DOCUMENT RESUME 7p 297 442 EA 020 170 AUTHOR Foote, Tom H. TITLE The Managerial Grid for Teachers: Evidence, Practical Applications, and Directions for Future Research. PUB DATE 28 Feb 88 NOTE 63p.; Paper presented at the Annual Meeting of the American Educational Research Association (New Orleans, LA, April 5-9, 198P,). PUB TYPE Reports Research/Technical (14:) -- Speeches /Conference Papers (150) EDRS PRICE MF01/PC03 Plus Postage. DESCRIPTORS Dropout Rate; Elementary Secondary Education; *Relevance (Education); *School Effectiveness; *Student Evaluation of Teacher Performance; *Student Needs; Teacher Education; *Teacher Effectiveness ABSTRACT Increasing dropout rates, marked decline in college preparatory enrollment, and reports of students' growing dissatisfaction with school prompted this exploration of the dimensions underlying teaching and the ways that microeconomics might positively influence teaching effectiveness. The literature review supports 10 advantages offered by student evaluations of teaching (SETS) in complementing student achievement as a schooling effectiveness measure. The Fox SETS studies show that teachers' enthusiasm accounts for twice the student achievement that lecture content does. This study's analysis was based on a sample of 60 teacher aggregates of 3,961 student questionnaires gathered over 2 years from the same high school. Factor analysis of 52 variables revealed "student-caring" versus "task-driven" as key research-based, teaching dimensions. The resulting "managerial grid" for teachers offered graphic perspectives of interrelationships not afforded by conventional frameworks. Using "student satisfaction with teacher performance" as the dependent variable, allocativa efficiency was probed using planar and other quantitative techniques. Results show that "student-caring" has substantially more influence on satisfaction than does "task-driven." Teachers are implicitly paid considerably less for caring than for task-driven behaviors. Reallocating salaries to produce teaching that interests students poses formidable technical and political problems. However, more caring for students, not necessarily more money allocated to it, should also produce higher percentages of satisfied students. The managerial grid should help define and achieve more appropriate teaching styles. Included are 128 endnotes. (Author/MLH) XXXXXXXXXXXXXX*MXXXXXXXXXXXXXXXX*XX*XXXXXX*XMXX3000000000000000000EX X Reproductions supplied by EDRS are the best that can be made X from the original document. XXXXXXXXXXXXXXXX***XXXXXXXXXXXXXXXXXXX*XXXXXXXXXX*X300000000EXXXXXXXXXXX
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DOCUMENT RESUME
7p 297 442 EA 020 170
AUTHOR Foote, Tom H.TITLE The Managerial Grid for Teachers: Evidence, Practical
Applications, and Directions for Future Research.PUB DATE 28 Feb 88NOTE 63p.; Paper presented at the Annual Meeting of the
American Educational Research Association (NewOrleans, LA, April 5-9, 198P,).
PUB TYPE Reports Research/Technical (14:) --Speeches /Conference Papers (150)
EDRS PRICE MF01/PC03 Plus Postage.DESCRIPTORS Dropout Rate; Elementary Secondary Education;
ABSTRACTIncreasing dropout rates, marked decline in college
preparatory enrollment, and reports of students' growingdissatisfaction with school prompted this exploration of thedimensions underlying teaching and the ways that microeconomics mightpositively influence teaching effectiveness. The literature reviewsupports 10 advantages offered by student evaluations of teaching(SETS) in complementing student achievement as a schoolingeffectiveness measure. The Fox SETS studies show that teachers'enthusiasm accounts for twice the student achievement that lecturecontent does. This study's analysis was based on a sample of 60teacher aggregates of 3,961 student questionnaires gathered over 2years from the same high school. Factor analysis of 52 variablesrevealed "student-caring" versus "task-driven" as key research-based,teaching dimensions. The resulting "managerial grid" for teachersoffered graphic perspectives of interrelationships not afforded byconventional frameworks. Using "student satisfaction with teacherperformance" as the dependent variable, allocativa efficiency wasprobed using planar and other quantitative techniques. Results showthat "student-caring" has substantially more influence onsatisfaction than does "task-driven." Teachers are implicitly paidconsiderably less for caring than for task-driven behaviors.Reallocating salaries to produce teaching that interests studentsposes formidable technical and political problems. However, morecaring for students, not necessarily more money allocated to it,should also produce higher percentages of satisfied students. Themanagerial grid should help define and achieve more appropriateteaching styles. Included are 128 endnotes. (Author/MLH)
XXXXXXXXXXXXXX*MXXXXXXXXXXXXXXXX*XX*XXXXXX*XMXX3000000000000000000EXX Reproductions supplied by EDRS are the best that can be madeX from the original document.XXXXXXXXXXXXXXXX***XXXXXXXXXXXXXXXXXXX*XXXXXXXXXX*X300000000EXXXXXXXXXXX
U.S. DEPARTMENT OF EDUCATION "PERMISSION TO REPRODUCE THISOffice of Educational Rematch and Improvement MATERIAL HAS BEEN GRANTED BYEDUCATIONAL RESOURCES INFORMATION
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TO THE EDUCATIONAL RESOURCESINFORMATION CENTER (ERIC)."
THE MANAGERIAL GRID FOR TEACHERS:
EVIDENCE, PRACTICAL APPLICATIONS,
AND DIRECTIONS FOR FUTURE RESEARCH
Tom H. Foote, Assistant Professor
Department of Educational Administration
Teachers College, Columbia University
February 28, 1988
Division A Paper Number 1011988 AERA Annual Meeting in New OrleansTo be presented as part of Session 49.18:"Career Aspirations and Career Structures"Saturday 8:15-10:15 A.M.Sheraton Grand Ballroom B, 5th Floor
Please direct comments to:
Tom H. FooteBox 13Teachers College, Columbia UniversityNew York, NY 10027Telephones:
Office 212/678-3857 or 3726c) Home/Recorder 212/678-1555
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 24
ABSTRACT
PROBLEM/OBJECTIVESPrecipitous increases in high school dropout rates, marked
declines in college preparatory enrollment, and reports that stu-dents are dissatisfied with school, prompted this exploration ofwhat dimensions underlie teaching and how microeconomics mighthelp efficiently produce teaching that genuinely interests,and challenges students.
PERSPECTIVES/THEORETICAL FRAMEWORKThe literature review finds support for ten advantages that
student evaluations of teaching (SETs) offer in complementing stu-dent achievement as a schooling effectiveness measure. Andreanalysis here of the Dr. Fox studies of SETs shows teacher'senthusiasm to not only strongly affect evaluations, but aso toconsistently account for over twice the student achievement thatlecture content does.
METHODS/DATA SOURCEThis study's main analysis, however, was based on a sample of
60 teacher aggregates of 3,961 student questionnaires gatheredover two years from the same high school. Factor analysis of 52variables revealed "student-caring" versus "task-driven," as keyteaching dimensions--dimensions that persist across fourteen citedmanagement and psychology studies of other supervisorycontexts.The resulting "managerial grid for teachers" offered graphic per-spectives of interrelationships not afforded by conventionalframeworks.
Using a proxy for "student satisfaction with teacher perfor-mance" as the dependent variable, allocative efficiency was probedwith planar, quadratic, Cobb-Douglas, probit and logit models ofeducational production functions fitted to proxies for the twogrid dimensions. Though the curved surface of the quadraticexplained the most variation and reflected textbook-like diminish-ing returns along both dimensions, the planar model best satisfiedconstraints of fit, and simplicity. Adding teacher's salarydeterminants and controlling statistically for nonteacherinfluences produced substantially unequal numerators and denom-inators for the requisite marginal-product-to-marginal-priceratios.
RESULTS/CONCLUSIONSAccording to microeconomic theory, these disparities imply
that the high school observed does not efficiently allocate sal-aries to produce teaching that interests students. Student-caringhas substantially more influence on satisfaction than does task-driven but teachers are implicitly paid considerably less forcaring than for task-driven behaviors., Moreover, teacher's salaryis explicitly driven most by teaching experience, and relativelyless by education--neither of which relate to student perceptionsof teacher performance (just as others, e.g., Hanushek, have foundthem not to relate to student achievement).
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MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 3
IMPORTANCE/POLICY IMPLICATIONSReallocating salaries to efficiently produce teaching that
interests students surely poses formidable technical and politicalproblems. Yet the data support the intuitively unsurprisingnotion thai.. more student - caring not necessarily more money real-located to it--should also produce higher percentages of satisfiedstudents. To that end, changes are suggested involving teacher-training institutions, hiring, career ladders, in-service enrich-ment programs, and teacher pay.
Policy change responsive to this study is well within reachin California. For example, just as the California AssessmentProgram (CAP) gathers achievement measures statewide, so too- -perhaps even on the same test instrument--could it gather SET datacovering teacher traits and student satisfaction. Indeed, just asCalifornia monetarily rewards CAP achievement gains, so too mightit reward improvements in the satisfaction and retention of stu-dents.
SCIENTIFIC IMPORTANCE/FUTURE RESEARCHFuture research is urged that uses the managerial grid as the
floor of a three dimensional space to: 1) analyze more comprehen-sive models in olving interaction of achievement, satisfaction,teaching styles and other key schooling variables; 2) establishquantitatively, the output consequences of teaching style trade-offs; and, 3) articulate preferred teaching styles (as Blake etal. did in applying their grid to other professions).
Above all, the grid should help define and achieve teachingstyles that better mix student-caring/task-driven inputs, andsatisfaction/achievement outputs--to aid the bigger picture oflong-term student wellbeing and reversal of trends that promptedthis study.
[Note: This work builds upon: earlier research done at StanfordUniversity, funded by the Ford Foundation. Although I alone, amresponsible for any errors or omissions, I remain especiallygrateful to Ed Bridges, Jay Chambers, Nathan L. Gage, Mike Garet,Michael Kirst, Henry Levin, Ray Perry, and others for theirgood ideas and feedback.]
t
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 4
1.1 PROBLEMIn April, 1983, the National Commission on Excellence in
Education (NCEE) reported that the percentage of students taking"general track" (i.e., noncollege preparatory and non-vocation0.) courses jumped from 12 percent in 1964 to 42 percentin 1979.1 In California, the percentage of students who drop outbetween the ninth and twelftn grades soared from 12 percent in1970, to 22 percent in 1979. This is consistent with an earlierreport of the California Commission for Reform of Intermediateand Secondary Education (RISE Commission, 1975) that stated"Increasing numbers of young people find schooling boring andineffective, unable to challenge their abilities, meet theirgoals, or prepare them for adulthood."' It also agrees with a1983 Carnegie Foundation study that states "Most seniors agreethat there should be more emphasis on academic subjects aod thatpoor teaching has interfered with their education . . . "'Indeed, the rash of 1983 reports seem to agree that "teachertraining should be revised; that there should be more emphasis onsubject matter and better approaches to teachingmethods."'
More recent reports have reaffirmed the above. The CarnegieForum on Education and the Economy, states:
Concern over the quality of education in this country hasbeen expressed in repeated warnings from the EducationCommission of the States' Task force on Education andeconomic Growth, the President's Commission on IndustrialCompetitiveness, the National Alliance of Business andothers ... Large numbers of American children are in limbo- -ignorant of the past and unprepared for the future. Manyare dropping out--not just out of school but out ofproductive society...An economy based on people who thinkfor a living requires schools dedicated to the creation ofenvironments in which students become very adept at thinkfor themselves, places where they master thg art oflearning and acquire a strong taste for it.°
If the above trends are as severe as reported, they may bedue, in part, to the lack of any systematic plan to produceteaching that attracts, challenges, and fulfills students. Moreprecisely, just as changing teachers' salgry determinants couldproduce more student learning per dollar, so too might a similarchange yield more effigient production of teaching that engagesand enlivens students.°
The RISE, NCEE, National Task Force on Education for Eco-nomic Growth (NTFEEG), and Carnegie reports, recommend changesconsistent with such a plan; e.g., they urge that teacher'ssalaries' and jobs'° be linked to teacher performance; thatlearners be considered "the 9rimary clientsthe most importantindividuals--served by the schools";" and, that staff evaluationprocedures 11,, . . allow for the consideration of representativeviews of those4gffected by the performance of the staff memberunder review."' The Carnegie report adds that presentincentives:
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MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88
...not only do not reward performance and productivity, butsometimes actually discourage them. Americans alreadyspend more per capita on education than any other countryin the free world. This plan will work only if those whomust finance it are convinc0 that the funds are being usedas efficiently as possible.
How to use those funds as efficiently as possible? If aschool district chose to follow the above recommendations in astrict economic sense, that is, if-- subject to a given budgetconstraint--it wanted to produce a maximum of teaching that trulyengages and enriches students--then it would first need toascertain the requisite microeconomic conditions of efficiency.Defining "efficiency" is aided by Levin's distinctions betweentechnical, allocative, and social efficiency, where:
1. Technical efficiency refers to transforming agiven combination of inputs into the maximum output(graphically depicted in two-input space by any com-bination of the two inputs on a given isoproductcurve);
2. Allocative or "price" efficiency considers relativeinput prices to find what technically efficient com-bination of inputs produces the maximum output for agiven budget (Graphically, this is where the budcntline is tangent to the highest possible isoquant)";and, finally,
3. Social efficiency means lifting society to itshighest possible indifference curve by "the optimal"combination of outputs (that point in utility spacewhere the highest possible social welfare functionis tang9nt to the grand utility possibility fron-tier)."
While this study speaks directly to allocative or priceefficiency (in allocating teachers' salaries to produce maximumstudent satisfaction), it also relates to views on socialefficiency. More specifically, some argue that society would bebetter off caring less about the traditional products (e.g.,achievement) of schools and more about how the schooling processaffects students and teachers. In his "Study of Schooling," JohnGoodlad concludes:
We can make our schools more efficient. But makingthem relevant in the lives of boys andigirls is one ofthe most demanding challenges we face.'
In a similar vein, Jencks et al. argue:
Instead of evaluating schools in terms of long-termeffects on their alumni, which appear to be relativelyuniform, we think it wiser to evaluate schools in terms
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MANAGERIAL GRID FOR 2EACHERS, T. Foote, 2/28/88 PAGE 6
of their immediate effects on teachers and students,which appear much more variable. Some schools are dull,depressing, even terrifying places, while others arelively, comfortable, and reassuring. If we think ofschool life as an end in itself rather than a means tosome other end, such differences would not do much tomake adults more equal, but it would do a great deal tomake the quality of children's (and teachers') livesmore equal. Since children are in school for a fifthof their 4xes, this would be a significant accom-plishment."
