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A machine learning, artificial intelligence approach to institutional effectiveness in higher education / (Record no. 51484)

MARC details
000 -LEADER
fixed length control field 03617nam a2200433Ii 4500
001 - CONTROL NUMBER
control field 9781789738995
003 - CONTROL NUMBER IDENTIFIER
control field UtOrBLW
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251029120201.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr un|||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 190715t20192019enk ob 001 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781789738995 (e-book)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781789739015 (ePUB)
040 ## - CATALOGING SOURCE
Original cataloging agency UtOrBLW
Language of cataloging eng
Description conventions rda
Transcribing agency UtOrBLW
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number LB2341
Item number .M69 2019
072 #7 - SUBJECT CATEGORY CODE
Subject category code JN
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code EDU015000
Source bisacsh
080 ## - UNIVERSAL DECIMAL CLASSIFICATION NUMBER
Universal Decimal Classification number 378
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Moye, John N.,
Relator term author.
9 (RLIN) 59513
245 12 - TITLE STATEMENT
Title A machine learning, artificial intelligence approach to institutional effectiveness in higher education /
Statement of responsibility, etc. John N. Moye.
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Place of production, publication, distribution, manufacture Bingley, U.K. :
Name of producer, publisher, distributor, manufacturer Emerald Publishing Limited,
Date of production, publication, distribution, manufacture, or copyright notice 2019.
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Date of production, publication, distribution, manufacture, or copyright notice ©2019
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xiii, 232 pages) ;
Dimensions cm
336 ## - CONTENT TYPE
Content type term text
Content type code txt
Source rdacontent
337 ## - MEDIA TYPE
Media type term computer
Media type code c
Source rdamedia
338 ## - CARRIER TYPE
Carrier type term online resource
Carrier type code cr
Source rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Prelims -- Chapter 1: Defining, measuring, and assessing effectiveness -- Chapter 2: Creating shared mission, vision, and values -- Chapter 3: Measuring and assessing program structure: intended performance -- Chapter 4: Measuring and assessing instruction: intended performance -- Chapter 5: Measuring and assessing support services: intended performance -- Chapter 6: Functional data modeling: identifying the drivers and constraints of actual performance -- Chapter 7: Institutional data modeling: looking beyond the data -- Chapter 8: Continuous quality improvement -- Afterword -- References -- Index.
520 ## - SUMMARY, ETC.
Summary, etc. The Institutional Research profession is currently experimenting with many strategies to assess institutional effectiveness in a manner that reflects the letter and spirit of their unique mission, vision, and values. While a "best-practices" approach to the measurement and assessment of institutional functions is prevalent in the literature, a machine learning approach that synthesizes these parts into a coherent and synergistic approach has not emerged.A Machine Learning, Artificial Intelligence Approach to Institutional Effectiveness in Higher Education presents a practical, effective, and systematic approach to the measurement, assessment, and sensemaking of institutional performance. Included are instruments and strategies to measure and assess the performance of Curriculum, Learning, Instruction, Support Services, and Program Feasibility as well as a meaningful Environmental Scanning method. The data collected in this system are organized into assessments of institutional effectiveness through the application of machine learning data processes that create an artificial intelligence model of actual institutional performance from the raw performance data. This artificial intelligence is visualized through five organizational sensemaking approaches to monitor, demonstrate, and improve institutional performance. Thus, this book provides a set of tools that can be adopted or adapted to the specific intentions of any institution, making it an invaluable resource for Higher Education administrators, leaders and practitioners.
588 0# - SOURCE OF DESCRIPTION NOTE
Source of description note Print version record
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
General subdivision Management.
9 (RLIN) 59514
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
General subdivision Measurement.
9 (RLIN) 59515
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
General subdivision Higher.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element
Source of heading or term bicssc
9 (RLIN) 59242
776 ## - ADDITIONAL PHYSICAL FORM ENTRY
International Standard Book Number 9781789739008
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://www.emerald.com/insight/publication/doi/10.1108/9781789738995">https://www.emerald.com/insight/publication/doi/10.1108/9781789738995</a>

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