Categorizing students into groups according to their learning attitudes based on cluster analysis

Tests are frequently used in any field of science education to assess students’ knowledge and skills. In this paper, we briefly introduce the results of the analysis on the test data of twelve grade students in Mongolia. These analyses are based on two approaches- classical test theories and cluster...

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Main Authors: Janchiv Shinebayar, Badarch Jadamba, Ochirbat Altangoo, Raash Namjildagva, Tumurbaatar Ganbaatar, Ravdandorj Togoo, Sukhbaatar Batchuluun
Format: Article
Language:English
Published: Mongolian National University of Education 2022-12-01
Series:Lavai
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Online Access:https://mongoliajol.info/index.php/Lavai/article/view/2493
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author Janchiv Shinebayar
Badarch Jadamba
Ochirbat Altangoo
Raash Namjildagva
Tumurbaatar Ganbaatar
Ravdandorj Togoo
Sukhbaatar Batchuluun
author_facet Janchiv Shinebayar
Badarch Jadamba
Ochirbat Altangoo
Raash Namjildagva
Tumurbaatar Ganbaatar
Ravdandorj Togoo
Sukhbaatar Batchuluun
author_sort Janchiv Shinebayar
collection DOAJ
description Tests are frequently used in any field of science education to assess students’ knowledge and skills. In this paper, we briefly introduce the results of the analysis on the test data of twelve grade students in Mongolia. These analyses are based on two approaches- classical test theories and cluster analysis. It is less important to measure learners’ attitudes through only one subject. We believe that students’ attitudes towards learning academic subjects and acquiring scientific education can be defined through their achievement data on their knowledge and skills on multiple subjects. According to learning attitudes, most researchers analyze the data using a survey that includes “Likert” scale statements and questions. In this paper, we have categorized students' learning attitudes based on their results of academic performances that assess only students’ knowledge and skills. Students are categorized into five groups according to their learning attitudes based on the two-step clustering components. Кластер анализ ашиглан суралцагчдыг сурах хандлагаар ангилсан нь Хураангуй Суралцагчдын мэдлэг, чадварыг үнэлэхэд ихэвчлэн тестийг ашигладаг. Уг өгүүлэлд Сүхбаатар аймгийн II сургуулийн 12-р ангийн суралцагчдын улсын шалгалтын үр дүнгийн өгөгдөлд классик тестийн онол, кластер анализ зэрэг аргыг хэрэглэн анализ хийсэн үр дүнг толилуулж байна. Ангийн суралцагчдын сурах хандлагын хэв маягийг зөвхөн нэг хичээлийн эцсийн дүнгээр хэмжих нь ач холбогдол багатай. Ихэнх судлаачид суралцагчдыг сурах хандлагаар ангилахдаа лайкертын хэмжээс бүхий өгүүлбэрүүд болон асуултуудыг агуулсан судалгааны асуулгаар цуглуулсан өгөгдөлд анализ хийдэг. Харин, бид бүхэн зөвхөн суралцагчдын мэдлэг, чадварыг үнэлэх академик гүйцэтгэлийн үр дүнгээр суралцагчдыг сурах хандлагаар ангилсан нь онцлогтой. Шинжлэх ухааны буюу академик боловсролтой холбоотой сурах хандлагыг олон хичээлийн мэдлэг, чадварын цогц байдлаар авч үзэх нь зүйтэй гэдгийг баталж, кластерчлалын хоёр алхамт аргад тулгуурлан суралцагчдыг сурах хандлагаар 5 бүлэгт ангиллаа. Түлхүүр үг: Классик тестийн онол, кластер анализ, сурах хандлага, үнэлгээ, даалгаврын хариултын онол
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publishDate 2022-12-01
publisher Mongolian National University of Education
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spelling doaj-art-e577f83a298c40b9a28463cb3e3f459c2025-08-20T02:15:05ZengMongolian National University of EducationLavai2410-45072959-93342022-12-01182721310.5564/lavai.v18i27.24932444Categorizing students into groups according to their learning attitudes based on cluster analysisJanchiv Shinebayar0Badarch Jadamba1Ochirbat Altangoo2Raash Namjildagva3Tumurbaatar Ganbaatar4Ravdandorj Togoo5Sukhbaatar Batchuluun6School of Educational Studies, Mongolian National University of Education, Ulaanbaatar, MongoliaSchool of Educational Studies, Mongolian National University of Education, Ulaanbaatar, MongoliaSchool of mathematics and natural sciences, Mongolian National University of Education, Ulaanbaatar, MongoliaSchool of Educational Studies, Mongolian National University