Matematizando situaciones Bayesianas en la escuela usando múltiples representaciones

III Congreso Internacional Virtual de Educación Estadística (CIVEEST), 21-24 febrero de 2019. [www.ugr.es/local/fqm126/civeest.html]Bayesian problem situations are well known as being difficult for people to judge adequately. Teachers in school are confronted with the question what can be done on the long run to support their students in coping with Bayesian situations. In this regard the paper refers to the learning about mathematizing Bayesian situations in school, especially focused on using the unit square in settings of learning with multiple representations. Firstly, the topic of Bayesian reasoning will be analysed from the different perspectives of mathematical, modelling, and mathematizing structure. Afterwards, potentials of theories of learning with multiple representations will be reflected within the topic of Bayesian reasoning. Bringing both together yields in in a 2x2 matrix which allows for categorizing task types about Bayesian situations.Se conocen bien las dificultades de las personas para juzgar adecuadamente las situaciones- problemas Bayesianas. Los profesores se enfrentan en la escuela a la cuestión de qué se puede hacer a largo plazo para apoyar a sus estudiantes en la resolución de situaciones Bayesianas. A este respecto este artículo refiere al aprendizaje de la matematización de situaciones Bayesianas en la escuela, especialmente centrado en el uso del cuadrado unidad en entornos de aprendizaje con múltiples representaciones. En primer lugar, se analizará el tema del razonamiento Bayesiano desde las diferentes perspectivas de matematización y modelización de la estructura matemática. Seguidamente, el potencial de teorías del aprendizaje que tienen en cuenta el uso de múltiples representaciones será reflejado dentro del tópico del razonamiento Bayesiano. Conjuntando ambos campos se elabora una matriz de 2x2 que permite la categorización de tipos de tareas sobre situaciones Bayesianas

