Multivariate analysis is a statistical solution effectively used to investigate educational phenomena. It operates simultaneously on many variables and data and allows the development of classifications and models by returning data-driven understandings. How does the international educational research community make use of multivariate analysis techniques? We conducted a methodological review to identify trends in applying these methods in education. We extracted only papers written in English, indexed in Scopus, and published from 2018 to 2022 in journals in the Education category. Our review included bibliometrics such as years of publications, leading journals, and most cited articles. We detected an increase in papers using multivariate analysis in the educational research in Scopus publications over the past five years, particularly in journals in quartiles Q1 and Q2. MANOVA represents the main method used for the analysis along with regression methods; the former may be overestimated due to the overlap of names with terms searched in the string. University students represent the preferred experimental subjects for investigation; the administration of surveys and questionnaires is the most practiced way to collect data; preferred analysis tools among those declared are non-free. Based on the topics, some research categories emerged: Teaching, Medical Education, STEM, Digital Education, Professional Development, Inclusion, Wellbeing. However, the number of citations is low (less than 8) for three-quarters of the articles in our selection. To increase the effective use, confidence, and understanding of multivariate analysis processes, appropriate skills in education, statistical analysis, and interpretation of results need to be strengthened.
Trends in the use of Multivariate Analysis in Educational Research: a review of methods and applications in 2018-2022 / DE SANTIS, Annamaria; Sannicandro, Katia; Bellini, Claudia; Minerva, Tommaso. - In: JE-LKS. JOURNAL OF E-LEARNING AND KNOWLEDGE SOCIETY. - ISSN 1826-6223. - 20:1(2024), pp. 47-55. [10.20368/1971-8829/1135946]
Trends in the use of Multivariate Analysis in Educational Research: a review of methods and applications in 2018-2022
Annamaria De Santis;Katia Sannicandro;Claudia Bellini;Tommaso Minerva
2024
Abstract
Multivariate analysis is a statistical solution effectively used to investigate educational phenomena. It operates simultaneously on many variables and data and allows the development of classifications and models by returning data-driven understandings. How does the international educational research community make use of multivariate analysis techniques? We conducted a methodological review to identify trends in applying these methods in education. We extracted only papers written in English, indexed in Scopus, and published from 2018 to 2022 in journals in the Education category. Our review included bibliometrics such as years of publications, leading journals, and most cited articles. We detected an increase in papers using multivariate analysis in the educational research in Scopus publications over the past five years, particularly in journals in quartiles Q1 and Q2. MANOVA represents the main method used for the analysis along with regression methods; the former may be overestimated due to the overlap of names with terms searched in the string. University students represent the preferred experimental subjects for investigation; the administration of surveys and questionnaires is the most practiced way to collect data; preferred analysis tools among those declared are non-free. Based on the topics, some research categories emerged: Teaching, Medical Education, STEM, Digital Education, Professional Development, Inclusion, Wellbeing. However, the number of citations is low (less than 8) for three-quarters of the articles in our selection. To increase the effective use, confidence, and understanding of multivariate analysis processes, appropriate skills in education, statistical analysis, and interpretation of results need to be strengthened.File | Dimensione | Formato | |
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