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Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters
The ‘Learning Meta-Learning’ dataset presented in this paper contains both categorical and continuous data of adult learners for 7 meta-learning parameters: age, gender, degree of illusion of competence, sleep duration, chronotype, experience of the imposter phenomenon, and multiple intelligences. C...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694062/ http://dx.doi.org/10.1016/j.dib.2023.109777 |
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author | Corraya, Sonia Mamun, Shamim Al Kaiser, M. Shamim |
author_facet | Corraya, Sonia Mamun, Shamim Al Kaiser, M. Shamim |
author_sort | Corraya, Sonia |
collection | PubMed |
description | The ‘Learning Meta-Learning’ dataset presented in this paper contains both categorical and continuous data of adult learners for 7 meta-learning parameters: age, gender, degree of illusion of competence, sleep duration, chronotype, experience of the imposter phenomenon, and multiple intelligences. Convenience sampling and Simple Random Sampling methods are used to structure the anonymous online survey data collection voluntarily for LML dataset creation. The responses from the 54 survey questionnaires contain raw data from 1021 current students from 11 universities in Bangladesh. The entire dataset is stored in an excel file and the entire questionnaire is accessible at (10.5281/zenodo.8112213) In this article mean and standard deviation for the participant's baseline attributes are given for scale parameters, and frequency and percentage are calculated for categorical parameters. Academic curriculum, courses as well as professional training materials can be reviewed and redesigned with a focus on the diversity of learners. How the designed courses will be learned by learners along with how they will be taught is a significant point for education in any discipline. As the survey questionnaires are set for adult learners and only current university students have participated in this survey, this dataset is appropriate for study andragogy and heutagogy but not pedagogy. |
format | Online Article Text |
id | pubmed-10694062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-106940622023-12-05 Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters Corraya, Sonia Mamun, Shamim Al Kaiser, M. Shamim Data Brief Data Article The ‘Learning Meta-Learning’ dataset presented in this paper contains both categorical and continuous data of adult learners for 7 meta-learning parameters: age, gender, degree of illusion of competence, sleep duration, chronotype, experience of the imposter phenomenon, and multiple intelligences. Convenience sampling and Simple Random Sampling methods are used to structure the anonymous online survey data collection voluntarily for LML dataset creation. The responses from the 54 survey questionnaires contain raw data from 1021 current students from 11 universities in Bangladesh. The entire dataset is stored in an excel file and the entire questionnaire is accessible at (10.5281/zenodo.8112213) In this article mean and standard deviation for the participant's baseline attributes are given for scale parameters, and frequency and percentage are calculated for categorical parameters. Academic curriculum, courses as well as professional training materials can be reviewed and redesigned with a focus on the diversity of learners. How the designed courses will be learned by learners along with how they will be taught is a significant point for education in any discipline. As the survey questionnaires are set for adult learners and only current university students have participated in this survey, this dataset is appropriate for study andragogy and heutagogy but not pedagogy. Elsevier 2023-11-07 /pmc/articles/PMC10694062/ http://dx.doi.org/10.1016/j.dib.2023.109777 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Corraya, Sonia Mamun, Shamim Al Kaiser, M. Shamim Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters |
title | Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters |
title_full | Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters |
title_fullStr | Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters |
title_full_unstemmed | Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters |
title_short | Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters |
title_sort | learning meta-learning (lml) dataset: survey data of meta-learning parameters |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10694062/ http://dx.doi.org/10.1016/j.dib.2023.109777 |
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