Analysis on the Multiple Intelligences of Students from Faculty of Physical Education and Sports

Autor: Razvan-Liviu Petre, Ana-Maria Suruba-Rusen, Daniela Murăreţu, Daniel Constantin Murăreţu, Marian Daniel Teodoru
Rok vydání: 2020
Předmět:
Zdroj: BRAIN. BROAD RESEARCH IN ARTIFICIAL INTELLIGENCE AND NEUROSCIENCE. 11:185-199
ISSN: 2067-3957
2068-0473
DOI: 10.18662/brain/11.4sup1/164
Popis: The present research is based on the theory developed in 1983 by the American psychologist Howard Gardner, according to which people possess eight distinct types of intelligence: verbal/ linguistic, mathematical/ logical, visual/ spatial, bodily/ kinesthetic, rhythmic/ musical, interpersonal, intrapersonal, naturalist. The way these multiple intelligences are combined differentiates us as humans, for example, in school, students react differently. Some students are more interested in learning, some are not. This may be due to different types of intelligence. Our research aims to highlight the dominant types of intelligence for second year students, depending on which teachers can adapt their teaching methods. The research was carried out over a period of 3 weeks. The participants in the research are 111 romanian students from National University of Physical Education and Sports, out of which 42 are female and 69 are male. The research methods used are: scientific documentation, questionnaire-based survey (multiple intelligences test was applied), statistical-mathematical method, graphical method. The results of the research provide us important data to see to what extent kinesthetic body intelligence is dominant in students practicing sports and what are the other types of intelligence present in athletes. Finding out the dominant types of student’s intelligence can provide us important information according to which we can adapt our teaching methods. Thus, we can conduct our didactic activity in an attractive manner, in which the potential of students is not wasted and feel motivated to learn and evolve in a traditional classroom.
Databáze: OpenAIRE
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