Summary |
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1 | (8) |
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Motivation and Panel Charge |
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1 | (1) |
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2 | (1) |
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Measurement Limitations and Key Areas for Model Enhancement |
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3 | (3) |
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3 | (1) |
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Quality Variation and Change |
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4 | (1) |
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5 | (1) |
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Segmentation by Institution Type |
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6 | (1) |
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Implications of Complexities for Measurement Prospects |
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6 | (1) |
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Developing the Data Infrastructure |
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7 | (2) |
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1 The Importance Of Measuring Productivity In Higher Education |
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9 | (10) |
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1.1 Social and Policy Context |
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10 | (3) |
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13 | (4) |
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1.3 Audience and Report Structure |
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17 | (2) |
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2 Defining Productivity For Higher Education |
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19 | (18) |
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21 | (10) |
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23 | (2) |
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25 | (4) |
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2.1.3 Instructional and Noninstructional Elements of the Higher Education Production Function |
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29 | (2) |
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2.2 Productivity Contrasted with Other Measurement Objectives |
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31 | (6) |
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2.2.1 Productivity and Cost |
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31 | (2) |
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2.2.2 Other Performance Metrics |
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33 | (4) |
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3 Why Measurement Of Higher Education Productivity Is Difficult |
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37 | (24) |
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3.1 Beyond the Degree Factory---Multiple Outputs and Joint Production |
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38 | (2) |
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3.2 Heterogeneity of Inputs and Outputs |
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40 | (3) |
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3.3 Nonmarket Variables and Externalities |
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43 | (1) |
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3.4 Quality Change and Variation |
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44 | (11) |
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45 | (5) |
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3.4.2 Outputs (and Outcomes) |
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50 | (5) |
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3.5 Measurement at Different Levels of Aggregation |
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55 | (5) |
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3.5.1 Course and Department Level |
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55 | (2) |
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57 | (1) |
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3.5.3 State or System Level |
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58 | (2) |
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60 | (1) |
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4 Advancing The Conceptual Framework |
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61 | (26) |
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61 | (2) |
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4.2 A Baseline Multi-Factor Productivity Model for Higher Education |
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63 | (8) |
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4.2.1 Multi-Factor Productivity Indices |
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64 | (1) |
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65 | (2) |
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67 | (1) |
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4.2.4 Allocations to Education |
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68 | (1) |
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4.2.5 Illustrative Productivity Calculations |
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69 | (2) |
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4.3 Institutional Segmentation and Disaggregative Indices |
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71 | (3) |
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4.3.1 Institutional Segmentation |
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72 | (1) |
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4.3.2 State Level and Single-Institution Indices |
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73 | (1) |
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4.4 Differentiating Labor Categories |
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74 | (4) |
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4.5 Differentiating Outputs |
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78 | (1) |
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4.6 Variations in Output Quality |
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79 | (8) |
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Technical Appendix: The Tornqvist Productivity Index |
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82 | (5) |
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5 Recommendations For Creating And Extending The Measurement Framework |
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87 | (20) |
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5.1 The Basic Productivity Measure |
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89 | (6) |
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5.1.1 Instructional Outputs and Benefits |
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90 | (3) |
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5.1.2 Instructional Inputs and Costs |
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93 | (2) |
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5.2 Adjusting for Research Production |
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95 | (4) |
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5.2.1 Project Driven Departmental Research |
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97 | (1) |
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5.2.2 Discretionary Departmental Research |
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98 | (1) |
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5.3 Dealing with Heterogeneity and Quality Issues |
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99 | (8) |
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5.3.1 Variation of Inputs |
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100 | (3) |
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5.3.2 Quality Variation and Change of Outputs |
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103 | (4) |
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6 Implementation And Data Recommendations |
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107 | (18) |
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107 | (2) |
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6.2 Recommendations for Improving the Data Infrastructure |
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109 | (16) |
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6.2.1 Data Demanded by the Conceptual Framework |
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109 | (1) |
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6.2.2 Envisioning the Next Generation IPEDS |
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110 | (4) |
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6.2.3 Administrative Data Sources |
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114 | (6) |
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6.2.4 Survey Based Data Sources |
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120 | (5) |
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REFERENCES AND BIBLIOGRAPHY |
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125 | (12) |
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A Commonly Used Performance Metrics for Higher Education |
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137 | (8) |
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B Methods for Measuring Comparative Quality and Cost Developed by the National Center for Academic Transformation |
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145 | (6) |
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C Overview of Data Sources |
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151 | (52) |
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D Estimating Project-Related Departmental Research |
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203 | (2) |
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E Biographical Sketches of Panel Members |
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205 | |