{"title":"HEURISTIC ANALYSIS OF THE NATIVE LANGUAGE CURRICULUM OF SUCCESSFUL COUNTRIES IN PISA AND TURKEY BY USING ANFIS","authors":"Dilan Kalaycı Alas, Necati Demir","doi":"10.24200/jonus.vol8iss2pp95-122","DOIUrl":null,"url":null,"abstract":"Background and Purpose: Current study analyzes the native language teaching programs of successful countries in the International Student Assessment Program (PISA) by using the Adaptive Neuro-Fuzzy Inference System (ANFIS). \n \nMethodology: The learning outcomes of listening, speaking, reading and writing skills included in the native language teaching programs of the selected countries were examined. The codes were determined under each skill appropriate to these outcomes. Numerical results of the code numbers have been obtained. The PISA results were correlated with the code and the number of learning outcomes for each skill based on data obtained from the native language teaching programs of the related countries. The converging parallel mixed method was adopted by combining document analysis and statistical analysis technique, ANFIS to evaluate language skills. \n \nFindings: PISA, the OECD’s International Student Assessment Program is a measure of student performance in mathematics, science and literacy. According to results obtained by ANFIS, coupled relations between language skills would have significant influence on the success in PISA while implementing all language skills resulted in irrelevant relationship. \n \nContributions: Current study implements an artificial intelligence technique, ANFIS as a guide to contribute for the development and re-preparation of native language teaching programs. \n \nKeywords: ANFIS, native language curriculum, artificial intelligence modelling techniques, successful countries, PISA. \n \nCite as: Kalaycı Alas, D., & Demir, N. (2023). Heuristic analysis of the native language curriculum of successful countries in PISA and Turkey by using ANFIS. Journal of Nusantara Studies, 8(2), 95-122. http://dx.doi.org/10.24200/jonus.vol8iss2pp95-122","PeriodicalId":16687,"journal":{"name":"Journal of Nusantara Studies (JONUS)","volume":"1 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nusantara Studies (JONUS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24200/jonus.vol8iss2pp95-122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"AREA STUDIES","Score":null,"Total":0}
引用次数: 0
Abstract
Background and Purpose: Current study analyzes the native language teaching programs of successful countries in the International Student Assessment Program (PISA) by using the Adaptive Neuro-Fuzzy Inference System (ANFIS).
Methodology: The learning outcomes of listening, speaking, reading and writing skills included in the native language teaching programs of the selected countries were examined. The codes were determined under each skill appropriate to these outcomes. Numerical results of the code numbers have been obtained. The PISA results were correlated with the code and the number of learning outcomes for each skill based on data obtained from the native language teaching programs of the related countries. The converging parallel mixed method was adopted by combining document analysis and statistical analysis technique, ANFIS to evaluate language skills.
Findings: PISA, the OECD’s International Student Assessment Program is a measure of student performance in mathematics, science and literacy. According to results obtained by ANFIS, coupled relations between language skills would have significant influence on the success in PISA while implementing all language skills resulted in irrelevant relationship.
Contributions: Current study implements an artificial intelligence technique, ANFIS as a guide to contribute for the development and re-preparation of native language teaching programs.
Keywords: ANFIS, native language curriculum, artificial intelligence modelling techniques, successful countries, PISA.
Cite as: Kalaycı Alas, D., & Demir, N. (2023). Heuristic analysis of the native language curriculum of successful countries in PISA and Turkey by using ANFIS. Journal of Nusantara Studies, 8(2), 95-122. http://dx.doi.org/10.24200/jonus.vol8iss2pp95-122