Classroom teaching

Classroom Teaching Practices:
Ten Lessons Learned

by

Alberto F. Cabrera
Professor & WISCAPE Sr. Research Associate
Department of Educational Administration
University of Wisconsin at Madison
1025 West Johnson St.
Madison, WI 53706
Tel: 608-262-3106
E-mail: Cabrera@education.wisc.edu

Steven M. La Nasa
Assistant Director of Human Resources & Payroll
George Mason University
4400 University Drive
Fairfax, VA 22030-4444

II Seminario
Calidad e Innovacion en el Sistema Universitario
9-11 de Enero de 2002

Classroom Teaching Practices:
Ten Lessons Learned
This manuscript provides a brief overview of ten key lessons we have learned regarding

effective classroom teaching practices. In talking about teaching, we have to define first what we

mean by effective teaching. In all honesty, we lack consensus as to what effective teaching is all

about. Whenever, the topic of effective teaching is brought to bear in research and practice circles,

the biblical story of the Tower of Babel comes to mind: a raucous mob speaking in different

tongues all at the same time. So let us briefly review three main perspectives on effective teaching.

One perspective defines effective teaching in terms of what teachers they themselves

consider effective teaching to be all about. After conducting a meta-analyses of 31 studies,

Feldman (1988) concluded that faculty’s three top choices of instructional dimensions were: a)

knowledge of the subject, b) enthusiasm for teaching or for the subject, and c) sensitivity to, and

concern with, class level and progress, in that order. The second approach defines effective

teaching from a student’s perspective (Young & Shaw, 1999). Feldman found that students’ top

choices of effective teaching were, in order of importance: a) sensitivity to, and concern with,

class level and progress, b) teacher’s preparation; organization of the course, and c) teacher’s

stimulation of interest in the course and its subject matter. Still another approach is to regard

effective teaching as those instructional techniques and practices both teachers and students agree

to be effective. Feldman found that both students and teachers concur in defining effective

instruction in terms of course preparation and organization of the class. And yet, discrepancies

remain between teachers and students. If judged under the lenses of faculty, then, effective teaching

would be defined in terms of knowledge and holding high standards. From a student’s perspective,

one would define effective teaching in terms of the outcomes of instruction. To avoid the problem

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of multiplicity of perspectives, we are going to adopt a very simple definition of effective teaching

in this manuscript, a definition that is consistent with the one fostered by major accrediting

programs of higher education (e.g., Accreditation Board for Engineering and Technology, 1998;

Middle States Association for Colleges & Schools, 1996); namely,

Effective teaching is one that produces demonstrable results in terms
of the cognitive and affective development of the college students

Having clarified what we mean by effective teaching, we need to provide a brief

description of how we are going to address our topic. The first section will devote itself to review

what we have learned about the nature of college teaching. In a nutshell: college teaching is

comprised by several behaviors a professor displays in class. This section will briefly review the

nature of those teaching behaviors. The second section will provide some advise regarding the

assessment of teaching. This advice can be summarized as follows: be alert of what you measure,

you may not be measuring teaching behaviors at all! The third section will describe how

knowledge of effective teaching is affecting American colleges and universities. If judged in terms

of what faculty do, the answer is not too much change at all. Though, we know what effective

teaching is all about few of us practice it. This section will also describe the major forces of

change that promise to revamp the way we think about teaching in the United States.

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I. What do we know about college teaching?

After almost 40 years of substantial research on college teaching we have learned our first

lesson: good teaching can promote student learning and development (Cabrera, Colbeck &

Terenzini, 1999; Feldman, 1989; Feldman & Paulsen, 1994; Murray, 1990). The second lesson

we learned is that in understanding teaching we need to recognize the fact that learning itself is a

social phenomenon (Cockrell, Caplow & Donaldson, 2000). In this social context, teaching is but

one of many factors that affect student development. Consequently, before reviewing the nature of

teaching in itself, we need to first address some contextual issues.

Teaching for Competence model

Advanced by Cabrera, Colbeck and Terenzini (1999), the Teaching for Competence

Model (see Figure 1) argues students’ outcomes such as learning takes place in a context shaped

by the students’ own characteristics, the instructional practices they encounter in the classroom,

and classroom climate created by the professor and the peers. In terms of students’ characteristics,

the model posits that students are likely to learn when they have the appropriate academic ability

and the motivation to do collegiate work. Students’ own learning styles also matter. They provide

the ways in which students can make sense of the reality surrounding them (Kolb, 1984). These

learning styles are affected by gender (Belenky, Clinchy, Goldberger, & Tarule , 1986), ethnicity

(Hurtado, 1992; Cabrera & Nora, 1994), and the particular discipline the student is pursuing

(Kolb, 1984). Classroom experiences include exposure to teaching methods, the curriculum, and

the classroom climate emerging by the nature of interactions among peers and with faculty. Though

both classroom experiences and classroom climate contribute to student development (Pascarella

& Terenzini, 1991; Kuh, Douglas, Lund & Ramin-Gyurnek, 1994), classroom experiences appear

to have a stronger and more varied effect on student outcomes (Cabrera, Colbeck & Terenzini,

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1999; Colbeck, Cabrera & Terenzini, in press; Volkwein, 1991; Volkwein & Lorang, 1996). The

model also presumes that a student’s characteristics, teaching practices and classroom climate

have a unique contribution on student development, reinforcing one another.

