國立虎尾科技大學 |

Sensemaking During the Use of Learning Analytics in the Context of a Large College System.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Sensemaking During the Use of Learning Analytics in the Context of a Large College System./
作者:	Morse, Robert Kenneth.
面頁冊數:	1 online resource (157 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-01(E), Section: A.
Contained By:	Dissertation Abstracts International79-01A(E).
標題:	Information science. -
電子資源:	click for full text (PQDT)
ISBN:	9780355145038

Sensemaking During the Use of Learning Analytics in the Context of a Large College System.
Morse, Robert Kenneth.

Sensemaking During the Use of Learning Analytics in the Context of a Large College System. - 1 online resource (157 pages)

Source: Dissertation Abstracts International, Volume: 79-01(E), Section: A.

Thesis (Ph.D.)--Indiana University - Purdue University Indianapolis, 2017.

Includes bibliographical references

This research took place as a cognitive exploration of sensemaking of learning analytics at Ivy Tech Community College of Indiana. For the courses with the largest online enrollment, quality standards in the course design are maintained by creating sections from a course design framework. This means all sections have the same starting content and the same framework for assessment. The course design framework is maintained by the curriculum committee composed of program chairs who oversee the program to which the course belongs. This research proposed to develop a learning analytics dashboard to elicit the best practices in instantiating a course design framework from the perspective of the program chair. The Instructional Design Implementation Dashboard, IDID, was designed to address the sensemaking needs of program chairs. The program chairs were asked to make sense of IDID built around the data collected from the course management system and the student information system. IDID leveraged metrics from the user activity and the learner performance from the learning management system, combined with data about the student demographics captured from the student information system. IDID was used to identify highly successful sections and examine the instructor behaviors that might be considered best practices. Data Frame Sensemaking theory was confirmed as an accurate description of the experience of program chairs when using IDID. A revised model of Data Frame Sensemaking theory was developed to explain the interaction of those using the IDID platform.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355145038Subjects--Topical Terms:

561178
Information science.
Index Terms--Genre/Form:

554714
Electronic books.

Sensemaking During the Use of Learning Analytics in the Context of a Large College System.
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504 $a Includes bibliographical references
520 $a This research took place as a cognitive exploration of sensemaking of learning analytics at Ivy Tech Community College of Indiana. For the courses with the largest online enrollment, quality standards in the course design are maintained by creating sections from a course design framework. This means all sections have the same starting content and the same framework for assessment. The course design framework is maintained by the curriculum committee composed of program chairs who oversee the program to which the course belongs. This research proposed to develop a learning analytics dashboard to elicit the best practices in instantiating a course design framework from the perspective of the program chair. The Instructional Design Implementation Dashboard, IDID, was designed to address the sensemaking needs of program chairs. The program chairs were asked to make sense of IDID built around the data collected from the course management system and the student information system. IDID leveraged metrics from the user activity and the learner performance from the learning management system, combined with data about the student demographics captured from the student information system. IDID was used to identify highly successful sections and examine the instructor behaviors that might be considered best practices. Data Frame Sensemaking theory was confirmed as an accurate description of the experience of program chairs when using IDID. A revised model of Data Frame Sensemaking theory was developed to explain the interaction of those using the IDID platform.
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