2020 IEEE Global Engineering Education Conference (EDUCON) 2020
DOI: 10.1109/educon45650.2020.9125281
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Deep learning practice for high school student engagement in STEM careers

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Cited by 12 publications
(11 citation statements)
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References 41 publications
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“…Os professores da Educação Básica que participaram da atividade lúdica validaram o jogo como um objeto educacional, com menções acima de 9 (Figura 5), a poder ser classificado como Material Didático segundo a referência de Produção Técnica da CAPES. Isto ressalta ainda mais a importância de que o paradidatismo seja construído em formato lúdico, a potencializar o aprendizado (SANTANA et al, 2020). Fonte: Elaborado pelos Autores.…”
Section: Resultsunclassified
“…Os professores da Educação Básica que participaram da atividade lúdica validaram o jogo como um objeto educacional, com menções acima de 9 (Figura 5), a poder ser classificado como Material Didático segundo a referência de Produção Técnica da CAPES. Isto ressalta ainda mais a importância de que o paradidatismo seja construído em formato lúdico, a potencializar o aprendizado (SANTANA et al, 2020). Fonte: Elaborado pelos Autores.…”
Section: Resultsunclassified
“…1); and filmed it 360° at rest and running jumping jacks (videos 25 fps). From the videos, the center of body mass of each student was estimated by the optimized models of training to identify patterns in PoseNet and DefNet videos [35], [36] using the database that defined the concept of center of mass for the type of targeting sample group [8], [12], [13], (Fig. 2).…”
Section: Methodsmentioning
confidence: 99%
“…(Mobasher et al, 2019) Students understood neural networks, including the evaluation of their performance and the impact of training parameters. (Santana et al, 2018;Estevez et al,2019) Regarding unsupervised learning through k-means, students understood different concepts of centroid, selection of the appropriate k cluster number, cluster analysis and were able to interpret patterns of the clustering result as well as to decide when clustering should be used. (Wan et al, 2020;Mobasher et al, 2019) More than 90% (n=12) of students understood the algorithms behind k-nearest neighbors.…”
Section: Positive Findingsmentioning
confidence: 99%
“…Recently some initiatives and projects have emerged to bring AI/ML to the High School level in diverse countries (Kim et al, 2021;House of Lords, 2017), as High School students may have the ability to understand the core concepts of AI/ML (Huang et al, 2021). At this age they begin to consolidate their hypothetical-deductive thinking ability, and their cognitive process is accelerated by problem-solving in different contexts using technologies (Santana et al, 2018). In addition, developing AI/ML literacy may encourage more students to consider STEM careers and provide solid preparation for higher education and their future career (Marques et al, 2020).…”
Section: Introductionmentioning
confidence: 99%