Some prefer this focus even if it results in a classical producttransformation curve--where gains in student satisfaction aretraded for declines in student achievement. Indeed, A.S. Neilwrites that he would rather see hools produce happy streetcleaners than neurotic scholars. Though related to Neil'sview, the bulk of this study will be considerably lessphilosophical, focusing largely on the technical and empiricalissut-I surrounding the allocative ficiency of producingschoc,ing that interests students."
1.2 QUESTIONSThe challenge of allocating all resources to efficiently
produce satisfied students is simplified by seeing that teacher'ssalaries and student satisfaction with teaching cover most of thebigger picture linking overall district budgets to studentsatisfaction with school in general. This follows becauseteachers' salaries consume approximately 70 percent of thosebudgets; and, roughly 80 percent of the student's time in schoolis spent with teachers.
Measuring satisfaction becomes empirically feasible byascertaining student perceptions of, and reactions to, teacherbehaviors via "Student Evaluation of Teacher" (SET)questionnaires.
From the above perspective, this study attempts to answerthe following:
1. What advantages might student evaluations of teachersoffer California public high schools as an added mea-sure of schooling effectiveness?
2. What fundamental dimensions of teaching underlie suchevaluations?
3. To what extent does one public high school in Califor-nia already satisfy the microeconomic conditions toeffciently produce teaching that interests students?That is, how much impact do specific teacher traits(e.g., knowledge of the subject matter, preparation forclass, enthusiasm) have on overall student satisfac-tion? What implicit monetary prices do districts payfor those traits? To what extent are the impact-to-price ratios disparate across those traits?
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MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 7
4. To what specific inefficiencies do any disparitiespoint and what policy changes do they imply?
2.1 PROBLEM CONTEXT"Efficiently translating dollars into desired educational
outcomes has long been a concern of economists. Writing over twocenturies ago in his Wealth of Nations, Adam Smith urged that theschool master be "partly, but not wholly paid by the public;because if he was wholly, or even principa)4y paid by it, hewould soon learn to neglect his business."' Such pessimismabout the effects of unsound incentives in schools has beenpersistent. Indeed, economists' claims of misguided incentjoie23lidNip inefficiencies in today's schools, are widespread."
° Most recently, Hanushek asserts: "The incentivesexisting within schools appear to provide a Nmpellingexplanation of public school inefficiencies" and ". . . thecurrent struggure of public education offers little hope for selfcorrection." Levin articulates the broader problems:
The conditions under which educational expenditureswill translate into improved educational outcomes arefairly stringent. First, there must be substantialagreement on which outcomes are important; second,there must be knowledge of how added resources can beused to improve those outcomes; and third, those whoare responsible for the educational process must haveincentives to maximize the socially desirable outcomes.In each case, the actual situation seems to contrastwith the assumptions that are necessary for added dol-lars to improve educational results . . There is noagreement on educational priorities, no body of know-ledge that can predict the effects of different schoolpolicies on educational outcomes, and no relation bet-weenstaff incentives and the rhetorical goals ofschools. This all suggests that school budgets are notlikely to be translated efficiently into improved edu-cational outcomes. Rather, the actual application ofthe increased support is likely to be determined by thepower and inWests of the decision makers them-selves
Important among the interests of decision makers--studentachievement aside--is maintainiqg illooth political sailing amongthe adults with whom they work.
Hanushek feels that evaluation difficulties furtherinfluence these interests at the expense of both student andcommunity interests:
The fact that school policies are so hard toevaluate makes it easier for teachers and school offi-cials to be influenced by their personal interestsWithout direct evaluations, teachers and school offi-cials need not confront the possibility that their pri-vately preferred policies Tqy be useless for the studentand bad for the community.'
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MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGES
Though school administrators' reluctance to evaluateteachers results, in part, from technical difficulties inmeasuring schooling outcomes, it also follows from the basicstructural characteristics of the public school setting; i.e.,service to captive clientele in a non-competitive, non-profitenvironment that yields nq,rewards to decision makers forefficiency in production." In discussing the correspondingadministrator strategies, Chambers argues:
Since they are unable to appropriate any pecuniary bene7fits to themselves and since they generally operate sub-ject only to a minimal survival mechanism, school deci-sion-makers find that the cost of inefficient behavior isrelatively low. Their efforts, however, directedtoward the reduction of the psychic costs involved in themanagement of district operations. Based upon these moti-vations, there is little incentive for school administra-tors to obtain precise evaluations of performance of theschool system. Any such evaluation of the outputs of thesystem could only serve to reveal possible deficienciesin their own managerial abilities and, thus, threatentheir survival. The more abstruse the method of evalua-tion, the greater reliance the school board and thecommunity must p149e in the judgment of these profes-sional educators.-"
According to Hanushek, administrators are likely to gobeyond mere abstrusive evaluation to help teachers because bothgroups' interests often coincide:
Administrators, who are typically drawn from the ranks ofteachers, share many conceptions about what is "right."Moreover, it generally serves the interest of admini-strators to accept teachers' arguments about reducingclass sizes, raising salaries, and increasing expendi-tures; such policies increase the administrators' domain;lessen conflicts with their em149yees, and ultimatelymust affect their own salaries.
These and other coincidental interests,36 and the absence ofrewards to educators to improve schooling, heighten the chances,,for interests of the deciders to encroach on those of children.'Moreover, any excellence that emerges is likely to flow moredespite such a system than because of it; i.e., likely to flowmore from personal goals and drive within especially motivatedindivtauals, than from organizational incentives external tothem."
2.2 ALLOCATION OF TEACHERS' SALARIESThe widespread time-honored system of paying teachers
according to years and units, rather than performance, clearlyfavors administrative convenience and political tranquillity overincentives for efficiency. Years and units are administrativelyeasy to measure and translate into higher salaries. The process
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requires no consideration of substantial inter-job differences insupply and demand, workloads, or required competencies (despitethe high costs of ignoring these differences). Above all, itrequires no periodic, conflict-producing evaluations of teachers.Indeed, the process is "automatic" in the senGe that each year,"action" is taken on salaries--they increase regardless ofclassroom performance.A-with little effort or political sacrificefrom administrators.'
Although the above salary' Aractice is nearly universalthroughout our public schools,a consistent body of research
Oon V2at it does not efficiently produce student achievement.'Indeed, Hanushek found no relationship whatsoever
between student achievement and teacher's years of service orpost B.A. units:
. . . the present set of hiring practices leads toan inefficient allocation of resources. The analysisindicates that teaching experience and graduate educa-tion do not contribute to gains in student achievementscores. Moreover, the characteristics that do matterare not highly correlated with these factors. Yet theseattributes are being purchased by the school district.Since turnover is costly, some average experience levelover one year would be reasonable. However, the cur-rent erage of over eleven years is certainly exces-sive.'"
After reviewing a far wider variety of inputs among 130 separatestudies, Hanushek adds: "Within the range of current schooloperations, variations in expenditures or in any other commonlyidentified determinants of school "quality" bear no systemacrelationship to variations in the performance of students."
Though certain studies show teacher expellenu'"
none-theless correlate positively with achievement,' theresearch of Keeler and McCall suggests that rather than highexperience causing high achievement, "the major reason for therelation between experience and achievement is the ability ofexpegenced teachers to get into the schools of the high achiev-ers."" Because most districts' teachers are concentrated nearthe high ends of the years and units scales, the cost of theseinputs represents a significant and periodically increasingnational expense.
The portion of this expense that serves to retain teacherscan be justified because it reduces the costs of recruiting andtraining. And relative to a more competitive performance-basedpay system, where older teachers might refrain from helpingyounger ones, the portion of years and units costs that encourageteamwork between old and young can also be justified. Yetwhatever the magnitude of these, and perhaps other, justifiableportions, it is likely that their total falls short of theentirety spent on these inputs nationally; especially with yearsand units often account4g for more than half of a district'smaximum teacher salary, and teacher's salaries consumingbetween 60 and 80 percent of districts' total operating budgets.
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2.3 BETTER ALLOCATION CRITERIA?If we reject the current pay criteria because the evidence
suggests it is inefficient, what better criteria are there?Hanushek's review of 130 input/output studieso mentioned earlier,reveals studies that do, and others that do not, showstatistically significant effects of teacher inputs on studentperformance. Though these results suggest that no input bearsany nationally generalizable relationship to student performance,this does not preclude that any one study might have accuratelymeasured effects that work well for the particOcar studentssampled. For example, Levin found, via linear regressioncoefficients, that reallocating teachers' salaries according toteachers' verbal scores could yield up to ten times the studentverbal achievement per dollar that present allocation toteachers' experience does. '4 And a later work by Levin showedteacher's verbal score to be four times as potent as teacherexperience. Though the Levin studies suggest that teacher'sverbal score might be a superior input, neither study issufficiently definitive to warrant widespread policy change.
While others argue t0.0 gonetition would force reallocationto more efficient inputs,' 5' this study tackles schools'incentives, evaluation, and salary allocation problems within theexisting non-competitive setting; by incorporating consumer(student) preferences into a microeconomic analysis of thoseproblems. More precisely, just as paying teachers according toyears and units appears inconsistent with efficiently producingstudent achievement, so too might it be inconsistent with effi-ciently producing teaching that attracts students. The lack ofany agreement on even the sign of the correlation between tea-cher's years experience and student ratings of teaching gRality(e.g., across the many studies reviewed by Costin et al.') sug-gests this might be so. And just as Levin found an input thatseems to produce learning more efficiently among a given studentsample, so too might a similar methodology reveal inputs thatproduce satisfaction more efficiently.
Such a methodology would require measuring students'perceptions of, and reactions to, specific teacher traits. Thisis commonly done with student evaluations of teachingquestionnaires (SETs). Such an effort assumes that SET resultswould offer valuable information not afforded by conventionalachievement measures--an assumption explored in the followingsection.
2.4 SETS AS A COMPLEMENTARY MEASURE OF SCHOOLING OUTPUTThe use of SETs as one meapRre of teacher output is
widespread at the college level - -and scant among high schools.This may result, in part, from there being more serious focus onpromotion and tenure for college instructors, and thereforegreater need to evaluate their teaching systematically. Sinceresearch on SETs in high schools is also scant, some of thefollowing arguments necessarily draw from college-level studies.
Though most would agree that student learning should be theprincipal output of schools, research on student evaluations ofteaching (SETs) shows that SETs complement student achievement
MANAGERIAL, GRID .FOR TEACHERS,, T. Foote, 2/28/88 PAGE 11
and other measures of school outputs with the followingadvantages:
1. SETs can measure dimensions of the schooling process,a long with other dimensions of its products: Standardized tests'were not designed to reveal the variety of ways in whichteaching and learning can be creativg4 favorably opportunistic,and uniquely meaningful to students." SETs, on the other hand,can be designed to measure at least some of these many teachingproOess variables.
2. SETs reflect a unique and central viewpoint: Studentssee a broad range of their teacher's behaviors over months ofexposure and personally know the students with whom they see theteacher interact. Furthermore, as the intended receivers ofteaching, students are the only true first-hand sources regardingthe receiving process and its effects.
3. SETs can reflect the quality of student life in school,which some believe is important in itself: Jencks et al., werecited above making this argument persuasively, i.e., urging thatschools be evaluated for immediate effects on teachers andstuftnts rather than for long-term effects on alumni (see Section1). Surely with se much of our childhood spent in school, itmakes sense to remove any unnecessary alienation or sadness thatschools might produce. But schools are hardly likely to learnthe existence, much less the source, of these ill feelings ifstudents have no mechanism to reveal them.
4. SETs can measure noncognitive traits (e.g., enthusiasm)exhibited hy teachers, and students. Recent research suggeststhat such traits are at least as important to students' latersuccess as are cognitive ones: In their latest study, Who GetsAhead, Jencks et al. find:
Taken together, noncognitive measures explained at leastas much of the variance in men's status and earnings astest scores did. While we could not isolate any singlepersonality characteristic that was critical to success,we can say that the relevant traits are largely inkpen-dent of both cognitive skills and parental status.°'
With noncognitive traits so important to later success, it makessense to begin measuring them and exploring their inter-relationships. Indeed, SETs carefully designed to reflectnoncognitive traits of both teachers and students, could aidresearch into the synergy between them.
5. The act, of seeking feedback throu hh SETS can be a tan-:-ble .gign to studor:-,s that teachers and offici aTS seek and valuestuderty..yietws. Moreover, the extent to which those views areact' Alaxe this a step, albeit a small one, toward some demo-cr:4 on of school decision making.
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6. SETs are highly reliable. And since they are lesscorrelated with student characteristics (e.g., sEal than areachievement tests, they are fairer to teachers. In summarizingthe empirical evidence on SETs, Gage writes:
As for reliability, the results are almost uniformlyhappy. Averaging the ratings of about 20 students on asingle item concerning a set of teachers, such as a ratingof the clarity of the teacher's explanations, yields amean rating that has a reliability of about .8 or .9.That is, these mean ratings would correlate about .8 or.9 with the mean ratings of another set of 20 equivalentstudents. This finding has been obtained with almostperfect consistency during the 50 years or so sinceRemmers (1929) first established. In short, the pooledratings of 20 or more students reveal substantial agree-ment within a class as comp4red with the amount ofvariation between classes.
This is consistent with "split class" reliabilities averaging .85for SET factor score9,found in junior-senior high-school classesby Veldman and Peck.'
Achievement tests, on the other hand, are ordinarily highlycorrelated with student characteristics. Glass writes:
Aside from the irrelevance of much of the content ofstandardized achievement tests, their use in evaluatingteachers is unjust. Nonrandomly constituted classes giveteachers of brighter pupils an unfair advantage. Thisremains true whether the statistician calculates simplegains, residual gains, true gains, true residual gains,covariance adjustments, etc fo available evidence indi-cates that teachers' effects on pupils' knowledge are notreliably measured by such tests."
Thus SETS are fairer to the teacher in the sense that they areless sensitive to between-student differences (or in the words ofGage, they "reveal substantial agreement within a class ascompared with the amount of variation between classes"). Thatis, they are fairer than are achievement tests, because they areless sensitive to student differences (like student'ssocioeconomic status) clearly beyond the teacher's control.
7. SET responses correlate positively with evaluations doi.eteacher-colleagueg,apg supervisors. At the University of
Washington, Guthrie " " found correlations ranging from 0.30 to0.63 between students' ratings and teacher-colleague ratings ofthe same teacher And at the junior-senior high school level,Veldman and Peck show agreement between SET results andevaluations by teacher's supervisors. This is consistent withthe following araument: Though teachers may question thevalidity of student ratings, teachers usually know which of theircolleagues they'd prefer their own children to study under, andsuch preferences tend to agree with the very ratings the teachersdiscount.
