Identification of Students in Late Elementary Grades With Reading Difficulties

dc.contributor.advisorKamata, Akihitoen_US
dc.contributor.authorLai, Cheng-Feien_US
dc.creatorLai, Cheng-Feien_US
dc.date.accessioned2012-10-26T04:02:10Z
dc.date.available2012-10-26T04:02:10Z
dc.date.issued2012
dc.description.abstractPiecewise 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.en_US
dc.identifier.urihttps://hdl.handle.net/1794/12406
dc.language.isoen_USen_US
dc.publisherUniversity of Oregonen_US
dc.rightsCreative Commons BY-NC-ND 4.0-USen_US
dc.subjectCurriculum-based measuresen_US
dc.subjectLatent class growth analysisen_US
dc.subjectReading comprehensionen_US
dc.subjectReading fluencyen_US
dc.titleIdentification of Students in Late Elementary Grades With Reading Difficultiesen_US
dc.typeElectronic Thesis or Dissertationen_US

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