5.3 Assignment: Business Simulation Final Report to CEO

Tonio12070514

TEMPLATE_Poster5.pptx

Home >Business & Finance homework help >Operations Management homework help >5.3 Assignment: Business Simulation Final Report to CEO

Abstract

In a response to intervention (RTI) model, educators in both general and special education use curriculum-based measurement (CBM) oral reading fluency (ORF) assessments across grades to monitor progress of students receiving reading intervention.

Researchers have explored average growth in ORF and found decelerating, nonlinear growth rates across grade-levels (e.g., Christ et al., 2010; Nese et al., 2012; Nese et al., 2013).

In this study, we examine growth for those students in Grades 1-8 specifically identified for reading intervention and receiving regular progress monitoring, and explore two growth models to determine (a) the within-year ORF growth, and (b) the growth across Tier II/III intervention.

Results

Table 1: Trajectory fixed effect parameters (intercept and slopes) were similar across Within-year and Tier II/II growth models.

Figure 1: The first testing occasion for Tier II/II students was nearly always in the early fall for all grades but first (winter).

Figure 2

Decelerating Tier II/II growth in Grades 1-5.

Linear Tier II/II growth in Grades 6-8.

Growth of progress monitored students similar to that of easyCBM 20th percentile group, but with lower intercepts and greater yearly gains in most grades.

Describing the Reading Fluency Growth of Progress Monitored Students

Joseph F. T. Nese, Julie Alonzo, Gerald Tindal

National Center on Assessment and Accountability for Special Education, 2013

References

Christ, T. J., Silberglitt, B., Yeo, S., & Cormier, D. (2010). Curriculum-based measurement of oral reading: An evaluation of growth rates and seasonal effects among students served in general and special education. School Psychology Review, 39, 447-462.

Muthén, L. K., & Muthén, B. O. (1998-2013). Mplus user’s guide (7th ed.). Los Angeles, CA: Muthén & Muthén.

Nese, J. F. T., Biancarosa, G., Anderson, D., Lai, C. F., & Tindal, G. (2012). Within-year oral reading fluency with CBM: A comparison of models. Reading and Writing, 25, 887-915. DOI: 10.1007/s11145-011-9304-0

Nese, J. F. T., Biancarosa, G., Cummings, K., Kennedy, P., Alonzo, J., Tindal, G. (2013). In search of average growth: Describing within-year oral reading fluency growth for Grades 1-8. DOI: 10.1016/j.jsp.2013.05.006

For More Information

Please contact Joe Nese: [email protected]. More information on this and related projects can be obtained at http://ncaase.com.

Funding Source

This project was funded through the National Center on Assessment and Accountability for Special Education (NCAASE) grant (R324C110004) from the U.S. Department of Education, Institute of Education Sciences. Opinions expressed do not necessarily reflect the opinions or policies of the U.S. Department of Education.

Selection Rules for

ORF Progress Monitoring Sample

Step	Rules			Students	Scores
	Original data			139,165	495,174
1)	Delete out of range scores (e.g., < 0 and > 365)			-	495,112
2)	Delete students in grades other than 1-8			137,848	-
3)	Delete students with any instance of off-grade-level testing			129,617	-
4)	Delete students who scored > 30th percentile on first benchmark or progress monitoring assessment			35,923	-
5)	Delete scores from assessments > 20th testing occasion			-	145,478
	Delete “invalid” scores			-	-
	If two scores are less than two weeks (14 days) apart AND are different by > 35 WCPM, delete the score that is least like adjacent scores.				57,787
	Based on the following rule of growth:
	[(Expected growth per week+SEg) * 2 weeks)]	+	( SEM * 2 weeks)	-	-
	[(1.5wcpm+1.0SEg) * 2]	+	(15*2)	-	-
	5	+	30	-	-
6)	Take the median of scores that are within 7 days keep scores that are >7 and <28 days of each other, and delete scores that > 28 days apart.				34,550
7)	Delete students with < 3 progress monitoring tests			5,373	30,628

Method

We conducted two latent growth models for each grade using Mplus version 7.11 (Muthén & Muthén, 1998-2013):

Within-year growth, where the time metric was the calendar year, such that the intercept was either late September or early October;

Tier II/III growth, where the time metric was the assessment occasion, such that the intercept was the first assessment occasion.

Discussion

Tier II/III interventions begin in the fall; less identification of at-risk students beyond fall.

Implications for winter/spring benchmarks in RTI system: Lost opportunities for educators and students for lack of RTI system training?

As hypothesized, growth rates are lower than 50th percentile and average empirical trajectories (e.g., Nese et al., 2013), except for Grades 4 & 5.

In all grades but sixth, linear growth rates greater in magnitude for the Tier II/II metric than the Within-year metric.

Tenuous evidence for effective interventions.

Limitations

Selected sample very specific.

Intervention information (if any) unknown.

Table 1. Fixed Effects and Within- and Between-Model Correlations for the Quadratic Within-year and Tier II/II Growth Models

Figure 1. Percent of Students First ORF Assessment for Each Month Across Grades 1-8

Figure 2. Predicted mean ORF scores in words correct per minute (wcpm) by grade based on the Within-year and Tier II/II time metrics, and observed mean ORF benchmark scores at the 20th and 50th percentiles for the easyCBM system.

Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 0.18518518518518501 4.6296296296296324 15 10.555555555555561 15.18518518518519 42.777777777777779 3.333333333333333 4.6296296296296324 3.518518518518519 0.18518518518518501 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 23.654995730145181 60.717335610589259 2.8181041844577281 1.3663535439795049 1.622544833475662 3.4158838599487589 2.2203245089666979 2.3911187019641331 1.7933390264731 0 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 19.915254237288131 68.898305084745772 1.525423728813559 1.271186440677966 1.0169491525423719 3.2203389830508469 2.28813559322034 1.101694915254237 0.76271186440677996 0 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 21.80257510729615 68.154506437768219 3.4334763948497828 1.459227467811159 1.2017167381974241 1.1158798283261799 0.94420600858369097 1.373390557939913 0.42918454935622302 8.5836909871244704E-2 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 23.80446333687566 65.249734325185969 5.4197662061636578 1.912858660998938 0.95642933049946899 1.381509032943677 0.42507970244420801 0.42507970244420801 0.42507970244420801 0 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 14.72081218274111 57.360406091370542 16.24365482233501 1.522842639593909 0 4.0609137055837561 3.0456852791878171 1.522842639593909 1.522842639593909 0 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 33.644859813084103 59.813084112149497 0 0.934579439252336 2.8037383177570101 0 0 0 0 0 0 Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun 25 31.944444444444439 2.7777777777777799 31.944444444444439 4.1666666666666661 0 0 0 2.7777777777777799 0 0

First ORF assessment (%)