In thelayc/laycca:

---

knitr::opts_chunk$set(fig.width = 12, fig.height = 8, fig.path = 'Figs/',
                      echo = FALSE, warning = FALSE, message = FALSE, digits = 1)

source('./R/utils.R')
source('./R/01_load.R')
source('./R/02_clean.R')
source('./R/03_analysis.R')

NWEA administration

Number of students who took the NWEA test for each period

r knitr::kable(nwea_sample)

Number of students who took the test more than twice

r knitr::kable(nwea_frequency)

Retention:

• r enrolled students enrolled at the Career Academy for school year 2014-15 (They had at least one NWEA score).
• r retained students had at least an academic pre-test and post-test
• Retention rate: r scales::percent(retained/enrolled)

Students' progress

Using NWEA scores

Out of the r sum(df$n) students who had matching NWEA pre / post tests, r scales::percent(df$percent[df$change == 'positive']) showed academic progress, as measured by the NWEA RIT Reading scale.

cohort_progress

On average, students showed an increase of r round(stat_test$estimate, 1) on the RIT scale between their pre and post test scores.
* r scales::percent(attributes(stat_test$conf.int)$conf.level) confidence interval: [r round(stat_test$conf.int[1], 1) ; r round(stat_test$conf.int[2], 1)]

scores_distribution

Appendix

This chart is not directly related to the PMF, but it gives a quick overview of students who made progress, and how much.

indiv_progress

thelayc/laycca documentation built on May 31, 2019, 9:48 a.m.