Beyond Multiple Choice

From Educational Exercises and Activities Community Group

Introduction

The contents of this wiki page are notes and materials intended for use by W3C Educational Exercises and Activities Community Group members attending the Beyond Multiple Choice 2019 Conference.

User input technologies

Text and natural language

Ideas for text-based input include features for students as they compose essays in Web browsers (e.g. spell checking, grammar checking, proofreading, automated essay scoring, and other technologies). These features can be provided via client-side, server-side, school-based or cloud-based technologies.

Ideas for text-based input include enhancing the interoperability between Web browsers and office software applications such as word processors.

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Handwriting

Web standards and technologies can be advanced by adding support for handwriting input. Handwriting input means input components for obtaining InkML from multiple input modalities: e.g. mouse, fingertip or stylus. Handwriting input components can be implemented in a number of ways and can surface in document markup in a number of ways, e.g. <input> or <canvas> elements.

Handwriting recognition, atop handwriting input, can also enhance Web standards and technologies. InkML from handwriting input can be processed client-side or streamed for server-side, school-based or cloud-based handwriting recognition scenarios. Text, mathematics and diagrams can be recognized from InkML.

Context data can enhance the performance of handwriting recognition algorithms.

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Speech

Web standards and technologies can be advanced by adding support for speech input. What is meant by speech input is input components for obtaining audio data from users. This audio data can be either raw or compressed, utilizing audio codecs such as MP3, Opus or Speex.

Speech recognition, atop speech input, can also enhance Web standards and technologies. Audio from speech input components can be processed client-side or streamed for server-side, school-based or cloud-based speech recognition scenarios. Text and mathematics can be recognized from audio data.

Context data can enhance the performance of speech recognition algorithms.

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Imagery and photography

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Video

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3D graphics and interaction

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Multiple modalities

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Dialogue systems

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Intelligent tutoring systems

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Automatic item generation

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Games and simulations

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Augmented and virtual reality

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Item response theory

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Multicriteria analysis

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Multi-device scenarios

Multi-device scenarios include those scenarios with interoperating: smartphones, tablet computers, desktop computers, smart televisions, video game consoles and AR/VR equipment.