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The training results of the MLFF showed that the proposed system could identify students' cognitive styles with high accuracy and the temporal effects should be considered while identifying students' cognitive styles during browsing.
The experimental results revealed that the proposed system could have significant impacts on temporal effects on students' engagement in learning, not only for students with cognitive styles known before browsing, but also for students with cognitive styles identified during browsing.
The results provide evidence of the effectiveness of the adaptive web-based learning system with students' cognitive styles dynamically identified during browsing, thus validating the research purposes of this study.
Training of the MLFF and an experiment were conducted to examine the accuracy of identifying students' cognitive styles during browsing with the proposed MLFF and the impact of the proposed adaptive web-based system on students' engagement in learning.
User interface provides the user access to GROMO using various input queries and provide links to additional information pages which guide the user during browsing of GROMO.
Citation selections are automatically acquired during browsing and used to dynamically update a likelihood model that includes authorship, journal and PubMed indexing information.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com