SUPPORTING LEARNING FOR NAVAJO STUDENTS THROUGH ETHNOMATHEMATICS

The purpose of this research was to address how culturally informed ethnomathematical methods of teaching can be utilized to support the learning of Navajo students in mathematics. The study was conducted over the course of four years on the Navajo Reservations at Tohatchi Middle School in Tohatchi New Mexico. The students involved in the study were all in 8th grade and were enrolled either in Algebra 1 or a Response to Intervention, RTI, class. The data collected came in the form of a student survey, student observation and student assessment. The teacher written survey, a math textbook word problem, and two original math textbook problems along with their rewritten version were the sources of these three studies. The first year of the study consisted of a math attitude survey and how Navajo students perceived math as a subject of interest. The students answered four questions pertaining to their thoughts about mathematics. The students’ responses were positive according to their written answers. The second year of the study involved the observation of how students worked through a math word problem as a group. This method tested how the students culturally interacted in order to solve a math problem. Their questions and reasoning to solve the problem were shared with peers and the teacher. The teacher supported the students in understanding and solving the problem by asking questions that kept the students focused on the goal of solving the problem. The students worked collaboratively and openly in order to complete the activity. During the iv study, the teacher was more able to notice the students’ deficiencies individually or as a group, therefore was able to support them in a more specific manner. The last study was conducted over a period of two different years. This study was used to determine how textbook bias in the form of its sentence structure or word choice affects the performance of students who are not culturally familiar with one or both. It was found that the students performed better and took less time on the rewritten problem than on the original problem. The data suggests that focusing on the culture, language and education of Navajo students can affect how the students learn and understand math.

E-Learning, E-Teaching und E-Assessment in der Hochschullehre

Wie lässt sich die Qualität des Lernens, Lehrens und Prüfens durch den Einsatz neuer Medien steigern? Übertragen auf die Komponenten und Bausteine des E-Education-Prozesses heißt das: - Mit welchen digitalen Materialien und Komponenten ist eine effiziente computergestützte Inhaltserschließung möglich? - Mit welcher Organisationsform der Lehre kann ein maximaler Qualitätsgewinn für die traditionelle Präsenzlehre erzielt werden? - Wie lassen sich traditionelle Prüfungsformen durch digitale Medien bereichern und mit technischer Hilfe auswerten? - Wie müssen digitale Inhalte beschaffen sein, um einen Mehrwert für den Lehr- und Lernprozess, möglicherweise in Selbstlernszenarien, zu erzielen? - Wie muss eine Lernplattformaufgebaut sein, um E-Education in ihrer gesamten Breite zu unterstützen und eine hohe Akzeptanz zu erreichen? Die Autoren sind Hauptakteure des Marburger „Linguistik Engineering Teams“, das in sich das gesamte Know-How für die Entwicklung und Nutzung verschiedener Lehr- und Lernszenarien vereinigt: von der Konzeption über die Programmierung bis hin zur Nutzung in allen denkbaren Varianten. Ihr Buch ist ein Leitfaden, der aufzeigt, wie mit einem komplexen E-Education-System nicht nur Qualitäts-, sondern auch Kapazitätsgewinne sowie erhebliche Aufwandsreduktionen erreicht werden können.

(Lifelong) learning in your pocket?

Der Beitrag fokussiert die Entwicklung, den Einsatz und die Nutzung von innovativen Technologien zur Unterstützung von Bildungsszenarien in Schule, Hochschule und Weiterbildung. Ausgehend von den verschiedenen Phasen des Corporate Learning, Social Learning, Mobile Learning und Intelligent Learning wird in einem ersten Abschnitt das Nutzungsverhalten von Technologien durch Kinder, Jugendliche und (junge) Erwachsene in Schule, Studium und Lehre betrachtet. Es folgt die Darstellung technologischer Entwicklungen auf Basis des Technology Life Cycle und die Konsequenzen von unterschiedlichen Entwicklungszuständen und Reifegraden von Technologien wie Content Learning Management, sozialen Netzwerken, mobilen Endgeräten, multidimensionalen und -modalen Räumen bis hin zu Anwendungen augmentierter Realität und des Internets der Dinge, Dienste und Daten für den Einsatz und die Nutzung in Bildungsszenarien. Nach der Darstellung von Anforderungen an digitale Technologien hinsichtlich Inhalte, Didaktik und Methodik wie etwa hinsichtlich der Erstellung von Inhalten, deren Wiederverwendung, Digitalisierung und Auffindbarkeit sowie Standards werden methodische Hinweise zur Nutzung digitaler Technologien zur Interaktion von Lernenden, von Lehrenden, sozialer Interaktion, kollaborativem Autorieren, Kommentierung, Evaluation und Begutachtung gegeben. Abschließend werden - differenziert für Schule und Hochschule - Erkenntnisse zu Rahmenbedingungen, Einflussgrößen, hemmenden und fördernden Faktoren sowie Herausförderungen bei der Einführung und nachhaltigen Implementation digitaler Technologien im schulischen Unterricht, in Lehre, Studium und Weiterbildung im Überblick zusammengefasst.