Automatic Loanword Identification Using Tree Reconciliation

Die Verwendung von computerbasierten Methoden in der Historischen Linguistik stieg in den letzten Jahren stetig an. Phylogenetische Methoden, welche zur Bestimmung der Evolutionsgeschichte und Verwandtschaftsgraden zwischen Organismen entwickelt wurden, erhielten Einzug in die Historische Linguistik. Die Verfügbarkeit von maschinenlesbaren Daten förderten deren Anpassung und Weiterentwicklung. Während einige Algorithmen zur Rekonstruktion der sprachlichen Evolutionsgeschichte übernommen wurden, wurde den Methoden für horizontalen Transfer kaum Beachtung geschenkt. Angelehnt an die Parallele zwischen horizontalem Gentransfer und Entlehnung, werden in dieser Arbeit phylogenetische Methoden zur Erkennung von horizontalem Gentransfer für die Identifikation von Lehnwörtern verwendet. Die Algorithmen für horizontalen Gentransfer basieren auf dem Vergleich zweier phylogenetischer Bäume. In der Linguistik bildet der Sprachbaum die Sprachgeschichte ab, während ein Konzeptbaum die Evolutionsgeschichte einzelner Wörter repräsentiert. Die Rekonstruktion eines Sprachbaumes ist wissenschaftlich fundiert, wohingegen die Rekonstruktion von Konzeptbäumen bisher wenig erforscht wurde. Eine erhebliche Innovation dieser Arbeit ist die Einführung verschiedener Methoden zur Rekonstruktion von stabilen Konzeptbäumen. Da die Algorithmen zur Erkennung von horizontalem Transfer auf einem Baumvergleich basieren, deuten die Unterschiede zwischen einem Sprachbaum und einem Konzeptbaum auf Lehnwörter innerhalb der Daten hin. Daher wird sowohl die Methodik, als auch ein geeigneter Algorithmus in einem linguistischen Kontext eingeführt. Die Ergebnisse der Lehnworterkennung werden mithilfe eines neu entwickelten Goldstandards evaluiert und mit drei weiteren Algorithmen aus der Historischen Computerlinguistik verglichen. Ziel der Arbeit ist zu erläutern, inwieweit Algorithmen basierend auf dem Vergleich zweier Bäume für die automatische Lehnworterkennung verwendet und in welchem Umfang Lehnwörter erfolgreich innerhalb der Daten bestimmt werden können. Die Identifikation von Lehnwörtern trägt zu einem tieferen Verständnis von Sprachkontakt und den unterschiedlichen Arten von Lehnwörtern bei. Daher ist die Adaption von phylogenetischen Methoden nicht nur lohnenswert für die Bestimmungen von Entlehnungen, sondern dient auch als Basis für weitere, detailliertere Analysen auf den Gebieten der automatischen Lehnworterkennung und Kontaktlinguistik.The use of computational methods in historical linguistics increased during the last years. Phylogenetic methods, which explore the evolutionary history and relationships among organisms, found their way into historical linguistics. The availability of machine-readable data accelerated their adaptation and development. While some methods addressing the evolution of languages are integrated into linguistics, scarcely any attention has been paid to methods analyzing horizontal transmission. Inspired by the parallel between horizontal gene transfer and borrowing, this thesis aims at adapting horizontal transfer methods into computational historical linguistics to identify borrowing scenarios along with the transferred loanwords. Computational methods modeling horizontal transfer are based on the framework of tree reconciliation. The methods attempt to detect horizontal transfer by fitting the evolutionary history of words to the evolution of their corresponding languages, both represented in phylogenetic trees. The discordance between the two evolutionary scenarios indicates the influence of loanwords due to language contact. The tree reconciliation framework is introduced in a linguistic setting along with an appropriate algorithm, which is applied to linguistic trees to detect loanwords. While the reconstruction of language trees is scientifically substantiated, little research has so far be done on the reconstruction of concept trees, representing the words’ histories. One major innovation of this thesis is the introduction of various methods to reconstruct reliable concept trees and determine their stability in order to achieve reasonable results in terms of loanword detection. The results of the tree reconciliation are evaluated against a newly developed gold standard and compared to three methods established for the task of language contact detection in computational historical linguistics. The main aim of this thesis is to clarify the purpose of tree reconciliation methods in linguistics. The following analyses should give insights to which degree the direct transfer of phylogenetic methods into the field of linguistics is fruitful and can be used to discover borrowings along with the transferred loanwords. The identification of loanwords is a first step into the direction of a deeper understanding of contact scenarios and possible types of loanwords present in linguistic data. The adaptation of phylogenetic methods is not only worthwhile to shed light on detailed horizontal transmissions, but serves as basis for further, more detailed analyses in the field of contact linguistics

Kesan perisian realiti berperantara berasaskan pendekatan inkuiri dalam pembelajaran sains

This study aims to investigate the effects of Augmented Reality (AR) software integrated with POE Inquiry based approach and Cognitive Theory of Multimedia Learning design principles toward spatial visualization ability and achievement in science. This study also investigates student interaction with the AR system and their corresponding correlations to spatial visualization ability and achievement in science. A pre-experimental one group pretest-posttest research design was employed with 34 grade 5 elementary school students as respondents, which consists of students with high spatial visualization abilities (KVST) and low spatial visualization abilities (KVSR). The findings revealed that learning through the AR software was effective to enhance students’ spatial visualization ability and achievement in science. The results of the t test analysis of students’ pre- and posttest scores on both tests demonstrate significant improvements in their mental rotation test (t = 19.795, p < 0.05) and achievement in science (t = 24.801, p < 0.05). Moreover, the findings also suggest that there exists a significant difference between the KVST and KVSR groups in terms of spatial visualization ability (t = 6.592, p < 0.05) and achievement in science (t = 2.419, p < 0.05), before and after the treatment session. The results of the content analysis towards student interaction with the AR software demonstrates that turning the AR markers, inspecting the AR elements and commenting on the AR elements are recorded the highest number of interactions compared to others. Results from a Spearman correlation analysis show that there are nine interactions that have significant correlations with spatial visualization ability and achievement in science among the KVST and KVSR students, with the correlation direction of each relationship is positive. Finally, a framework for KVST and KVSR students in learning through the AR software was developed through data mining analysis using a decision tree technique. This framework recommends a series of guidelines that can further enhance students’ spatial visualization ability and achievement in science through the application of AR in learning

