 3, and the mean (SD) rating was 2.81 (1.44). 22 of 50 (44%) students submitted comments about concept mapping. Some (9 of 22) found concept mapping useful, expressing themes such as “learning the material better” and delving into the “details.” Others (7 of 22) did not, expressing themes such as preferring “other study methods” and feeling that concept mapping was “busy work” or “stressful.” Conclusions: Integrating concept maps into a medical student oncology curriculum was feasible, and we demonstrated reliability evidence as an assessment tool. Future studies should explore whether integrating concept maps earlier in medical school, producing multiple concept maps over time with training and feedback, or developing concept maps collaboratively may increase utility as a learning and assessment tool.

This article describes a small-scale piece of research using concept mapping to elicit A level students’ understandings of particle physics, which was presented in the Special Session on Physics Education and Outreach at ICNFP 2017. Fifty-nine Year 12 (16- and 17-year-old) students from two London schools participated in the research. The exercise took place during school physics lessons. Students were shown how to make a concept map and were provided with topic-specific key words. Their concept maps were analysed by identifying the knowledge propositions the students had represented, and comparing these with propositions developed from the examination specification they were studying. The only correct statement made by most of the students in both schools was that annihilation takes place when matter and antimatter collide, although some students may have been unable to distinguish between annihilation and pair production. A high proportion of students knew of up, down and strange quarks, and that the electron is a lepton. However, some students appeared to have a misconception that everything is made of quarks. Students found it harder to classify tau particles than they did electrons and muons. Where students made incorrect links about muons and tau particles their concept maps suggested that they thought they were mesons or quarks.

This research aims to determine the use of concept maps to develop higher order thinking skills of students. Assignment concept map performed in groups and using the software C-Map Tools. Therefore, the assessment of students 'concept maps and students' performance during the process of making a concept map. The research method used is descriptive research. Quantitative data generated from the manufacture of students' concept maps are described and analyzed to determine changes in thought processes of students in higher-order thinking. The results of this study indicate a change students' thinking processes marked with the percentage change scores on each concept map assessment kriteria, that is the determination of the relevant concepts, propositions, hierarchy, and the cross-links, so that higher-order thinking skills can be developed by assigning students create a concept map. Based on the assessment of student performance during the process of mapping concept is known that most students already have a self-management skills, teamwork, time management, respect for opinions, solving problems, and expressed the opinion that good. However, students 'skills in analyzing questions and a positive attitude toward the task is still not good. Key words: higher order thinking, concept maps, electrolyte and nonelectrolyte solutions

Concept maps have now been used as a research and evaluation tool. It enables students to visualize the structure of knowledge, interrelated concepts and the relationships among various concepts and sub-concepts. Concept mapping has been found to be an effective teaching method which enhances meaningful learning. Concept mapping was significantly more effective than the traditional or expository teaching strategies in enhancing learning. Cognitive mapping differs from traditional methods by making underlying cognitive structures transparent and giving a focus to the set of propositions by which learners construct meaning. Concept map structure correlates with the perceived data. They provide quick summary and help to identify topics to elicit new information. Concept mapping is a strategy that can be used to impart content knowledge with sense within a limited period of time.Concepts learned by rote learning tends to be quickly forgotten. Teaching methods and tools should transform knowledge from short-term memory to long-term memory. Several research studies have supported Concept mapping in academic and non-academic fields. This article describes how the concept mapping can be used to transform abstract knowledge and understanding into concrete visual representations. It is underlined that the Concept maps will serve as a suitable tool to support educators in promoting students comprehension and understanding of new concepts.

This study investigated the concepts of nine volunteers from a non - governmental organization who read stories to hospitalized children. We conducted three to five semistructured interviews with each storyteller which were analyzed using concept maps, resulting in 376 propositions. A semantic grouping of the propositions resulted in 13 categories. Results suggest that storytellers associate their activities to altruism and conceive it chiefly as a way of bringing relief and joy to children in the hospital environment, seen as extremely aversive. Few references are made to the specific features and benefits of shared reading. The study reveals characteristics and challenges which are specific to the practice of shared reading in the hospital setting and suggests directions for volunteer training in this context.

Concept maps provide a way to assess how well students have developed an organized understanding of how the concepts taught in a unit are interrelated and fit together. However, concept maps are challenging to score because of the idiosyncratic ways in which students organize their knowledge (McClure, Sonak, & Suen, 1999). The construct a map or C-mapping" task has been shown to capture students' organized understanding. This "C-mapping" task involves giving students a list of concepts and asking them to produce a map showing how these concepts are interrelated. The purpose of this study was twofold: (a) to determine to what extent the use of the restricted C-mapping technique coupled with the threefold scoring rubric produced reliable ratings of students conceptual understanding from two examinations, and (b) to project how the reliability of the mean ratings for individual students would likely vary as a function of the average number of raters and rating occasions from two examinations. Nearly three-fourths (73%) of the variability in the ratings for one exam and (43 %) of the variability for the other exam were due to dependable differences in the students' understanding detected by the raters. The rater inconsistencies were higher for one exam and somewhat lower for the other exam. The person-to-rater interaction was relatively small for one exam and somewhat higher for the other exam. The rater-by-occasion variance components were zero for both exams. The unexplained variance accounted for 19% on one exam and 14% on the other. The size of the reliability coefficient of student concept map scores varied across the two examinations. A reliability of .95 and .93 for relative and absolute decision was obtained for one exam. A reliability of .88 and .78. for absolute and relative decision was obtained for the other exam. Increasing the number of raters from one to two on one rating occasion would yield a greater increase in the reliability of the ratings at a lower cost than increasing the number of rating occasions. The same pattern holds for both exams.

