Learning Meta-Learning (LML) dataset: Survey data of meta-learning parameters

被引:0
|
作者
Corraya, Sonia [1 ]
Al Mamun, Shamim [1 ]
Kaiser, M. Shamim [1 ]
机构
[1] Jahangirnagar Univ, Inst Informat Technol, Savar, Bangladesh
来源
DATA IN BRIEF | 2023年 / 51卷
关键词
Multiple Intelligence; Learners' biosocial parameter; Chronotype; Imposter phenomenon; Illusion of competence;
D O I
10.1016/j.dib.2023.109777
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
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页数:6
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