4,970 research outputs found
Development Communication: 1. History and Theories
This entry includes three articles, each dealing with a different aspect of the subject: History and Theories Alternative Systems Projects
The first and third cover predominantly the Western (especially the U.S.) approach; the second raises some criticisms directed at both the theoretical and the practical limitations of the Western perspective and presents alternative views
Computers, the internet, and cheating among secondary school students: Some implications for educators
This article investigates in greater depth one particular aspect of cheating within secondary education and some implications for measuring academic achievement. More specifically, it examines how secondary students exploit the Internet for plagiarizing schoolwork, and looks at how a traditional method of educational assessment, namely paper-based report and essay writing, has been impacted by the growth of Internet usage and the proliferation of computer skills among secondary school students. One of the conclusions is that students’ technology fluency is forcing educators to revisit conventional assessment methods. Different options for combating Internet plagiarism are presented, and some software tools as well as non-technology solutions are evaluated in light of the problems brought about by “cyberplagiarism.
Web logs and online discussions as tools to promote reflective practice
This article reports on the use of Web logs (“blogs”) and online discussion forums in an instructional technology course in a teacher preparation program. Key goals behind the use of these tools included exposure for students to computer-supported communication and collaboration, encouragement of reflective practice, and a better understanding of the pedagogical and learning benefits derived from integration of these technologies. Management and assessment challenges for instructors derived from the volume of writing, as well as pedagogical considerations, are noted. Some of the issues raised led to a call for improvements in the tools and for additional research in a wider variety of context
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Computers, The Internet, and Cheating Among Secondary School Students: Some Implications for Educators
This article investigates in greater depth one particular aspect of cheating within secondary education and some implications for measuring academic achievement. More specifically, it examines how secondary students exploit the Internet for plagiarizing schoolwork, and looks at how a traditional method of educational assessment, namely paper-based report and essay writing, has been impacted by the growth of Internet usage and the proliferation of computer skills among secondary school students. One of the conclusions is that students’ technology fluency is forcing educators to revisit conventional assessment methods. Different options for combating Internet plagiarism are presented, and some software tools as well as non-technology solutions are evaluated in light of the problems brought about by “cyberplagiarism.” Accessed 102,733 times on https://pareonline.net from March 30, 2000 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right
Situating teacher education: From the university classroom to the real classroom
This article presents a descriptive case study on the first experience moving a required teacher preparation instructional technology course from the university classroom into an elementary school setting. The key motivation was to help future teachers become more adept at integrating technology into their practice by learning about commonly used applications and best practices in an authentic setting, framed within a constructivist approach. In addition to lab time focused on the acquisition of computer skills, the course design included classrooms visits and observations, conversations with teachers and the principal, and development of a lesson or unit plan. The format was an intense one-week workshop, meeting for six hours each day and cotaught by two university faculty and a school-based coordinator, instead of a quarter-long course meeting once or twice a week for two hours or less with a single instructor. Students reacted very favorably to the course format and location. Detailed analysis of the curriculum and future plans are described
Redes neuronales artificiales aplicadas a la predicción de parámetros en alimentos acogidos a marcas de calidad
[ES] Los alimentos acogidos a Marcas de Calidad presentan características particulares debidas a su
origen geográfico, a las materias primas utilizadas o a los propios procesos de elaboración. Estos
alimentos deben cumplir requisitos de calidad adicionales no exigidos al resto de los alimentos,
por lo que pertenecer a una Marca de Calidad garantiza a los consumidores la adquisición de un
alimento con características excepcionales y a los productores de situaciones fraudulentas
derivadas de la competencia desleal de las imitaciones.
Por esta razón se requieren métodos objetivos, rápidos y baratos que puedan caracterizar las
materias primas empleadas para la elaboración de un alimento, determinar características
composicionales del mismo o predecirsu calidad y características organolépticas finales. Dentro
de las técnicas analíticas, la Espectroscopía de Infrarrojo Cercano (NIRS) es una herramienta que
cumple con estos requisitos además de ser no destructiva, no requerir preparación previa de las
muestras ni emplear reactivos cuyo uso pudiera ser tóxico o contaminante. Por otro lado, las
Redes Neuronales Artificiales(ANN) han demostrado su utilidad tanto para la categorización de
las muestras como para la predicción de valores de parámetros característicos a partir de los
datos de entrada.