Figure 1. Teaching for Professional Skill Development Model

Teaching Practices
Teaching Practices
•Instructor Interaction & Feedback
•Instructor Interaction & Feedback
§Clarity
§Clarity
•Organization
•Organization
•Collaborative Learning
•Collaborative Learning

Students’ Characteristics
Students’ Characteristics
Student Outcomes
Student Outcomes
•Ability
•Ability
•Aspirations
•Aspirations •Group Skills
•Group Skills
•Parents’ Education
•Parents’ Education •Problem Solving Skills
•Problem Solving Skills
•Ethnicity
•Ethnicity •Occupational Awareness
•Occupational Awareness
•Gender
•Gender •Learning
•Learning
•Learning styles
•Learning styles

Classroom Climate
Classroom Climate

•Faculty
•Faculty
•Peers
•Peers

The learner as a component of teaching: Learning styles, ability and background.

Among factors known or presumed to affect students’ learning in college one can find:

students’ own intellectual ability, their educational aspirations, and the education level attained by

their parents (Astin, 1993, Pascarella & Terenzini, 1991). Central in all of this are the student’s

learning styles themselves.

Kolb (1984) argues that individuals experience learning on the basis of concrete

experiences, conceptualizing of experiences, working with ideas or concepts or actively

experimenting with or manipulating objects. Kolb arranged these four cognitive styles under two

cognitive domains that may be seen as two poles of a continuum: a) the concrete-reflective domain

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and b) the abstract-active experimentation domain. Table 1 summarizes the components of each of

the two learning domains.

Table 1. Cognitive domains and strategies

Concrete-Reflective Domain Abstract-Active Domain

Concrete Experience Reflective Observation Abstract Conceptualization Active Experimentation

Affective: Perceptual: Symbolic: Behavioral:
Dealing with people Gathering information Testing theories & ideas Making decisions
Being sensitive to values Organizing information Analyzing quantitative data Seeing & exploiting
Being sensitive to people’s Listening with an open mind Experimenting with new ideas opportunities
feelings Seeing how things fit in the big Designing experiences Setting goals
Being personally involved picture Generating alternative ways of Committing self to objectives
Working in groups Developing comprehensive doing Able to adapt to changing
plans Building concept models circumstances
Imagining implications for Influencing & leading others
ambiguous situations

Kolb further postulated the intersection of these two domains produces four learning styles

in which two of the four cognitive traits dominate. These learning styles are:

1. Convergent. Dominant learning style stresses abstract conceptualization and active
experimentation
2. Divergent. Dominant learning style stresses concrete experiences and reflective
observations
3. Assimilator. Dominant learning style stresses conceptualizations and reflective
observations
4. Accommodator. Dominant learning style stresses concrete experiences and active
experimentation.

In the Kolbian model, learning is maximized most when the classroom environment matches

any of the four learning styles. Kolb also noticed that academic disciplines seem to call for

different learning styles. Having collected learning scores from 800 managers, Kolb found that

learning styles correlated with particular majors, a discovery leading him to postulate that certain

learning styles as best fitting specific majors (see Figure 2)

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Figure 2. Learning styles & majors
Adapted from Kolb (1984)

Concrete

Concrete
History
Business Political Science
ACCOMODATORS DIVERGERS English
Psychology

Active Reflective

Economics
Mathematics
Nursing
Sociology
Abstract CONVERGERS ASSIMILATORS
Physics
Engineering
Chemistry
Foreign Languages

Active Abstract Reflective

Students' preferences towards learning styles have been well documented by research other

than Kolb's. Pask (1988) for instance, demonstrated students learn best when the instructor's

teaching style matches their learning preferences; mismatches, on the other hand, lessened this

learning. Research has also shown that students tend to study in academic disciplines most

resembling their learning styles (Feldman, 1989). Under some conditions, gender and race can also

influence what and how students learn (Oakes, 1990). Opinions differ, however, about the reasons

for gender and race-related learning differences. The most compelling argument lies on differences

in learning styles (Belenky, Clynchy, Goldberger & Tarule, 1986; Lundeberg & Diemert, 1995;

Baxter-Magolda, 1992; Martínez-Alemán, 1997). According to this approach, women and

minorities are more likely than white men to prefer collaborative learning settings because their

learning styles emphasize connected knowing, cooperative problem solving, and socially based

knowledge. In contrast, men (and some women educated in college by men) may be more likely

than other women to prefer traditional pedagogy given their more analytical, individualistic, and

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competitive learning styles (e.g. Belenki, at al., 1986). Research evidence regarding gender or

race based learning styles is mixed. Lundeberg and Diemert’s (1995) qualitative study of women

attending a private, single-sex midwestern college found women did prefer collaborative learning.

