Index

Annulis, H. M., 15–28 
Aaron, B. C., 38, 40, 173–187  application objectives, 22, 23 
accountability, 30  Ask.com, 193 
action planning  ASTD Competency Model: Mapping the Future, 

applications, 113 

266

benefits, identifying intangible, 120 

 

communicating, 112 

data collection using, 31, 34 

Balanced Scorecard, The (Kaplan and Norton), 

defined, 108–109 

247

effectiveness of, 117 

basic maintenance course 

follow-up, 118, 119 

background, 355–356 

how it works, 109, 110 

evaluation planning and methodology, 

integrate into ADDIE, 109, 111–112 

356–357, 364 

knowledge check, 122–123 

knowledge check, 371 

managers/supervisors, role of, 112 

objectives, 356, 358–363 

monetary value, determining, 114–117 

recommendations, 368, 370 

objectives, identifying, 109, 111 

results, 364–368, 369–370 

participants, 112 

benefit-cost ratio (BCR), 214–215 

peer/facilitator review of, 117–118 

Block, P., 249 

reporting results, 120–122 

briefings, executive, 254 

return-on-investment, calculating, 119–120, 

Brinkerhoff, R. O., 125–134, 298, 387–391, 323 

121

Broad, M. L., 392–395 

role of, 113 

Broslawsky, T., 239–251 

teaching, 114 

Burkett, H., 31, 34, 107–124 

time needed for, 114 

business requirement, defining, 6 

why use, 107–108 

 
ADDIE, 1, 109, 111–112 
Aldrich, C., 374  Cardenas, J., 201–211 
Angoff method, 80–81  case studies, 32, 34–35, 241 
   
central tendency measures, 150–152 

statistics, 193, 196 

Chain of Evidence, 273–274 

steps for, 194–195, 197 

Chi-square, 162 

techniques for, 191–195, 196 

communication/reporting  Cornell University, School of Hospitality 

audience, 245 

Management, 193 

case studies, value of, 241 

Coscarelli, W. C., 73–84 

Chain of Evidence, 273–274 

costs, 7, 8 

credibility of program team, role of, 242 

analysis, 38–39, 41 

feedback, 248–249 

categories, 203–207 

format, 246, 247 

estimating, 207, 208–209 

implementation and, 288–289 

estimating implementation, 226–227 

importance of, 239–240 

estimating planning, 226 

knowledge check, 250–251 

fully loaded, 202 

media selection, 241, 246 

identifying, 201–211 

plan, 242–244 

importance of, 201–202 

reactions to, 250 

knowledge check, 210 

reasons for, 244–245 

pressure to disclose, 202 

results to management, 249 

prorated versus direct, 203 

scorecards, 246–248 

sources of, 203 

targeted, 241 

without benefits, 202 

testimonials, 242 

Crane, K., 165–171 

timely, 240 

criterion, 18 

unbiased, 242 

criterion-referenced tests (CRTs) 
competency skill assessments 

cut-off scores, 79–81 

benefits and pitfalls of, 12 

designing, 73–74 

needs assessment and, 13 

guidelines for creating, 82–83 

condition, 19 

knowledge check, 81–82 

conduct, 19 

length of, 77–79 

content validity, 76 

model for, 74, 75 

control groups, 174, 175, 176–178 

validity, 76–77 

converting measures to monetary value 

value of, 74 

benefits to, 228 

weighting items, 78–79 

databases, 193, 196 

current state, identifying, 7 

estimating, 194, 195, 196 

cut-off scores, 79–81 

experts, 193, 196 

 

guidelines, 198 

historical costs, 193, 196 

data, hard and soft, 23 

importance of, 189–191 

data analysis

intangible measures, 196, 197 

advantages and disadvantages of, 39, 40–41

knowledge check, 198–199 

converting measures to monetary value,

standard values, 191–193, 196 

189–199

   
data analysis (continued estimating future value 

costs, identifying, 201–211 

implementation costs and benefits, 226–227 

costs/financial, 38–39, 41 

knowledge check, 234 

isolating effects, 38, 40, 173–187 

planning costs and benefits, 226 

key questions, 39, 41 

rationale for, 224 

planning, 35, 42–43 

return-on-investment, 226–232 

qualitative, 38, 40, 165–171 

statistical analysis, 232 

return-on-investment, calculating, 38–39, 

systems modeling, 232–233 

40–41, 213–222 

timing (continuum), 224–227 

statistics, 38, 40, 149–164 

tips, 233–234 

type to use, 147 

utility analysis, 233 

databases, 193, 196  evaluation. See measurement and evaluation 
data collection  evaluation planning. See planning 

action planning, 31, 34, 107–124 

executive briefings, 254 

advantages and disadvantages of, 32, 33–35 

executive interviews, 254 

case studies, 32, 34–35 

Executive Leadership Institute (ELI) program. 

