Education Statistics: Education Attainment| World DataBank The Aggregation Rules function defines the methodologies to be used when deriving custom aggregates. These rules apply only to custom country groups you have created. They do not apply to official groups presented in your selected database. For each selected series, choose your Aggregation Rule and Weight Indicator (if needed) from the corresponding drop-down boxes. Aggregation Rules include: 1. Note 1: In none of the above methodologies are missing values imputed. Note 2: Aggregation results apply only to your custom-defined groups and do not reflect official World Bank aggregates based on regional and income classification of economies.
Educational needs of the 16–19 age group: A sociological perspective This paper attempts to draw a sociological profile of young people in Europe between 15–19 years of age. It points out changes in the socialisation functions of the three institutions, family, school and peer group. The second half of the article surveys quantitative aspects of the educational performance of this age group, pointing out similarities and dissimilarities between the various European countries. The final part is concerned with the effects of inequality of opportunity (socio-cultural, sex-based, and regional) on educational achievement. It is evident that education for this age group is in a state of ferment — new aspects include: the growing importance attached to guidance, the abolition of traditional types of examinations in many countries, the individualisation of instruction, the increased emphasis on technological training, and the greater range of options. In diesem Aufsatz wird versucht, ein soziologisches Bild von Fünfzehn- bis Neunzehnjährigen in Europa zu geben.
Knewton : la big data au service de l’éducation | Les startups de l’éducation La « big data », terme qui désigne l’explosion des données générées et les défis à relever pour les analyser, a déboulé dans le paysage du Web au cours des deux dernières années : tous les secteurs sont concernés, des transports en commun au marketing, en passant par l’éducation. Je vous propose donc un portrait de Knewton, une start-up américaine spécialisée dans la production et l’analyse de la « big data pédagogique ». Pour son fondateur, « l’éducation est même le plus gros marché de la data au monde ». « Nous vivons dans un monde ou la personnalisation est devenue une norme. Améliorer l’orientation des étudiants grâce à des algorithmes et l’analyse de données quantitatives ? Knewton a développé une technologie « d’adaptative learning » : l’adaptative learning (au XXIème siècle, on ne rougit plus de pointer vers Wikipédia mes chers lecteurs) consiste à adapter le contenu d’un cours en fonction des spécificités de chaque étudiant ou groupe d’étudiants. Si vous souhaitez approfondir :
2Dsearch Education Data Model (National Forum on Education Statistics). Strategies for building education software systems. The National Education Data Model is a conceptual but detailed representation of the education information domain. The Education Data Model strives to be a shared understanding among all education stakeholders as to what information needs to be collected and managed at the local level in order to enable effective instruction of students and superior leadership of schools. NEDM is a conceptual data model and NOT a data collection. The Common Education Data Standards (CEDS) project is a national collaborative effort to develop voluntary, common data standards for a key set of education data elements to streamline the exchange, comparison, and understanding of data within and across P-20W institutions and sectors.
Manuscripts Online Les outils du scientifique des données - Université Johns-Hopkins | Coursera À propos du cours In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. Please note: we are offering a Chinese version of this course starting March 2, re-running on a monthly basis and sharing the same schedule with the English version. Programme du cours Upon completion of this course you will be able to identify and classify data science problems. Expérience recommandée No prior backround required. Format du cours This course consists of weekly video lectures, weekly quizzes, and a final peer-assessed project. How do the courses in the Data Science Specialization depend on each other? Will I get a Statement of Accomplishment after completing this class? How does this course fit into the Data Science Specialization? Russian subtitles for this course are courtesy of IBS.
PDF Drive - Search and download PDF files for free. Etudiants, emparez-vous des données éducatives ouvertes Education, school, Ziven, ShutterStock Initiative du Département de l’éducation américain, MyData Button vise à connecter les «consommateurs éducatifs» avec les données qui sont collectées sur eux. L’idée est d’inciter toute l’industrie de l’éducation (écoles, universités, compagnies de tests, fournisseurs de services, etc.) à offrir un service de téléchargement de données dans un format standardisé, lisible par des machines, pour les «consommateurs» qu’ils servent. Ainsi on espère stimuler la création d’une nouvelle vague d’applications utiles et créer un nouveau marché d’opportunités pour la persévérance scolaire, la planification financière, l’apprentissage personnalisé, la préparation de leçons, etc. Ultimement, c’est l’étudiant qui décide à qui il transmet les données recueillies. À un autre niveau, ce format vise également à faciliter la mobilité des étudiants, spécialement ceux qui changent d’école et de ville durant une année ou d’une année à l’autre. Références
Konik Method for Making Useful Notes Once upon a time, I shared a rough sketch of what my process for active and passive research looked like. It looked something like this: But I never had a chance to write out an explanation of how these pieces fit together... until this week. Of course, everybody always asks what tools and philosophies and methods I use to accomplish this relatively straightforward process of making and using useful notes, so here's my best attempt to write it all down. This is not intended to be a guide to "doing things my way" so much as an attempt to explain how and I why I do things, in hopes that seeing the metacognition behind the workflow helps at least one person improve their life in some small way. Motivations: Start with the WHY I generally come at the process of note making from one of three angles. Pleasure Reading Problem Solving The next most common reason I approach information to make notes about is that I need to solve a problem. Pursuing Serendipity With Videos With People First, a caveat.
Invitational Summit on Educational Data Visualization | May 6-7, 2014 Zotero Storage Zotero Storage provides online storage space for your Zotero files, allowing you to synchronize PDFs, images, web snapshots, and other files among all your devices, share your Zotero attachments in group libraries, and access files via your online library on zotero.org. Individual Pricing In addition to individual storage subscriptions, we also offer storage plans for labs and institutions. Group Libraries Zotero groups can also use Zotero Storage at no additional charge. More Information Zotero is a project of the Corporation for Digital Scholarship, a nonprofit organization dedicated to the development of software and services for researchers and cultural heritage institutions. Development, maintenance, support, and infrastructure costs for Zotero services are funded by storage subscriptions from individuals and organizations. Still have questions?