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8. SETs offer wide applicability across courses: Unlikestandardized tests, one SET form can apply to a wide variety ofschool subjects, thus permitting control of instrument typeacross courses.
9. SETs may help improve instruction: Most instructorswould aoknowledge that certain student feedback can help improveinstruction (especially those who, because of feedback, no longlioloq the
4view of their own chalkboard work). And many studies
73 / do show greater gains in student ratings forteachers who have received and acted on SET feedback (thoughrated improvement has yet to be proven equivalent to actualimprovement).
10. SET's are valid in that they relate positively--thoughnot strongly--to student achievement: The central challenge tothe advocate of SET'sWg a measure of teaching effectiveness, isto disprove the likelihood of either of the two following errors:
a. The demanding teacher produces much achievement butreceives low student evaluations (Type I error:good teacher rated as poor teacher);
b. The well-liked easy teacher produces little studentachievement but gets high ratings (Type II error:poor teacher rated as excellent teacher)."
The most celebrated studies to this end are the series of "Dg.,Fox studies." These began when Naftulin, Ware, and Donnellyattempted to prove that a charismatic though nonsubstantivelecturer could receive high ratings even from highly educatedprofessionals. Remarkably, a large number of the listeners--includinvpsychiatrists, psychologists, and educators--didevaluate the Dr. Fox lecture favorably; even though, accordingto the authors, the lecture contained no substantive information.The authors conclude that this "suggests to the educator that theextent to which his students are satisfied with his teaching, andeven the degree to which they feel they have learned4Oreflectslittle more than their illusions of having learned."' Yetwithout any effort whatsoever to test whether, or how much, thelisteners may have learned, the authors conclude much more thantheir results support.
The,Rut8op' approach improved considerably in three laterstudies." ° °' In short, those studies actually measured howstudent satisfaction and student achievement varied acrossdifferent levels of teacher enthusiasm, and measurable lecturecontent. In the last of the above studies, they conclude ". . .
the results observed to date suggest that student ratings ofhighly expressive instructors may not reflect two importantdimensions of teaching effectiveness, namely, sw4stantiveness ofinstruction and degree of student achievement."'
14
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 14
FIGURE 2.1DR. FOX STUDIES: PROPORTION OF ACHIEVEMENT AND SATISFACTIONSTATISTICALLY ASSOCIATED WITH LECTURE CONTENT VERNS TEACHER
ENTHUSIASM AS MEASURED BY OMEGA- SQUARED
PROPORTIONACHIEVEMENTCAPTURED BY:
TEACHER'S ENTHUSIASMLECTURE CONTENT
ENTHUSIASM/CONTENT RATIO
PROPORTIONSATISFACTIONCAPTURED BY:
TEACHER'S ENTHUSIASMLECTURE CONTENT
ENTHUSIASM/CONTENT RATIO
STUDY 21975
0.090.04
2.25<
0.240.04
6.00<
STUDY 41977
0.130.06
>2.17
0.240.04
>6.00
84
What they fail to report about their own data, however, isthe remarkably consistent across-study pattern concerning thepercentage of achievement and satisfaction attributableto lecture content versus teacher enthusiasm (as measured byomega-squared, the r-squared analog for ANOVA). Across bothstudies, variation in enthusiasm accounts for nearly twice (2.25for Study 2 versus 2.17 for Study 4) the variation in achievementthat variation in lecture content does. And again, across bothstudies, enthusiasm accounts for exactly 6.00 times the variationin satisfaction that content does. This surprising consistencysuggests the intuitively appealing hypothesis that if lecturecontent is held constant and high, then how much of that contentis learned, will depend strongly on how enthusiastically theteacher delivers it. This makes sense, since little is likely tobe learned, regardless of how content-rich the lecture, if thelecturer fails to obtain the students' attention.
Though none of the Dr. Fox material or any other researchcategorically proves or disproves the likelihood of either theabove Type I or II errors (a fact that should caution anyinterpretation of SET results), the most carefully conductedstudies of the cor5etion between SET's and studentachievement 8b 6 °°
l§doshow, on average, low positive correla-
tion between ratings of teachers' overall effectiveness andstudents' final exam score.
";R fact, these correlations (e.g.,
those of Sullivan and Skanes) higher than those found inmeta-§Raiises seeking what teacher behaviors affect achieve-ment.
In meta-analysis of links between ratings and achievement1Cohen used 41 independent validity studies reporting on 68separate multisection college courses. He found achievement
15
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 15
correlated an average of .43 with overall instructor rating, and0.47 with the overall course rating. He concludes:
We can be quite confident that the relationship betweenratings and achievement described in this meta-analysisis characterized by what Bracht and Glass (1968) term"external validity." That is, the present findings canbe generalized to different students, instructors, insti-tutions, and subject matter areas . . . Based on thefindings of the meta-analysis, we can safely say thatstudent ratings of instruction are a valid index ofinstructional effectiveness. Students do a pretty goodjob of distinguishing among teachers on the basis of howmuch they have learned. Thus, the present study lendssupport to the use of ratings as one Rqmponent in theevaluation of teaching effectiveness.'
Indeed, the majority who have seriously studied SETs (Cohen,Gage, Costin et al.) conclude that they do relate, though notstrongly, to student achievement.
Do the teachers who are easy grader§,' gq the highestratings? Sow §Eudies say that they do, " others say that,,they do not,' " and still others that report mixed results."Costin et al. suggest that those positive relationships that werefound between rating and grade received, are likely to resultfrom higher interW in the course triggering both higher ratingsand higher grades" (i.e., not from desperate teachers buyinghigher ratings by giving higher grades).
2.5 SET'S: SUMMARY VIEWSIt must again be stressed that although this study focuses
on high schools, the relative scarcity of high school SETresearch meant heavy reliance here on college-level studies.
In summarizing t'leir extensive review of SET research(which, like this review, covered some high school SET studies,though mostly college-level research), Costin et al. made thisoverall assessment:
A review of empirical studies indicates that students'ratings can provide reliable and valid information on thequality of courses and instruction. Such information canbe of use to academic departments in constructing norma-tive data for the evaluation of teaching and may aid theindividualinstructor in improving his teaching effec-tiveness.'
However, with specific regard to using SET's for personneldecisions, McKeachie cautions:
Student ratings of teaching are related to teachereffectiveness as measured by the achievement of theteacher's students. Nevertheless this does not meanthat student ratings are sufficient evidence of teachingeffectiveness. Ideally one would gather evidence from anumber of sources . . . Moreover, ratings should be
16
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 16
obtained over several courses and several semestersbefore being admitted as data in the faculty evaluationprocess. A rating of a particular course in a partic-ular semester may be influenced by special circumstancesthat affect its validity. Even when ratings from sev-eral courses are available, they need to be interpretedby peers or administrators who know somethingAbout thenature of the courses and students involved.'"
Exactly which teacher traits affect students' overallsatisfaction with the teacher? French-Lazovik found that at thecollege level, over 90 percent of the variation in studentratings of overall teacher effectiveness could be explained bystudent ratings on the following three teacher trait items: 1)Interprets abstract ideas and theories clearly; 2) Gets studentsinterested in the subject matter; and 3) Has increased student'sskills in thinking. Moreover, the relative importance of theseand other items in predicting overall student perceived teachingeffectiveness maintained ". . . surprising consistency across a15-year time span on two quite different campuses with differentstudent and faculty populations."1°
At the junior-senior high level, Veldman and Peck'sresearch showed a 38-item questionnaire to embody these fivefactors: 1) friendly, cheerful, admired; 2) knowledgeable,poised; 3) interestingA,preferred; 4) strict control; and 5)democratic procedure.'" Persisting over three separatesemester's data sets (554 teachers total), this structure, likethat found by French-Lazovik, appears steadfast with respect totime. (These factors also closely resemble those that emerged inthis study's Sections 6, 7, and 8; namely "student-caring"; and"task-driven.")
In short, the French-;,wvik results. the many studiesresults.by Costin et al., and Cohen, , and Veldman and
Peck's junior-senior high-school level research suggest thatstudent criteria for teaching effectiveness are substantive andfairly stable over time.
3.1 METHODS, OVERVIEWThe main empirical question posed here involves
ascertaining the extent one California public high schoolefficiently produces teaching that interests students.That question will be answered by gathering two years of SETdata; adding to it teacher salaries and variables that determinesalary; and using regression models to find the extent the datasatisfy microeconomics' specific conditions for allocativeefficiency. The regression work involves specifying tworegression models with salary and student satisfaction as therespective dependent variables and teacher traits as the inde-pendent ones; estimating the equations' respective coefficients;and finally, plugging those coefficients into the correspondingmarginal product to price ratios--the ratios required by micro-economics to determine allocative efficiency.
The original sample of 5,076 student-level questionnairescomes from a medium-sized public high school in the San FranciscoBay Area whose students are largely middle-class,
17
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 17
The 31 questionnaire items used to measure teacher traitsessentially cover all achievement-producing tKpits noted by R.W.Heath and M.A. Nielson, RosenshipR,and Furst and some ofthose tested by Gage and Hedges."' Moreover, they cover mostof those satisfaction-re kted traits revealed by the earlier-mentioned French- Lazovik and Veldman and Peck studies.studies.
3.2 OBTAINING A MEASURE OF OVERALL STUDENT SATISFACTIONOverall student satisfaction with teacher performance was
measured as the percentage of each teacher's students whoresponded "yes" to the question "Would you take a class with thisteacher again?" This measure is analogous to the economists'notion of "repeat buyers," i.e., it does the best we can do inpractice to ascertain who would go back for more of the sameteacher, if free to do so. More specifically, though economistswould much rather observe the act of repeat buying, rather than amere response to the question 77.7E;uld you buy again," therigidities of high school class scheduling generally prevent thestudent from ever performing that act.
3.3 SINGLE-SHEET SUMMARY OF MODEL AND METHODSMethodologies here embody both process and input-output
views of schooling. More specifically, exploring links betweenschooling dollars and student satisfaction begins by articulatingprocesses that should efficiently translate budgets into teachingthat attracts, challenges, and fulfills students--a process sum-marized on the single sheet of Figure 3.1 and described asfollows:
The roughly 70 percent of district budgets that go forteachers' salaries can be disaggregated into components key tothis study. Total salary (ST, or Salary Total) appears in Figure3.1 as a vector--the vector sum of that component that exactlycompensates the teacher for traits yielding desired impact(labeled SI for Salary yielding desired Impact) plus that resid-ual (SR, or Salary Residual) having nothing to do with thatimpact (e.g., rewards for remaining with the district). Intheory, then, that part of total salary that compensates desiredimpact is the projection of SI onto ST. In turn, SI can beviewed as the sum of manifold cost vectors, each corresponding toa specific impact-producing teacher trait.
The total impact a teacher has on students over time (shownin Figure 3.1, as "impact vectors" labeled with I's) is thenproportional to levels of certain teacher traits and school andstudent characteristics (e.g., powerful ncnteacher influenceslike student's socioeconomic status). This impact stimulatescognitive achievement, perceptions of teacher traits, and otheroutcomes (shown with arrows pointing different directions).
In short, this study explores those perceptions by havingstudents indicate how much their teacher exhibits specific traits(indicated by the PTik's, or Perceived Trait 1 evaluated by thekth student) and also whether the teaching would attract them to
18
. MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 18
FIGURE 3.1FLOWCHART OF TEACHING SERVICE EXCHANGE,
AND THIS STUDY'S METHODOLOGIES
PIXEDSCHOELBUDGET
DISTRICTHIRES ORRETAINSTEACHERACCORDINGTO TRAITS
OTHER COSTS!AD3INISTRATION,OTHER OVERHEAD,BOOKS, SUPPLIES,NEW EQUIPNENT
OTH:11 INFLUENC
VE
=PACT VECT
TINE
HOLD.-LINED BLOCKS INDICATE MAJOR ECONOMIC DECISIONPOINTS FOR THE
SCHOOL. SCHOOL DISTRICT
ITti
DISTRICT C=IENSAPICN TO IEACHEHS ISFROFOnTIONAL TC TEACHER POSSE-SION OETRAITS(YEARS EXPERIENCE on COLLEGECREDITS)
MYX18
at
StS
St
4
SSy
S
SA
TEACHER DELIVERS SERVICE, COHFONENTSAND INTENSITY OF WHICH ARE PROPORTIONALTO TEACHER POSSESSION OF TRAITS, THOUGHALSO INFLUENCED BY SCHOOL AND STUDENTCHARACTERISTICS
)11.5.--'-'T 2 1 It
STUDENT 13 EXPOSED TO TEACtLR S SERVICE.IMPACT OF WHIC: IS PROPORTIONAL TO BOTHTEACHLR ME STUDENT TRAITS
STUDENT ACHIEVEMENT
SERCEPTION VECTORS--4P P
ST TOTAL TEACHER SALARY
Sy* CONFONENT OF TEACHER'SSALARY WHICH rLACTLY COM-PENSATES TEACHER FOR T/LIITSWHICH AFFECT DESIRABLE IMPACTS
.
S. RESIDUAL COMPONENT OFTEACHER'S SALARY WHICH BUYSMINIMIZATION OF TEACEMH/ADMIN'INSTRATOR CONFLICT AND ALSOINCLUDES BASE PLUS ERROR
. ANGLE OF SALARY/IMPACT=EFFICIENCY
OTHER OUTCOIIES
OTHEE INFLUENCES
STUDENT FIRCEFIIONS OF EXTENT TEACHERPCSEEZSES CERTAIN TRAITS AND STUDENTSATISFACTION WITH THAI' EXTENT
FLOWCHART OF PROPOSED METHODOLOGY
(f:1721
PTIA
Pi
PTik INDEX OF STUDENT k's rERCEPTIONOF EXTENT TO WHICH THE T.:ACHER POSSEISESBAIT 3.
"(*---411TH;RsiT NTAINTAITANsponsx
PTJ1
1A CLASS WITH TLIII TEACHER AGAIN
722.:PT2k..:Prac
PTA pijk
ULTRIX OF PERCEPTION RESPONSESOF ALL NiS TEACHER'S STUDENTS
yvi tr2 Vic
VECTOR OF XES/NO RESPONSESOr ALL THIS TEACHER'S STUDENTS
70
STUDENT INDICATESEXTENT TEACHEREXHIBITS TRAITSMD INDICATESWHETHER WOULDTAKE A CLASS WITHTHIS TEACHER AGAIN.THIS YIELDS APERCEIVED TRAITVECTOR AND ADICHOTOMOUSSATISFACTIONMEASURE
CLASS- AVERAGEFACTOR, OR ITEM-.GROUP SCORESFOR TRAIT H(M << 3)
CvREOATE PTA,' p.THE PRINCIPAL REOR SION ENA/ 411
Zr ht +1'1;.1, ) 1'2 A2) +..+Cr,r1 An
ST Sit 4 Pt ) +I P2 (I,PTA2 ) +. +1, MVECTOR OF PERCEIVEDRAITS AVERAGED OVERALL THIS TEACH: R'SSTUDENNTS
THE
SCALAR INDICATIVO THEPERCENTAGE OF ALL THISTEACHER'S STUDENTS WHORESPONDED YES
19
- I. ''')..