criterion-referenced tests, 73–84 

See leadership development case example 

focus groups, 31, 34, 97–106 

executive surveys, 254 

interviews, 31, 33–34, 85–95 

executive viewpoints 

key questions, 32 

application measures, 259–260 

multiple methods, using, 89 

impact and return-on-investment measures, 

performance records, 32, 35, 135–145 

260–262 

planning, 30 

importance of, 253, 254 

planning template, 32, 36–37 

influencing, 262–263 

success case method, 125–134 

investment level, 255 

surveys and questionnaires, 31, 33, 55–72 

knowledge check, 263 

tests, 31, 33 

learning measures, 258 

Davis, W. R., 21 

methods for obtaining, 254 

decision making, 30 

metrics and, 255–256 

de Rosairo, N., 35 

reaction data, 257 

descriptive statistics, 150   
DeTuncq, T. H., 355–372 
Dugas, S., 18  feedback, 248–249 
  financial analysis, 38–39, 40–41 
Fischer, D. H., 53 
Ebscohost, 193  Fitz-enz, J., 396–399 
Edwards, L. A., 97–106  Flawless Consulting (Block), 249 
estimating, 181–184  focus groups 

converting measures to monetary value, 

assessment of, 105 

194–195, 196 

benefits and pitfalls of, 12 

forecast analysis, 174, 175, 180–181 

conducting the session, 104 

   
focus groups (continued) 

data collection using, 31, 34 

Historians’ Fallacies (Fischer), 53 

facilitator, selecting, 98, 99 

Hoole, E., 321–336 

group interview questions, 99–100 

Hubble, C., 55–72 

importance of, 97–98 

human resources, implementation and, 290–291 

Ishikawa diagrams, 100–101, 102 

 

knowledge checks, 105 

needs assessment and, 12 

Iannetta, J., 150 

nominal group technique, 101–104 

impact objectives, 22–23 

participants, selecting, 98 

impact studies, 254 

session format, 98–99 

implementation 

solutions, identifying, 105 

advocacy and support, 285 

Ford, D. J., 29–51 

checklist, 292 

forecast analysis, 174, 175, 180–181 

communication, 288–289 

See also estimating future value 

experience, use of individual, 285–286 

 

experts, use of subject matter, 286–287 

goals, 284 

Gadd, R., 307–319 

human resources and, 290–291 

Galwey, 298 

identifying what to avoid, 284 

gap analysis, 6 

knowledge check, 293 

between current state and business 

outcomes, developing, 285 

requirements, 7 

performance improvement, 289–290 

Gaudet, C. H., 15–28 

plan, 292 

global programs 

senior leadership, role of, 287–288 

background, 337–338 

technology and, 291 

business impact, 350 

inferential statistics, 150 

business tools, 341, 343 

input objectives, 19–20 

content and design of, 341, 342 

interviewers, selecting and training, 92–93 

converting measures to monetary value, 

interviews 

350–351 

advantages and disadvantages of, 11, 88 

isolation methods, 350 

assessment of, 93–94 

knowledge check, 353 

data collection using, 31, 33–34 

project team and steering committee, 341 

evaluation of training using, 87 

recommendations, 353 

executive, 254 

results, 345, 350 

focus group, 99–100 

return-on-investment methodology, 343–353 

guidelines for planning and conducting, 

scorecard, 352–353 

89–94 

value-based selling and pricing, 338–339 

knowledge check, 94 

Google, 193 

needs assessment and, 10–11 

Grabowski, J., 159 

objectives, 89 

Greenberg, I., 151, 157 

pilot testing, 92 

   
interviews (continued) 

