Curriculum pacing: A new approach to discover instructional practices in classrooms

Nirmal Patel, Aditya Sharma, Collin Sellman, Derek Lomas

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

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Abstract

This paper examines the use of “pacing plots” to represent variations in student learning sequences within a digital curriculum. Pacing plots are an intuitive and flexible data visualizations that have a potential for revealing the diversity of blended classroom instructional models. By using curriculum pacing plots, we identified several common implementation patterns in real-world classrooms. After analyzing two years’ worth of data from over 150,000 students in a digital math curriculum, we found that a PCA and K-Means clustering approach was able to discover pedagogically relevant instructional practices.

Original languageEnglish
Title of host publicationIntelligent Tutoring Systems - 14th International Conference, ITS 2018, Proceedings
EditorsJulita Vassileva, Roger Nkambou, Roger Azevedo
PublisherSpringer
Pages345-351
Number of pages7
ISBN (Print)9783319914633
DOIs
Publication statusPublished - 2018
Event14th International Conference on Intelligent Tutoring Systems, ITS 2018 - Montreal, Canada
Duration: 11 Jun 201815 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10858 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th International Conference on Intelligent Tutoring Systems, ITS 2018
CountryCanada
CityMontreal
Period11/06/1815/06/18

Keywords

  • Clustering
  • Curriculum analytics
  • Curriculum pacing
  • Sequence mining
  • Visualization

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