• School Characteristics Related to Student Learning
• Availability and Quality of Indicator Data
• Current Status of School Quality
• Summary
• References

More specifically, the report’s primary goals are to

• review the literature on school quality to help policymakers and researchers understand what is known about the characteristics of schools that are most likely related to student learning;
• identify where national indicator data are currently available and reliable; and
• assess the current status of our schools by examining and critiquing these national indicator data.

The research described in this report indicates that school quality affects student learning through the training and talent of the teaching force, what goes on in the classrooms, and the overall culture and atmosphere of the school. Within these three areas, this report identifies 13 indicators of school quality that recent research suggests are related to student learning and reviews the national data showing the current status of our schools. These indicators are summarized in figure A. The figure illustrates that these school quality factors can affect student learning both directly and indirectly. For example, school context characteristics like school leadership can have an impact on teachers and what they are able to accomplish in the classroom, and this in turn may influence student learning. In addition, various teacherlevel attributes can affect the quality of the classroom and, in turn, student learning. Traits at each of these levels can also directly affect student learning.

Figure A.—School quality indicators and their relationship to student learning

Substantial research suggests that school quality is enhanced when teachers have high academic skills, teach in the field in which they are trained, have more than a few years of experience, and participate in high-quality induction and professional development programs. Students learn more from teachers with strong academic skills and classroom teaching experience than they do from teachers with weak academic skills and less experience. Teachers are less effective in terms of student outcomes when they teach courses they were not trained to teach. Teachers are thought to be more effective when they have participated in quality professional development activities, but there is no statistical evidence to evaluate this relationship.

To understand the effectiveness of classrooms, research suggests that it is necessary to understand the content of the curriculum; the pedagogy, materials, and equipment used; and the conditions under which the curriculum is implemented. Students appear to benefit when course content is focused and has a high level of intellectual rigor and cognitive challenge. Younger students, especially disadvantaged and minority students, appear to learn better in smaller classes. Nationally representative data on the process of schooling, now becoming available for the first time, will further our understanding of the role of these factors in determining school quality.

How schools approach educational leadership and school goals, develop a professional community, and establish a climate that minimizes discipline problems and encourages academic excellence clearly affects school quality and student learning. For three reasons, however, the effect of school-level characteristics is more difficult to ascertain than the effect of teachers and classrooms. First, even though they are integral to a school, these characteristics are difficult to define and measure. Second, their effect on student learning is likely to be exerted indirectly through teachers and classrooms, compounding the measurement problem. And last, with some exceptions, reliable school-representative information about these indicators of quality is minimal. These difficulties should not overshadow the importance of collecting such data to learn more about how these characteristics operate and affect student learning through teachers and classrooms. The preponderance of national, regional, and local efforts to develop quality schools heightens the benefits that would be derived from additional refined and reliable school-representative measures of school characteristics.

The quality of existing data on these three types of indicators varies (table A). Where the dimension being measured is straightforward, or if it has been measured for an extended period of time, the data are high quality. Where there is little information about a particular important facet of an indicator, the data quality is moderated in some aspect. And where the indicator is more complex than the data, the quality is poor. For a few indicators, concrete statistical evidence of an association with learning is thin, even though experts agree that these indicators should show changes in student learning.

Table A.—Quality of national school quality indicator data

The indicators of teaching assignment, teacher experience, and class size each represent straightforward concepts and are easy to measure, and the data on these indicators are high quality. In addition, data on teacher experience and class size have been collected over several decades, further ensuring their quality. Data on teacher academic skills are also high quality, albeit less straightforward. While the academic skills of teachers are only one aspect of teaching ability, standardized tests that measure the academic skills of future teachers are quite advanced and have consistently shown links to student learning.

Data on indicators of professional development, course content, technology, discipline, and academic environment are moderate in quality. National data collection efforts pertaining to these indicators are relatively new, and these dimensions of schools are more complex than the data currently collected. Consequently, data on professional development are limited and provide little insight into important principles of successful professional development programs. National data on indicators of course content and academic environment are based primarily on course titles and are consequently too vague to be high quality. Current data on technology primarily measure the availability of hardware and access to the Internet and provide too little information on the instructional role of technology in the classroom. Nationally representative data on school discipline incidents and on school discipline policies are well defined, but administrators may underreport their discipline problems. In addition, there are limited data documenting a link to student learning, the implementation of discipline policies, and their perceived fairness.

