2019\u5e746\u670819\u65e5\u306bTALIS\uff08\u56fd\u969b\u6559\u54e1\u6307\u5c0e\u74b0\u5883\u8abf\u67fb\uff092018\u5e74\u8abf\u67fb\u7d50\u679c\u304c\u516c\u8868\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n
TALIS - The OECD Teaching and Learning International Survey (OECD)\nhttp:\/\/www.oecd.org\/education\/talis\/<\/a>\n\n\n\u300cOECD\u56fd\u969b\u6559\u54e1\u6307\u5c0e\u74b0\u5883\u8abf\u67fb\uff08TALIS\uff092018\u8abf\u67fb\u7d50\u679c\u300d\uff08\u6587\u90e8\u79d1\u5b66\u7701\uff09\nhttp:\/\/www.mext.go.jp\/b_menu\/toukei\/data\/Others\/1349189.htm<\/a>\n\n\n\u300cOECD \u56fd\u969b\u6559\u54e1\u6307\u5c0e\u74b0\u5883\u8abf\u67fb(TALIS) 2018\u5e74\u5831\u544a\u66f8\u306b\u3064\u3044\u3066\u300d\uff08\u56fd\u7acb\u6559\u80b2\u653f\u7b56\u7814\u7a76\u6240\uff09\nhttps:\/\/www.nier.go.jp\/kenkyukikaku\/talis\/index.html<\/a>\n\n\n\u300e\u6559\u54e1\u74b0\u5883\u306e\u56fd\u969b\u6bd4\u8f03 OECD\u56fd\u969b\u6559\u54e1\u6307\u5c0e\u74b0\u5883\u8abf\u67fb\uff08TALIS\uff092018\u5831\u544a\u66f8 \u5b66\u3073\u7d9a\u3051\u308b\u6559\u54e1\u3068\u6821\u9577\u300f\uff08\u304e\u3087\u3046\u305b\u3044\uff09\nhttps:\/\/shop.gyosei.jp\/products\/detail\/10041<\/a><\/pre>\n\u8abf\u67fb\u7d50\u679c\u306b\u3064\u3044\u3066\u306e\u6982\u8981\u3084\u5206\u6790\u306f\uff0c\u4e0a\u8a18\u306e\u30b5\u30a4\u30c8\u304b\u3089\u8cc7\u6599\u3084\u5831\u544a\u66f8\u3092\u5165\u624b\u3057\u3066\u3044\u305f\u3060\u304f\u3068\u3057\u3066\uff0c\u4eca\u56de\u306fOECD\u304c\u63d0\u4f9b\u3057\u3066\u3044\u308b\u8abf\u67fb\u56de\u7b54\u30c7\u30fc\u30bf\u3092R\u3067\u5229\u7528\u3057\u3088\u3046\u3068\u3044\u3046\u306e\u304c\u672c\u984c\u3002\u4ee5\u524d\uff0cPISA2015\u3067\u6311\u6226\u3057\u305f\u3053\u3068\u3092TALIS2018\u3067\u3082\u3084\u3063\u3066\u307f\u3088\u3046\u3068\u3044\u3046\u3053\u3068\u306b\u306a\u308a\u307e\u3059\u3002\uff08R\u3067PISA2015<\/a>\uff0fR\u3067PISA2015\u3008\u305d\u306e\uff12\u3009<\/a>\uff0fR\u3067PISA2015\u3008\u30b0\u30e9\u30d5\u3009<\/a>\uff09<\/p>\n
—<\/p>\n
OECD\u306eTALIS 2018\u30b5\u30a4\u30c8\u3067\u516c\u958b\u3055\u308c\u3066\u3044\u308b\u30c7\u30fc\u30bf\u306f\u3053\u3061\u3089<\/p>\n
TALIS 2018 Data\nhttp:\/\/www.oecd.org\/education\/talis\/talis-2018-data.htm<\/a><\/pre>\n\u305d\u308c\u305e\u308c\u306e\u7d71\u8a08\u51e6\u7406\u30d1\u30c3\u30b1\u30fc\u30b8\uff08SAS, SPSS, STATA\uff09\u7528\u306e\u30c7\u30fc\u30bf\u304c\u914d\u5e03\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u3068\u308a\u3042\u3048\u305aSPSS\u7528\u306e\u30d5\u30a1\u30a4\u30eb\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u307e\u3059\u3002<\/p>\n