Lundeberg and Diemert also observed the collaborative nature of the student interactions promoted

intellectual risk taking and connected understanding of concepts. On the other hand, Tinto (1997)

found collaborative learning effective in promoting persistence in college, regardless of a

student’s gender or race/ethnicity. Summing up, the third lesson we have learned is students have

different ways of knowing whose effectiveness may vary by type of academic discipline or

major, gender and ethnicity.

Teaching as a component of classroom experiences

Interest in classroom experiences has increased as research mounts regarding their

connection with a diverse array of student outcomes, including academic and cognitive

development, knowledge acquisition, clarity in educational goals, interpersonal skills, and the

quality of student effort spent in academic activities (e.g. Astin, 1993; Colbeck, Cabrera,

Terenzini, in press; Murray, 1990; Pascarella & Terenzini, 1991; Tinto, 1997; Volkwein, 1991;

Volkwein & Lorang, 1996; Volkwein & Cabrera, 1998). This research also shows that teaching

practices are part of a complex process defining classroom experiences. Those experiences

embrace teaching practices, the delivered curriculum as perceived by the students, and the climate

permeating interactions among students and between the instructor and the students (Cabrera &

Nora, 1994; Ewell, 1996; Stark & Latuca, 1997).

Teaching as a multidimensional phenomenon

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The two lessons we have learned from research on classroom experiences are: a) college

teaching is multidimensional in nature (lesson # 4), and b) the effectiveness of each college

teaching dimension s varies as a function of the student outcome under consideration- lesson #

5- (Cabrera, Colbeck & Terenzini, 1999; Colbeck, Cabrera & Terenzini, in press, McKeachie,

1988, 1990; Murray, 1990; Kulik & Kulik, 1979).

The dimensions of teaching. Teaching embodies a variety of classroom behaviors. Having

observed 24 professors of political sciences in the classroom, Solomon, Rosenberg and Bezdek

(1964) reported faculty engaging in 169 teaching variables. Subsequent factor analyses of those

169 teaching variables revealed 8 underlying dimensions; namely, 1) control vs. permissiveness,

2) lethargy vs. energy, 3) protectiveness vs. aggressiveness, 4) vagueness vs. clarity, 5) emphasis

on student growth, 6) dryness vs. flamboyance, 7) emphasis on participation, and 8) coldness vs.

warmth. As important as this study was in highlighting the multidimensionality of teaching

practices, several methodological problems prevented us from reaching firm conclusions. To

begin with, many of the teaching practices reported by the researchers consisted of global and

vague traits difficult to report by observers other than the researchers themselves; this is to say,

many of the classroom activities Solomon and associated documented demanded high-inference on

the part of the observer (e.g., clarity, informality, flexibility). Reliance on a handful of observers

compounded the problem of using of high-inference practices still further (Murray, 1990).

However, the study’s key finding regarding the multifaceted nature of teaching prompted a series

of studies regarding the nature of the teaching function. Of them, Murray’s studies are seminal.

Twenty-one years after Solomon and associates’ study, Murray (1985) replicated their

findings regarding the multifaceted nature of college teaching. To avoid the methodological pitfalls

Solomon and associates encountered, Murray focused on observable (low-inference) teaching

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behaviors rather than on vague or global traits that call for a high degree of inference on the part of

the observer (high-inference). He also relied on trained observers rather than on students. Once

these ratings were collected over a five-year period of time in a multiple section of introductory

psychology, Murray found that these behaviors could be grouped into six dimensions. Those were:

1) enthusiasm, 2) clarity, 3) interaction, 4) task orientation, 5) rapport, and 6) organization.

As seminal as the Murray’s study was and the research on teaching behaviors it prompted

(Murray, 1990), its reliance on a handful of majors (e.g., political science, psychology, arts,

natural sciences) has raised questions regarding the generalizability of its findings to another

disciplines. Do professors in other fields engage in a variety of teaching practices? A recent study

answered the question of the multidimensionality of teaching behaviors as far as engineering is

concerned. Cabrera, Colbeck and Terenzini (1999) examined the extent to which 1,258

engineering students observed their instructors being engaged in 20 classrooms behaviors. All

those teaching behaviors were drawn from the research literature on effective instructional

practices and activities. A principal components factor analysis of these low-inference teaching

behaviors produced 3 groups of teaching practices interpreted as Collaborative Learning,

Instructor Interaction and Feedback and Clarity and Organization. Table 2 lists each of the

classroom behaviors comprising each dimension. Their results, then, clearly show faculty in such

hard majors as engineering do use a variety of teaching practices as complex as the ones engaged

by their peers in other disciplines (Murray, 1990). Equally important in this study is the discovery

that students themselves can be reliable raters of the teaching behaviors they observe. The alpha

coefficients for each teaching dimension ranged from .77 to .88, alpha coefficients values well

above the .70 benchmark for scales considered to be highly reliable (Litwin, 1995).

