Predicting students’ writing performance on the NAEP from student- and state-level variables

Predicting students’ writing performance on the NAEP from student- and state-level variables This study examines the relationship between students’ demographic background and their experiences with writing at school, the alignment between state and National Assessment of Educational Progress (NAEP) direct writing assessments, and students’ NAEP writing performance. The study utilizes primary data collection via content analysis of writing assessment prompts and rubrics and secondary analysis with NAEP data through hierarchical linear modeling. Results indicate students from states with writing tests more similar to the NAEP do not perform significantly better than students from states with writing tests less similar to the NAEP. Rather, student demographic characteristics, including gender, ethnicity, SES, disability status, and English learner status significantly predict NAEP writing performance, as do factors related to frequency of writing across subject areas, frequency of writing for varied purposes, frequency of writing process use, and computer use in writing. The implications of the findings for writing instruction are discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Reading and Writing Springer Journals

Predicting students’ writing performance on the NAEP from student- and state-level variables

Loading next page...
 
/lp/springer_journal/predicting-students-writing-performance-on-the-naep-from-student-and-a0LSnpIIcY
Publisher
Springer Journals
Copyright
Copyright © 2016 by Springer Science+Business Media Dordrecht
Subject
Linguistics; Language and Literature; Psycholinguistics; Education, general; Neurology; Literacy
ISSN
0922-4777
eISSN
1573-0905
D.O.I.
10.1007/s11145-016-9698-9
Publisher site
See Article on Publisher Site

Abstract

This study examines the relationship between students’ demographic background and their experiences with writing at school, the alignment between state and National Assessment of Educational Progress (NAEP) direct writing assessments, and students’ NAEP writing performance. The study utilizes primary data collection via content analysis of writing assessment prompts and rubrics and secondary analysis with NAEP data through hierarchical linear modeling. Results indicate students from states with writing tests more similar to the NAEP do not perform significantly better than students from states with writing tests less similar to the NAEP. Rather, student demographic characteristics, including gender, ethnicity, SES, disability status, and English learner status significantly predict NAEP writing performance, as do factors related to frequency of writing across subject areas, frequency of writing for varied purposes, frequency of writing process use, and computer use in writing. The implications of the findings for writing instruction are discussed.

Journal

Reading and WritingSpringer Journals

Published: Oct 12, 2016

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off