interviews and, 94 

protocol, sample, 91–92 

isolating effects and, 185 

questions, writing, 90 

leadership development and, 335 

schedules, 92 

mLearning and, 318 

structured versus unstructured, 86–87 

objectives and, 27 

Ishikawa diagrams, 100–101, 102 

performance records and, 143–144 

isolating effects 

planning evaluations and, 50 

chain of impact, 175–176 

qualitative analysis and, 170 

control groups, 174, 175, 176–178 

questionnaires and surveys and, 70–71 

data analysis and, 38, 40 

results and, 280–281 

estimating, 181–184 

return-on-investment, calculating and, 221 

forecast analysis, 174, 175, 180–181 

simulation training and, 383 

importance of, 173–174 

statistical analysis and, 163–164 

knowledge check, 185 

Success Case Method and, 133 

techniques for, 174–175 

technology and, 304 

trend line analysis, 174, 175, 179–180  kurtosis (skewed data), 159–161 
   
job relatedness, 76–77  leadership development case example 
 

background, 322–323 

benchmarking/best practices, 330–331 

Kaplan, R., 247 

knowledge check, 335 

Kaufman, R., 400–403 

multiple methods, 324–329 

Kirkpatrick, D. L., 404–408 

outcomes defined, 323–324 

Kirkpatrick, J. D., 265–282 

participant survey, 326–329 

Kirkpatrick, W. K., 265–282 

results, presenting, 332–334 

Kirkpatrick four levels, 266–267, 309–310, 323  Learn.com, 299–300 
KnowledgeAdvisors, 298  learning and development 
knowledge checks 

See also mLearning 

action planning and, 122–123 

objectives, 20–21 

basic maintenance course and, 371 

opportunities for, viii–viv 

communication/reporting and, 250–251 

legal defensibility of tests, 76–77 

converting measures to monetary value and, 

 

198–199 

M 

costs, identifying, 210 

Manalu, R. H., 135–145 

criterion-referenced tests and, 81–82 

Mankin, D., 30 

estimating future value and, 234 

Marrelli, A. F., 85–95 

executive viewpoints and, 263 

Martineau, J., 321–336 

focus groups and, 105 

McLinden, D., 223–236 

global program and, 353 

mean, 150–152 
   

implementation and, 293 

 
measurement and evaluation

benefits, xiv–xv 

objectives 

challenges, vii–viii, xii–xiv 

application, 22, 23 

need for, xi 

constructing, 16, 18–19 

steps, xv–xvii 

impact, 22–23 

trends, viii 

importance of, 15 

median, 150–152 

input, 19–20 

mLearning

interview, 89 

defined, 307–308 

knowledge check, 27 

Kirkpatrick levels, 309–310 

learning, 20–21 

knowledge check, 318 

levels of, 16, 17, 19–27 

role of, 308–309 

meaning and value of, 16 

traditional training versus, 310–316 

reaction, 20, 21 

Metrics That Matter, 298 

return-on-investment, 23–24 

Microsoft Excel, 153, 154, 157, 161 

SMART, 16, 18 

Minitab, 153 

summary of, 25 

mode, 150–152 

V-model, 26 

monetary value. See converting measures to   

monetary value 

Mooney, T. P., 125–134  payback period (PP), 216–217 
Mussoline, G. R., 149–164  performance improvement, 289–290 
  performance records 

converting measures to usable data, 142–143 

needs assessment 

data collection and, 32, 35 

business requirement, defining, 6 

data sources, 141 

costs, 7, 8 

importance of, 135–136 

current state, identifying, 7 

knowledge check, 143–144 

gap analysis, 6 

linking with business measures, 136–140 

gaps between current state and business 

records, identifying appropriate, 140–141 

requirements, 7 

Phillips, J. J., 253–264, 409–414 

importance of, 3 

Phillips, P. P., 189–199, 213–222 

key questions, 4–5 

Pierre, C., 63 

methods for, 10–13 

planning 

order taker versus the consultant, 4–5 

See also action planning 

solutions, identifying, 7–8 

evaluation project, 29–51 

steps, list of, 6 

importance of, 29–30 

training, value of, 8–10 

needs assessment, 3–14 

net present value (NPV), 217–218 

objectives, developing, 15–28 

nominal group technique, 101–104 

tool, comprehensive, 44–48 

norm-referenced tests (NRTs), 73–74  Provencher, D., 192 
   
Norton, D., 247  rank or order, 62 
  rating, 63 
types of, 61, 62–63 
qualitative analysis  writing interview, 90 

data analysis and, 38, 40 

 