Table 2. Results of Cabrera, Colbeck & Terenzini (1999) study

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Teaching Dimensions
Teacher behavior Collaborative Instruction Clarity
Factors and highest loading behaviors Teaching Interaction &
& Organization
Feedback
Discuss ideas with classmates .822
Wok cooperatively with students .739
Opportunities to work in groups .753
Get feedback from classmates .753
Students teach & learn from one another .679
Interact with classmates outside of class .650
Required participation in class .589
Interact with instructor as part of the course 780
Interact with instructor outside of class .741
Instructors gives detailed feedback .713
Instructor gives frequent feedback .689
Guided student learning, versus lecturing .578
Assignments/activities clearly explained .767
Assignments/presentations clearly related .722
Instructor makes clear expectations for .677
activities
Internal Consistency Reliability (Alpha) .88 .83 .77

Effective teaching practices. Earlier we defined teaching effectiveness in terms of their

effects on students. This connection brings us to the fifth lesson we have learned: not only are

teaching practices multidimensional, each teaching dimension plays a varied and complex role

on a student’s cognitive and affective development. Table 3 summarizes research findings

regarding the linkage between teaching practices and students’ outcomes.

Table 3. Teaching practices & students’ outcomes
Teaching Practice Student Outcomes
Teaching clarity • Motivation to re-enroll in courses
• Achievement
• Academic effort
Continuous & specific feedback • Achievement

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Lecturing • Acquisition of knowledge
Class discussion • Problem solving skills
• Long-term retention of knowledge
Problem solving methods • Critical thinking skills
• Long term retention of knowledge
• Acquisition of knowledge
• Achievement
Coaching • Design skill
Collaborative learning • Persistence in college
• Problem solving skills
• Long term retention of knowledge
• Group skills
• Design skills
• Intellectual risk-taking
• Connected knowledge
• Achievement
• Openness to diversity
• Academic effort
• Understanding science & technology
• Analytical skills

Teacher clarity and organization, for instance, has been found to correlate with student

motivation to re-enroll in courses (Murray, 1983), student achievement (Feldman, 1989; Murray,

1990), self-reported gains in knowledge (Solomon, Rosenberg & Bezdek, 1964), problem solving

and in occupational awareness (Cabrera, Colbeck & Terenzini, 1999). Continuous, specific and

immediate feedback has been found to improve mastery of foreign languages (Cardelle & Corno,

1981) and achievement (Kulik & Kulik, 1979). While both lecturing and class discussion

correlate with acquisition of knowledge, class discussion appears to be more effective for

enhancing problem solving skills (Kulik & Kulik, 1979). In addition to class discussion, students’

critical thinking skills can be positively influenced by encouragement from teachers and a

teacher’s articulation of problem solving procedures (McKeachie, 1988, 1990). Explaining

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assignments and activities, clearly stating course expectations, and articulating assignments to the

content of the class are some of the teaching practices that have been found to enhance a student’s

ability to solve problems (Cabrera, Colbeck & Terenzini, 1999).

Of the teaching practices, collaborative learning has been singled out as the most promising

to bring about student development (Gamson, 1994; Tinto, 1997, 1998). Collaborative learning,

extensively used and researched in the K-12 arena (Slavin, 1990), emerged as an important

pedagogy in higher education during the late 1980s (Bruffee, 1993; Goodsell, Maher, & Tinto,

1992). Collaborative learning departs from traditional learning theory in that it is premised on the

notion learning is socially based (Cokrell, Caplow & Donaldson, 2000). Accordingly,

collaborative learning restructures the classroom away from the traditional lecture to small group

work requiring intensive interactions between students and the faculty member while working

through complex projects. Through completion of projects, learning is supposed to be enhanced as

students build upon their personal experiences while working with other students espousing a

variety of views and skills. In this context, the role of faculty is as facilitator rather than as a

knowledge source (Bruffee, 1993; Johnson, Johnson, & Smith, 1992; Slavin, Karweit, & Madden,

1989). Collaborative learning, in all its manifestations (e.g. peer-learning, peer tutorial, problem

case solving), has been found to positively correlate with problem solving, long term retention of

knowledge, achievement, application of concepts, sensitivity to fellow students’ feelings, positive

attitudes toward subject area, student leadership behavior, occupational awareness, student

openness to diversity, gains in groups skills, and persistence (Cabrera, Colbeck & Terenzini,

1999; Cabrera, Nora, Bernal, Terenzini & Pascarella, 1998; Cokrell, Caplow & Donaldson, 2000;

Johnson, Johnson & Smith, 1991; Levine & Levine, 1991; McKeachie, 1990; Pascarella &

Terenzini, 1991; Tinto, 1997).

