3 datasets found
  1. f

    Descriptive statistics (n = 7,065).

    • figshare.com
    xls
    Updated Jun 21, 2023
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    Cheyeon Ha; Alysia D. Roehrig; Qian Zhang (2023). Descriptive statistics (n = 7,065). [Dataset]. http://doi.org/10.1371/journal.pone.0284385.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Cheyeon Ha; Alysia D. Roehrig; Qian Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The aim of the study was to explain the relationships between self-regulated learning strategy use and academic achievement of 6th-grade students in South Korea. An existing database (i.e., the Korean Educational Longitudinal Study; KELS) with 6th-grade students (n = 7,065) from 446 schools was used to run a series of 2-level hierarchical linear models (HLM). This large dataset enabled us to consider how the relationship between learners’ self-regulated learning strategy use and academic achievement may differ at individual and school levels. We found that students’ metacognition and effort regulation positively predicted their literacy and math achievement both within and across schools. The average literacy and math achievement were significantly higher in private schools than in public schools. Also, the math achievement of urban schools was significantly higher than in non-urban schools when controlling other cognitive and behavioral learning strategies. This study on 6th-grade learners’ self-regulated learning (SRL) on academic achievement explores how their SRL strategies may be different from the features of successful adult learners from the previous findings, offering new insights into the development of SRL in elementary education.

  2. Demographic information of participants.

    • plos.figshare.com
    xls
    Updated Jun 21, 2023
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    Cheyeon Ha; Alysia D. Roehrig; Qian Zhang (2023). Demographic information of participants. [Dataset]. http://doi.org/10.1371/journal.pone.0284385.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 21, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Cheyeon Ha; Alysia D. Roehrig; Qian Zhang
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The aim of the study was to explain the relationships between self-regulated learning strategy use and academic achievement of 6th-grade students in South Korea. An existing database (i.e., the Korean Educational Longitudinal Study; KELS) with 6th-grade students (n = 7,065) from 446 schools was used to run a series of 2-level hierarchical linear models (HLM). This large dataset enabled us to consider how the relationship between learners’ self-regulated learning strategy use and academic achievement may differ at individual and school levels. We found that students’ metacognition and effort regulation positively predicted their literacy and math achievement both within and across schools. The average literacy and math achievement were significantly higher in private schools than in public schools. Also, the math achievement of urban schools was significantly higher than in non-urban schools when controlling other cognitive and behavioral learning strategies. This study on 6th-grade learners’ self-regulated learning (SRL) on academic achievement explores how their SRL strategies may be different from the features of successful adult learners from the previous findings, offering new insights into the development of SRL in elementary education.

  3. Difficult Words for Hearing Impaired Children

    • kaggle.com
    zip
    Updated Oct 21, 2019
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    NUST-EME (2019). Difficult Words for Hearing Impaired Children [Dataset]. https://www.kaggle.com/nusteme/difficult-words-for-hearing-impaired-children
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    zip(44029 bytes)Available download formats
    Dataset updated
    Oct 21, 2019
    Authors
    NUST-EME
    Description

    Context

    This dataset is used as a result and part of research for identification of difficult English words for assisting hearing impaired children in learning language. Anything that is made by the combination of characters, words, sentences, and paragraphs is considered as text. Sentences are made by the combination of complex, simple words or both. Usage of more complex words in the text makes it a difficult one which causes problems not only in reading but in writing as well. This ultimately results in poor academic achievement of students. It is more difficult for hearing impaired children to learn and understand the difficult text as compared to their normal hearing peers. This happens because they lack increase knowledge of vocabulary. Speech language Pathologist/Therapist, their teachers and parents indulge them in different learning activities to increase their vocabulary. During this, they usually used flash cards, containing different words, pictures, printed papers, real objects and toys. But if presented words are difficult for them to learn, then it will be very difficult for others to develop understanding of the word in child’s mental lexicon. This will also require a lot of effort and time not only from SLP’s, parents, and teachers but also from hearing impaired students. Research will help in identification of difficult words to make the readability of the text easy for such children. It will help child to use simple words in daily routine to enhance their vocabulary knowledge as they can learn more words in short period of time. It will also help their parents and teachers to prepare reading and writing materials simpler to learn for them .It will help the child to learn language in simple way.In Pakistan, Educational institutes specific for hearing impaired children, adults, children, parents and Speech Language Pathologists (SLP’s) can effectively make use of the proposed methodology in daily routine to identify difficult text from the study materials, newspapers, online on web stores and can prepare activities during speech therapy. It will save time and resources currently utilized manually. It will also enhance child’s vocabulary as they can learn simple words rather than focusing and spending hours on difficult ones.

    Content

    Collection of the dataset for this research is not a simple task. Dataset is collected from the English textbooks and online sources being taught at elementary and secondary level at schools established specifically for hearing impaired children. Unstructured data is annotated and then preprocessed. The main objective for this is to ensure an accurate generation of linguistic rules that helps to label a particular word as difficult or not difficult. Data is then annotated by experts. Word is annotated as difficult if 2 or more annotators have annotated it as difficult. It consist of 1000 words which is divided into two sets. one set is used for training purpose and is constitue of 600 words, whereas , remaining 400 words are used for testing purpose. Different features are then extracted based on rules applicable and specific to hearing impaired children. Character count / Word Length: Maximum the number of characters found in the word, Word is difficult Syllable Count: More the number of syllable count more will be the chance of word to be considered as difficult. Part of Speech Tags: Nouns are easier to learn as compared to verbs and adjective; whereas adverbs are difficult as they describe the abstract idea. Hearing Impaired children learn concrete words easily than abstract words. Presence of ch/st/th/f/sh in words: Ch /st/th/f/sh produce high-frequency sounds during pronunciation and considered as high-frequency letters. So their presence makes the word difficult to understand for hearing impaired children Presence of C or K in words: Sometimes pronunciation of c and k are the same or different in context. So it is difficult for the child to recognize during reading or writing, what to read. Presence of G or J in words :Sometimes pronunciation of g and j are the same or different in context. So it is difficult for the child to recognize during reading or writing, what to read. Frequency of occurrence: If a word appears more frequently, then the word is easy otherwise difficult.

    Acknowledgements

    Special thanks to all the efforts made and help provided by the teachers from the hearing impaired children during creation of this dataset.

    Inspiration

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Click to copy link
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Close
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Cheyeon Ha; Alysia D. Roehrig; Qian Zhang (2023). Descriptive statistics (n = 7,065). [Dataset]. http://doi.org/10.1371/journal.pone.0284385.t002

Descriptive statistics (n = 7,065).

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
Jun 21, 2023
Dataset provided by
PLOS ONE
Authors
Cheyeon Ha; Alysia D. Roehrig; Qian Zhang
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The aim of the study was to explain the relationships between self-regulated learning strategy use and academic achievement of 6th-grade students in South Korea. An existing database (i.e., the Korean Educational Longitudinal Study; KELS) with 6th-grade students (n = 7,065) from 446 schools was used to run a series of 2-level hierarchical linear models (HLM). This large dataset enabled us to consider how the relationship between learners’ self-regulated learning strategy use and academic achievement may differ at individual and school levels. We found that students’ metacognition and effort regulation positively predicted their literacy and math achievement both within and across schools. The average literacy and math achievement were significantly higher in private schools than in public schools. Also, the math achievement of urban schools was significantly higher than in non-urban schools when controlling other cognitive and behavioral learning strategies. This study on 6th-grade learners’ self-regulated learning (SRL) on academic achievement explores how their SRL strategies may be different from the features of successful adult learners from the previous findings, offering new insights into the development of SRL in elementary education.

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