2019 CSDMS meeting-038: Difference between revisions

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{{CSDMS meeting personal information template-2019
{{CSDMS meeting personal information template-2019
|CSDMS meeting first name=Andrew
|CSDMS meeting first name=Andrew
|CSDMS meeting last name=Moody
|CSDMS meeting last name=Moodie
|CSDMS meeting institute=Rice University
|CSDMS meeting institute=Rice University
|CSDMS meeting city=Houston
|CSDMS meeting city=Houston
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{{CSDMS meeting select clinics2 2019
{{CSDMS meeting select clinics2 2019
|CSDMS_meeting_select_clinics2_2019=5) Will not attend a clinic
|CSDMS_meeting_select_clinics2_2019=1) PyMT - The CSDMS Python Modeling tool
}}
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{{CSDMS meeting select clinics3 2019
{{CSDMS meeting select clinics3 2019
|CSDMS_meeting_select_clinics3_2019=5) Will not attend a clinic
|CSDMS_meeting_select_clinics3_2019=2) Deep Neural Networks Classification
}}
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{{CSDMS scholarships yes no
{{CSDMS scholarships yes no
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{{CSDMS meeting abstract yes no 2019
{{CSDMS meeting abstract yes no 2019
|CSDMS meeting abstract submit=Yes
|CSDMS meeting abstract submit=No
}}
{{CSDMS meeting abstract title temp2019
|CSDMS meeting abstract title=CLINIC - Developing and teaching interactive sedimentology and stratigraphy computer activities
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{{CSDMS meeting abstract template 2019
|CSDMS meeting abstract=In this clinic, we will first demonstrate existing interactive computer-based activities used for teaching concepts in sedimentology and stratigraphy. This will be followed by a hands-on session for creating different modules based on the participants’ teaching and research interests. Active learning strategies improve student exam performance, engagement, attitudes, thinking, writing, self-reported participation and interest, and help students become better acquainted with one another (Prince, 2004). Specifically, computer-based active learning is an attractive educational approach for post-secondary educators, because developing these activities takes advantage of existing knowledge and skills the educator is likely to already have.
The demonstration portion of the clinic will focus on the existing rivers2stratigraphy (https://github.com/sededu/rivers2stratigraphy) activity, which illustrates basin-scale development of fluvial stratigraphy through adjustments in system kinematics including sandy channel migration and subsidence rates. The activity allows users to change these system properties, so as to drive changing depositional patterns. The module utilizes a rules based model, which produces realistic channel patterns, but simplifies the simulation to run efficiently, in real-time. The clinic will couple rivers2stratigraphy to a conventional laboratory activity which interprets an outcrop photograph of fluvial stratigraphy, and discuss logistics of using the module in the classroom.
 
For the second part of the clinic, familiarity with Python will be beneficial (but is not required); we will utilize existing graphical user interface (GUI) frameworks in developing new activities, aimed to provide a user-friendly means for students to interact with model codes while engaging in geological learning. Participants should plan to have Python installed on their personal computers prior to the workshop, and a sample module will be emailed beforehand to let participants begin exploring the syllabus.
 
Prince, M. (2004). Does Active Learning Work? A Review of the Research. Journal of Engineering Education, 93(3), 223-231. doi: 10.1002/j.2168-9830.2004.tb00809.x.
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Latest revision as of 10:23, 4 February 2019





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Andrew Moodie choose to not submit an abstract for this conference.