En esta tesis se propone el uso de las ANN como herramienta quimiométrica para interpretar
los resultados obtenidos con técnicas analíticas como el NIRS, marcándose como objetivos los
de la construcción de un modelo de ANN capaz de clasificar alimentos conforme a criterios
preestablecidos, la determinación de las variables que más influyen sobre el comportamiento
de la red, la optimización de los parámetros de la red que mejoran su rendimiento y la bonanza
de la misma para la predicción de parámetros característicos de productos acogidos a Marcas
de Calidad
En los tres artículos recogidos en esta tesis, se han empleado ANN para la interpretación de los
resultados analíticos obtenidos sobre muestras de jamón curado, chorizo y queso. En un primer
artículo, se ha tratado de predecir parámetros sensoriales relacionados con el aspecto, el olor,
el sabor y la textura, a partir de los datos obtenidos por espectroscopia NIR sobre muestras de
jamón curado procedente de cerdos con genética y sistemas de alimentación diferentes.
En un segundo artículo, se han comparado dos técnicas de regresión múltiple como son las ANN
y la Regresión por Mínimos Cuadrados Parciales Modificada, a partir de los resultados obtenidos
por NIRS, para predecir parámetros sensoriales sobre chorizo relacionados con la degustación
en boca y las percepciones externas y al corte.
Un tercer artículo aborda la estimación del recuento de células somáticas (SCC) de la leche de
oveja empleada para la elaboración de quesos, a partir del análisis composicional físicoquímico
y su interpretación con redes neuronales.
Las conclusiones que se derivan de los estudios realizados, señalan que la utilización conjunta
de la espectroscopía NIR y las ANN para procesar sus resultados, puede predecir parámetros
sensoriales de jamón ibérico y chorizo con precisiones relativamente altas, permitiendo su
implementación “in-line” en las líneas de procesado, ahorrando tiempo y el coste derivados
respecto del análisis sensorial a través de un panel de cata. También que las ANN son una
herramienta eficaz para la clasificación de quesos en función del SCC de la leche de oveja
utilizada como materia prima. Por todo lo anterior, se puede decir que el uso de las Redes
Neuronales Artificiales, aplicadas en el sector de los productos asociados a Marcas de Calidad,
son una herramienta adecuada que permite obtener excelentes resultados tanto en la
predicción de parámetros sensoriales, como en la clasificación de los productos según criterios
de calidad diferenciada
Using classifiers to predict linear feedback shift registers
Proceeding of: IEEE 35th International Carnahan Conference on Security Technology. October 16-19, 2001, LondonPreviously (J.C. Hernandez et al., 2000), some new ideas that justify the use of artificial intelligence techniques in cryptanalysis are presented. The main objective of that paper was to show that the theoretical next bit prediction problem can be transformed into a classification problem, and this classification problem could be solved with the aid of some AI algorithms. In particular, they showed how a well-known classifier called c4.5 could predict the next bit generated by a linear feedback shift register (LFSR, a widely used model of pseudorandom number generator) very efficiently and, most importantly, without any previous knowledge over the model used. The authors look for other classifiers, apart from c4.5, that could be useful in the prediction of LFSRs. We conclude that the selection of c4.5 by Hernandez et al. was adequate, because it shows the best accuracy of all the classifiers tested. However, we have found other classifiers that produce interesting results, and we suggest that these algorithms must be taken into account in the future when trying to predict more complex LFSR-based models. Finally, we show some other properties that make the c4.5 algorithm the best choice for this particular cryptanalytic problem.Publicad
Flow and cooperative learning in civic game play
Flow theory offers an individualistic explanation of media enjoyment, while cooperative learning theory posits a social explanation for enhanced learning in groups. This classroom-based experimental study examines whether game players can experience both conditions and the influence of each on several types of civic knowledge, skills, and dispositions. We find that high quality cooperative learning contributed to acquiring civic knowledge and skills. In contrast, flow was more influential for developing dispositions to empathy and interest in learning more about the game topics. Thus, we conclude that players can experience flow while engaged in cooperative learning, but that these two conditions may support different kinds of civic learning
Simulating REAL LIVES: Promoting global empathy and interest in learning through simulation games
In response to an increasingly interdependent world, educators are demonstrating a growing interest in educating for global citizenship. Many definitions of the “good global citizen” value empathy as an especially important disposition for understanding others across national borders and cultural divides. Yet it may be difficult for people to achieve empathy with others who are perceived as psychologically and geographically distant. Can computerized simulation games help foster global empathy and interest in global civic learning? This quasiexperimental classroom study of 301 Northern California high school students in three schools examined the effects of playing REAL LIVES, a simulation game that allows players to inhabit the lives of individuals around the world. Compared with a control group, students who played the simulation game as part of their curriculum expressed more global empathy and greater interest in learning about other countries. Identification with REAL LIVES characters was also positively related to global empathy. These findings support claims that computerized simulations can cultivate important dispositions for global learning and citizenship
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