Os mapas conceituais (MCs) são úteis para representar o conhecimento e promover a aprendizagem significativa, porém recentes trabalhos na literatura apontam que não estão sendo plenamente explorados, pois raramente são utilizados para representar o conhecimento diversificando as proposições. As proposições são unidades fundamentais de conhecimento nos mapas conceituais (MCs). Diferentes mapeadores podem responder a mesma pergunta focal realizando diferentes conexões e relacionando os conceitos de formas diferentes para representar o conhecimento. A proposta do trabalho consiste na elaboração de uma análise de proposições (n=1455) presentes em MCs (n= 104) coletados na disciplina Ciências da Natureza (EACH-USP/Leste) em 2009, durante o período da primeira (MC5) e terceira avaliação (MC15). A análise proposicional proposta utilizou-se de um esquema taxonômico para classificação de proposições estáticas e dinâmicas em seis categorias. As proposições estáticas representam o conhecimento com definições e classificações, enquanto que as proposições dinâmicas expressam relações de ação, influência, dependência, interdependência funcional, proporcionalidade e causa e efeito entre os conceitos. O número de proposições por categoria passou por métodos de estatística descritiva, para mostrar os parâmetros estatísticos como, média, mediana, quartil inferior, quartil superior, mínimo da amostra, e máximo da amostra para descrever cada uma das seis variáveis consideradas na análise proposicional proposta neste trabalho. A comparação dos valores médios de cada categoria para análise proposicional das avaliações MC5 com os valores médios de cada categoria das avaliações MC15 foi feita utilizando-se o teste-t. O método de estatística exploratória multivariada foi empregado para realizar análise hierárquica de agrupamentos (HCA) a fim de observar possíveis tendências entre os alunos e/ou categorias. A HCA agrupou as seis categorias de proposições propostas por este trabalho, sendo que em MC15 houve uma maior distribuição dos tipos de proposições entre as categorias dinâmicas. A HCA formou três agrupamentos para ambas as avaliações e, ainda que tendências dos agrupamentos tenham se mantido, houve um aumento do número total de proposições, sendo que mais de 60% dos alunos optaram pelas proposições dinâmicas, comprovando a eficácia dos estímulos fornecidos nas avaliações. Os resultados apontam para a necessidade da utilização da análise proposicional no mapeamento conceitual para diversificar formas de representação do conhecimento, ou seja, que não sejam somente com o objetivo de descrever, definir e classificar conceitos, mas que sejam utilizadas para incentivar relações conceituais de ação, influência, dependência, proporcionalidade, interdependência funcional e causa e efeito.
The concept maps (CMs) are useful for representing knowledge and promote meaningful learning, but recent studies in the literature indicate that they are not being fully exploited because they are rarely used to represent knowledge by diversifying the propositions. The propositions are fundamental units of knowledge in concept maps (CMs). Different authors may answer the same question different focal performing connections and related concepts in different ways to represent knowledge. Our purpose is to prepare an analysis of propositions (n = 1455) present in MCs (n = 104) collected in the course of Nature Sciences (EACH-USP/Leste) in 2009, during the first (MC5) and third assessment (MC15). The analysis used the propositional proposed a scheme for taxonomic classification of static and dynamic propositions in six categories. The proposals represent the static knowledge with definitions and classifications, while the dynamic propositions expressing relations of action, influence, dependence, and proportionality between cause and effect concepts. The number of propositions in each category went through descriptive statistical methods, to show the statistical parameters as mean, median, lower quartile, upper quartile, the sample minimum and maximum sample to describe each of the six variables considered in the analysis proposed propositional this work. A comparison of mean values for each category analysis of propositional evaluations MC05 to mean values for each category of MC15 evaluation was made using t-test. The exploratory multivariate statistical method was used to perform hierarchical cluster analysis (HCA) to observe possible trends among students and / or categories. HCA grouped the categories and in MC15 was a greater distribution of the types of propositions between the dynamic categories. The HCA was formed three groups for both assessments and, although trends of groupings have been kept, there was an increase in the total number of propositions, and more than 60% of students opted for dynamic propositions, proving the effectiveness of the stimuli provided in the evaluations . The results point to the necessity of using propositional analysis of the conceptual mapping to diversify forms of knowledge representation, they are not solely for the purpose of describing, defining and classifying concepts, but are used to encourage conceptual relations action, influence, dependence, proportionality and cause and effect.