importance of, 165–166 

knowledge check, 170 

Ray, R., 385–386 

quantitative versus, 166 

reaction objectives, 20, 21 

steps, 168–169 

reporting. See communication/reporting 

techniques, 167–168 

results 

validity and, 167, 168 

for business executives, 271–272, 273, 

quantitative analysis, 166 

276–277 

questionnaires and surveys 

for business supervisors and managers, 271, 

accuracy, 64–65 

273, 275–276 

assessment of, 65 

Chain of Evidence, 273–274 

benefits and pitfalls of, 11 

communicating, 273–274 

body of, 60–61 

example of, 278–280 

conclusion of, 61 

for instructional designers and trainers, 269, 

content, creating, 57, 60–63 

273, 275 

data collection using, 31, 33 

Kirkpatrick levels, 266–267, 309–310 

distribution of, 65–70 

knowledge check, 280–281 

drafting, 63–64 

purpose of, 266 

effectiveness, optimizing, 63–65 

for training leaders and consultants, 

executive, 254 

269–271, 273 

feedback, 64 

for training participants, 268–269, 273, 274 

follow-up, 68–69 

types of, 267–268 

functionality, 64 

return-on-investment (ROI), 23–24 

introduction to, 57, 60 

benefit-cost ratio, 214–215 

knowledge check, 70–71 

benefits, defining, 228–229 

needs assessment and, 10 

calculating, 38–39, 40–41, 119–120, 121, 

planning, 56–57, 58–60 

213–222 

purpose of, 55 

chain of impact, 220 

response rates, 65–66, 67 

converting benefits to monetary values, 228 

sample size, 65, 66 

costs, defining, 227 

scope of, 56–57 

defined, 215–216 

steps in developing, 55–56 

example of forecasting, 230–232 

structure of, 57 

forecasting, 226–232 

testing of, 64–65 

importance of, 213–214 

questions 

knowledge check, 222 

close-ended, 62, 86 

net present value, 217–218 

finalizing, 61, 63 

payback period, 216–217 

   
intent, 61 

t-test, 162 

open-ended, 62, 86–87 

variation measures, 152–153 

return-on-investment (ROI) (continued)  Stawarski, C. A., 307–319 

programs suitable for, 220–221 

Stewart, A. C., 373–384 

sensitivity analysis, 230 

structured versus unstructured interviews, 

targets, 218 

86–87 

Robinson, D. G., 415–419  Success Case Method (SCM), 298, 323 
Rothwell, W. J., 420–426 

applications, 125–126 

 

business case, 127–128 

knowledge check, 133 

sample variance, 153 

mean or average effect, 128 

Scherwinski, M., 70 

training realities, 127–133 

Schirmer, F. C., 337–354  SurveyGizmo, 325 
scorecards, 246–248  SurveyMonkey, 297, 325 
Sensei/ROI, 298–299  surveys. See questionnaires and surveys 
sensitivity analysis, 230  systems modeling, 232–233 
7-Eleven, Field Consultant Certification   

Training, 278–280 

Shrock, S. A., 73–84  technology 
Simulations and the Future of Learning 

decision-making tips, 296–297, 300–304 

(Aldrich), 374 

examples, 300 

simulation training. See training, simulation 

implementation and, 291 

versus traditional 

KnowledgeAdvisors, 298 

SMART objectives, 16, 18 

knowledge check, 304 

Smith, K., 295–305 

Learn.com, 299–300 

solutions, identifying, 7–8 

objectives, classifying, 301 

SPSS, 153 

Sensei/ROI, 298–299 

standard variation, 153 

SurveyMonkey, 297 

statistical analysis  tests, data collection using, 31, 33 

central tendency measures, 150–152 

training 

Chi-square, 162 

effective versus effectiveness, 267–268 

converting measures to monetary value, 193, 

realities, 127–133 

196

success, 126–127 

data analysis and, 38, 40 

value of, 8–10 

descriptive, 150 

training, comparison of simulation versus 

estimating future value, 232 

traditional 

importance of, 149–150 

data collection, 376 

inferential, 150 

differences in leader effectiveness, 382 

interpreting and understanding data, 

differences in perception of leadership, 

153–158 

379–381 

   

knowledge check, 163–164 

Vance, D., 22 

kurtosis (skewed data), 159–161 

variation measures, 152–153 
training, comparison of simulation versus  VL2007, 374–375 
(continued)  V-model, 26 

knowledge check, 383 

 

outcomes, 376–377 

research method use, 375 

Wallace, D., 283–294 

results, 377–378 

Williams, J. A., 373–384 

VL2007, 374–375 

Willmore, J., 41 
trend line analysis, 174, 175, 179–180   
t-test, 162 
  Yahoo!, 193 
 
unstructured versus structured interviews, 

86–87 

Zoomerang, 325 
utility analysis, 233  Zuniga, L., 3–14 
   
 
validity   

approaches to managing, 168 

 

qualitative analysis and, 167 

 

test, 76–77 

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