of Education, Ulaanbaatar, MongoliaSchool of mathematics and natural sciences, Mongolian National University of Education, Ulaanbaatar, MongoliaLaboratory of theory and high energy physics, Institute of Physics and Technology, Mongolian Academy of Sciences, Ulaanbaatar, MongoliaSecondary school of Baruun-Urt soum, School No. 2, Sukhbaatar, MongoliaTests are frequently used in any field of science education to assess students’ knowledge and skills. In this paper, we briefly introduce the results of the analysis on the test data of twelve grade students in Mongolia. These analyses are based on two approaches- classical test theories and cluster analysis. It is less important to measure learners’ attitudes through only one subject. We believe that students’ attitudes towards learning academic subjects and acquiring scientific education can be defined through their achievement data on their knowledge and skills on multiple subjects. According to learning attitudes, most researchers analyze the data using a survey that includes “Likert” scale statements and questions. In this paper, we have categorized students' learning attitudes based on their results of academic performances that assess only students’ knowledge and skills. Students are categorized into five groups according to their learning attitudes based on the two-step clustering components. Кластер анализ ашиглан суралцагчдыг сурах хандлагаар ангилсан нь Хураангуй Суралцагчдын мэдлэг, чадварыг үнэлэхэд ихэвчлэн тестийг ашигладаг. Уг өгүүлэлд Сүхбаатар аймгийн II сургуулийн 12-р ангийн суралцагчдын улсын шалгалтын үр дүнгийн өгөгдөлд классик тестийн онол, кластер анализ зэрэг аргыг хэрэглэн анализ хийсэн үр дүнг толилуулж байна. Ангийн суралцагчдын сурах хандлагын хэв маягийг зөвхөн нэг хичээлийн эцсийн дүнгээр хэмжих нь ач холбогдол багатай. Ихэнх судлаачид суралцагчдыг сурах хандлагаар ангилахдаа лайкертын хэмжээс бүхий өгүүлбэрүүд болон асуултуудыг агуулсан судалгааны асуулгаар цуглуулсан өгөгдөлд анализ хийдэг. Харин, бид бүхэн зөвхөн суралцагчдын мэдлэг, чадварыг үнэлэх академик гүйцэтгэлийн үр дүнгээр суралцагчдыг сурах хандлагаар ангилсан нь онцлогтой. Шинжлэх ухааны буюу академик боловсролтой холбоотой сурах хандлагыг олон хичээлийн мэдлэг, чадварын цогц байдлаар авч үзэх нь зүйтэй гэдгийг баталж, кластерчлалын хоёр алхамт аргад тулгуурлан суралцагчдыг сурах хандлагаар 5 бүлэгт ангиллаа. Түлхүүр үг: Классик тестийн онол, кластер анализ, сурах хандлага, үнэлгээ, даалгаврын хариултын онолhttps://mongoliajol.info/index.php/Lavai/article/view/2493classical test theorycluster analysisattitude to learningevaluationitem response theory
spellingShingle Janchiv Shinebayar
Badarch Jadamba
Ochirbat Altangoo
Raash Namjildagva
Tumurbaatar Ganbaatar
Ravdandorj Togoo
Sukhbaatar Batchuluun
Categorizing students into groups according to their learning attitudes based on cluster analysis
Lavai
classical test theory
cluster analysis
attitude to learning
evaluation
item response theory
title Categorizing students into groups according to their learning attitudes based on cluster analysis
title_full Categorizing students into groups according to their learning attitudes based on cluster analysis
title_fullStr Categorizing students into groups according to their learning attitudes based on cluster analysis
title_full_unstemmed Categorizing students into groups according to their learning attitudes based on cluster analysis
title_short Categorizing students into groups according to their learning attitudes based on cluster analysis
title_sort categorizing students into groups according to their learning attitudes based on cluster analysis
topic classical test theory
cluster analysis
attitude to learning
evaluation
item response theory
url https://mongoliajol.info/index.php/Lavai/article/view/2493
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AT ochirbataltangoo categorizingstudentsintogroupsaccordingtotheirlearningattitudesbasedonclusteranalysis
AT raashnamjildagva categorizingstudentsintogroupsaccordingtotheirlearningattitudesbasedonclusteranalysis
AT tumurbaatarganbaatar categorizingstudentsintogroupsaccordingtotheirlearningattitudesbasedonclusteranalysis
AT ravdandorjtogoo categorizingstudentsintogroupsaccordingtotheirlearningattitudesbasedonclusteranalysis
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