IMPACT'-TO-PnCE RATIOSIFOR EACH
1
LELPt
t2
P2 Pm
"POLICY IMPLICATIONS'
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 19
take a course with the teacher again (shown by the YNk, a Yes orNo response of the kth student). Teacher-level aggregates- -Perceived Traits Averaged, shown by PTA4's, and the percentresponding "Yes" to the above teaching evestion (the Yt's)--werethen generated from the student-level questionnaires.
The PTAi's served as independent variables, and Yt's andteachers' salaries, as dependent variables for the marginalimpact and marginal price regression models, respectively (asshown in the lower right hand corner of Figure 3.1, labeled "THEPRINCIPAL REGRESSION EQUATIONS"). Several different regressionmodels (simple planar, simple quadratic, Cobb Douglas, logit andprobit) helped estimate the marginal impacts of teacher traits onoverall student satisfaction (components of the I vector:12, . . . IM- -shown under Figure 3.1's heading "THE IMPACT-TO-PRICE RATIOS FOR EACH TRAIT") and the implicit marginal pricespaid for those traits (components of the P vector: Pi,P21 PM ). The simple planar equations in the lower rightcorner of the flow chart produced linear estimates of the rawI's and P's, which, in turn, represented the increment in studentsatisfaction (percent total yes) and the marginal price (theimplicit marginal increase in total teacher salary, ST),respectively, per unit change in a teacher's class-average scorefor trait m, ceteris paribus.
In short, computing the marginal-impact-to-marginal-price(I/P) ratio for each trait produced disparate I/P ratios acrosstraits. This, in turn, suggested specific inefficiencies andcorresponding policy implications.
4.1 OVERVIEW OF HOW THE VARIABLES INTERRELATE:THE MANAGERIAL GRID FOR TEACHERSPerhaps the best overview of how 41 the varialplps inter-
relate is seen in the following SPSS-X"' quartimax'"rotation in Table 4.1:
20
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 20
TABLE 4.1QUARTIMAX ROTATION, FACTOR MATRIX USING
ALL TEACHER-LEVEL VARIABLES, BOTH YEARS COMBINED
FACTOR 1 FACTOR 2 FACTOR 3 FACTOR 4
STUDENT-CARING (THIS STUDY)PEOPLE-CENTERED (BLAKE AND MOUTON)
TABLE 4.1, CONTINUEDQUARTIMAX ROTATION, FACTOR MATRIX USING
ALL TEACHER-LEVEL VARIABLES, BOTH YEARS COMBINED
PHWOCCAPHWALWSHMWORKLGRADETESTS
PHADTOPROTHERPRTEACH
SALARYYEARSEDUNITS
PBLKHISPHISPPWHITE
FACTOR 1 FACTOR 2
FACTOR
.91782
.87422
.80756
5 FACTOR 6
SALARYAND ITSDETERMINANTS
FACTOR 3
-.95045.95045
-.92664.61684.51948
PAGE 21
FACTOR 4
STUDENTS'WORK ANDEVALUATION
REASON FORTAKING THECOURSE
.95620 ETHNICITY
.89316 MIX IN CLASS-.82414
-.97378.96245
-.90992
Though the questionnaire was never consciously designed toproduce specific factors, the above loadings suggest variablegroupings with the follow descriptions:
FACTOR 1: The extent to which the teacher cares about thesocio-emotional well-being of students (STUDENT-CARING).
FACTOR 2: The degree to which the teacher is driven towardcompletion of the tasks at hand (TASK-DRIVEN);
FACTOR 3: The student's work and evaluation;
FACTOR 4: The student's reasons for taking the course;
FACTOR 5: The teacher's salary variables; and,
FACTOR 6: The ethnicity mix of the students within a giventeacher's aggregation;
The first two factors, STUDENT-CARING and TASK-DRIVEN,account for 69.6 percept of the total variation among teachertrait variable's alone" and replicate the same two latentdimensions that persist across other studies from psychology and
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88
FIGURE 4.1
THE MANAGERIAL GRID OF BLAKE AND MOUTON112
1 2 3 4 5 6 7
HIGH +
C0
9
11,9 ManagementThoughtful attention to needs+of people for satisfying rela-
8 ltionships leads to a comfort-N able friendly organizationC +atmosphere and work tempo.
7 I
N
F61O +
51
O4 i
P +
L 3
PAGE 22
8 9
ManagementWork accomplishment is francommitted people; interdepen-dence through a "common stake"in organization purpose leadsto relationships of trust andrespect.
5,5 ManagementAdequate organization perfor-mance is possible throughbalancing the necessity to getout work with maintaining mor-ale of people at a satisfac-tory level.
+la Management2 Exertion of minimum effort to
get required work done is+appropriate to sustain organi-
1 Ization membership.LOW I
la ManagementEfficiency in operationsresults fran arranging condi-tions of work in such a waythat human elements interfereto a minimum degree.
Couch,' Fiedler,' and Fleishman et al.'"). Labeling thesedimensions as "concern for people" and "concern for production"Blake and Mouton plot and discuss five managerial styles on theirresulting "Managerial Grid," reproduced in Figure 4.1. Accordingto Blake and Mouton, that grid:
. . . has been applied in widely different organizationalsettings in the United States, Canada, Europe and Asia.Included are industrial facilities of manufacturing,sales, R&D, and union organizations as well as military,governmental, professional and welfare settings such ascommunity agencies . . . it seems to provide descriptionsof managerial alternatives that are equally useful whenapplied to managerial dilemmas in the U.S., in countriesof Europe that are somewhat similar to our own, and in
23
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 23
cultures of Asia, which are far different. The schema, inother words, seems to be relatively culture-free and,therefore, of general relevance for understanding problemsof management wherever men work in concert . . . itsapplication is not limited to any particular level in theorganization hierarchy. It applies in solving problems atthe bottom where concrete supervisory skills are requiredand at the top where executive decision-making inv9lxingfar more subtle and complex judgments is demanded."'
Likewise, Fleishman, Harris and Burtt describe what appear to bethe same factors discussed by Blake and Mouton:
Actually, we were able to extract two leadership factorswhich were quite independent, both of which will be dis-cussed in detail later. One identified as 'consideration'included such characteristics between supervisors andsubordinates as friendliness, mutual trust, and respect.The other, termed 'initiating structure,' involved estab-lishing patterns of organization, chanMcs of communica-tion, and ways of getting things done.'"
The four teacher traits loading heaviest on the "studentcaring" versus "task driven" factors of this study's "ManagerialGrid for Teachers," and the other authors' respective versions ofits dimensions, appear in Table 4.2.
24
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 24
TABLE 4.2FOUR VARIABLES LOADING HEAVIEST ON =DENT-CARING AND TASK-DRIVEN FACTORS
AND OTHER AUTHOR'S LABELS FOR THEIR VERSIONS OF THESE FACTORS
FACTOR LABELSFOR THIS STUN I STUDENT-CARING
VARIABLESLOADINGHEAVIEST ONTHESE FACIORS
TASK DRIVEN
DEGREE TO WHICH YOUR TEACHER:
1. IS UNDERSTANDING (UNDRST)2. STIMULATES YOUR INTEREST
AND INVOCVEKENT IN THECOURSE (INVOLV)
3. IS RESPECTED BY YOU(RESPEC)
4. IS FLEXIBLE (FLEXBL)
DEGREE TO WHICH YOUR 'TEACHER:
1. IS PREPARED FOR CLASS(PREPAR)
2. IS WELL ORGANIZED (ORGNZD)3. MAKES OONSTRUCTIVE USE OF
CLASS TIME (CTIME)4. IS KNOWLEDGEABLE ABOUT THE
SUBJECT MAiTER (KNOWL)
AUTHORS' LABELS FOR SIMILAR FACTORS FOUND IN PSYCHOLOGY ANDMANAGEMENT LITERATURE:
BALES
BLAKE ANDMOUTON
COUCH
FIEDLER
FLEISHMAN,ET AL.
SOCIO-EMOTIONAL SPECIALIST
PEOPLE-CENTERED
SOCIAL EXPRESSIVITY
RELATIONSHIP MOTIVATED
OXIST_DERATION
TASK SPECIALIST
PRODUCTION-CENTERED
TASK SERIOUSNESS
TASK MOTIVATED
INITIATING STRUCTURE
The other authors' labels for their versions of these twodimensions have also been inserted in the following plot of thefactor loadings (Figure 4.3).
It should be no surprise that evaluations of teachersproduce the very two dimensions widely believed to be key amongmanagers. Though big differences exist between their respectivejobs, both are responsible for getting a subordinate group ofpeople to accomplish prespecified tasks, and reward them forit.
2 5
- MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 25
FIGURE 4.3QUARTIMAX ROTATION PLOT OF FIRST TWO OF THE ABOVE FACTORS:
THE MORE TASK-DRIVEN THE TEACHERTHE FEWER THE TIMES THAT STUDENTSMISSED CLASS.
STUDENT-CARING (THIS STUDY)PEOPLE-CENTERED (BLAKE AND MOUTON)CONSIDERATICN (FTEISHMAN, ET AL.)SCCIO-EMOTIONAL SPECIALIST (BALES)RELATIONSHIP MOTIVATED (FIEDLER)SOCIAL EXPRESSIVITY (CCUCH)
INote: The overall satisfaction measure, PERCENT YES, loads on TASK-
DRIVEN negatively here, but positively in other rotation methods. For the
main analyses, however, the varible chosen to represent TASK DRIVEO, "IS
PREPARED FOR CLASS" (variable 37 above) does relate positively to satisfac-tion.
26
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 26
4.2 THE GRID AND RELATIONSHIPS AMONG KEY VARIABLESThe meanings of other variables plotted in Figure 4.3 also
seem to agree with their locations within the TASK-DRIVEN versusSTUDENT-CARING grid. For example, the strongly negative loadingof "how mal4 class periods of this course have you missed"(MISSED24 on the plot) confirms that the more task-driven theteacher, the fewer the class periods the students will miss (orwill report having missed).
Of considerably greater importance, here, is that overallsatisfaction (the percentage of students who want to take acourse again with the teacher, PERCENT YES--->42 on the plot)loads quite positively on STUDENT-CARING, and, ambiguously onTASK-DRIVEN (though its positive correlationiwith the strongestproxy for task-driven, is less unambiguous).'" Moreover, itsloadings are distant from, and carry opposite signs of, theloadings for salary. Taken together, this suggests that studentsatisfaction relates strongly to student-caring, considerablyless to task - driven,, and perhaps negatively, if at all, tosalary. In short, this hints that salary is not allocated toproduce satisfaction efficiently.
5. SPECIFYING, AND ESTIMATING THE EQUATIONSDespite distinct differences in each rotation method's
objectives, Table 5.1 shows that for this particular sample (bothyears of teacher-level aggregates combined and weighted) eachproduced roughly similar rank-orderings of variables loading highon each of both factors. Indeed, the consistently high loadingsof the same variables across the five different techniques arguesfor using these variables as proxies for the grid dimensions theyload high on. Substituting proxies for the grid dimensions will,in turn, avoid what in earlier runs involved messy computationsand interpretations of factor scores; a substitution consistentwith our goal of constructing a model that is parsimonious, andeasy to interpret.
Table 5.1 shows that the STUDENT-CARING versus TASK-DRIVENfactors will be best represented by either UNDERSTANDING andORGANIZED (ranked first on each of the two dimensions forquartimax) or UNDERSTANDING and PREPARED (first ranked for bothvarimax and equamax).
27
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88
TABLE 5.1RANK ORDERING OF FOUR HIGHEST LOADING VARIABLES ON
STUDENT-CARING VERSUS TASK-DRIVEN FACTORSFOR DIFFERENT ROTATION TECHNIQUES
Makes constructive use of class time.Is flexible.Stimulates your interest and involvemei in the course.
Is knowledgeable about the subject matter.Is well organized.Respects you as an individual; seems to be interested in you asa person.Is prepared for class.Is respected by you.Is understanding.Is warm/friendly.Makes you feel that your contributions are important andmeaningful.
5.1 ESTIMATING THE COEFFICIENTSAfter numerous attempts with more complicated models, the
preferred models contain only the earlier determined proxies foreach of the grid dimensions, and the inputs the district actuallypays for (teacher's post-B.A. education units, and teacher'syears experience), for a total of four independent variables.
Regressions were done uzing five models: simple planar,simple quadratic, Cobb-Douglas, probit, and logit. In short, thesimple planar model has PYES move as a linearly increasingfunction of a given trait variable (ceteris paribus), while thequadratic has PYES move as a curvilinearly increasing (squared)function--with decreasing slope (diminishing returns). ThoughCobb-Douglas, probit and logi are also curvilinear, Cobb-Douglasembodies a slightly more sophisticated exponential of which thenatural log is taken; Probit involves the cumulative normal
28
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88
TABLE 5.2ADJUSTED R-SQUARED VALUES FOR THE DIFFERENT MODELS
probability function; And logit uses a "logistic function" of theodds that a given student will respond "yes" to the question"Would you take a class again with this teacher?"
Table 5.2's rows labeled "DIRECT" indicate where PYES wasused directly as the dependent student satisfaction variable,while rows labeled "CONTROLLED," refer to regressions that con-trolled PYES for effects beyond the teacher's control (effectsdiscovered earlier, which we had promised to deal with at thisregression stage).
Despite the virtues of "controlled" regressions over"direct" ones, direct versions were still run to understand thenature of the raw production function, and to see the degree towhich the controlling process "dulls" the regression equations interms of lower R-squareds, wider standard errors about thecoefficients, and lower significance levels. As the adjusted R-squareds of Table 5.2 show, this dulling effect is considerable.
2)
4
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 29
5.3 SIMPLE PLANAR APPROACHConsistent with the hope that the model be parsimonious, the
earlier-mentioned trait proxies for STUDENT CARING (UNDRST) ANDTASK DRIVEN (PREPAR) were plugged into the following planarmodel:
Though the planar fits offer respectable R-squareds, thelinearity embodied in the above will not reveal the extent towhich diminishing marginal returns (curvilinear phenomena) mightoperate.
