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  • Online Education Using Learning Objects
    Online Education Using Learning Objects

    'E-learning is integral to on-site education institutions worldwide, and the rapid explosion of interest in the subject means that this timely, cutting-edge book will be an instant and indispensable resource.Among educators, the development of reusable learning objects made accessible via the internet is ever more important to teaching and learning.This book provides a comprehensive look at a state-of-the-art online education, and presents advice on the creation, adaptation and implementation of learning objects and metadata.Including articles written by some of the leading innovators in the field, this book takes the reader through: designing effective learning objects; creating learning objects; transforming existing content into reusable learning objects; building a metadata management system.This book will be essential reference material for learning technologists, course developers at learning institutions, postgraduate students, teachers and learners in the field of e-learning.'

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  • Distance Learning and Online Education
    Distance Learning and Online Education


    Price: 108.50 £ | Shipping*: 0.00 £
  • Effective Personal Tutoring in Higher Education
    Effective Personal Tutoring in Higher Education

    This is an important title for all academic and professional staff within higher education (HE) who have a personal tutoring, student support or advising role. It examines key topics in relation to tutoring including definitions, coaching, core values and skills, boundaries, monitoring students, undertaking group and individual tutorials and the need to measure impact.Throughout, the text encourages reflection and the need to think critically about the role of the personal tutor. A scholarly and practical text, it comprehensively brings together relevant academic literature to inform tutoring practice as well as contextualising the role within the HE policy and quality assurance landscape. Please also see The Higher Education Personal Tutor’s and Advisor’s Companion where the themes of this book are illustrated by real life case studies form universities around the UK.

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  • Initial Teacher Education at Scale : Quality Conundrums
    Initial Teacher Education at Scale : Quality Conundrums

    Debates about what constitutes quality in initial teacher education have resulted in a series of quality conundrums that have to be unravelled by teacher educators.Using the lens of scale and adopting a new approach to understanding quality, this book draws upon empirical research into five large-scale, high-quality university-based teacher education providers in Australia, Canada, England, New Zealand and the US.The resulting model of initial teacher education practice shows how ideological concepts and accountability structures around teacher education are in constant tension with operational realities.The book explores how successful large-scale providers have reconciled those tensions and conundrums to ensure their provision is consistently high quality.The accounts also present a robust defence for university-based teacher education. The practice-based accounts of how tensions around quality and scale are being reconciled reveal the competing discourses around teacher professionalism, research and the role of the university in teacher education.The analysis presented promises to change the way we view high-quality teacher education across all providers and international contexts, not just those of large scale. This book will be of great interest to teacher educators, policymakers and educational leaders.

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  • What is the scale in mathematics?

    In mathematics, scale refers to the ratio of the size of an object in a drawing or model to the size of the actual object. It is used to represent objects that are too large or too small to be drawn at actual size. Scale is often represented as a fraction or ratio, such as 1:100 or 1/4, where the first number represents the size of the drawing or model and the second number represents the actual size of the object. Understanding scale is important in fields such as architecture, engineering, and map-making to accurately represent objects in a smaller or larger format.

  • How do you calculate the scale in mathematics?

    In mathematics, the scale factor is calculated by comparing the measurements of an object in the original figure to the measurements of the corresponding object in the enlarged or reduced figure. The scale factor is found by dividing the length of a side in the enlarged or reduced figure by the length of the corresponding side in the original figure. This ratio gives the scale factor by which the original figure has been enlarged or reduced.

  • How can you convert a scale in mathematics?

    To convert a scale in mathematics, you can use a proportion. First, determine the ratio of the original scale to the desired scale. Then, set up a proportion with the original scale on one side and the desired scale on the other side. Finally, solve for the unknown value by cross-multiplying and dividing. This will give you the equivalent value in the new scale.

  • Why don't the children use the online learning resources?

    There could be several reasons why the children are not using online learning resources. Some possible reasons could include lack of access to technology or internet connectivity, difficulty navigating the online platforms, lack of motivation or engagement with the material, or preference for traditional in-person learning methods. It is important to understand the specific barriers that are preventing the children from using online resources in order to address them effectively and promote their learning.

