The Influence of Financial Technology, Minimum Capital, and Financial Literacy on Student Investment Interest

Theodorus, Fanuel; Patricia, Velia Inda; Meiryani,

doi:10.1051/e3sconf/202342601109

Cited by 1 publication

(1 citation statement)

References 34 publications

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“…Testing in this research used the SPSS v26 and Sobel applications. After the hypothesis test is complete, the researcher will try to analyse the magnitude of the effect by estimating an R square value of .75, which is in the strong category, an R honest value of .50 in the medium category, and an R honest value of .25 which is in the weak category (Theodorus et al, 2023). After finding insignificant deals and a weak influence between the variables studied, the researcher tried to find several things behind these findings and conducted structured interviews or cross-checks (validating the truth of the researcher's conclusions) with several teachers who taught CAD and students who had taken CAD lessons at five vocational schools majoring in mechanical engineering in the city of Yogyakarta, Indonesia.…”

Section: Analysis Statisticsmentioning

confidence: 99%

Desire or Routine? Evaluating Their Influence on Computer-Aided Design Learning Achievement

Indra,

Pardjono,

Rahdiyanta

et al. 2023

JTET

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Technological progress can be felt in various sectors, including vocational schools. One of these technological advances is computer-aided design (CAD). Many articles discuss the desire to learn and the learning routine influencing learning achievement. However, only some discuss how significant the influence is and what factors affect the results of this contribution to learning achievement in CAD theory and practice. This article explores in depth the direct and indirect influence between the variables of desire to learn and learning routine on learning achievement in CAD theory and practice of vocational school students majoring in mechanical engineering, analysing their influence and what factors influence the findings. Ex-post facto research was conducted involving 339 participants. Data was collected through questionnaires, multiple-choice tests (primary data), and structured interviews (cross-check). Path analysis tests the direct and indirect effects of several variables. The findings show that the proposed model can directly influence CAD learning achievement in theory and practice with significant value, and its contribution is in the weak category. Indirectly, the desire to learn variable cannot mediate the CAD practice learning achievement variable through CAD theory learning achievement. Still, on the contrary, the learning routine variable can reconcile the CAD practice learning achievement variable through the CAD theory learning achievement variable as an intervening variable. Several factors that influence this include unexplained absences, exclusion at school, inappropriate learning methods, psychological, economic, health, family, environmental, and social.

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Section: Analysis Statisticsmentioning

confidence: 99%