5.4 SIMPLE CURVILINEAR (QUADRATIC) APPROACHTo detect and measure marginal returns, the following
quadratic form was run on both pairs of factor proxies:
As Table 5.2 reveals, this particular model explained more varia-tion in satisfaction than did any other, in both direct, andcontrolled versions. Moreover, as Table 5.4 shows, it consis-tently yielded negative coefficients on the squared terms--i.e.,empirical evidence the diminishing returns discussed above.
5.5 CLOSER INSPECTION OF PLANAR AND QUADRATIC FORMSSince both the planar and quadratic forms require no trans-
lation o:g any of the original variables (unlike Cobb-Douglas,ldgit, and probit), both can be discussed in the context ofthree-dimensional plots whose dimensions measure the locations ofteacher aggregates in the relevant production space. That spacewill measure student satisfaction (PERCENT YES) as a function ofteaching that is student-caring (pywied by UNDERSTANDING), andtask-driven (proxiccl by PREPARED). 141 The 60 actual teacheraggregates plotted22 in that space appear in Figure 5.2:
31
. MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 31
,Polt,"014.11104,1r i&e,10.. i 441/4,10411P ,,,,-..-
.1.'*44. 4.4 /
4-44
N = 60 ACTUAL TEACHER AGGREGATES OF 3,961 STUDENTS.
ABOVE PLOT OCCUPIES ONLYUPPER QUADRANT OF THEORIGINAL "PREPARED VERSUSUNDERSTANDING" FLOOR
6,
32
3,0
a,o
Eao
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 32
As the above plot confirms, the high ratings received onaverage by all teachers, confine the data to the greater-than-4.0quadrant of the original floor. All 60 data points do not appearin the plot because the plotting software, designed to show thecorresponding surface, depicts only the approximate view thatwould result from draping a sheet over the points. That is, itconceals all data points that lie under the sheet (All the actualdata points are more conveniently plotted and discernible insubsequent figures depicting two - dimensional slices of the pro-duction space). Despite the concealment, the surface does sug-gest that PERCENT YES tends to rise as a function of theteacher's average for PREPARED, and UNDERSTANDING. Plots of thecorresponding planar and quadratic fits (whose statistics weredetailed earlier) confirm the nature of that trend (Figures 5.3and 5.4). The four-term quadratic equation produces the expectedsurface with positive first, and negative second, derivativeswith respect to both inputs.
e
I lip is.
410
II
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 34
FIGURE 5.4
PERCENT YES AS A QUADRATIC FUNCTION OF'
100(A 95V3 90)' BS
80151005
W 5080
0is. 051C)
ro 4 0
505
ZC4 15P to23 c
5r
UNDERSTANDING VERSUS PREPAREDPLANAR SLICE AT THE MEANOF UNDERSTANDING
ACTUAL SAMPLE SIZE WAS N = 60 T AGGREGATES OF 3,961 STUDENTS
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 35
Detailed comparison of the planar versus quadratic fits isenhanced by taking vertical slices of the surfaces, at the meansof the respective inputs. For example, Figure 5.5 represents anenhanced version of the slice shown in the three dimensionalquadratic plot of Figure 5.4. This PERCENT YES versus PREPAREDcross section taken at the average value for UNDERSTANDING (equalto 5.17) shows both the corresponding planar and quadraticcurves,, and superimposes projections of all the actual datapoints (represented with 'Au's for Actuals or u*u's for where twoor more points overlap). The word projections is emphasizedbecause if one misperceives the points and crrves to share thesame plane, then one understates the goodness of fit between thedata cloud and the fitted surfaces.
Figure 5.6 shows a second slice, this time taken at the meanof PREPARED (equal to 5.48). Together, Figures 5.5 and 5.6reveal, as do the equations in the bottom of each plot, thatstudent satisfaction increases most steeply with respect to stu-dent-caring, and very gradually with respect to task-driven.
36
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 36
FIGURE 5.5
SLICE DEPICTING ACTUAL, PLANAR, AND QUADRATIC FITS PROJECTED AGAINST PYES VERSUS PREPAR PLANE,
WITH UNDRST HELD CONSTANT AT ITS MEAN. SEE EQUATION DETAIL IN LOWER PORTION OF BOX.
A.C 100 +T.UAL.S 90. +
A
N
0
80. +
A
A
A
A A
A
A
A A A A
A
A
Q fQ
A
A
A A
A A
A
A
P
L
A 60. +
N
A
R
A 50. +
N
D
0 .
U 40. +
A
0
R
A
1 30. +
I
C
A
A
A
A A
A A
A
A A .
+
A A +
A A .
+
+A.A = ACTUAL PERCENTAGE OF TEACHER'S STUDENTS RESPONDING YES TO .
THE QUESTION 'WOULD YOU TAKE A COURSE WITH THIS TEACHER AGAIN?' .
P = PLANNI FIT = PLYESPU=-111.58839 + 31.08833+5.17873 + 5.22761,PREPAR +
X it STUDENT-CARING PROXY = UNORST = TEACHER'S AVERAGE RATING ON
'DEGREE TO WHICH YOU THINK YOUR TEACHER IS UNDERSTANDING'
!
. MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 38
Prior to the above plots, the quadratic model appeared tooffer several substantial advantages over the planar form. Itcaptured the most variation of all the models while producingsignificant coefficients that reflect diminishing returns andallow for determination of point marginal products. Yet as theslices show, the point marginal products (slopes) are sensitiveto the particular grid coordinates at which those surface pointsare evaluated. By contrast, the planar fit reflects a goodapproximation to the quadratic one, and embodies what might beseen as an "overall average" slope that is constant and positivethroughout the range of the respective input. Though the quad-ratic's point-specific slopes are more accurate than the planarform's "average" view, there is no stringent need here for suchaccuracy. The planar form offers more simplicity, and, slopevalues generalizable to the entire range of input values--whileclosely approximating the corresponding quadratic slopes. More-over, the simpler planar model will greatly aid the final processthat must include estimating marginal products and marginalprices of not only UNDERSTANDING and PREPARED, but also the in-puts for which the district pays explicit prices (years exper-ience and educational units). Finally the reader is remindedthat this is the most common form of educational production func-tion. For the above reasons, the final regressions embodied thefollowing simple planar form:
5.6 FINAL REGRESSIONSTable 5.3 presented coefficients for the planar form using
just the two grid-dimension proxies as predictors. Heweve::, toanalyze the school district's actual allocation polic:y relativeto those two theory-based inputs, the inputs to which thedistrict actually allocates (teacher's years experience, coded"Y2A5," and education beyond theiiNchelor's degree, coded"EDUNITS") must also be included."'
To estimate the marginal impact coefficients, YEARS andEDUNITS were added to the equation predicting PYES. Theresulting coefficients appear in Table 5.5:
- MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 39
5.7 FINAL RATIOSWith the marginal impact estimates in hand, calculating the
following marginal-impact-to-marginal-price ratios,
MI1
? MI2 ? ? MIK
MR MP2 MPK
requires that we now estimate the implicit marginal prices (theMPi's of the denominators). These are obtained by replacing onlyPYES with SALARY in the same model that generated the MIi's, thenrerunning the regressions; i.e., by changing:
and estimating the new coefficients.The coefficients from the student-weighted regressions
predicting satisfaction, combined with those from the unweightedregressions predicting salary, yield the long-sought "marginalimpact to marginal price" ratios of Table 5.6.
The extreme disparities among Table 5.6's quotients, suggestthat the district allocates its budget inefficiently with respectto producing teaching that attracts students. The quotients
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88
TABLE 5.6FINAL MARGINAL IMPACT TO MARGINAL PRICE RATIOS
AND RELATED STATISTICAL DETAIL(* => p < .05)
UNDRST=IS
PREDICTORS--->UNDER-STANDING
(STD. ERROR B) ( 3.905)(T STATISTIC) ( -4.02 )
(SIG. OF COEFS.) (.000 )
(PART. CORR.) (.73 )
PREPAR=ISPREPAREDFOR CLASS
( 5.376)( 0.93 )
(.355 )
(.30 )
YEARS=YEARSTEACHINGEXPERIENCE
( 0.633)( -1.99 )
(.052 )
(-.19 )
PAGE 40
UNITS=EDUCATIONUNITSBEYOND B.A.
(0.104)(0.83 )
(.408 )
( -.17 )
ACTUAL SLOPES FROM SYSTAT WEIGHTED NO-CONSTANTCOEFFICIENTS REGRESSION ADJUSTED MULTIPLE R-SQUARED = .430OF PYESEQUATION >*33.952* 5.015 -1.256 0.087
ACTUAL > -169.057 *819.285* *811.026* *25.347*COEFFICIENTSOF SALARY SLOPES FROM 60 TEACHER UNWEIGHTED SALARYEQUATION REGRESSION ADJUSTED MULTIPLE R-SQUARED = .960
(STD. ERROR B) (300.664)(T STATISTIC) ( -.562)(SIG. OF COEFS.) (.5000 )
TABLE 7.7CORRELATION MATRIX OF MAIN ANALYSIS VARIABLES
USED TO OBTAIN THE ABOVE RATIOS
The following was computed from teacher-level aggregateswhere each aggregate was weighted by the square root of thenumber of students in the aggregate (* => p < .05).
themselves, however, cloud the more useful picture offered bytheir marginal-impact and marginal-product numerators anddenominators. That picture begins with TABLE 5.8's discussion ofthe coefficients:
41
- MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88
TABLE 5.8DISCUSSION OF THE PRECEDING
MARGINAL- IMPACT -TO- MARGINAL -PRICE COEFFICIENTS(* .) p < .05)
UNDRST PREPAR YEARS EDUNITS1MI1 ? MI2 ? MI3 ?-* =
MP1 MP2 MP
3me
4
The proxy for student-car-
ing, the degree to which theteacher "is understanding,"has considerably moreimpact on satisfaction than"is prepared" does.
PYESEQUATION---->1-7133.952*1
I
PAGE 41
The proxy for task-driven teaching,the degree to which the teacheris prepared for class, is notstatistically significant, yet itcarries a high and statisticallysignificant implicit price of $819.28.
Although the pricecoefficient for UNDER-STANDING is not sta-tisticeily significant,
UNDERSTANDING Las themost impact, of allvariables, on studentsatisfaction.
Explicit allocations to YEARS andUNITS relate tightly to salarybecause they determine salary. Yetthey purchase no, if not negative,amounts of student satisfaction.
Table 5.8's data and comments are hardly definitive.Indeed, they embody many of the same limitations of the otherresearch of educational production functions. Nonetheless, likethat research, the above empirical findings do quantify andsupport much of the theory about economic and human behavioralphenomena in schools.
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 42
6.1 CONCLUSIONSEvidence of nationwide student dissatisfaction with school
prompted the research questions posed in Section 1. Thosequestions, and this study's answers to them follow:
Question 1: What advantages might student evaluations ofteachers (SETs) offer California public high schools as anadded measure of schooling effectiveness?
Section 2 reviewed studies from colleges and high schools- -studies suggesting that SETs could augment achievement and othermeasures of schooling outputs by offering these advantages:
1. SETs measure affective dimensions of the schoolingprocess (i.e., students' and teachers' feelings aboutthe process) and other dimensions of its products(e.g., the learner's self esteem);
2. SETs reflect the unique viewpoint of the intendedreceivers of teaching--the most important first-handsources regarding the receiving process and itseffects--the only sources who experience so broad arange of a teacher's behaviors over months of expo-sure;
3. SETs reveal the quality of student life in school- -what Jencks et al. urge we begin seeing "as an end initself, rather than a means to some other end";
4. SETs can measure noncognitive traits (e.g., enthusiasm)exhibited by teachers, and students. In Who Gets Ahead,Jencks et al. argue that such traits are at least as impor-tant to students' later success as are cognitive ones;
5. The act of seeking feedback through SETs can be a tan-gible sign to students that teachers and officialsseek and value students' views.
6. SETs are highly reliable. And they are fairer toteachers in the sense that they are less correlatedwith student characteristics (e.g., SES) than areachievement tests.
7. SET responses correlate positively with evaluationsdone by teacher-colleagues and supervisors.
8. Unlike achievement tests, SETs apply to a wide varietyof school subjects in a single instrument and thuspermit control of instrument type across courses;
9. SETs provide teachers with feedback which, evidenceshows, can help them improve their teaching; and fin-ally,
43
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 43
10. SETs offer validity in the sense that higher studentevaluations of teaching do correlate--though notstrongly--with higher student achievement. This isconsistent with findings in the "Dr. Fox" studies thatshow ratings to effectively measure teacher's enthus-iasm, and enthusiasm to have twice the impact on learn-ing that lecture content does.
Question 2: What fundamental dimensions of teaching under-lie such evaluations?
The factor analysis reported in Section 4 showed two factorsto predominate: STUDENT-CARING and TASK - DRIVEN. These twoaccounted for 70 percent of the variation among all teacher traitvariables, and replicated the same two latent dimensions provenuseful in studies from psychology to managerial leadership (e.g.,Bales Blake and Mouton, Couch, Fiedler, and Fleishman etal.).'" Borrowing from Blake and Mouton's extensive worksarticulating management styles on the "Managerial Grid," thesedimensions now found in teaching, provide conceptual frameworkfor a "Managerial Grid for Teachers."
Here, the grid first helped reveal--from where variablesfell on the factor plot--interrelationships of all SET variablesat a glance. For example, it showed that overall studentsatisfaction strongly related to STUDENT-CARING, much lessstrongly to TASK-DRIVEN, and negatively, if at all, to teacher'ssalary. In short, it told a preliminary graphic story of allo-cative inefficiency with respect to producing satisfaction--oneof several stories told by several groupings of plotted varia-bles.
Later, when we changed the dimensions from meaning "degreeof correlation with a factor" to meaning "degree teacher is task-driven or student-caring," the grid prompted useful images andquestions linking teaching styles to achievement, satisfaction,and any other variables plottable on the grid--images andquestions discussed in this chapter's final section,"Implications for Future Research."
Because other authors (e.g., Blake and Mouton et al.)125have devoted many useful books to grid-related leadership styles?or other professionals (e.g. managers, nurses, salesmen, aca-demic administrators)--surely the same could be done for teach-ers. Moreover, as will be discussed in the final section,augmenting the grid with achievement, satisfaction, or otheroutput surfaces, provides a conceptual framework for seeingteaching style tradeoffs and their output consequences- -suggesting still more questions for future research.