Cognition and Student Learning Through the Arts

An increasing number of recent research studies suggest connections between cognition, social and emotional development, and the arts. Some studies indicate that students in schools where the arts are an integral part of the academic program tend to do better in school than those students where that is not the case. This study examines home/school factors that contribute most to variance in student learning and achievement and the arts from over 8,000 students in grade 5. The findings suggest in-school arts programs may have less of an impact on student achievement than proposed by previous research.

The Comprehensive Assessment of Leadership for Learning: A Next Generation Formative Evaluation and Feedback System

Recent developments in federal policy have prompted the creation of state evaluation frameworks for principals and teachers that hold educators accountable for effective practices and student outcomes. These changes have created a demand for formative evaluation instruments that reflect current accountability pressures and can be used by schools to focus school improvement and leadership development efforts. The Comprehensive Assessment of Leadership for Learning (CALL) is a next generation, 360-degree on-line assessment and feedback system that reflect best practices in feedback design. Some unique characteristics of CALL include a focus on: leadership distributed throughout the school rather than as carried out by an individual leader; assessment of leadership tasks rather than perceptions of leadership practice; a focus on larger complex systems of middle and high school; and transparency of assessment design. This paper describes research contributing to the design and validation of the CALL survey instrument.

A Step in the Right Direction: Development of the Computerized Assessment for Preschool Social Emotional Learning (CAPSEL)

Invited commentary on "Computerizing Social-Emotional Assessment for School Readiness".

GLMP for automatic assessment of DFS algorithm learning

We describe how to use a Granular Linguistic Model of a Phenomenon (GLMP) to assess e-learning processes. We apply this technique to evaluate algorithm learning using the GRAPHs learning environment.

Statistical Machine Learning for Automatic Assessment of Physical Activity Intensity Using Multi-axial Accelerometry and Heart Rate

This work explores the automatic recognition of physical activity intensity patterns from multi-axial accelerometry and heart rate signals. Data collection was carried out in free-living conditions and in three controlled gymnasium circuits, for a total amount of 179.80 h of data divided into: sedentary situations (65.5%), light-to-moderate activity (17.6%) and vigorous exercise (16.9%). The proposed machine learning algorithms comprise the following steps: time-domain feature definition, standardization and PCA projection, unsupervised clustering (by k-means and GMM) and a HMM to account for long-term temporal trends. Performance was evaluated by 30 runs of a 10-fold cross-validation. Both k-means and GMM-based approaches yielded high overall accuracy (86.97% and 85.03%, respectively) and, given the imbalance of the dataset, meritorious F-measures (up to 77.88%) for non-sedentary cases. Classification errors tended to be concentrated around transients, what constrains their practical impact. Hence, we consider our proposal to be suitable for 24 h-based monitoring of physical activity in ambulatory scenarios and a first step towards intensity-specific energy expenditure estimators

An approach to automatic learning assessment based on the computational theory of perceptions

E-learning systems output a huge quantity of data on a learning process. However, it takes a lot of specialist human resources to manually process these data and generate an assessment report. Additionally, for formative assessment, the report should state the attainment level of the learning goals defined by the instructor. This paper describes the use of the granular linguistic model of a phenomenon (GLMP) to model the assessment of the learning process and implement the automated generation of an assessment report. GLMP is based on fuzzy logic and the computational theory of perceptions. This technique is useful for implementing complex assessment criteria using inference systems based on linguistic rules. Apart from the grade, the model also generates a detailed natural language progress report on the achieved proficiency level, based exclusively on the objective data gathered from correct and incorrect responses. This is illustrated by applying the model to the assessment of Dijkstra’s algorithm learning using a visual simulation-based graph algorithm learning environment, called GRAPHs

Overview of international research in generic competence assessment

The competency assessment is a key issue for improving the quality of teaching and learning within the current European Higher Education Area (EHEA). The aim of this paper is to review the current research on assessment of generic competences, especially through online tools. It has conducted a search of the Web of Knowledge (Thomson Reuters) from keywords. It have been reviewed the abstracts and the results have been classified by time periods, countries and research area. It has selected a set of articles of the period 2010?2012, in which we have analyzed future trends. It is concluded that the research of assessment generic competences is been developing nowadays in educational area, although is still more important in the professional one. Additionally, it is surprising that appears most often used in preuniversity education levels. The academic context has increased research activities over the past five years, with different developments in the Anglo?Saxon countries over that those countries attached to the Bologna Process. The latest reports indicate that the learning competences must meet the individual reality of each person, so that the use of ICTs in their development and evaluation are essential given its immediacy and motivational ability. There is a clear trend towards an evaluation model that includes a 360º specific and generic competences analysis.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Web Classroom Application. Digital technologies to study theory, history and criticism of architecture at Escuela Superior de Arquitectura UPMadrid. The search for some guides to direct the inquiry learning

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