Only poor-quality data are available on teachers’ pedagogy, school leadership, school goals, and professional community. These indicators are complex and therefore more difficult to measure, and historically they have not been prominent in national data collection efforts. It is difficult to isolate and measure critical elements of pedagogy because the teaching process consists of a complex set of interactions between students, the teacher, and the curriculum. Measuring human actions, incentives, and opinions to estimate the effects of school-level attributes such as leadership, goals, and professional community is an equally complex task.

As a group, the teacher-focused measures of school quality are less complex and have been collected for some time. School-level attributes of quality are nearly the opposite. We have more reliable information on indicators with high-quality data, while indicators with lower quality data provide an incentive and direction for improved national data collection. Nine indicators have high- or moderate-quality data and describe the current status of school quality.

Students learn more from teachers with strong academic skills (Ballou 1996; Ehrenberg and Brewer 1994, 1995; Ferguson 1991; Ferguson and Ladd 1996; Mosteller and Moynihan 1972), but graduates whose college entrance examination scores are in the top quartile are half as likely as those in the bottom quartile to prepare to teach (9 vs. 18 percent) (Henke, Chen, and Geis 2000). Teachers in the top quartile are more than twice as likely as teachers in the bottom quartile to teach in private schools (26 vs. 10 percent) and are less than one-third as likely as teachers in the bottom quartile to teach in high-poverty schools (10 vs. 31 percent). Furthermore, graduates in the top quartile who teach are twice as likely as those in the bottom quartile to leave the profession within less than 4 years (32 vs. 16 percent) (Henke, Chen, and Geis 2000).

Middle and high school students learn more from teachers who hold a bachelor’s or master’s degree in the subject they are teaching (Darling–Hammond 2000; Goldhaber and Brewer 1997; Monk and King 1994), but out-of-field teaching occurs with regularity (Bobbitt and McMillen 1994; Henke et al. 1997; Ingersoll 1999; Lewis et al. 1999).

Studies suggest that students learn more from experienced teachers than they do from less experienced teachers (Darling–Hammond 2000; Murnane and Phillips 1981; Rivkin, Hanushek, and Kain 1998). As of 1998, the highest poverty schools and schools with the highest concentration of minority students had about double the proportion of inexperienced teachers (those with 3 or fewer years of experience) than schools with the lowest poverty (20 vs. 11 percent) and lowest concentration of minority students (21 vs. 10 percent).

Experts agree that high-quality professional development should enhance student learning (Choy and Ross 1998; Mullens et al. 1996; U.S. Department of Education 1999), but data permitting an analysis of the relationship are not yet available. In 1998, 99 percent of the nation’s public school teachers had participated in some type of professional development program within the past 12 months (U.S. Department of Education 1999). However, most teachers participated in these activities for only 1 to 8 hours, or for no more than 1 day. Teachers with 3 or fewer years of experience were more likely (Lewis et al. 1999) to have reported participating in an induction program in 1998–99 than in 1993–94 (65 vs. 59 percent).

Research shows that as students take higher level academic courses they learn more (Raizen and Jones 1985; Sebring 1987). From 1982 to 1998, there was an increase in the percentage of students enrolling in higher level mathematics and science courses (National Center for Education Statistics 2000). High school graduates in 1998 were more likely than their 1982 counterparts to take more advanced mathematics courses, such as algebra II, trigonometry, precalculus, and calculus. In science, the trend is similar. High school graduates in 1998 were more likely to take chemistry II or physics II and physics I and chemistry I (National Center for Education Statistics 2000). Despite these encouraging signs, the experience is not reflected equally among racial/ethnic and income groups. In 1998, white and Asian/Pacific Islander high school graduates were usually more likely than black, Hispanic, and American Indian/Alaska Native students to complete advanced academic level mathematics and the highest level science courses (National Center for Education Statistics 2000). Students from low-income families were less likely than students from higher income families to be enrolled in a college preparatory track through which they would be more likely to take such courses (Green et al. 1995).

Research suggests that student learning is enhanced by computers when the computers are used to teach discrete skills (President’s Committee of Advisors on Science and Technology, Panel on Educational Technology 1997). Computer availability and usage are increasing in schools (Anderson and Ronnkvist 1999). In 1999, there was an average of 6 students for each computer, up from a 125 to 1 ratio in 1983 (Coley, Cradler, and Engel 1997; Williams 2000). Internet access existed at 95 percent of public schools in 1999, up from 35 percent in 1994 (Williams 2000). Internet access is likely to be used most if the computers are in instructional rooms. Over half (63 percent) of all instructional rooms (classrooms, computer or other labs, and library media centers) had access to the Internet in 1999, up from 3 percent 5 years before (Williams 2000). For schools with high concentrations of poverty (more than 70 percent eligible for free or reduced-price lunch), 39 percent of all instructional rooms had Internet access compared with 62 to 74 percent for schools with lower concentrations of poverty (Williams 2000).

