为教育工作者设计的基于模板的间隔重复学习解决方案

Ayman Hajja, Austin J. Hunt
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摘要

这篇创新实践工作进展的论文介绍了一个免费的基于api的间隔重复教育平台。间隔重复,或间隔重复学习,是学习者通过反复接触分散在时间中的信息来提高长期知识记忆的一种技术,传统形式是抽抽卡问题。自19世纪首次被研究以来,在不同时间内反复接触信息的概念,以及它对提高人类记忆力的有效性,一直在不断发展。最近,新的移动和网络学习应用程序一直在使用间隔重复算法和技术来提高学生的记忆力;尽管在学生中越来越受欢迎,但我们认为这些系统存在某些缺陷,我们在这项工作中着手解决这些问题。首先,现有的解决方案主要只针对学生作为用户,而没有提供以教师为中心的功能来补充他们的教学;通过包含以教师为中心的界面和报告机制,我们探索了关于间隔重复学习对学生记忆的影响的潜在见解。其次,据我们所知,目前流行的间隔重复算法纯粹是基于问题的;也就是说,重新曝光延迟只计算每个问题,而不是每个主题。为了解决这个问题,我们提出了一个新的问题模板框架,1)可以根据代表主题的问题组来评估和分析知识保留,而不仅仅是特定的问题,2)为教师提供了一个工具,可以通过创建随机模板来有效地管理学习材料,从而为每个学生提供类似但独特的问题集。第三,现有的解决方案广泛使用间隔重复来帮助记忆,而没有利用它来帮助概括;我们的目标是强调间隔重复模型的潜力,以促进一般技能的保留(可在不同的挑战中转移)。最后,也是最重要的是,我们寻求提供一个免费的应用程序编程接口(API),可以与任何自定义的移动或web用户界面集成,为研究社区提供一个高度集成的工具包,用于探索关于间隔重复学习的新问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Template-Based Spaced Repetition Learning Solution Designed for Educators
This Innovative Practice Work in Progress paper introduces a freely available API-based platform for spaced repetition education. Spaced repetition, or spaced repetition learning, is a technique used by learners to improve long-term knowledge retention through repeated exposure to information spread out through time, traditionally in the form of flashcard questions. The concept of repeated exposure to information at varying lengths of time, and its effectiveness to improve human memory, has been evolving since first being investigated in the 19th century. Recently, new mobile and web learning applications have been employing spaced repetition algorithms and techniques to improve students' retention; although increasingly popular amongst students, we believe there are certain drawbacks to these systems that we set out to address in this work. First, existing solutions primarily target only students as users without providing instructor-focused functionality for supplementing their teaching; we explore, through the inclusion of instructor-focused interfaces and reporting mechanisms, potential insights to be gained about the effect of spaced repetition learning on student retention. Secondly, to the best of our knowledge, current popular spaced repetition algorithms are purely question-based; that is, re-exposure delays are calculated only per question, and not per topic. To address this, we present a novel question-templating framework that 1) enables knowledge retention to be assessed and analyzed in terms of groups of questions representing topics instead of only specific questions, and 2) provides a tool for instructors to efficiently manage learning material by creating randomizable templates to feed on the fly generation of similar-but-unique question sets for each student. Third, existing solutions widely employ spaced repetition to aid memorization without leveraging it to aid generalization; we aim to highlight a potential for the spaced repetition model to promote retention of generalized skills (transferable among different challenges). Lastly, and most importantly, we seek to provide a free application programming interface (API) that can be integrated with any custom mobile or web user interface to provide the research community with a highly integrable toolkit for exploring new questions about spaced repetition learning.
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