\u4eca\u56de\u306f\u300cSPSS_international.zip\u300d\u3092\u5148\u306b\u8997\u3044\u3066\u307f\u308b\u3053\u3068\u306b\u3057\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u6821\u9577\nACGINTT3.sav\uff08\u5c0f\u5b66\u6821\uff09 \nBCGINTT3.sav\uff08\u4e2d\u5b66\u6821\uff09\nCCGINTT3.sav\uff08\u9ad8\u7b49\u5b66\u6821\uff09\n\u6559\u54e1\nATGINTT3.sav\uff08\u5c0f\u5b66\u6821\uff09\nBTGINTT3.sav\uff08\u4e2d\u5b66\u6821\uff09\nCTGINTT3.sav\uff08\u9ad8\u7b49\u5b66\u6821\uff09<\/pre>\n\u3069\u306e\u30d5\u30a1\u30a4\u30eb\u304c\u4f55\u306b\u8a72\u5f53\u3059\u308b\u306e\u304b\u8aac\u660e\u304c\u6dfb\u3048\u3089\u308c\u3066\u3044\u306a\u3044\u306e\u3067\uff0c\u4e2d\u8eab\u304b\u3089\u5224\u65ad\u3057\u307e\u3059\u3002<\/p>\n
\u8cea\u554f\u6587\u3092\u53c2\u7167\u3059\u308b\u305f\u3081\u306b\u306f\u8cea\u554f\u7d19\u30c7\u30fc\u30bf\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u307e\u3059\u3002<\/p>\n
TALIS 2018 questionnaires\nhttp:\/\/www.oecd.org\/education\/school\/talis2018questionnaires.htm<\/a><\/pre>\n\u56fd\u7acb\u6559\u80b2\u653f\u7b56\u7814\u7a76\u6240\u3067\u516c\u958b\u3055\u308c\u3066\u3044\u308b\u65e5\u672c\u8a9e\u7248\u3084\u5404\u56fd\u306e\u8cea\u554f\u7528\u7d19\u306f\uff0cOECD\u306e\u56fd\u969b\u7248\u3092\u30d9\u30fc\u30b9\u306b\u4f5c\u6210\u3055\u308c\u3066\u3044\u308b\u306e\u3067\u554f\u984c\u756a\u53f7\u306e\u5bfe\u5fdc\u306f\u81ea\u5206\u3067\u8abf\u3079\u307e\u3059\u3002<\/p>\n
\u3068\u308a\u3042\u3048\u305a\uff0c\u5c0f\u5b66\u6821\u6559\u54e1\u7528\u8cea\u554f\u7d19\u300cATGINTT3\u300d\u306e\u554f\u984c\u756a\u53f7\u3068\u82f1\u8a9e\u30fb\u65e5\u672c\u8a9e\u306e\u8cea\u554f\u6587\u5bfe\u5fdc\u30c7\u30fc\u30bf\u3092\u4f5c\u6210\u3057\u307e\u3057\u305f\u306e\u3067\u3053\u308c\u3092\u4f7f\u3044\u307e\u3059\u3002\u305d\u308c\u304b\u3089\u56fd\u540d\u3082\u65e5\u672c\u8a9e\u306e\u65b9\u304c\u3044\u3044\u3067\u3057\u3087\u3046\u3002<\/p>\n
ATGINTT3 \u8cea\u554f\u6587\u30c7\u30fc\u30bf\nhttp:\/\/www.edufolder.jp\/files\/talis2018\/ATGINTT3_Q.csv<\/a>\n\n\u56fd\u5225\u30b3\u30fc\u30c9\u3068\u56fd\u540d\u30c7\u30fc\u30bf\nhttp:\/\/www.edufolder.jp\/files\/talis2018\/ISO3166.csv<\/a><\/pre>\n\u5c0f\u5b66\u6821\u6559\u54e1\u7528\u8cea\u554f\u7d19\u300cATGINTT3\u300d\u7528\u306e\u307f\u3067\u3059\u304c\uff0c\u6700\u4f4e\u9650\u5fc5\u8981\u306a\u30c7\u30fc\u30bf\u306f\u63c3\u3044\u307e\u3057\u305f\u3002<\/p>\n
\u672c\u6765\u306a\u3089\u3070\uff0c\u8cea\u554f\u9805\u76ee\u306b\u5bfe\u5fdc\u3057\u305f\u56de\u7b54\u9805\u76ee\u30c7\u30fc\u30bf\u3082\u4f5c\u6210\u3057\u3066\uff0c\u56de\u7b54\u3082\u65e5\u672c\u8a9e\u3067\u5206\u304b\u308a\u3084\u3059\u304f\u8868\u793a\u3067\u304d\u308b\u3068\u3088\u3044\u306e\u3067\u3059\u304c\uff0c\u30c7\u30fc\u30bf\u4f5c\u6210\u306e\u624b\u9593\u306e\u554f\u984c\u306a\u306e\u3067\uff0c\u3068\u308a\u3042\u3048\u305a\u5f8c\u306b\u56de\u3057\u307e\u3059\u3002<\/p>\n
—<\/p>\n
\u3055\u3066\uff0cR\u3068R Studio\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3066\u304a\u304d\u307e\u3059\u3002\u3053\u308c\u306f\u4ee5\u524d\u306ePISA2015\u3067\u306e\u8a18\u9332\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