In helping us seek allocative efficiency with respect tosatisfaction alone, the grid provided the foundation !or tacklingthe remaining research questions--those questions marking thisstudy's destination:
Question 3: To what extent does one public high school inCalifornia already satisfy the microeconomic conditions toefficiently produce teaching that interests students? Thatis, how much impact do specific teacher traits (e.g., know-
44
- MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 44
ledge of the subject matter, preparation for class, enthus-iasm) have on overall student satisfaction? What implicitmonetary prices do districts pay for those traits? To whatextent are the impact-to-price ratios disparate across thosetraits?
Section 5 examined this question by fitting planar, quad-ratic, Cobb-Douglas, probit and logit models to proxies for thegrid dimensions. After adding teacher's salary determinants tothe model and controlling statistically for influences beyond theteacher's control, coefficients were computed to produce thisstudy's final quantitative product, the marginal-product-to-marginal-price ratios of Tables 5.6 and 5.8.
The quotients' substantially unequal numerators anddenominators--four of which are statistically significant--suggest failure in meeting the above efficiency conditions. Moreprecisely, they imply that this particular public high school isnot already allocating its teachers' salaries to efficientlyproduce teaching that students would like to return to. Detailsof the inefficiencies follow.
Question 4: To what specific inefficiencies do any dispari-ties point and what policy changes do they imply?
The aboNcv inefficiency stems mostly from the followinglinkages:
1. Student-caring has far more influence on our satis-faction measure than task-driven does; but
2. Teachers are implicitly paid far less for student-caring behaviors than they are for task-driven ones.
3. Teacher's salary is driven predominantly by teachingexperience, and relatively less by education.
4. Yet neither experience nor e'ucation have any appre-ciable impact on student satisfaction.
In short, the district's heavy payments to experience andeducation do not, coincidentally buy the inputs that would booststudent satisfaction (though at $819 per rating point of "Isprepared for class," they do coincidentally buy task-driventeaching).
6.2 CAUTIONSThe above findings must be interpreted with caution. First,
they are not surprising since, in general, conventionalallocation methods were never intended to promote student satis-faction in the first place. Indeed, producing teaching thatinterests students is only one aspect of what teachers aresupposed to produce. As was stated at the outset, most wouldagree that student achievement is a more important outputmeasure. And, of course, there are many other outputs (e.g.,student's social skills, self esteem, etc.) whose simultaneous
45
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 45
maximization with satisfaction, could strongly effect theallocations indicated here.
Moreover, the sample is limited to just one high school setin a middle-class California neighborhood. The results foundhere are not necessarily stable across other high schools; or,for that matter, across specific subject or teacher situations,or different groups of students.
Finally, although our dependent variable PYES did let usempirically measure student satisfaction, it was far from ideal.It does not, for example measure actual satisfaction the way thatobserving actual repeat buying would. Nor is it likely to linkfirrly to the actual student dropout numbers mentioned in Section1 (though future research could ameliorate this by administeringquestionnaires to recent dropouts--students who, in short, havechosen not to be repeat buyers of the entire bundle of schoolingservices).
But just as Levin and others found that changing salarydeterminants could boost the allocative efficiency of producingachievement, the above findings do hint that similar changescould improve the efficiency with which schools produce teachingthat interests students (assuming schools chose that as theirsole output objective).
6.3 POLICY IMPLICATIONSSince this study's scope is limited by a focus on allocative
efficiency with respect to student satisfaction only, itspractical policy implications are also limited--especiallyrelative to the bigger picture of how student satisfaction andstudent achievement might interact. Indeed, much of this study'svalue lies in its implications for future research involving thisbigger picture.
Nonetheless, the findings here do urge an important policydirection: Since the data show student-caring to have far moreimpact on student satisfaction than task-driven does more caring(not necessarily more money reallocated to it) should producehigher percentages of satisfied students.
It is hardly surprising that students would care more aboutteaching that cares more about them. Though dismissing so simplea conclusion is tempting, in the context of the seriousdisinterest and dropout problems documented earlier, districtswould do well to heed this empirical linkage, and promote morestudent-caring.
Policy SpecificsPrecisely how might districts inject more student caring
into the teaching they offer? The following changes involvingteacher training institutions, hiring, career ladders, inserviceprograms, and compensation, would help:
Teacher-Training Institutions: Schools of education couldemphasize the evidence on the importance of student-caring,stressing it's most important trait components (those thatcorrelated highest with satisfaction in this study), and spe-cifically how to deliver those traits. They might also impartthe needec' skills for that delivery through internships involvingfrequent standardized SET feedback and counseling.
46
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 46
Hiring: Districts could require standardized internshiprecords cf SET feedback to help screen for teachers strong instudent-caring. Further screening could be done via careerladders that begin with probationary hiring--with permanentemnloyment contingent on SET results (among other measures).
Career Ladders: Career ladders have already started inCalifornia and Florida, largely to offer teachers successivesteps of position, pay, responsibility and status. Such ladderscould also be implemented to promote teaching that interestsstudents. That is, ladder steps could be implemented, in part,as incentives for continued enrichment of key teaching skills.And this enrichment could be officially supported and tracked byin-service programs involving SETs.
In-Service Feedback and Enrichment Programs: Research pre-sented in Section 2 suggests that SET feedback can improveteaching. Formal programs to regularly measure, plot, andcounsel on the basis of feedback--feedback from student eval-uations, expert teachers, and video tapes--have been successful.Indeed, the instrument on which this study is based came fromsuch a program. Teacher participation was entirely voluntary;plotted improvement in ratings for teachers who truly wanted toimprove, was substantial.
Compensation: Besides offering nonpecuniary rewards forbonafide improvements in teaching--via personal recognition fromsuperiors, formal awards, and all the nonmoney benefits of highersteps on the career ladder--serious thought ought to be given torevamping teacher salary schedules. These schedules have longfostered well-documented problems of insufficient incentives forteacher retention, growth, and excellence; low esteem of theteaching profession in general; teacher shortages in science andmath; and allocative inefficiency for producing eithersatisfaction or achievement.
Three PaychecksA practical response to problems of allocative ineffi-
ciency--and teacher retention, shortages, equity, aniclj.ncen-tives--is offered by Lawler's three paycheck system. In it,pay reflects differences between jobs, employees, and perfor-mance. Modified to Jerve public schools, this system would givea teacher a single check written for the total of each of thesethree checks:
Paycheck 1: The Job Differences Check, would cover thebase pay for a given job. It would reflect differentpay for differences in a) supply and demand factors(e.g., math teachers would start at a higher base thanP.E. teachers); b) workload (more pay to bilingualteachers having to prepare lesson plans in both Spanishand English rather than just English); and c) othercompetencies and responsibilities not reflected in a)or b).
Paycheck 2: The Employee Differences Check, wouldreflect between-teacher differences in a) length ofservice to the district (this membership reward can be
47
. MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 47
justified since it would save the district on recruit-ment and training costs); and, b) any economically jus-tifiable educational attainments beyond those requiredto obtain the job (i.e., beyond those paid for in Pay-check 1);
Paycheck 3: Performance Differences Check: a bonusvarying strictly according to performance. As a formof merit pays this bonus would be paid only at the mar-in; the first two checks would form the much largersalary base.
Limitations of the Performance Differences CheckIt is Paycheck 3 that most involves the allocative effi-
ciency considered here; and Paycheck 3 that is the most prob-lematic. This performance differences check represents meritpay, plain and simple. And merit pay has not fared well in mostof the districts that have tried it-- thoug.i it has succeeded in afew.
Success of any merit pay plan is critically dependent onobtaining objective measures of performance--measures thatteachers trust.
Do SETs provide such measures? McKeachie (Section 2) feltthat although SETs do reflect teacher effectiveness in teaching,they are not sufficient evidence of that effectiveness. Itfollows that EE777.731.7Id best serve as just one of severalperformance measures, taken over a sufficiently large sampling ofclasses, and cautiously interpreted by respected peers sensitiveto the bigger picture of context--the subject matter, studentsinvolved, etc. Other measures might include classroomobservation by respected peers-, and progress on objectivespredetermined by the teachers themselves.
The formidable problems of attempting Paycheck 3, may, inpart, be redumi by an intriguing extenLion resembling theScanlon plan."' Developed by Joseph Scanlon of the United SteelWorkers Union, "The Scanlon plan overcomes almost all theobjections of individual and small group 4.qgentive plans andgenerally is considered very successful."'" Applied to thecontext of schools, the plan would have administrators set asidebonus monies in proportion to the extent district effectivenessobjectives were met overall (e.g., targets of aggregateachievement gain scores, reduction in the costs of schoolvandalism, increased teaching that interests students).
For example, assume that last year's annual teacher's;payroll of $1 million produced average ratings of 1.0 forstudent-caring. If this year, the same $1 million payroll booststhe average to 1.1--and the increase is substantive--the districtreaps additional "output" for what might otherwise have cost it,say, $50,000. That amount would go into a bonus fund to rewardspecific teachers for high bonafide '.as in caring.
Though implementation of such a plan would surely involveformidable technical and political problems, a year-end bonusfund proportional to the success of the group, would serve twoends. It would encourage individuals to boost their output,while encouraging all to work cooperatively with their colleagues
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 48
as a team. Moreover, with a union member as its originator, andunion concerns at its heart, it might even be palatable toteachers' unions.
Unfortunately, the politics (see Section 2), competencies,levels of commitment, and interaction of a vast fabric of otherinterdependent fcirces makes prediction of any plan's successdifficult in any cuntext. In short, the particular success ofthe above suggestions cannot be known for a given context untilit is tried--tried where every effort is made to motivatecommitment,. agree on goals, work to measure them objectively, andreward their attainment irreproachably. A tall order in anyadministrator's book.
6.4 IMPLICATIONS FOR FUTURE RESEARCHAs mentioned earlier, much of this study's value lies in its
implications for future research, especially regarding questionsprompted by the managerial grid for teachers. Among the seriousquestions that remain are: Precisely where would the all-important output "average achievement gains controlling for stu-dent background" fall on the grid? And if we change thedimensions from meaning "degree of correlation with a factor" tomean "degree teacher is task-dri',7cn or student-caring," wherewould maximum achievement fall? Does it sit at the respectivemaximums for STUDENT-CARING and TASK-DRIVEN (i.e., the upperright hand corner of the plot)? Or do diminishing returnsoperate so that excesses of either factor actually impedeachievement (placing it closer to the origin along the northeast45-degree-angle line)? Or does achievement not correlate as wellwith one factor as it does with another (e.g., placing it furtherout on task-driven, and not so far on student-caring)? To besure, knowing the precise coordinates for the point of maximumachievement would establish an important landmark by which tonavigate. Yet as seen in the 1:ollowina, empirically fitting itsentire surface would offer still more valuable navigation data.
Fitting and Superimposing, the Achievement SurfaceIf the empirical fit of an achievement surface were added
atop the surface already fitted for satisfaction (see the three-dimensional plot in Section 5), the heights of the surfaces abovethe grid floor (measured with standardized scores) would showpredicted achievement gains and satisfaction, respectively, asfunctions of how much a teacher is student-car ng versus task-driven. The relative distances between the two surfaces atdifferent grid coordinates would show tradeoffs between satis-faction and achievement outputs as functions of different combi-nations of student-caring versus task-driven inputs. And, suchtradeoffs, once quantified, would let us contemplate thecompromises inherent in trying to maximize both achievement andsatisfaction simultaneously.
The above approach is well within reach. For example, justas the California Assessment Program (CAP) gathers achievementmeasures statewide, so too--perhaps even on the same testinstrument--could it gather SET data covering teacher, traits andstudent satisfaction. indeed, just as California monetarily
49
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 49
rewards CAP achievement gains, so too could it rewardsatisfaction gains.
6.5 LOOKING BACK: SIMPLER WAS BETTERThis study leaves behind it a path strewn with highly
technical concerns and sophisticated tools; e.g., concerns about:1) assumptions violated with a bounded dependent variable; 2)
whether the independent variables should be factors, proxies, orfused groups of original variables; 3) appropriate functionsincluding Cobb-Douglas, logit, probit, planar and quadratic forms(and related concerns regarding the error of predictions thataccount for diminishing returns versus those that don't; wildlynegative intercepts and their interpretation; and more). We alsoexamined statistical controls for effects beyond the teacherscontrol, corrections for heteroscedasticity; and, relatedregression algorithms that use a constant term versus those thatdon't.
Curiously in the end, however, the simplest model amplyanswered the questions we sought concerning this particularsample. Surely this speaks well for "simpler is better" and theoverall robustness of basic least squares regression. Moreimportant, however, it hints that preoccupation with doing thingsright threatens any research from doing the right things;like using complicated logit or probit forms and missing thatsimpler model that well answers the most important questions athand; in this case, that simple planar model that clarifies themajor forces at work, their magnitude, and direction.
6.6 IN CLOSINGSome are certain to object to attempts to boost teaching
that interests students--even when done in concert with trying toboost acheivement. But equally certain are dropout trends con-firming that if students are not pulled, challenged and fulfilledby schooling, growing numbers of them won't stay around toachieve anything.
The major value of this study, however, lies not so much inthe satisfaction and price coefficients it sought and obtained,but rather in the general relationships observed, and moreimportant, the simple methodology developed to observe them.
The managerial grid for teachers helped us conveniently seethose relationships and question others at a glance. ndeed, byoffering new ways of seeing, and empirically fitting teacherinput/output, the grid should help us model more complicated con-cepts involving interaction of satisfaction, achievement,teaching styles, and any otter plottable schooling variables. Itshould suggest, quantitatively, the consequences of teachingstyle tradeoffs. And it should help articulate preferred styles(as did Blake et al. for other professions).
Above all, the grid should help us define and achieve teach-ing styles that better mix student-caring/task-driven inputs andsaisfaction/achievement outputs--all to aid a bigger picture:that of long-term student wellbeing and reversal of trends thatprompted this study.
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88
NOTES
PAGE 50
1 National Commission on Excellence in Education, "ANation at Risk: The Imperative for Educational Reform,"Washington D.C., April, 1983, p.18.
2Catherine Camp, Joel Gibbs, Marilee Monagan, "SchoolDropouts," California Legislature, Assembly Office ofResearch, May, 1980, p. 11.
3California Commission for Reform of Intermediate andSecondary Education, The RISE Report, California StateDepartment of Education, Sacramento, Ca., 1975; p. xii.Additional evidence of alienation in our schools is cited inFred M. Newman, "Reducing Student Alienation in HighSchools: Implications of Theory," Harvard EducationalReview, Vol. 51, No. 4, Nov. 1981, p. 548.
