MARC details
| 000 -LEADER |
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| fixed length control field |
03508nam a2200409Ii 4500 |
| 001 - CONTROL NUMBER |
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| control field |
9781789738995 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
UtOrBLW |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20210303084833.0 |
| 006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
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| fixed length control field |
m o d |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
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| fixed length control field |
cr un||||||||| |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
190715t20192019enk ob 001 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781789738995 (e-book) |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
UtOrBLW |
| Language of cataloging |
eng |
| Description conventions |
rda |
| Transcribing agency |
UtOrBLW |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
LB2341 |
| Item number |
.M69 2019 |
| 072 #7 - SUBJECT CATEGORY CODE |
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| Subject category code |
JN |
| Source |
bicssc |
| 072 #7 - SUBJECT CATEGORY CODE |
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| Subject category code |
EDU015000 |
| Source |
bisacsh |
| 080 ## - UNIVERSAL DECIMAL CLASSIFICATION NUMBER |
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| Universal Decimal Classification number |
378 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
378.101 |
| Edition number |
23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Moye, John N., |
| Relator term |
author. |
| 245 12 - TITLE STATEMENT |
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| 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 |
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| Name of producer, publisher, distributor, manufacturer |
Emerald Publishing Limited, |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
1 online resource (xiii, 232 pages) ; |
| Dimensions |
cm |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc. note |
Includes bibliographical references and index. |
| 505 0# - FORMATTED CONTENTS NOTE |
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| 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. |
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| 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 |
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| Source of description note |
Print version record |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Education, Higher |
| General subdivision |
Management. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Organizational effectiveness |
| General subdivision |
Measurement. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Education |
| General subdivision |
Higher. |
| Source of heading or term |
bisacsh |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Education. |
| Source of heading or term |
bicssc |
| 776 ## - ADDITIONAL PHYSICAL FORM ENTRY |
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| International Standard Book Number |
9781789739008 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
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| 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> |