\u4eca\u56de\u3082\u6700\u521d\u306b\u4e00\u5ea6\u8aad\u307f\u8fbc\u3080\u305f\u3081\u306e\u300ctalis2018_base.R\u300d\u3068\u8cea\u554f\u30b0\u30e9\u30d5\u3092\u751f\u6210\u3059\u308b\u6bce\u306b\u5b9f\u884c\u3059\u308b\u300ctalis2018_script.R\u300d\u3068\u3044\u3046\uff12\u3064\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u30d5\u30a1\u30a4\u30eb\u306b\u5206\u3051\u3066\u4f5c\u6210\u3057\u307e\u3057\u305f\u3002<\/p>\n
\u8cea\u554f\u9805\u76ee\u3054\u3068\u306b\u56de\u7b54\u306e\u6570\u304c\u7570\u306a\u308b\u306e\u3067\uff0c\u6bce\u5ea6\u4fee\u6b63\u3057\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3068\u3044\u3046\u8ab2\u984c\u306f\u6b8b\u3063\u3066\u3044\u307e\u3059\u304c\uff0c\u3068\u308a\u3042\u3048\u305a\u52d5\u4f5c\u3059\u308b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n
\u300ctalis2018_base.R\u300d<\/p>\n
# talis2018_base.R\n# For TALIS2018\n# K.RIN\n#\n\n#\u30e9\u30a4\u30d6\u30e9\u30ea\u8aad\u307f\u8fbc\u307f\nlibrary(readr)\nlibrary(tidyverse)\nlibrary(plyr)\nlibrary(haven)\n\n#\u30c7\u30fc\u30bf\u30d5\u30a1\u30a4\u30eb\u8aad\u307f\u8fbc\u307f\nATGINTT3 <- read_sav(\"ATGINTT3.sav\")\n\nquestion_items <- read_csv(\"ATGINTT3_Q.csv\", col_names = TRUE, col_types = list(col_character(), col_character(), col_character()))\n\ncountry_code <- read_csv(\"ISO3166.csv\", col_names = TRUE, col_types = list(col_character(), col_character(), col_character(), col_character()))<\/pre>\n\u300ctalis2018_script.R\u300d<\/p>\n
#\u00a0talis2018_script.R\n# For TALIS2018\n# K.RIN\n#\n# \u2605\u8a2d\u5b9a\u9805\u76ee\uff08\u2605\u30de\u30fc\u30af\uff09\n# \u30fb\u8cea\u554fID\uff08\u300cselected_question = \" \"\u300d\u306e\u90e8\u5206\uff09\n# \u30fb\u8868\u793a\u9806\uff08\u300corder_setting = 1\u300d\u306e\u90e8\u5206\uff09\n# \u30fb\u8868\u793a\u9806\u306e\u7d44\u5408\u308f\u305b\uff08\u300cmutate('list_order' = `1`)\u300d\u306e\u90e8\u5206\uff09\n\nlibrary(plyr)\nlibrary(tidyverse)\n\n#\u2605\u8cea\u554f\u756a\u53f7\nselected_question = \"TT3G55I\"\n\n#\u2605\u8868\u793a\u9806\uff08\u964d\u98061,\u6607\u9806-1\uff09\norder_setting = 1\n\n#\u30e9\u30d9\u30eb\ny_label <- \"\u30d1\u30fc\u30bb\u30f3\u30c8 %\"\nx_label <- \"\u56fd\"\nlegend_label <- \"\u56de\u7b54\"\n\n#\u8cea\u554f\u6587\u30c7\u30fc\u30bf\u304b\u3089\u8cea\u554f\u756a\u53f7\u306b\u8a72\u5f53\u3059\u308b\u8cea\u554f\u6587\u3092\u62bd\u51fa\nif (is.na(question_items$ja[grep(selected_question, question_items$q_no, value = FALSE, fixed = FALSE)][[1]])) {\nq_title <- paste(\"\u3010\", selected_question,\"\u3011\")\n} else { #\u8cea\u554f\u6587\u304c\u7a7a\u6b04\u3067\u306a\u3051\u308c\u3070\u2026\nq_title <- paste(\"\u3010\", selected_question,\"\u3011\", question_items$ja[grep(selected_question, question_items$q_no, value = FALSE, fixed = FALSE)][[1]])\n}\n\n#\u56de\u7b54\u30c7\u30fc\u30bf\u62bd\u51fa\nstu_tmp <- subset(ATGINTT3, ATGINTT3[[selected_question]] != \"NaN\") #\u7121\u56de\u7b54\u3092\u9664\u304f\uff08\u8cea\u554f\u3057\u3066\u306a\u3044\u56fd\u3082\u3042\u308b\u305f\u3081\uff09\ndata_ans <- table(stu_tmp[[\"CNTRY\"]],stu_tmp[[selected_question]]) #\u8cea\u554f\u756a\u53f7\u306e\u30c7\u30fc\u30bf\u3092\u62bd\u51fa\n\nans_df <- as_tibble(data_ans,validate = FALSE) #df\uff08\u30c7\u30fc\u30bf\u30d5\u30ec\u30fc\u30e0\uff09\u3078\u5909\u63db\ncolnames(ans_df) <- c(\"CNT\", \"answer\", \"count\") #df\u306e\u5217\u30e9\u30d9\u30eb\u8a2d\u5b9a\nans_wide <- spread(ans_df, answer, count) #\u6a2a\u9577df\u3078\u5909\u63db\n\n#\u884c\u756a\u53f7\u3092\u30c7\u30fc\u30bf\u306b\u5909\u63db\u3057\u3066\u5217\u3068\u3057\u3066\u8ffd\u52a0\n#\u2605\u30b0\u30e9\u30d5\u8868\u793a\u9806\u3092\u6c7a\u3081\u308b\u56de\u7b54\u9805\u76ee\u306e\u6570\u5024\u5408\u8a08\u3092\u5217\u3068\u3057\u3066\u8ffd\u52a0\uff3b +`2`+`3`+`4`+`5`\uff3d\nans_wide <- ans_wide %>% rownames_to_column('num') %>% mutate('list_order' = `2` + `3`)\n\n#num\u5217\u306e\u6570\u5b57\u3092\u6587\u5b57\u304b\u3089\u6570\u5024\u306b\u30e2\u30fc\u30c9\u5909\u63db\nmode(ans_wide$num) <- \"integer\"\ntypeof(ans_wide$num)\n\n#\u56fd\u30b3\u30fc\u30c9\u3092\u3082\u3068\u306b\u56fd\u540d\u3092country_name\u5217\u3068\u3057\u3066\u8ffd\u52a0\nans_wide <- ddply(ans_wide, \"CNT\", transform, country_name = country_code$Name_ja[grep(CNT, country_code$Alpha3)])\n#\u5217\u30e9\u30d9\u30eb\u306e\u8a2d\u5b9a\ncolnames(ans_wide) <- c(\"num\", \"CNT\", \"1\", \"2\", \"3\", \"list_order\", \"country_name\") #\u203b\u56de\u7b54\u9805\u76ee3\u3064\u306e\u5834\u5408\uff08, \"4\"\uff09\n\n#\u7e26\u9577df\u306b\u5909\u63db\nans_df <- gather(ans_wide, answer,count,-num,-CNT,-list_order,-country_name)\n\n#\u56fd\u30b3\u30fc\u30c9\u3068\u56de\u7b54\u3067\u4e26\u3079\u66ff\u3048\nans_df <- arrange(ans_df, desc(CNT), desc(answer))\n\n#\u30d1\u30fc\u30bb\u30f3\u30c8\u8a08\u7b97\uff08\u63cf\u753b\u8a08\u7b97\u7528\u30d1\u30fc\u30bb\u30f3\u30c8\uff09\nans_df <- ddply(ans_df, \"CNT\", transform, percent = count \/ sum(count) * 100, 0.1)\n#\u5c0f\u6570\u70b9\u4ee5\u4e0b\uff11\u6841\u51e6\u7406\uff08\u8868\u793a\u7528\u30d1\u30fc\u30bb\u30f3\u30c8\uff09\ncountry_ans <- ddply(ans_df, \"CNT\", transform, percent_rounded = round_any(count \/ sum(count) * 100, 0.1))\n#\u6570\u5024\u5408\u8a08\u3057\u305f\u5206\u306e\u30d1\u30fc\u30bb\u30f3\u30c8\u6570\u5024\u3092\u8a08\u7b97\uff08\u8868\u793a\u9806\u5e8f\u7528\u30d1\u30fc\u30bb\u30f3\u30c8\uff09\ncountry_ans <- ddply(country_ans, \"CNT\", transform, list_percent_order = round_any(list_order \/ sum(count) * 100 * order_setting, 0.1))\n\n\n#\u30e9\u30d9\u30eb\u4f4d\u7f6e\u8a08\u7b97\ncountry_ans <- ddply(country_ans, \"CNT\", transform, percent_label_y = cumsum(percent)-0.5*percent)\n\n#\u30d5\u30a9\u30f3\u30c8\u6e96\u5099\uff08Mac\u7528\uff09\n#\nquartzFonts(HiraKaku = quartzFont(rep(\"HiraginoSans-W3\", 4)))\npar(family = \"HiraKaku\")\n\n#\u30b0\u30e9\u30d5\u63cf\u753b\u6e96\u5099\n#\ngraph <- ggplot(country_ans, aes(x = reorder(country_name, list_percent_order), y = percent, fill = answer)) + \nggtitle(sprintf(\"%s\", q_title)) + #\u30bf\u30a4\u30c8\u30eb\nylab(y_label) + #\u56fd\u30e9\u30d9\u30eb\nxlab(x_label) + #\u30d1\u30fc\u30bb\u30f3\u30c8\u30e9\u30d9\u30eb\ncoord_flip(expand = FALSE) + \ngeom_bar(stat = \"identity\", position='stack') + \ngeom_text(aes(y = percent_label_y, \nlabel = paste(format(percent_rounded, nsmall = 1),\"\")), color = \"white\", size = 4) + #\u30c7\u30fc\u30bf\u30e9\u30d9\u30eb\nscale_y_reverse(breaks = c(100.0,75.0,50.0,25.0,0.0), \nlabels = c(\"0%\",\"25%\",\"50%\",\"75%\",\"100%\")) + #\u6a2a\u8ef8\nscale_color_manual(values = rainbow(7)) + #\u30ab\u30e9\u30fc\ntheme_bw() + \ntheme(plot.margin = margin(1, 1, 1, 1, \"cm\"),\nplot.title = element_text(family = \"HiraKaku\", size = 10), \nplot.caption = element_text(family = \"HiraKaku\", size = 10),\nlegend.title = element_text(family = \"HiraKaku\", size = 10), \nlegend.text = element_text(family = \"HiraKaku\", size = 7), \naxis.title = element_text(family = \"HiraKaku\", size = 9), \naxis.title.y = element_text(angle = 0, vjust = 0.5), \naxis.text.x = element_text(family = \"HiraKaku\", size = 9), \naxis.text.y = element_text(family = \"HiraKaku\", size = 10))\n\nprint(graph) #\u30b0\u30e9\u30d5\u63cf\u753b<\/pre>\n\u4ee5\u4e0a\u3067\u300cPlots\u300d\u30a6\u30a4\u30f3\u30c9\u30a6\u306b\u30b0\u30e9\u30d5\u304c\u63cf\u753b\u3055\u308c\u308b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n
\u307e\u305f\u8a73\u7d30\u306f\u3008\u305d\u306e\uff12\u3009\u3092\u4e88\u5b9a\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"
2019\u5e746\u670819\u65e5\u306bTALIS\uff08\u56fd\u969b\u6559\u54e1\u6307\u5c0e\u74b0\u5883\u8abf\u67fb\uff092018\u5e74\u8abf\u67fb\u7d50\u679c\u304c\u516c\u8868\u3055\u308c\u307e\u3057\u305f\u3002 TALIS – The OECD Teaching and Learning International Survey (OE […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[2,5],"tags":[162,160,161,125],"class_list":["post-3552","post","type-post","status-publish","format-standard","hentry","category-resources","category-topics","tag-oecd","tag-r","tag-talis","tag-125"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/p4WGyZ-Vi","jetpack_likes_enabled":false,"_links":{"self":[{"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=\/wp\/v2\/posts\/3552","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3552"}],"version-history":[{"count":8,"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=\/wp\/v2\/posts\/3552\/revisions"}],"predecessor-version":[{"id":3560,"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=\/wp\/v2\/posts\/3552\/revisions\/3560"}],"wp:attachment":[{"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3552"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3552"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.con3.com\/rinlab\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3552"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}