Methods for engineering symbolic human behaviour models for activity recognition

This work investigates the ability of symbolic models to encode context information that is later used for generating probabilistic models for activity recognition. The contributions of the work are as follows: it shows that it is possible to successfully use symbolic models for activity recognition; it provides a modelling toolkit that contains patterns for reducing the model complexity; it proposes a structured development process for building and evaluating computational causal behaviour models

The relationship between learning styles, modes of content presentation and visuo-semiotic reasoning in Biology

In the 21st century, acquiring knowledge of the life sciences, particularly in the discipline of biology, requires attaining a set of visualisation skills among students. These skills include the ability to interpret, reason and understand the discipline by processing visual stimuli to comprehend spatial relationships between objects, and to visualize images. Since the start of the 4th industrial revolution, the use of visuo-semiotic models in teaching and learning have increased. The integration of visuo-semiotic models, such as images and visual presentations in textbooks and computer interfaces, have promoted more effective learning of visually and spatially complex topics in biology and molecular biology. The integration and interpretation of visuo-semiotic models is a complex process and depends on prior knowledge of the domain of biology, as well as familiarity with visualisations and complexities of the visuo-semiotic model. Consequently, the present study aimed to investigate the relationship between learning styles, modes of content presentation and visuo-semiotic reasoning in biology. This will aid in understanding how both teaching and learning can be enhanced through visuo-semiotic models, in a preliminary manner. The present study adopted a quantitative, quasi-experimental research approach. A non-probability, purposive sampling method was used to select participants from a public school located in Gauteng, West of Johannesburg. Data was obtained from selfadministered questionnaires which were completed by Grade 10 biology students (n=76). The findings of this study suggests that a relationship exists between learning styles, modes of content presentation and visuo-semiotic reasoning associated with learning difficulties related to conceptual understanding of the cell cycle. Furthermore, the results also showed that content knowledge, which was presented using simulations, performed by using bead-work, animation and paper-based worksheets did not improve student performance.Science and Technology EducationM. Ed. (Natural Science Education

Investigating the learning potential of the Second Quantum Revolution: development of an approach for secondary school students

In recent years we have witnessed important changes: the Second Quantum Revolution is in the spotlight of many countries, and it is creating a new generation of technologies. To unlock the potential of the Second Quantum Revolution, several countries have launched strategic plans and research programs that finance and set the pace of research and development of these new technologies (like the Quantum Flagship, the National Quantum Initiative Act and so on). The increasing pace of technological changes is also challenging science education and institutional systems, requiring them to help to prepare new generations of experts. This work is placed within physics education research and contributes to the challenge by developing an approach and a course about the Second Quantum Revolution. The aims are to promote quantum literacy and, in particular, to value from a cultural and educational perspective the Second Revolution. The dissertation is articulated in two parts. In the first, we unpack the Second Quantum Revolution from a cultural perspective and shed light on the main revolutionary aspects that are elevated to the rank of principles implemented in the design of a course for secondary school students, prospective and in-service teachers. The design process and the educational reconstruction of the activities are presented as well as the results of a pilot study conducted to investigate the impact of the approach on students' understanding and to gather feedback to refine and improve the instructional materials. The second part consists of the exploration of the Second Quantum Revolution as a context to introduce some basic concepts of quantum physics. We present the results of an implementation with secondary school students to investigate if and to what extent external representations could play any role to promote students’ understanding and acceptance of quantum physics as a personal reliable description of the world

San Juan County Index, 05-11-1900

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