Predicting and Improving Memory Retention: Psychological Theory Matters in the Big Data Era
Predicting and Improving Memory Retention: Psychological Theory Matters in the Big Data Era
复制标题
预测和提高记忆保留：心理学理论在大数据时代很重要
DOI：
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复制
发表时间：
2016
期刊：
影响因子：
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通讯作者：
Robert V. Lindsey
中科院分区：
文献类型：
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作者：
M. Mozer;Robert V. Lindsey
认知心理学长期以来的目标是理解人类记忆的机制，并期望这种理解将产生支持学习和记忆的实用技术。虽然研究见解为学生和教育工作者提供了定性建议，但我们提出了一种提供定量、个性化指导的补充方法。我们的方法综合了理论驱动和数据驱动的方法。心理学理论描述了群体成员之间共享的人类记忆的基本机制，而机器学习技术则利用对群体的观察来推断个体。我们认为，尽管有大数据的力量，心理学理论对模型提供了本质的约束。我们提出了遗忘和间隔练习的模型，以预测个别学生对特定材料的动态时变知识状态。我们将这些模型整合到检索练习软件中，以帮助学生复习以前掌握的材料。在一项为期一年的中学外语课程干预中，我们展示了系统评估对长期教育成果的价值，但更具体地说，适应性评估的价值是利用来自学习者群体的数据，根据个人的学习历史和过去的表现提出个性化建议。
Cognitive psychology has long had the aim of understanding mechanisms of human memory, with the expectation that such an understanding will yield practical techniques that support learning and retention. Although research insights have given rise to qualitative advice for students and educators, we present a complementary approach that offers quantitative, individualized guidance. Our approach synthesizes theory-driven and data-driven methodologies. Psychological theory characterizes basic mechanisms of human memory shared among members of a population, whereas machine-learning techniques use observations from a population to make inferences about individuals. We argue that despite the power of big data, psychological theory provides essential constraints on models. We present models of forgetting and spaced practice that predict the dynamic time-varying knowledge state of an individual student for specific material. We incorporate these models into retrieval-practice software to assist students in reviewing previously mastered material. In an ambitious year-long intervention in a middle-school foreign language course, we demonstrate the value of systematic review on long-term educational outcomes, but more specifically, the value of adaptive review that leverages data from a population of learners to personalize recommendations based on an individual’s study history and past performance.
DOI：
10.1037/h0087426
发表时间：
2003-09-01
影响因子：
1.3
作者：
Masson, MEJ;Loftus, GR
通讯作者：
Loftus, GR
影响因子：
2.5
作者：
Ridgeway, Karl;Mozer, Michael C.;Bowles, Anita R.
通讯作者：
Bowles, Anita R.
影响因子：
2.6
作者：
Benjamin AS;Tullis J
通讯作者：
Tullis J