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The impact of teaching practices extends well beyond cognitive issues; they also matter for

a student’s affective development. The more faculty interact with students, provide frequent and

detailed feedback, create opportunities for collaborative learning and make assignments and

expectations clear, the greater the gains in students’ intentions to complete their degrees, sense of

responsibility for their own learning, confidence, and motivation to pursue their majors.

Moreover, students become more aware of what their future occupations may look like as a result

of their interactions and feedback from instructors ((Colbeck, Cabrera & Terenzini, in press;

Cabrera, Colbeck & Terenzini, 1999).

Classroom Experiences: Classroom Climate.

The sixth lesson we have learned is: the nature of the relationships permeating the

interaction among students, and between students and faculty is as important for student

learning and development as is teaching. A classroom climate saturated by prejudice and

discrimination on the part of faculty and peers has emerged as an explanatory factor accounting for

differences in college adjustment, majoring in hard sciences, and persisting in college between

white men, women and minority students (Cabrera, Colbeck & Terenzini, 1999; Cabrera & Nora,

1994; Cabrera et al., 1999; Colbeck, Cabrera & Terenzini, in press; Drew, 1996, 1992, 1994;

Eimers & Pike, 1997; Fleming, 1984; Whitt et al., 1998). On the other hand, faculty can play a

pivotal role in enhancing the quality of the classroom climate. Faculty who foster equity and

tolerance improve the vitality of the classroom experience to the point of overcoming the negative

role of perceptions of prejudice and discrimination (Volkwein & Cabrera, 1998).

II. On assessing teaching & student outcomes

Several strategies and methods have been applied to the assessment of teaching. These include

faculty peers, unobtrusive observers that sit in the classroom pretending to be students, recording,

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videotaping, and even reviewing samples of classroom assignments (Ewell, 1996, Murray, 1990).

In so doing, the seventh lesson we learned is: trust the students for they are excellent raters of

what takes place in the classroom. The key in producing reliable assessmements of teaching lies

on what is being assessed. Murray's (1990) review of the literature led him to conclude that

classroom teaching ratings tend to be reliable whenever observable (low-inference) teaching

behaviors are the focus of evaluation. The rule is simple: traits or global measures (e.g.

flexibility, caring for students) tend to produce low agreement among raters, while observable

teaching behaviors (e.g. instructor explains class assignments clearly) increases it. For instance,

Cabrera, Colbeck and Terenzini's (1999) found that the1,250 engeneering students under study

provided quite consistent ratings for each of the 20 teaching behaviors under consideration. The

level of rating error in each of the three teaching dimension they evaluated ranged from as low as

12% to as high of 23%; a very low level of rating error in social sciences. Hativa and Birenbaum

(2000) reached similar results while examining student evaluations of teaching behaviors among

engineering and education undergraduates at a major Israeli university. The reliabilities for the

four behavioral-based teaching scales they employed ranged from.82 to .94, representing a

measurement error ranging from 6% to 18%.

Assessing student cognitive and affective outcomes is as important as evaluating teaching

practices. Judgments of effective teaching rest on strong correlations between teaching and student

outcomes (Murray, 1990). During the last 20 years considerable progress has been made in

assessing cognitive and affective development of the students before they enter in college and as

result of their exposure to college. Table 4 displays some of the most important measures seeking

to capture the cognitive and affective development of the student before and during and as a result

of college.

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Table 4. Cognitive and affective measures

Basic & Entry-Level: Attitudes, Motivation College Related
Aspirations
Aptitudes & Abilities Skills, Competencies, Gains
• ACT Collegiate Assessment of Academic Proficiency • ACT Assessment
(CAAP) • College BASE: Reading, literature, writing, general math,
• SAT-Math, Verbal algebra, lab & field work, history, social science
• ACT ASSET (Reading, Writing, Numerical, & Study (Osterlind & Merz, 1992)
Skills) • Watson Glazer-Critical Thinking
• CLEP-Composition • ETS Descriptive Test of Language Skills
• College Board English Composition • ACT’s CAAP
• Nelson Denny Reading • College GPA
• Doppelt Math • Student’s portfolio
• ACT COMPASS • Pace’s (1987) College Student Experiences
• High School GPA and rank Questionnaire (CSEQ)
• Proficiency exams
• Course patterns vs formal curriculum
• Student credit hours
Motivation, Aspirations Collegiate Experiences, Goal Attainment &
Growth
• College Board/ASQ Admitted Student Questionnaire • Pace’s (1987) College Student Experiences
• ACT Entering Student Survey Questionnaire
• CIRP/HERI Student Information • Astin's (1993) College Student Survey
• NCHEMS Entering Student Questionnaire • ACT Evaluation Survey Services (ESS)
• Self-Reported Growth
• Student portfolio
• Community College Student Experiences Questionnaire
• College Assessment Program Survey (CAPS)
• Academic & Social Integration Scales (Pascarella &
Terenzini, 1980)

Assessing cognitive development as a result of collegiate experiences has been

approached under two lenses: a)’objective’ standardized tests, and b) self-reported measures of

growth (see Table 4). The use of either approach has been controversial (Pike, 1995, 1996).

