Dataset

PISA 2018 data

PISA Indonesia

library(haven)
library(tidyverse)
library(here)

pisa_idn <- read_csv(here("dataset", "pisa_idn.csv"))

Rows: 12098 Columns: 1118
-- Column specification --------------------------------------------------------
Delimiter: ","
chr  (14): CNT, CYC, NatCen, STRATUM, ST011D17TA, ST011D18TA, ST011D19TA, OC...
dbl (462): CNTRYID, CNTSCHID, CNTSTUID, SUBNATIO, OECD, ADMINMODE, LANGTEST_...
lgl (642): LANGTEST_PAQ, ST196Q02HA, ST196Q03HA, ST196Q04HA, ST196Q05HA, ST1...

i Use `spec()` to retrieve the full column specification for this data.
i Specify the column types or set `show_col_types = FALSE` to quiet this message.

skor <- pisa_idn %>% select(ST184Q01HA, ST185Q01HA, ST185Q02HA, ST185Q03HA, ST034Q01TA,PV1MATH,PV2MATH,PV3MATH,PV4MATH,PV5MATH,
                        PV6MATH, PV7MATH, PV8MATH, PV9MATH, PV10MATH, CNTSTUID, CNTSCHID, CNTRYID) %>%
  filter(CNTSCHID == 36000271 | 
        CNTSCHID == 36000272 |
        CNTSCHID == 36000273 |
        CNTSCHID == 36000274 |
        CNTSCHID == 36000275 |
        CNTSCHID == 36000276 |
        CNTSCHID == 36000277 |
        CNTSCHID == 36000278 |
        CNTSCHID == 36000279 |
        CNTSCHID == 36000280 |
        CNTSCHID == 36000285 |
        CNTSCHID == 36000286 |
        CNTSCHID == 36000287 |
        CNTSCHID == 36000288 |
        CNTSCHID == 36000289 |
        CNTSCHID == 36000290 |
        CNTSCHID == 36000291 |
        CNTSCHID == 36000292 |
        CNTSCHID == 36000293 |
        CNTSCHID == 36000294) %>%
  mutate(math=(PV1MATH+PV2MATH+PV3MATH+PV4MATH+PV5MATH+
                 PV6MATH+PV7MATH+PV8MATH+PV9MATH+PV10MATH)/10) %>%
  mutate(growth1=recode(ST184Q01HA, "1" = "4", "2" = "3", "3" = "2", "4"="1")) %>%
  mutate(sekolah=CNTSCHID) %>%
  mutate(growth=ST184Q01HA)

Growth mindset dan skor matematika
20 sekolah
700+ siswa

Jumlah siswa per sekolah

skor <- skor %>% filter(growth != "NA")
knitr::kable(count(skor, CNTSCHID))

CNTSCHID	n
36000271	21
36000272	39
36000273	40
36000274	29
36000275	39
36000276	35
36000277	30
36000278	38
36000279	40
36000280	36
36000285	38
36000286	39
36000287	39
36000288	38
36000289	39
36000290	40
36000291	40
36000292	39
36000293	36
36000294	38

Ringkasan Statistik

skor %>% 
  group_by(CNTSCHID) %>% 
  summarise(mean = mean(math, na.rm = T), 
            SD = sd(math, na.rm = T), 
            miss = mean(is.na(math))) %>% 
  mutate_if(is.numeric, ~round(., 2)) %>% 
  print(n = 50)

# A tibble: 20 x 4
   CNTSCHID  mean    SD  miss
      <dbl> <dbl> <dbl> <dbl>
 1 36000271  328.  49.4     0
 2 36000272  506.  43.4     0
 3 36000273  425.  59.8     0
 4 36000274  302.  39.4     0
 5 36000275  479.  48.4     0
 6 36000276  325.  41.6     0
 7 36000277  367.  42.3     0
 8 36000278  437.  42.4     0
 9 36000279  347.  56.6     0
10 36000280  343.  47.4     0
11 36000285  454.  33.2     0
12 36000286  500.  41.8     0
13 36000287  422.  51.0     0
14 36000288  371.  73.7     0
15 36000289  307.  54.8     0
16 36000290  393.  64.2     0
17 36000291  442.  54.2     0
18 36000292  475.  44.3     0
19 36000293  362.  48.8     0
20 36000294  381.  60.8     0