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Implementing Multiple Different Active Learning Techniques In Online Road Geometric Design Courses.

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Title: Implementing Multiple Different Active Learning Techniques In Online Road Geometric Design Courses.
Authors: GARCÍA-RAMÍREZ, YASMANY1 ydgarcia1@utpl.edu.ec
Source: Advances in Engineering Education. Jan2024, Vol. 12 Issue 1, p25-44. 20p.
Subject Terms: *Online education, *Psychology of students, *Cognitive styles, Road construction, Civil engineers
Geographic Terms: Ecuador
Abstract: Due to its positive results, active learning has spread to most areas of knowledge of Civil Engineering. Many of these studies used only one technique, which is limiting given the diverse learning styles that the students may have. The road geometric design is the area that has been the least explored in Civil engineering. Therefore, the objective of this study is to show the implementation of multiple different active learning techniques in online road geometric design courses. The study shows an iterative implementation of multiple active learning techniques throughout the sequence of the three undergraduate courses in Ecuador. As a result, positive student perception was found from the combination of several active techniques. Each technique, called 'learning moment', was distributed weekly and separated from the others. The students gave the courses an average score between 8.34 to 9.06/10. At each learning moment, there were many positive comments and some easily resolved negative ones. The combination of multiple different active learning techniques, shown in this study, can be used in other courses of Civil Engineering, Engineering, or in similar areas of knowledge. [ABSTRACT FROM AUTHOR]
Copyright of Advances in Engineering Education is the property of ASEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: *<searchLink fieldCode="DE" term="%22Online+education%22">Online education</searchLink><br />*<searchLink fieldCode="DE" term="%22Psychology+of+students%22">Psychology of students</searchLink><br />*<searchLink fieldCode="DE" term="%22Cognitive+styles%22">Cognitive styles</searchLink><br /><searchLink fieldCode="DE" term="%22Road+construction%22">Road construction</searchLink><br /><searchLink fieldCode="DE" term="%22Civil+engineers%22">Civil engineers</searchLink>
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  Data: Due to its positive results, active learning has spread to most areas of knowledge of Civil Engineering. Many of these studies used only one technique, which is limiting given the diverse learning styles that the students may have. The road geometric design is the area that has been the least explored in Civil engineering. Therefore, the objective of this study is to show the implementation of multiple different active learning techniques in online road geometric design courses. The study shows an iterative implementation of multiple active learning techniques throughout the sequence of the three undergraduate courses in Ecuador. As a result, positive student perception was found from the combination of several active techniques. Each technique, called 'learning moment', was distributed weekly and separated from the others. The students gave the courses an average score between 8.34 to 9.06/10. At each learning moment, there were many positive comments and some easily resolved negative ones. The combination of multiple different active learning techniques, shown in this study, can be used in other courses of Civil Engineering, Engineering, or in similar areas of knowledge. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Advances in Engineering Education is the property of ASEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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