Researchers have found that greater gains in student achievement occur in classes with 13 to 20 students compared with larger classes, especially for primary-grade disadvantaged and minority students (Krueger 1998; Mosteller, Light, and Sachs 1996; Robinson and Wittebols 1986). In 1998, the average public elementary school class had 23 students (Lewis et al. 1999). Large-scale efforts to reduce class size may result in negative consequences if, as was the case recently in California, large numbers of unqualified teachers are hired because there are not enough qualified teachers available to staff the smaller classes (Bohrnstedt and Stecher 1999).

Researchers have found that a positive disciplinary climate is directly linked to student learning (Barton, Coley, and Wenglinsky 1998; Bryk, Lee, and Holland 1993; Chubb and Moe 1990). Research also suggests that the most effective policies to reduce the incidence of offenses in a school vary according to the targeted behavior. To reduce serious incidents, including drug offenses, only a policy of severe punishment seems to be effective (Barton, Coley, and Wenglinsky 1998). Serious violent crime incidents occurred in 10 percent of all public schools in 1996–97 (Kaufman et al. 1999). The level of school-related criminal behavior changed little between 1976 and 1997, and no differences in victimization rates were found between white and black high school seniors in 1997 (National Center for Education Statistics 1999). However, the percentage of middle and high school students who fear attack or other bodily harm while at school has been on the rise. In each year from 1989 to 1995, a larger proportion of black and Hispanic students than white students feared attacks at school, and the percentage of black students who feared for their safety nearly doubled between 1989 and 1995 (Kaufman et al. 1999).

Students learn more in schools that emphasize high academic expectations (Bryk, Lee, and Holland 1993; Chubb and Moe 1990), and academic expectations have been on the rise (National Center for Education Statistics 1998). The percentage of public school districts with graduation requirements that meet or exceed the National Commission on Excellence in Education (NCEE) recommendations (4 years of English, 3 years of mathematics, 3 years of science, 3 years of social studies, and a half year of computer science) increased from 12 to 20 percent between 1987–88 and 1993–94 (National Center for Education Statistics 1998). A common criticism of the NCEE recommendations is that they only specify the number of courses to be taken, not their rigor. But there is evidence that increasing numbers of students have been enrolling in more difficult courses. From 1982 to 1998, there was an increase in the percentage of students enrolling in higher level mathematics and science courses (National Center for Education Statistics 2000).

School quality needs to be defined, assessed, and monitored if we are to ensure the existence of quality schools (Special Study Panel on Education Indicators 1991). This report highlights 13 indicators of school quality that recent research suggests may be related to student learning and identifies where and why more precise measures are needed. These indicators fall into three categories: the characteristics of teachers, the characteristics of classrooms, and the characteristics of schools as organizations. Research suggests that students learn more from teachers with high academic skills and teachers who teach subjects related to their undergraduate or graduate training than they do from teachers with low academic skills and teachers who teach subjects unrelated to their training. In addition, students, on average, learn more from teachers with 3 or more years of teaching experience than they do from teachers with less experience. Though the research is less conclusive regarding professional development, experts agree that participation in high-quality professional development should lead to better teaching. At the level of the classroom, research suggests that students benefit from a focused and rigorous curriculum, time spent using computers, and being in smaller classes. We still need to learn more about the relationship between pedagogy and student learning. At the school level, a school’s goals, leadership, faculty, discipline policy, and academic environment are all indicators of school quality. Student learning, however, is thought to occur primarily as a result of students’ interaction with teachers, other students, and the curriculum, and the link between learning and these factors is not firmly established for all of these indicators.

Better measures are needed to accurately monitor the status of school quality, especially for indicators of pedagogy, school leadership, goals, and professional community. Furthermore, certain important facets of professional development, course content, technology, academic environment, and discipline are missing. Finally, even when quality data are available, they lose their value if they are not appropriately defined and kept up to date. Moreover, even though experts would agree that certain indicators should show changes in student learning, there is not always concrete statistical evidence to support their supposition; improving the data collected on the dimensions of schools thought to be associated with school quality should help us better understand the relationship of these indicators to student learning.

The findings documented in this report, like all research, are time sensitive and part of an iterative process. The status of schools as identified by indicators with high-quality data is changing rapidly and will need to be continually updated. As research on school effectiveness proceeds, indicators with only poor-quality data will need to be improved to understand the complete picture of school quality as recommended by the Special Study Panel on Education Indicators for NCES.