Standardized tests not only are expensive to develop (Ewell & Jones, 1993), they may also fail to

capture the full range of verbal, quantitative and analytical skills associated to different

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disciplines, curriculum and class-level teaching (Anaya, 1999). This is to say, standardized tests

generally measure achievement accurately, but for a limited range of behaviors or content subject

(Astin, 1993). Foundation in Engineering (FE) illustrates this problem. After substantial monetary

and time expense, the much heralded ability of the FE test to capture knowledge all first-year

students should master was doubted. Watson (1998) examined FE test results in the period 1993-

96 for students in twelve engeneering disciplines. He found FE test scores to correlate poorly with

end of the year GPAs. Having examined the degree of association between FE test scores and GPA

for each of the 12 engineering fields under study, Watson judged FE to be not applicable to all

enginneering disciplines as the test was originally intended to accomplish. On the other hand, self-

reported measures tend to measure a broad variety of behaviors and content; however, they may

not be as precise as standardized tests (Astin, 1993). Questions about reliability of self-reported

measures of growth is another problem.

Recent research has taught us lesson number eight: students may be as reliable in

assessing their cognitive development resulting from classroom experiences as are

standardized tests. After examining a representative sample of college students who took the GRE

in 1989, Anaya (1999) concluded that self-reported measures of gains in math and verbal skills

were valid proxies of cognitive skills as measured by the verbal and math components of the GRE.

Likewise, Pike (1995) found self-reported measures of educational gains to have convergent

validity with achievement tests (e.g., College BASE).

Extreme caution should be exercised when using self-reported growth measures as proxies

of achievement tests, however. The National Center for Higher Education Management Systems

recommended four criteria for using self-reported measures: a) they should represent broad-based

outcomes, b) the measures should represent significant phenomena that could be used to inform

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policy makes, c) the measures should covariate with other assessments; and d) the observed

relationships between these covariates should remain across different educational settings (Ewell

et al., 1994). Recently, Pike (1995, 1996) demonstrated that self-measures should also meet a fifth

condition: the self-reported measures should reflect the content of the learning outcome under

consideration. He concluded that high content overlap between self-reported measures and test

scores is a key consideration for using self-reported measures as proxies.

Developing content valid measures of cognitive growth is not an easy enterprise. It precludes

a deep understanding of the cognitive and affective domains of a particular discipline and its

curricular objectives (Astin et al., 2000; Ewell, 1996; Farmer & Napieralski, 1997). In short,

valid cognitive measures are those in which learning is clearly connected with the curricular

values and objectives (Astin et al., 2000). Jones and associates (1994a, 1994b, 1996, 1997), for

instance, were able to identify the components of critical thinking, problem solving and

communication skills engineering students should master after a series of carefully implemented

Delphi studies among faculty members, administrators and employers.

Once the condition of content validity is met, however, students are quite reliable in

assessing their cognitive growth. Using Pace’s (1987) College Student Questionnare, Kuh, Pace

and Vesper (1997), for instance, found that college students were highly reliable in assessing their

cognitive gains in general education, personal-social development and intellectual skills. While

relying on 23 items patterned after the themes identified by Jones and associates, Cabrera, Colbeck

and Terenzini (1999) also reported a high degree of internal consistency among engineering

students' self-reported gains in group skills, problem solving and occupational awareness as result

of taking enginnering courses (See Table 5). The reliability of three cognitive growth domains was

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substantially high, ranging from .81 to .94. In other words, the margin of mearurement error ranged

from 6% to 19%.

Table 5. Cognitive growth domains

Factor Loadings
Self-reported growth measures
Group Problem- Occupational
Skills Solving Awareness
Skills
Developing ways to resolve conflict & reach agreement .779
Being aware of feelings of members in group .841
Listening to the ideas of others with open mind .829
Working on collaborative projects as member of a team .815
Organizing information to aid comprehension .679
Asking probing questions that clarify facts, concepts .606
Developing alternatives that combine best from previous work .618
Ability to do design .578
Solve an unstructured problem .697
Identify knowledge, resources & people to solve problem .666
Evaluate arguments and evidence of competing alternatives .675
Apply an abstract concept or idea to a real problem .735
Divide problems into manageable components .744
Clearly describe a problem orally .679
Clearly describe a problem in writing .667
Develop several methods to solve unstructured problem .732
Identify tasks needed to solve an unstructured problem .752
Visualize what the product of a design project would look .584
Weight the pros and cons of possible solutions to a problem .623
Understanding what engineers do .754
Understanding language of design .721
Understanding engineering has a non-technical side .710
Understanding of the process of design .703
Internal Consistency Reliability (Alpha) .926 .943 .813

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III. Does knowledge of effective instruction promotes change?

