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ID 48748
file
title alternative
A Multiple Hurdle Model for Students’ Conversions in Online English Learning Materials
creator
abstract
The present study provides a multiple hurdle model which computationally explains complex patterns of students’ engagement levels in online learning materials. It has been empirically known that online learning log data such as login counts and the number of learning contents studied by students quite often deviate from ordinary discrete probabilistic distributions such as a Poisson distribution and a negative binomial distribution. As an underlying mechanism of this empirical fact, the present study posits that there are latent sub-processes to obtain learning outcomes, which we call micro conversions, and between them, the model also assumes hurdles that students clear and fail. This modeling framework was statistically implemented as a finite mixture distribution model that mixes a hurdle negative binomial distribution and an ordinary negative binomial distribution. Using Bayesian modeling with the Hamiltonian Monte Carlo method, the model was fitted to the real login data of 899 students in Hiroshima university and achieved a relatively good fit.
journal title
Hiroshima Studies in Language and Language Education
issue
Issue 23
start page
45
end page
61
date of issued
2020-03-01
publisher
広島大学外国語教育研究センター
issn
1347-0892
ncid
language
jpn
nii type
Departmental Bulletin Paper
HU type
Departmental Bulletin Papers
DCMI type
text
format
application/pdf
text version
publisher
rights
Copyright (c) 2020 広島大学外国語教育研究センター
department
Institute for Foreign Language Research and Education
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