Personalized Education through Individualized Pathways and Resources to Adaptive Control Theory-Inspired Scientific Education (iPRACTISE): Proof-of-Concept Studies for Designing and Evaluating Personalized Education

IF 2.2 Q3 Social Sciences

Journal of Statistics Education Pub Date : 2024-01-08 DOI:10.1080/26939169.2024.2302181

Sy-Miin Chow, Jungmin Lee, Jonathan Park, Prabhani Kuruppumullage Don, Tracey Hammel, Michael N. Hallquist, Eric A. Nord, Zita Oravecz, Heather L. Perry, Lawrence M. Lesser, Dennis K. Pearl

引用次数: 0

Abstract

Personalized educational interventions have been shown to facilitate successful and inclusive statistics, mathematics, and data science (SMDS) in higher education through timely and targeted reduct...

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通过适应性控制理论启发的科学教育的个性化途径和资源进行个性化教育 (iPRACTISE)：设计和评估个性化教育的概念验证研究

个性化教育干预措施已被证明能够通过及时和有针对性地减少高等教育中统计、数学和数据科学（SMDS）的学习成本，促进高等教育的成功和包容性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Statistics Education EDUCATION, SCIENTIFIC DISCIPLINES-

CiteScore

1.20

自引率

0.00%

发文量

审稿时长

12 weeks

期刊介绍： The "Datasets and Stories" department of the Journal of Statistics Education provides a forum for exchanging interesting datasets and discussing ways they can be used effectively in teaching statistics. This section of JSE is described fully in the article "Datasets and Stories: Introduction and Guidelines" by Robin H. Lock and Tim Arnold (1993). The Journal of Statistics Education maintains a Data Archive that contains the datasets described in "Datasets and Stories" articles, as well as additional datasets useful to statistics teachers. Lock and Arnold (1993) describe several criteria that will be considered before datasets are placed in the JSE Data Archive.