Almost forty years of research has taught us that active teaching practices, problem-based

teaching, instructor's interaction and feedback, class discussion and group participation are not

only preferred by students but are strongly linked to student development (e.g., Cabrera, Colbeck

& Terenzini, Feldman & Paulsen, 1994; Hativa & Birenbaum, 2000; Murray, 1990). The same

research shows that lecturing from class notes is not only disliked the most by students (Hativa &

Birenbaum, 2000), but correlates negatively with teaching effectiveness (Murray, 1990). In light of

this research one would expect innovative teaching techniques to rule the landscape of pedagogical

practices in the US. Judging by the results of national faculty surveys, the ninth lesson we have

learned is that few full-time faculty use innovative teaching methods. Based on a 1993 national

representative sample of full-time faculty, Leslie (1998) reported that more than two-thirds of

college professors relied on lecture as their primary teaching practice (see Table 6). Few full-time

faculty, if any, used active learning methods (5%) while one out of six full-time faculty relied on

class discussions or seminars.

Table 6. Percentage of teaching methods employed by 1993 Full-time Faculty
Teaching Method Percentage used by
Faculty
Lecture 69.4
Seminar or discussion 17.0
Labs or internship 8.9

Active learning 4.7
Based on Leslie (1998)

20

Two reasons come to mind when seeking to explain the high prevalence of lecturing among

college professors: a) the nature of academic work, and b) the reward system. The use of

innovative teaching techniques presumes specialized knowledge on the part of faculty that only

constant training and substantial experience can provide. On the other hand, graduate education at

the Ph.D. level is geared towards preparing scholars and researchers, not teachers. The message

graduate education conveys is clear: research paves the way to academic success (Clark & Centra,

1985). This message is furthered strengthened by the manner in which future faculty are socialized

into the academic field; namely their own professors (Clark & Corcoran, 1986), who, as we

already know, prefer lecturing.

The reward system further minimizes the importance of teaching in salary and promotion

decisions (Strathman, 2000). Konrad and Pfeffer (1990) found a substantial negative relationship

between teaching and faculty salary when examining the 1969 Carnegie Commission on Higher

Education Faculty Survey. Fairweather (1993) studied the connection between teaching, research

and faculty compensation across a variety of postsecondary institutions ranging from liberal arts

colleges to research universities among 8,383 full and part time faculty from 424 colleges and

universities who participated in the 1987-88 National Survey of Postsecondary Faculty.

Irrespectively of institutional type, mission and academic discipline, Fairweather found that

“…faculty who spend more time on research and publishing, and less time on teaching earn the

most income” (p.11).

For an assistant or associate professor confronting the competing demands for research and

service the message is clear: we don't train you to be a teacher, nor do we reward your

commitments to demanding instructional techniques. In short, the tenth lesson we have learned is

effective teaching can take place when faculty are trained in teaching and rewarded for it.

21

Forces of Change

As faculty peacefully roam their classrooms regurgitating their old, yellowed and crumpled

notes to sleeping classes, two major forces are hurtling towards oblivious institutions that will

revolutionize the way American professors teach. Attention to outcomes and demonstrable results

is playing an increasingly important role in public policy. Ewell (1998) estimates that two-thirds

of the states have developed assessment mandates compelling institutions of higher education to

establish mechanisms for assessing and reporting student performance. Ewell’s observations

regarding changes in the orientation of performance indicators in public policy seem to be

confirmed by a recent study of the use of performance indicators in eleven states.

Burke and Serban (1998) found that fewer than 15 percent of the eleven states they

surveyed used resource or reputation indexes. Instead, most of the states surveyed had introduced

indicators gauging impacts or results, particularly in the area of student development and gains in

professional competencies, to guide public policy (see Figure 3).

Emphasis on demonstrable changes in student outcomes is beginning to influence state-

funding practices as well. Some state initiatives like the 1998 Maryland’s Higher Education

Reorganization Act seek institutional change by making public funding contingent upon

demonstrated ability to foster student learning and to retain students. The 1998 New York Plan

calls for the allocation of state funding ranging from 3% to 5% on the basis of four major groups of

performance indicators: “student achievement”, “faculty achievement”, “academic robustness”,

and “quality of campus services.” Though few states have adopted performance funding, Burke and

Serban (1998), estimate that by the end of this century slightly more than fifty percent of the states

22

will adopt funding schemes in which portions of state allocations to higher education institutions

would be linked to demonstrated performance1.

Figure 3. Use of indicators in performance funding
among 11 states.
50
44
45 42

40
35 2-year
30 25
25 23 4-year
20
20 16
15
15
10 8
3 4
5
0
Inputs Proces Output Outcome Combine
&
Reputatio s s s d
n
Based on: Burke &Serban (1998). Performance funding for public higher education: Fad or
trend?

