• Title/Summary/Keyword: suitability of words and sentences

Search Result 3, Processing Time 0.02 seconds

An Analysis on Suitability of Words and Sentences in Mathematics Textbooks for Elementary First Grade (초등학교 1학년 수학 교과서의 어휘 및 문장 적합성 분석)

  • Chang, Hyewon;Lim, Miin
    • Journal of Educational Research in Mathematics
    • /
    • v.26 no.2
    • /
    • pp.247-267
    • /
    • 2016
  • It has been pointed out that the mathematics textbooks according to 2009 revised national curriculum cause difficulty not by mathematical knowledge but concomitantly by words and sentences for the first graders who just started learning Korean alphabets. This study focused on the suitability of words and sentences in mathematics textbooks for elementary first grade. We analyzed the degree of difficulty and familiarity in terms of words and the structure, length, and expression in terms of sentences. The results show some causes that lead the first graders to the difficulty. In more detail, we found 108 difficult words and 6 unfamiliar words for the first graders. And it is noticed that the textbooks contain 37 compound sentences, 727 complex sentences, and 38 compound-complex sentences. They also contain 237 long sentences that are composed of 9 words or more, 168 sentences that assign two activities or more, and 52 sentences that contain three nouns or adjectives or more successively. Based on these results and discussions, we suggested several implications for writing mathematics textbooks for the lower grades in elementary school.

Evaluation of the Readability and Suitability of Printed Educational Materials on Metabolic Syndrome (대사증후군 교육 인쇄물의 이독성과 적합성 평가)

  • Kim, Jung Eun;Yang, Sook Ja
    • Journal of Korean Public Health Nursing
    • /
    • v.30 no.1
    • /
    • pp.149-163
    • /
    • 2016
  • Purpose: The aim of this study was to assess the readability and suitability of printed educational materials related to metabolic syndrome in South Korea. Methods: Data were collected on 15 educational materials on metabolic syndrome from public health centers in Seoul. The 9 Graded Korean Vocabulary Classification and Korean version of SAM (Suitability Assessment of Materials) were used for the readability evaluation and the suitability evaluation respectively. Results: Overall average of the readability was 3.0th grade level. The percentage of 1st to 4th grade words was 79.4%. The printed educational materials on metabolic syndrome were written according to recommended reading levels. In suitability assessment, 2 out of 15 materials(13.3%) were scored as superior, 12 materials(80.0%) were scored as adequate and only 1 (6.7%) was scored as inadequate. The total average score of suitability was adequate. However, there are limitations in "summary and review" and "context is given first" due to limited writing pages. Conclusion: Readability and suitability of educational materials for metabolic syndrome were evaluated as adequate level. However, future health educational materials should be evaluated for readability via different factors including length of sentences, numbers of sentences, and structure of sentences. In addition, for easier understanding and motivation of readers, materials should use summary & review, context and proper interaction.

Korean Learning Assistant System with Automatically Extracted Knowledge (자동 추출된 지식에 기반한 한국어 학습 지원 시스템)

  • Park, Gi-Tae;Lee, Tae-Hoon;Hwang, So-Hyun;Kim, Byeong Man;Lee, Hyun Ah;Shin, Yoon Sik
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.1 no.2
    • /
    • pp.91-102
    • /
    • 2012
  • Computer aided language learning has become popular. But the level of automation of constructing a Korean learning assistant system is not so high because a practical language learning system needs large scale knowledge resources, which is very hard to acquire. In this paper, we propose a Korean learning assistant system that utilizes easily obtainable knowledge resources like a corpus, web documents and a lexicon. Our system has three modules - problem solving, pronunciation marker and writing assistant. Automatic problem generator uses a corpus and a lexicon to make problems with one correct answer and three distracters, then verifies their suitability by utilizing frequency information from web documents. We analyze pronunciation rules for a pronunciation marker and recommend appropriate words and sentences in real-time by using data extracted from a corpus. In experiment, we evaluate 400 automatically generated problems, which show 89.9% problem suitability and 64.9% example suitability.