4Ernest L. Boyer and the Carnegie Foundation for theAdvancement of Teaching, High School: A Report on SecondaryEducation in America, New York: Harper and Row, 1983, p. 22.
5Michael W. Kirst, Who Controls Our Schools, Stanford:The Portable Stanford, 1984, p. 17. Kirst summarizes agree-ment among these rep,rts:
Mortimer J. Adler, The Paideia Proposal, New York: Macmil-lan, 1982.
Ernest L. Boyer, High School, New York: Harper And Row, 1983.College Board Education Equality Project, Academic Prepar-
ation For College: What Students Need To Know And BeAble To Do, New York: College Board, 1983.
Education Commission Of The States' Task Force On Educa-tion For Economic Growth, Action For Excellence, Den-ver: Education Commission Of The States, 1983.
John I. Goodlad, A Place Called School: Prospects for theFuture, New York: McGraw-Hill, 1984.
National Commission On Excellence In Education, A NationAt Risk, Washington, D.C. t U.S. Government PrintingOffice, 1983.
Theodore R. Sizer, Horace's Compromise: The Dilemma of theAmerican High School, Boston: Houghton Mifflin, 1984.
Twentieth Century Fund Task Force On Federal Elementary andSecondary Education Policy, Making The Grade, New York:Twentieth Century Fund, 1983.
6Carnegie Forum on Education and the Economy, "A NationPrepared: Teachers for the 21st Century, The Report of the TaskForce on Teaching as a Profession." May, 1986. CarnegieCorporation of New York, p. 13, 2, 21.
7All the following studies contain empirical evidenceof higher achievement per dollar possible by reallocatingteachers' salaries according traits other than experience or
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 51
post-B.A. units (e.g., teacher's verbal score): H.M. Levin,"Measuring Efficiency in Educational Production," PublicFinance Quarterly, Vol. 2, No. 1, (Jan. 1974). H.M. Levin,'A Cost-Effectiveness Analysis of Teacher Selection," Jour-nal of Human Resources, Vol. 5, pp. 24-33, 1970. E. Cohn;S.D. Millman and I. Chew Input-Output Analysis in PublicEducation, Ballinger Publishing Co., Cambridge, Mass., 1975.
8Though the research evidence is mixed, overall it sug-gests that teaching rated highly by students does correlateslightly positively with student achievement.
9Specifically, the NCEE report recommends that teach-ers' salaries: "should be increased and should be profes-sionally competitive, market-sensitive and performance-based. Salary, promotion and tenure . . . should be tied toan effective evaluation system that includes peer review sothat superior, teachers can be rewarded, average ones encour-aged, and poor ones either improved or terminated." NationalCommission on Excellence in Education, p. 30.
10More precisely, the National Task Force on Educationfor Economic Growth, established under the auspices of theEducation Commission of the States, recommends re-examina-tion of lifetime teacher tenure and higher pay for teacherswho have reached the "upper levels of seniority and effec-tiveness." This pre-release of recommendations took placein Raleigh, North Carolina on May 4, 1983; New York Times,May 5, 1983, pp. 1, 10.
11 RISE, p, 7.
12RISE, p. 23.
13Carnegie Forum on Education and the Economy, p. 87.
1 4Levin argues that "so-called technical inefficiency"can always be reduced to allocative efficiency. See H.M.Levin, "Measuring Efficiency in Educational Production,"Public Finance Quarterly, Vol. 2, No. 1, Jan. 1974.
15H.M. Levin, "Concepts of Economic Efficiency and Edu-cational Production" in Education as an Industry edited byFroomkin and Jamison, Cambridge, Mass.: Ballinger PublishingCompany, 1976.
16Cited in John I. Goodlad, A Place Called School,Prospects for the Futures New York, N.Y.: McGraw-Hill,1984, p. 29.
17Christopher Jencks; M. Smith, H. Ackland, M. Bane,D. Cohen, H. Gintis, B. Heyns, S. Michaelson, Inequality, AReassessment of Family and Schooling in America, BasicBooks, 1972, p. 256.
52
. MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 52
18A.S. Neil, Summerhill, A Radical Approach to ChildRearing, New York, N.Y.: Hart Publishing Co., 1960, p. 5.
19Though the more pertinent context of producing stu-dent achievement and satisfaction simultaneously is treated inthe concluding section, under "Future Research."
20This section drew largely from the valuable sugges-tions of three of the author's colleagues at San Diego StateUniversity's College of Business, Department of Management:David Belcher, Steve Jenner and Penny Wright.
21 Adam smith, An Inquiry into the Nature and Causes ofthe Wealth of Nations, 1776. Edited version by Edwin Cannan,1937, New York: The Modern Library, 1937, p. 737.
22Milton M. Friedman, Capitalism and Freedom, Chicago:University of Chicago Press, 1962, pp. 85-107.
23Milton M. Friedman and Rose Friedman, Free to Choose,A Personal Statement, New York: Harcourt, Brace, Javanovich,1980. pp. 150-188.
24J.G. Chambers, "Toward a Model of the Public and Non-profit Enterprise: An Evaluation of Decision Making in Pub-lic School Districts," updated from a chapter in "The Impactof Collective Bargaining for Teachers on Resource Allocationin Public School Districts," Ph.D. dissertation, StanfordUniversity, 1975.
25H.M. Levin, "Effects of Expenditure Increases on Edu-cational Resource Allocation and Effectiveness," in TheLimits of Educational Reform, M. Carnoy and H.M. Levin,(eds.), New York: David McKay Co., 1976.
2 8Eric A. Hanushe4, "Throwing Money at Schools," Journalof Policy. Analysis and Management, vol. 1. no.1, 1981, pp.19-41.
p. 31.
p. 37.
29Levin, p. 176.
30Chambers, p. 9.
31Levin, p. 182.
32Hanushek, p. 31.
33Chambers, "Toward a Model of the Public and NonprofitEnterprise," pp. 8-9.
3 4Ibid., p. 9.
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 53
35Hanushek, p. 33.
36Separate arguments for why teacher training institu-tions, state and federal education agencies, and localschool boards also "tend to view themselves as representingteachers and teachers' interests" are given in Hanushek, p. 33.
37Chambers, p.9.
38James S. Coleman directed a study to compare publicschools with schools operating in a more competitive con-text; i.e., e4 Catholic schools and 27 other private schoolsfacing the more formidable incentives of "produce or per-ish." Though highly controversial, widely criticized, andgenerally favorable to the Catholic schools, that studyfound that when compared to public schools, Catholic schoolsshowed higher achievement, less segregation, and lowerachievement differences between students of vary'ng socio-economic backgrounds. See James S. Coleman, Thomas Hoffer,and Sally Kelgore, Public and Private Schools, NationalOpinion Research Center, University of Chicago, April, 1981.Also see James S. Coleman, Thomas Hoffer, and Sally Kelgore,"Questions and Answers: Our Response," Harvard EducationalReview, vol. 51, no. 4, November, 1981, pp. 526-545; JamesS. Coleman, "Quality and Equality in American Education:Public and Catholic Schools," Phi Delta Kapoan, Nov. 1981,p. 159; Diane Ravitch, "The Meaning of the New ColemanReport," Phi Delta Kappan, Nov., 1981, p. 159; Ellis B. Pageand Timothy Z. Keith: "Effects of U.S. Private Schools: ATechnical Analysis of Two Recent Claims," EducationalResearcher, August/September, 1981; and James S. Coleman,"Response to Page and Keith," Educational Researcher,August/ September, 1981. Also, Andrew Greeley found resultssimilar to Coleman's. Greeley concludes that public schoolsappear to be more successful at educati,.g the affluent while'Catholic schools do better with the poor. See AndrewGreeley, Minority Students in Catholic Secondary Schools,Report for the Ford and Spenser Foundations, Chicago:National Opinion Research Center, 1981.
39The potential cost savings of pay for seniority--what thecompensation literature calls "membership rewards"-- will also bediscussed in this paper's concluding section. Also see RichardJ. Murnane, "Seniority Rules and Educational Productivity:Understanding and Consequences of a Mandate for Equality"Institute for Research on Educational Finance and Governance,Stanford University, Stanford, Ca., 1980.
41Eric Hanushek, The Value of Teachers in Teaching, RM-6362-CC/RC: Santa Monica, Ca.: The Rand Corporation, pp. 12,21.
54
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 54
42H.M. Levin, "A Cost-Effectiveness Analysis of TeacherSelection," Journal of Human Resources, vol. 5, 1970, pp.24-33.
43H.M. Levin, "Measuring Efficiency in Educational Pro-duction," Public Finance Quarterly, vol. 2, no. 1, Jan 1974,p. 306.
44E. Cohn; S.D. Millman and I. Chew Input-Output Anal-ysis in Public Education, Cambridge, Mass.: Ballinger Pub-lishing Co., 1975.
4 5Eric Hanushek, The Value of Teachers in Teaching, pp.12, 21. Also see John D. Owen, "Toward a Public EmploymentWage Theory: Some Econometric Evidence on Teacher Quality,"Industrial and Labor Relations Review, Jan. 1972, vol. 25,pp. 213-222. Owen also found no relationship betweenteachers salaries and quality of teaching.
46Hanushek, Journal of Policy Analysis and Management,p. 37.
47J. Burkhead; T.G. Fox, and J.W. Holland, Input andOutput in Large City High Schools, New York: Syracuse Uni-versity Press, Syracuse, 1967.
48D. Greenberg; and J. McCall, "Analysis of the Educa-tional Personnel System: Teacher Mobility in San Diego,"Santa Monica, Ca.: The Rand Corporation, R-1071-HEW, 1973.
4 9J.W. Guthrie, "A Survey of School Effectiveness Stu-dies," in Do Teachers Make a Difference?, Washington, D.C.:HEW, Office of Education, 1970.
50E. Keeler and J. McCall, "A Note on the Effectivenessof Teacher Experience," The Rand Paper Series, Santa Monica,Ca.: The Rand Corporation, 1973.
51California's State Department of Education maintainscomputer-based data on all its 1,044 districts' salaryschedules along with the distributions of teachers on thoseschedules. It follows that actual measurement of the state-wide expense for these nonproductive inputs should requirelittle more than the writing of a computer program. SinceCalifornia comprises over ten percent of the U.S. popula-tion, so simple an analysis would mean a bfg step in thedirection of obtaining the nationwide cost.
52As is true for both salary schedules used in thisstudy.
53The problems of using linear slope estimates for whatis necessarily assumed to be a curvilinear production func-tion, are discussed here in Section 5.
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 55
54Levin, J-urnal of Human Resources, p. 31.
55Levin, Public Finance Quarterly, p. 306.
56M. Friedman, Capitalism and Freedom, Chicago, Ill.:University of Chicago Press, 1962, pp. 85-107.
57C. Jencks, "Educational Vouchers; A Proposal fc7.7
Diversity and Choice," in Schooling in a Corporate Society,first ed., M. Carnoy (ed.), New York: David AcKay Co. Inc.,1972.
58J.E.Coons, and S.D. Sugarman, Education la Choice:The Case for Family Control, Berkeley, Ca.: University ofCalifornia Press, 1978.
59F. Costin, W.T. Grenough and R.J. Menges, "StudentRatings of College Teaching: Reliability, Validity, andUsefulness, Review of Educational Research, vol. 41, 1971,p. 518.
60J.W. Gustad, "Policies and Practices in Faculty Eval-uation." Educational Record, 1961, vol. 42, pp. 194-211. Insurveying methods of teacher evaluation among 584 collegesand universities, Gustad found student evaluation of teach-ing to be the method cited most often.
61 G.V. Glass, "Statistical and Measurement Problems inImplementing the Stull Act," in Mandated Evaluation of Edu-cators: A Conference on CalifoiEiTE7TEull Act, N.L. Gage(ed.), Stanford Center for Research and Development inTeaching, School of Education, Stanford University, 1973,pp. 53-54.
62C. Jencks; M. Smith, H. Ackland, M. Bane, D. Cohen,
H. Gintis, B. Heyns, S. Michaelson, Inequality, A Reassess-ment of Family and Schooling in America, New York: BasicBooks, 1972, p. 256.
63C. Jencks, with S. Bartlett, M. Corcoran, J. Crouse,D. Eaglesfield, G. Jackson, K. McClelland, P. Mueser, M.Olneck, J. Schwartz, S. Ward, and J. Williams. Who GetsAhead? The Determinants of Economic Success in America, NewYork: Basic Books, 1979, p. 229.
6 -4pi.L. Gage, "Students' Ratings of College Teaching:Their Justification and Proper Use," in Second UCSB Confer-ence on Effective Teaching, N.S. Glassman and B.R. Killait(eds.), Graduate School of Education and Office of Instruc-tional Development, University of California, Santa Barbara,1974. Also, the study that Gage cites, is H.H. Remmers,"The College Professor as the Student Sees Him," PurdueUniversity Studies in Higher Education, vol. 29, 1929, p.75.
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 56
"D.J. Veidman and R.F. Peck, "Student Teacher Char-acteristics from the Pupils' Viewpoint," Journal of Educa-tional Psychology, vol. 54, 1963, pp. 346-355.
"Glass, Mandated Evaluation of &locators, pp. 54, 56.
67E.R. Guthrie, "The Evaluation of Teaching," Educa-tional Record, 1949, vol. 30, pp. 109-115.
68E.R. Guthrie, "The Evaluation of Teaching: A progressReport. Seattle: University of Washington, 1954.
69D.J.
70B.W.Feedback toEducational
Veidman and R.F. Peck, 1963.
Tuckman, and W.F. Oliver, "Effectiveness ofTeachers as a Function of Source," Journal ofPsychology, vol. 59, 1968, pp. 297-301.
71M.T. Miller, "Instructor Attitudes Toward, and theUse of Student Ratings of Teachers," Journal of EducationalPsychology, vol. 62, 1971, pp. 235-239.
73J.A. Central "Two Studies on the Utility of StudentRatings for Instructional Improvement: 1) The Effectivenessof Student Feedback in Modifying College Instruction, 2)Self-ratings of College Teachers: A Comparison with StudentRatings." Princeton, NJ: Educational Testing Service, 1972.
74H.S. Pambookian, "Initial Level of Student Evaluationof Instruction as a Source of Influence on Instructor ChangeAfter Feedback," Journal of Educational Psychology, vol. 66,1974, pp. 52-56.
75J.U. Overall and H.W. Marsh, "The RelationshipBetween Students' Evaluations of Faculty and InstructionalImprovement," Paper presented at the International Confer-ence on Improving University Teaching. Available from Pro-grams in Administration, California State College, DominguesHills, Ca, 1976.