Interest in student development is also heightened by industrial leaders’ calls for college

graduates who can work in teams and solve real world problems (Augustine, 1996; Black, 1994;

Bucciarelli, 1988). In 1992, the National Educational Goals Panel, for instance, declared student

developmental outcomes such as critical thinking, problem solving, effective communication and

responsible citizenship essential when judging the effectiveness of its institutional affiliates.

Accrediting agencies have contributed to this trend by shifting their focus from global resource and

reputational measures to indicators of teaching effectiveness. In 1996, for example, the Middle

States Association of Colleges and Schools Agency placed teaching and learning as the

centerpiece in institutional self-assessment. Recently, the North Central Accreditation Commission

1
This estimate is based on a 1997-telephone survey of all state higher education finance officers in the fifty states, Puerto Rico and

23

encouraged institutional evaluators to focus their attention to students’ gains in group interaction,

and problem solving skills. Regional accreditation efforts are being matched by professional

accrediting organizations. The Accreditation Board for Engineering and Technology (ABET), the

sole agency responsible for accrediting engineering degrees in the US, recently enacted criteria

requiring colleges of engineering by the year 2,001 to demonstrate their graduates have developed

eleven competencies, including the abilities “to design systems or components, or process to meet

desired needs”, “to function on multi-disciplinary teams”, and “to communicate effectively”

(ABET, 1998).

Conclusions

Bringing a unified understanding of what effective college teaching is all about is a

daunting task, quite beyond the scope of this manuscript. What we did was to attempt to derive

some lesson regarding effective teaching when approached in terms of its effects on students.

Using this approach, the 10 lessons we have learned can be summarized as follows:

1. Good teaching can promote student development. Instruction can bring value added to the

potential the college student brings with himself or herself to the classroom.

2. Learning is a social phenomenon. Learning is the product of a complex process. The

classroom climate, the student’s own learning needs, goals and preferences along with

teaching strategies and curriculum all interact in producing cognitive and affective

development. Assessment of both learning and teaching should reflect this complexity by

including a variety of assessment methods capturing the nature of the classroom

interactions, teaching practices, values and performance on a series of well defined

cognitive and affective domains (Astin et al., 2000).

the District of Columbia.

24

3. Students have different ways of knowing. Classroom practices and even the curriculum

itself should take into account the fact that students’ way of knowing are affected by a

variety of factors ranging from their preferences towards learning, their learning needs

(e.g. vocational vs. academic), their gender and even their own culture.

4. College teaching is multidimensional. Teaching is complex. It embodies a wide variety

of practices and methods.

5. The effectiveness of each teaching dimension varies as function of the student outcome

under consideration. There is no best way to teach. Effective teaching can only take place

once curricular objectives clearly specify the specific knowledge, skills and values the

students are supposed to master. Only in this manner would the college professor be able

to choose that pedagogy most fitting to the specific student outcome under consideration.

6. Classroom climate matters. A classroom climate dominated by prejudice and

discrimination lessens learning. College professors are key in creating a nurturing

environment by stressing equity and fairness in the relationships among students and

between students and faculty.

7. Students can evaluate effective teaching. Students can be excellent raters of teaching

performance. The key for good assessment rests on the extent to which teaching behaviors

themselves are the object of assessment. This implies that institutions should spend

considerable effort identifying relevant teaching behaviors and incorporating them as part

of the student evaluation forms.

8. Students can evaluate their cognitive and affective growth. Again, the key in good

assessment rests on content valid measures. That is, growth measures need to evolve from

a deep understanding of the curricular objectives and the subject matter.

25

9. College professor do not use innovative teaching methods. No matter how much

knowledge exists regarding effective instruction, college professors still use traditional

lecturing as the main mechanism of knowledge transmission.

10. Effective teaching precludes training and rewards. Most college professors are not

trained to teach, nor rewarded when they are effective. Accreditation and performance

funding is creating the impetus to revisit the manner in which teaching is valued and

rewarded. To the extent this impetus remains, we should expect major changes in the nature

of the faculty work in the modern American universities.

The debate over the role of teaching was crystallized and received widespread attention in

the United States through Ernest Boyer’s Scholarship Reconsidered (1990). Boyer’swork brought

to the forefront the conflict over the role of research and teaching; the “scholarship of discovery”

versus the “scholarship of teaching.” Boyer argued that greater attention must me made to the

scholarship of teaching to benefit not only faculty and students; simply put: “the work of the

academy must relate to the world beyond the campus” (Boyer, 1990, p. 75). In closing

Scholarship Reconsidered, Boyer predicted that the 1990s would witness continued exploration

of the importance of teaching. The work of accrediting bodies, the assessment movement, and

research on teaching has helped confirm his prediction. The ten lessons summarized in this

manuscript reveal much of the progress made within American higher education since Boyer’s

calls for reform.

26

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