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Uniciencia
versão On-line ISSN 2215-3470versão impressa ISSN 1011-0275
Resumo
VALVERDE, Juan Carlos; ROMERO-ZUNIGA, Mariela e VARGAS-FONSECA, Lupita. Contrasts in the learning process among Forest Engineering students. Uniciencia [online]. 2022, vol.36, n.1, pp.670-686. ISSN 2215-3470. http://dx.doi.org/10.15359/ru.36-1.43.
(Objective)
This study is focused on the analysis of learning styles and perceptions of university forestry engineering students at three different levels (beginning, intermediate and advanced).
(Methodology)
Tests were applied to determine students' knowledge of topics related to the career, such as their perception of the career and topics or concepts that they considered to be complicated or problematic, all a using double-blind methodology with previously validated tests; a model of learning styles was subsequently developed.
(Results)
The results showed significant differences between beginning students and intermediate and advanced students. The group of beginners tends to be deficient in rote and meaningful learning, which improves as students advance in the program of study. In addition, it was determined that improvement in learning areas such as teamwork, soft skills and working under pressure increase students' learning abilities. When the model was analyzed, it was determined that students' expectations showed little relationship with the proposed model, regardless of the level of learning. Aspects such as prior knowledge and social influences significantly affect learning, which indirectly affects student satisfaction.
(Conclusions)
The proposed model is adaptable to forestry engineering students and helps them to better understand critical concepts and skills for the career; however, improvements must be made in the first stage of the program of study (for beginners) to reduce the need for memorization and promote learning through observational and discovery methods that would give students greater capabilities and motivation.
Palavras-chave : Learning techniques; forestry learning model, Forest Engineering..