76The widely used, but nondescript terms, "Type I" and"Type II error," refer to the two types of mistakes possiblein making the probabilistic inference required of a hypothe-sis test. In more descriptive terms, a Type I error is madewhen we infer that a systematic effect exists when, in fact,it does not (e.g., as in concluding that a problematic trendexists among teachers when it does not). As the reverse ofthe Type I Error, the Type II error occurs when we inferthat no systematic effect exists when, in fact, it does(e.g., as in failing to detect what is actually problematicteaching). In the arena of policy making, concluding an
. MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 57
effect exists when it does not, can trigger advocacy of anunnecessary policy change (e.g., reprimanding good teach-ers)--whereas failure to detect what does exist tends tofavor the status quo--resulting in no such advocacy, no suchwalks out on the limb. In the highly political context ofeducational decision making, it follows that the Type Ierror is often the more severe of the two (though in school-ing and other contexts, it needn't be--and clearly was notwhen, for years, scientists failed to detect the linkagebetween thalidomide and birth defects in Europe).
77D.H. Naftulin, J.E. Ware Jr., and F.A. Donnelly, "TheDoctor Fox Lecture: A Paradigm of Educational Seduction,"Journal of Medical Education, vol. 48, 1973, pp. 630-635(Fox 1).
7 8Ibid., p. 635.
79J.E. Ware and R.G. Williams, "The Dr. Fox Effect: AStudy of Lecturer effectiveness and ratings of Instruction,'Journal of Medical Education; vol. 50, Feb. 1975, pp. 149-156 (Fox 2).
80R.G. Williams and J.E. Ware, "Validity of StudentRatings of Instruction Under Different incentive Conditions:A Further Study of the Dr. Fox Effect," -ournal of Educa-tional Psychology, vol. 68, 1976, pp. 48-56 (Fok 3).
81R.G. Williams and J.E. Ware Jr., "An Extended Visitwith Dr. Fox; Validity of Student Satisfaction with Instruc-tion Ratings after Repeated Exposures to a Lecturer," Ameri-can Educational Research Journal, vol. 14, 1977, pp. 449-457(Fox 4).
82Ibid.
83Omega-squared was developed in W.L. Hays, Statisticsfor Psychologists. New York: Holt Rinehart, and Winston,Inc., 1963. The form used *-o calculate the entries in theabove table was:
OMEGA SQUAREDSSbetween - (KGROUPS -1)MSwithin
SStotal MSwithin
For discussion of omega-squared in the context of other mea-sures of correlation, see Roger E. Kirk, ExperimentalDesign: Procedures for the Behavioral Sciences, BelmontCalifornia: Wadsworth Publishing Company, Inc., pp. 126-127.
84Study 3's design differed substantially from those ofStudies 2 and 4, precluding its comparison with those stu-dies here.
58
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85A.M. Sullivan and G.R. Skanes, "Validity of StudentEvaluation of Teaching and the Characteristics of SuccessfulInstructors," Journal of Educational Psychology, vol. 66,1974, pp. 584-590.
86J.A. Central "Student Ratings of Instruction andTheir Relation to Student Learning," American EducationalResearch Journal, vol. 14, 1977, pp. 17-24.
87N.R. Ellis, and H.C. Retention, "Evaluating theTeaching of Introductory Psychology," Teaching of Psychol-ogy, vol. 4, 1977, pp. 128-132.
88P.A. Cohen, "Student Ratings of Instruction and Stu-dent Achievement: A Meta-analysis of Multisection ValidityStudies," Review of Educational Research, vol. 51.3, 1981,pp. 281-309.
89Sullivan and Skanes, Journal of Educational Psychol-ogy., pp. 584-590.
90N.L. Gage, The Scientific Basis of the Art of Teach-ing, New York: Teachers College Press, 1978.
91 L.V. Hedges, "A Meta-Analysis of Four Teacher Behav-ior Variables," unpublished manuscript, Stanford University,1978.
92Cohen, Review of Educational Research, pp. 281-309.
93After reviewing 50 studies, Rosenshine and Furst con-cluded that the following teacher traits tended to correlatepositively with student achievement: 1) clarity, 2) varia-bility, 3) enthusiasm, 4) task-oriented or business-likebehavior, 5) providing student opportunity to learn cri-terion material. See g. Rosenshine and N. Furst, "Researchon Teacher Performance Criteria," Research in Teacher Educa-tion, a Symposium, B.O. Smith (ed.), for AERA, New Jersey:Prentice Hall, 1971. Yet Heath and Nielson criticized thosefindings concluding that "the research literature on therelation between teacher performance and student achievementdoes not offer an empirical basis for the prescription ofteacher-training objective" p. 481. See R.W. Heath and M.A.Nielson, "The Research Basis for Performance-Based TeacherEducation," Review of Educational Research, 44:463-484,1974. Subsequently Gage and Hedges have attacked the Heathand Nielson study- See N.L. Gage, The Scientific Basis ofthe Art of Teaching, New York: Teachers College Press, 1978;and L.V. Hedges; "A Meta-Analysis of Four Teacher BehaviorVariables," unpublished manuscript, Stanford University,1978.
94A.M. Anikeef "Factors Affecting student Evaluation ofCollege Faculty members," Journal of Applied Psychology,vol. 137, 1953, pp. 458-460.
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 59
95C.T. Steward and Leslie F. Malpass. "Estimates ofAchievement and Ratings of Instructors," Journal of Educa-tional Research, vol. 59, April, 1966, pp. 347-350.
96H.H. Remmers, "To What Extent Do Grades InfluenceStudent Ratings of Instructors," Journal of EducationalResearch, vol. 21, 1930, pp. 314-317.
97R.G. Weigel et al. "Differences in Course Grades andStudent Ratings of Teacher Performance," School and Society,vol. 99, Jan. 1971, pp. 60-62.
98Costin et al. cite fifteen studies showing no rela-tionship between grades and ratings, one study showing anegative relationship, and twelve studies showing a positiverelationship. See Frank Costin et al., Review of EducationalResearch,p. 518.
99Ibid., p. 530.
100w.j. Mckeachie, Teaching Tips, A Guidebook for theBeginning College Teacher, 7th ed., Lexington, Ma: D.C.Heath and Co., 1978, pp. 270-271. Besides the above-citedexcellent summaries of SET research, see also, Kenneth O.Doyle, Student Evaluation of Instruction Lexington, Ma:Lexington Books, 1975.
101G. French-Lazovik, "Predictability of Students' Eval-uations of College Teachers from Component Ratings," Journalof Educational Psychology, vol. 66, 1974, p. 376.
102D:J. Veidman and R.F. Peck, "Student Teacher Char-acteristics froth the Pupils' Viewpoint," Journal of Educa-tional Psychology, vol. 54, 1963, pp. 346-355.
103F . Costin et al. Review of Educational Research,pp. 511-535.
104Cohen, Review of Educational Research, pp. 281-309.
105B. Rosenshine and N. Furst, "Research on Teacher Per-formance Criteria," Research in Teacher Education, a Sym-posium, B.O. Smith (ed.), for AEU., New Jersey: PrenticeHall, 1971. See also R.W. Heath and M.A. Nielson, "TheResearch Basis for Performance-Based Teacher Education,"Review of Educational Research, 44:463-484, 1974.
106N. L. Gage, The Scientific Basis of the Art of Teach-ing; New York: Teachers College Press, 1978; and L.V.Hedges, "A Meta-Analysis of Four Teacher Behavior Varia-bles," unpublished manuscript, Stanford University, 1978.
60
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107G. French-LaZovik, "Predictability of Students' Eval-uations of College Teachers from Component Ratings," Jcurnalof Educational Psychology, vol. 66, pp. 373-385, 1974.
108D.J Veldman and R.F. Peck, "Student Teacher Charact-eristics from the Pupils' Viewpoint," Journal of EducationalPsychology, vol. 54, pp. 346-355, 1963.
109SPSS-X is the extended version of SPSS, and repre-sents a major revision of that old standby. See SPSS Inc.,SPSS-X User's Gnide; A Complete Guide to SPSS-X Language and.Operations, New York: McGraw-Hill Inc., 1983, pp. 647-661.
110Besides the quartimax loadings shown here, the author canprovide the corresponding varimax, equamax, and oblimin loadings.The following summary of each of these techniques should clarifythe context in which quartimax was preferred. Quartimax rotatesthe orthogonal factor axes to simplify each variable's row of thefactor loading matrix. That is, quartimax minimizes the numberof high loadings and maximizes the number of near-zero loadingsfor a given variable (in turn, permitting many variables to loadhigh on a given factor). In contrast, varimax aims to simplifyeach factor's column; i.e., it minimizes the number of high load-ings and maximizes the number of near-zero loadings for a givenfactor (in turn, permitting several high loadings across factorsfor a given variable). By attempting to compromise between thegoals of both quartimax and varimax, Equamax seeks to satisfy alittle of each simultaneously. More precisely, it seeks arotation that minimizes high loadings and maximizes near zeroloadings in both rows and columns. Finally, unlike all the aboveorthogonal rotations, oblimin is an oblique rotation, i.e., onethat relaxes the orthogonality constraint (thereby permittingcorrelation among factors), rotating the axes to whatever anglewill best cluster the variables into factor groupings. For theexcellent summary of factor analysis from which the above war;drawn, see N.H. Nie, C.H. Hull, J.G. Jenkins, K. Steinbrenner,D.H. Bent; Statistical Package For the Social Sciences, 2nd ed.,McGraw Hill Book Co., New York, 1970, pp. 515-518.
111This 69.6 percent figure was determined by isolatingthose 30 teacher trait variables within the separate principalcomponents analysis. The relative importance of these twofactors was determined through eigenvalues and a Scree plot ofthose eigenvalues.
112R.R. Blake and J.S. Mouton, The Managerial Grid,Orientations for Achieving Production Through People, GulfPublishihg Company, Houston Texas, 1964, pp. 5-17. Also see:Robert R. Blake and Jane S. Mouton, The Grid for SupervisoryEffectiveness, Scientific Methods, Inc. Austin, Texas, 1975;Robert R. Blake and Jane S. Mouton, The Versatile Manager: AGrid Profile, Dow Jones-Irwin, 1980, pp. 10-26. Blake andMouton have also applied the grid in the following books:Corporate Excellence Through Grid Organization Development,Building a Dynamic Corporation through Grid Organization
61
y MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 61
Development/ The Grid for Sales Excellence, The MarriageGrid, Grid Approaches for. Managerial Leadership in Nursing,Grid Approaches for Managing Stress, The Academic Adminis-trator Grid.
113R.F. Bales, Personality and Interpersonal Behavior,New York: Holt, Rinehart, and Winston, 1970, pp. 395-396.Also see "Task Roles and Social Roles in Problem-SolvingGroups," in B.E. Maccoby, T.M. Newcomb, and Eugene L.Hartley, eds., Readings in Social Psychology, New York: HoltRinehart, and Winston, Inc., 1958, pp. 437-447.
116F.E.Fiedler, M.M. Chemers and L. Mahar, ImprovingLeadership Effectiveness: The Leader Match Concept, JohnWiley and Sons, Inc. New York, 1976. pp. 6-13.
117E.A. Fleishman,ship and Supervision ingraphs, Number 33, Ohio27, 33, 42, 89.
118R.R. Blake and J.S. Mouton, The Managerial Grill Key
E.F. Harris and H.E. Burtt; Leader -Industry, Educational Research Mono-State University, 1955, pp. 5, 7,
Orientations for Achieving :oduction Through People, GulfPublishing Company, Houston fexas, 1964, p. 10.
119Fleishman, Harris and Burtt, Leadership and Super-vision in Industry, p. 5.
120PERCENT YES loaded slightly negatively on principalcomponents and quartimax plots and slightly positively onequimax, varimax and oblimin plots. Correlations show it relat-ing positively (r = .302, p = .02) to the best proxy for TASK-DRIVEN (IS PREPARED FOR CLASS), with that proxy having 0.22 thepositive impact on satisfaction that STUDENT-CARING does.
121Because it was unclear which of the proxies for task-driven might produce the better fits, all, the plots pre-sented here were also run replacing PREPARED with ORGANIZED.Those plots are available on request.
122The plotting software, Menugrah, was developed by thestaff at the Universfty Computing Center at San Diego StateUniversity, and was run on a VAX/VMS computer in concertwith a Cat -Comp plotter.
123Though possessing a master's degree earns the teacheran additional $100 annually, the corresponding variable MAS-TERS was intentionally omitted because it's largely embeddedin YEARS (r = 0.826)--not in EDUNITS (r = 0.405). Moreover,
.4
MANAGERIAL GRID FOR TEACHERS, T. Foote, 2/28/88 PAGE 62
it's smallness relative to the district's payments for YEARSand EDVNITS hardly justifies its complicating the equation(and causing multicolinearity problems).
124See the above citations for Bales, Personality andInterpersonal Behavior. Maccoby, Newcomb, and Hartley, Readingsin Social Psychology. Blake and Mouton, The Managerial Grid, KeyOrientations for Achieving Production Through People; The Gridfor Supervisory Effectiveness; The Versatile Manager: A Grid Pro-file; Corporate Excellence Through Grid Organization Development;Building a Dynamic Corporation Through Grid Organization Devel-opment; The Grid for Sales Excellence; The Marriage Grid; GridApproaches for Managerial Leadership in Nursing; Grid Approachesfor Managing Stress; and, The Academic Administrator Grid.Couch, "Psychological Determinants of Interpersonal Behavior,"Unpublished Doctoral dissertation. Fiedler, Chemers and Mahar,Improving Leadership Effectiveness: The Leader Match Concept.Fleishman, Harris and Burtt, Leadership and Supervision inIndustry.
125See those listed in the preceding footnote.
126Edward E. Lawler, III, Pay and Organization Effective-ness: A Psychological View, New York: McGraw-Hill Inc., 1971,p. 167. Although Belcher discusses these three components inhis book Compensation Administration, (pp. 224-225) citedearlier, the descriptions that follow were aided most of allby a personal interview with Belcher,, The author is deeplygrateful to David Belcher for his contributions to thissection.
127Carl F. Frost et al., The Scanlon Plan for Organiza-tion Development: Identity, Partici:Dation, and Equity, Mich-igan State University, 1974. pp. 2-5. See also Frederick G.Lesieur, ed., The Scanlon Plan, Cambridge: MIT, 1958. AndW.B. Wolf, "The Scanlon Plan--Device to Increase Profits andProductivity," Pacific Northwest Business, June, 1956, pp.18-27.
128Patten, Pay: Employee Compensation and Incentive Plans,p. 418.