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  • Data Management in Large-Scale Education Research
    Data Management in Large-Scale Education Research

    Research data management is becoming more complicated.Researchers are collecting more data, using more complex technologies, all the while increasing the visibility of our work with the push for data sharing and open science practices.Ad hoc data management practices may have worked for us in the past, but now others need to understand our processes as well, requiring researchers to be more thoughtful in planning their data management routines. This book is for anyone involved in a research study involving original data collection.While the book focuses on quantitative data, typically collected from human participants, many of the practices covered can apply to other types of data as well.The book contains foundational context, instructions, and practical examples to help researchers in the field of education begin to understand how to create data management workflows for large-scale, typically federally funded, research studies.The book starts by describing the research life cycle and how data management fits within this larger picture.The remaining chapters are then organized by each phase of the life cycle, with examples of best practices provided for each phase.Finally, considerations on whether the reader should implement, and how to integrate those practices into a workflow, are discussed. Key Features:Provides a holistic approach to the research life cycle, showing how project management and data management processes work in parallel and collaborativelyCan be read in its entirety, or referenced as needed throughout the life cycleIncludes relatable examples specific to education researchIncludes a discussion on how to organize and document data in preparation for data sharing requirementsContains links to example documents as well as templates to help readers implement practices

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  • Stochastic Optimization for Large-scale Machine Learning
    Stochastic Optimization for Large-scale Machine Learning

    Advancements in the technology and availability of data sources have led to the `Big Data' era.Working with large data offers the potential to uncover more fine-grained patterns and take timely and accurate decisions, but it also creates a lot of challenges such as slow training and scalability of machine learning models.One of the major challenges in machine learning is to develop efficient and scalable learning algorithms, i.e., optimization techniques to solve large scale learning problems. Stochastic Optimization for Large-scale Machine Learning identifies different areas of improvement and recent research directions to tackle the challenge.Developed optimisation techniques are also explored to improve machine learning algorithms based on data access and on first and second order optimisation methods. Key Features:Bridges machine learning and Optimisation. Bridges theory and practice in machine learning. Identifies key research areas and recent research directions to solve large-scale machine learning problems. Develops optimisation techniques to improve machine learning algorithms for big data problems. The book will be a valuable reference to practitioners and researchers as well as students in the field of machine learning.

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  • Digital Pocket Scale 100G-0.01G Mini Scale Electronic Gauge Scale Electronic Scale Table Scale
    Digital Pocket Scale 100G-0.01G Mini Scale Electronic Gauge Scale Electronic Scale Table Scale

    Digital Pocket Scale 100G-0.01G Mini Scale Electronic Gauge Scale Electronic Scale Table Scale

    Price: 4.01 € | Shipping*: 1.99 €
  • Digital Pocket Scale 100G-0.01G Mini Scale Electronic Gauge Scale Electronic Scale Table Scale
    Digital Pocket Scale 100G-0.01G Mini Scale Electronic Gauge Scale Electronic Scale Table Scale

    Digital Pocket Scale 100G-0.01G Mini Scale Electronic Gauge Scale Electronic Scale Table Scale

    Price: 4.01 € | Shipping*: 1.99 €
  • How does determining the scale factor and scale work?

    Determining the scale factor involves comparing the measurements of corresponding sides of two similar figures. The scale factor is the ratio of the lengths of the sides of the two figures. To find the scale factor, you can divide the length of a side of the larger figure by the length of the corresponding side of the smaller figure. The scale is the ratio of the dimensions of the actual object to the dimensions of the model or drawing. It is used to accurately represent the size of an object in a smaller or larger form.

  • How does one determine the scale factor and scale?

    To determine the scale factor, one must compare the measurements of corresponding sides of two similar figures. The scale factor is calculated by dividing the length of a side in the larger figure by the length of the corresponding side in the smaller figure. The scale is then determined by using the scale factor to create a ratio between the measurements of the figures. This ratio can be used to accurately resize or recreate the figures at a different scale.

  • What is the difference between interval scale and ratio scale?

    The main difference between interval scale and ratio scale is the presence of a true zero point. Ratio scale has a true zero point, meaning that a value of zero indicates the absence of the quantity being measured. Interval scale, on the other hand, does not have a true zero point, and a value of zero does not necessarily indicate the absence of the quantity being measured. Additionally, ratio scale allows for meaningful ratios to be calculated, while interval scale does not.

  • Can a regular scale be used as a kitchen scale?

    Yes, a regular scale can be used as a kitchen scale as long as it has the capacity to measure in smaller increments typically used in cooking, such as grams or ounces. However, kitchen scales are specifically designed for food measurements and often come with features like tare function, which allows you to zero out the weight of the container. So while a regular scale can be used in a pinch, a kitchen scale may be more convenient and accurate for cooking and baking purposes.

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