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Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning./
作者:
Kime, Kristian.
出版者:
Ann Arbor : ProQuest Dissertations & Theses, : 2021,
面頁冊數:
150 p.
附註:
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Contained By:
Dissertations Abstracts International83-03B.
標題:
Computer science. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28714988
ISBN:
9798460409792
Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning.
Kime, Kristian.
Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning.
- Ann Arbor : ProQuest Dissertations & Theses, 2021 - 150 p.
Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Thesis (Ph.D.)--Brandeis University, 2021.
This item must not be sold to any third party vendors.
In this dissertation, we propose a computer-supported method, called insightful learning systems, for tracking student progress that yields human actionable insights. We cover our theories, experiments and applications that aim to pave the way for more effective understanding of student progress, in key skills for a course, by looking at students answers to questions. Our goal was to find a sweet spot balancing the complexity of a learning model needed for the analytic techniques to obtain accurate results, with the desire to keep everything simple enough, so a human could under- stand what’s happening and ensure the manual work needed to create the system is minimal. To demonstrate this, we chose the domain of Introductory Calculus. We worked with an expert to build a skill-based model for that domain. We developed several methods for using Analytic frameworks to predict student outcomes and mas- tery from that model. We implemented a system, the CalcTutor, to allow real-world testing of our theories. We then collected data, both within the CalcTutor and from regular Calculus classes, that were used to show our analytics were accurate and pro- vided predictive insights. This dissertation provides evidence that Insightful Learning Systems could fundamentally transform STEM education over the coming decade.
ISBN: 9798460409792Subjects--Topical Terms:
573171
Computer science.
Subjects--Index Terms:
Assessment
Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning.
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