Identification of Students in Late Elementary Grades With Reading Difficulties
Piecewise latent class growth analysis (LCGA) was used to examine growth patterns in reading comprehension and passage reading fluency on easyCBM, a popular formative assessment system. Unlike conventional growth modeling, LCGA takes into account the heterogeneity of growth and may provide reliable...
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University of Oregon
2012
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ndltd-uoregon.edu-oai-scholarsbank.uoregon.edu-1794-124062019-05-17T16:34:59Z Identification of Students in Late Elementary Grades With Reading Difficulties Lai, Cheng-Fei Lai, Cheng-Fei Kamata, Akihito Curriculum-based measures Latent class growth analysis Reading comprehension Reading fluency Piecewise latent class growth analysis (LCGA) was used to examine growth patterns in reading comprehension and passage reading fluency on easyCBM, a popular formative assessment system. Unlike conventional growth modeling, LCGA takes into account the heterogeneity of growth and may provide reliable predictions for later development. Because current methods for classifying students are still questionable, this modeling technique could be a viable alternative classification method to identifying students at risk for reading difficulty. Results from this study suggested heterogeneity in reading development. The latent classes and growth trajectories from the LCGA models were found to align closely with easyCBM's risk rating system. However, results from one school district did not fully generalize across another. The implications for future research on examining growth in reading are discussed. 2012-10-26T04:02:10Z 2012-10-26T04:02:10Z 2012 Electronic Thesis or Dissertation http://hdl.handle.net/1794/12406 en_US Creative Commons BY-NC-ND 4.0-US University of Oregon |
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en_US |
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Curriculum-based measures Latent class growth analysis Reading comprehension Reading fluency |
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Curriculum-based measures Latent class growth analysis Reading comprehension Reading fluency Lai, Cheng-Fei Lai, Cheng-Fei Identification of Students in Late Elementary Grades With Reading Difficulties |
description |
Piecewise latent class growth analysis (LCGA) was used to examine growth patterns in reading comprehension and passage reading fluency on easyCBM, a popular formative assessment system. Unlike conventional growth modeling, LCGA takes into account the heterogeneity of growth and may provide reliable predictions for later development. Because current methods for classifying students are still questionable, this modeling technique could be a viable alternative classification method to identifying students at risk for reading difficulty. Results from this study suggested heterogeneity in reading development. The latent classes and growth trajectories from the LCGA models were found to align closely with easyCBM's risk rating system. However, results from one school district did not fully generalize across another. The implications for future research on examining growth in reading are discussed. |
author2 |
Kamata, Akihito |
author_facet |
Kamata, Akihito Lai, Cheng-Fei Lai, Cheng-Fei |
author |
Lai, Cheng-Fei Lai, Cheng-Fei |
author_sort |
Lai, Cheng-Fei |
title |
Identification of Students in Late Elementary Grades With Reading Difficulties |
title_short |
Identification of Students in Late Elementary Grades With Reading Difficulties |
title_full |
Identification of Students in Late Elementary Grades With Reading Difficulties |
title_fullStr |
Identification of Students in Late Elementary Grades With Reading Difficulties |
title_full_unstemmed |
Identification of Students in Late Elementary Grades With Reading Difficulties |
title_sort |
identification of students in late elementary grades with reading difficulties |
publisher |
University of Oregon |
publishDate |
2012 |
url |
http://hdl.handle.net/1794/12406 |
work_keys_str_mv |
AT laichengfei identificationofstudentsinlateelementarygradeswithreadingdifficulties AT laichengfei identificationofstudentsinlateelementarygradeswithreadingdifficulties |
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1719190903364517888 |