Identifying Variables Important to the Success of K-12 Students in Blended Learning

Kerry Rice; Jui-Long Hung

Identifying Variables Important to the Success of K-12 Students in Blended Learning

Educational Leadership, Research, and Technology

Research output: Contribution to conference › Presentation

Abstract

Presents findings from a blended learning program evaluation, using student end-of-course survey data combined with data mining. Findings suggest that it is possible to apply educational data mining techniques in blended learning classrooms to identify key variables important to the success of learners.

Original language	American English
State	Published - 1 Oct 2015
Event	33st Annual Conference of the Northern Rocky Mountain Educational Research Assocation - Boise, ID Duration: 1 Oct 2015 → …

Conference

Conference	33st Annual Conference of the Northern Rocky Mountain Educational Research Assocation
Period	1/10/15 → …

EGS Disciplines

Educational Methods

Cite this

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title = "Identifying Variables Important to the Success of K-12 Students in Blended Learning",

abstract = " Presents findings from a blended learning program evaluation, using student end-of-course survey data combined with data mining. Findings suggest that it is possible to apply educational data mining techniques in blended learning classrooms to identify key variables important to the success of learners.",

author = "Kerry Rice and Jui-Long Hung",

year = "2015",

month = oct,

day = "1",

language = "American English",

note = "33st Annual Conference of the Northern Rocky Mountain Educational Research Assocation ; Conference date: 01-10-2015",

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T1 - Identifying Variables Important to the Success of K-12 Students in Blended Learning

AU - Rice, Kerry

AU - Hung, Jui-Long

PY - 2015/10/1

Y1 - 2015/10/1

N2 - Presents findings from a blended learning program evaluation, using student end-of-course survey data combined with data mining. Findings suggest that it is possible to apply educational data mining techniques in blended learning classrooms to identify key variables important to the success of learners.

AB - Presents findings from a blended learning program evaluation, using student end-of-course survey data combined with data mining. Findings suggest that it is possible to apply educational data mining techniques in blended learning classrooms to identify key variables important to the success of learners.

M3 - Presentation

T2 - 33st Annual Conference of the Northern Rocky Mountain Educational Research Assocation

Y2 - 1 October 2015

ER -

Identifying Variables Important to the Success of K-12 Students in Blended Learning

Abstract

Conference

EGS Disciplines

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