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Variation in district learning outcomes overtime: Which district covariates matter?

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Abstract:

Research on correlates of student achievement from developing countries in general, and India in particular, is yet limited. In this paper we use a unique, nationally representative, longitudinal data set from India recently collected by Assessment Survey Evaluation Research (ASER), New Delhi to identify important district level covariates of student achievement.

The analysis is conducted at the district level using the Growth Curve Analysis (GCA) technique. Specifically, we first identify districts that have shown improvements and deceleration in terms of student math and reading outcomes from 2006-2009. Next, we use various district level covariates of infrastructure, community participation, and economic and social well-being to identify what about the district background may be able to explain the gains and declines in overall district performance over time.
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Association:
Name: 55th Annual Conference of the Comparative and International Education Society
URL:
http://www.cies.us


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URL: http://citation.allacademic.com/meta/p493018_index.html
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MLA Citation:

Chudgar, Amita. and Miller, Karyn. "Variation in district learning outcomes overtime: Which district covariates matter?" Paper presented at the annual meeting of the 55th Annual Conference of the Comparative and International Education Society, Fairmont Le Reine Elizabeth, Montreal, Quebec, Canada, <Not Available>. 2014-11-26 <http://citation.allacademic.com/meta/p493018_index.html>

APA Citation:

Chudgar, A. and Miller, K. "Variation in district learning outcomes overtime: Which district covariates matter?" Paper presented at the annual meeting of the 55th Annual Conference of the Comparative and International Education Society, Fairmont Le Reine Elizabeth, Montreal, Quebec, Canada <Not Available>. 2014-11-26 from http://citation.allacademic.com/meta/p493018_index.html

Publication Type: Panel Paper
Abstract: Research on correlates of student achievement from developing countries in general, and India in particular, is yet limited. In this paper we use a unique, nationally representative, longitudinal data set from India recently collected by Assessment Survey Evaluation Research (ASER), New Delhi to identify important district level covariates of student achievement.

The analysis is conducted at the district level using the Growth Curve Analysis (GCA) technique. Specifically, we first identify districts that have shown improvements and deceleration in terms of student math and reading outcomes from 2006-2009. Next, we use various district level covariates of infrastructure, community participation, and economic and social well-being to identify what about the district background may be able to explain the gains and declines in overall district performance over time.


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