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Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning./
Author:	Kime, Kristian.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2021,
Description:	150 p.
Notes:	Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
Contained By:	Dissertations Abstracts International83-03B.
Subject:	Educational technology. -
Online resource:	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:

556755
Educational technology.
Subjects--Index Terms:

Assessment

Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning.
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100 1 $a Kime, Kristian. $0 (orcid)0000-0002-6873-2676 $3 1413417
245 1 0 $a Insightful Learning Systems: Supporting STEM Education with Accessible Cyberlearning.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2021
300 $a 150 p.
500 $a Source: Dissertations Abstracts International, Volume: 83-03, Section: B.
500 $a Advisor: Hickey, Timothy J.
502 $a Thesis (Ph.D.)--Brandeis University, 2021.
506 $a This item must not be sold to any third party vendors.
520 $a 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.
590 $a School code: 0021.
650 4 $a Educational technology. $3 556755
650 4 $a Computer science. $3 573171
653 $a Assessment
653 $a Calculus
653 $a Courseware
653 $a Education
653 $a Learning analytics
690 $a 0710
690 $a 0984
710 2 $a Brandeis University. $b Computer Science. $3 1413418
773 0 $t Dissertations Abstracts International $g 83-03B.
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791 $a Ph.D.
792 $a 2021
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28714988