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Schooling: Impact on Cognitive and Motivational Development
Schooling: Impact on Cognitive and Motivational Development Ulrich Trautwein, University of Tübingen, Tübingen, Germany Hanna Dumont, German Institute of International Educational Research, Berlin, Germany Anna–Lena Dicke, University of Tübingen, Tübingen, Germany Ó 2015 Elsevier Ltd. All rights reserved. This article is a revision of the previous edition article by F.E. Weinert, volume 20, pp. 13589–13594, Ó 2001, Elsevier Ltd.
Abstract How strongly does a student’s cognitive and motivational development depend on various characteristics of schooling? This article describes the origins and developing profile of the field of research on differential effects of learning environments, the current knowledge about central characteristics of schooling, persistent methodological challenges, and implications for educational practice.
How much difference does it make for math achievement if one has the best math teacher in the best school of town rather than an average teacher in a typical school? How strongly is a student’s motivation affected by the students she or he is studying with? These and similar questions are extremely important issues – for both research and practice. Millions of parents around the world think about these issues when they make decisions about their children’s school biographies, and an increasing number of researchers from several different disciplines are busy in finding adequate ways of gauging the effects of schooling. In examining “effects of schooling,” it is important to distinguish between two perspectives. When school versus no school conditions (e.g., “is there an effect of two more years of schooling on cognitive development?”) are compared, one studies ‘general’ or ‘average’ effects of schooling on cognitive or motivational development. When differences among classes, tracks, schools, school systems, and the like are studied (e.g., “how much difference does school quality make?”), the primary focus is on what we will call “differential effects of learning environments.” Learning environments such as school classes, schools, or school types function as differential learning and developmental environments “when young people – independent of, and over and above, their individual intellectual, cultural, social, and economic resources – are afforded different developmental opportunities” depending on the class, school, or school type they attend (adapted from Baumert et al., 2006, p. 99, own translation). This article focuses on the emerging field of research on differential effects of learning environments as evidenced in large-scale school achievement studies.
Schools as Differential Learning Environments: The Emergence of an Interdisciplinary Research Field The starting point of modern empirical research on the impact of schooling on children’s development is typically seen as back in the 1960s when the Coleman report (Coleman et al., 1966) was published and the International Association for the Evaluation of Educational Achievement (IEA) conducted its first study comparing the academic achievement of 13-year-olds in 12 countries (Foshay et al.,
International Encyclopedia of the Social & Behavioral Sciences, 2nd edition, Volume 21
1962). Since these pioneer studies, empirical research on the impact of schooling has increased tremendously – not only with respect to national studies, but also regarding large-scale cross-national studies: The IEA now conducts several studies with up to 60 participating education systems. The Organization for Economic Development and Cooperation (OECD) has started its own Programme for International Student Assessment (PISA) in 2000 involving more than 70 countries to date. The increasing breadth of the data base also concerns the variables under study. Whereas earlier studies on the effects of schooling (including international school achievement studies) had their main focus on students’ academic achievement, in the last two decades students’ motivational development and their engagement in learning have become a key focus of empirical studies on the impact of schooling. From its beginning, research on the effects of schooling has been a field that attracted researchers with diverse disciplinary backgrounds, and this multidisciplinary background has contributed to the richness of conceptualizations of the effects of schooling. As observed by Wang et al. (1993), researchers from different disciplines typically had a focus on different variables. For instance, sociologists were usually concerned with demographic variables such as social class as well as institutional differences between schools. Political scientists studied the impact of federal, state, and district policy variables. Psychologists typically studied individual characteristics of teachers and learners and the interactions between them. Adding to that list, pedagogical research concentrated on the aims of schooling and the design and content of curriculum. Over the last two decades, new developments can be observed with regard to the disciplinary composition of research on the effects of schooling. Additional disciplines have increased their efforts in this field, making the field more heterogeneous. Notably, economics of education has attracted much interest (e.g., Hanushek et al., 2010) and brought in a focus on efficiency and the so-called ‘returns to education’ (the monetary exchange value of education). Moreover, the field of didactics has become more important, specifically when explaining domain-specific outcomes of teaching. In addition, the construction of standardized achievement tests and decisions about research designs has increasingly been informed by psychometricians. Although currently more
http://dx.doi.org/10.1016/B978-0-08-097086-8.26056-X
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focused on learning processes rather than learning outcomes, the emerging field of ‘neuroeducation’ might also contribute to research on the effects of schooling in the future. On the one hand, these developments have added additional perspectives and methodologies to the study of the effects of schooling; on the other hand, they have helped to move toward more integrative frameworks that bring together the wisdom from various disciplines. In fact research on schooling effects (and, more broadly, effects of educational institutions) has become an interdisciplinary field in itself, to varying degrees across different countries, which brings together different streams of theorizing from disciplines such as educational research, psychology, sociology, economics, statistics, and others. In some countries, the interdisciplinary endeavor to study effects of schooling has become a separate discipline in its own right. Integrative frameworks on the effects of schooling come in different forms. The so-called Educational Effectiveness Models (Creemers, 2009; Scheerens and Bosker, 1997; Wang et al., 1993) integrate the wisdom from various disciplines by systematically collecting variables at various different analytical levels with potential effects on academic outcomes and gauge their relative effect. For instance, in the theoretical framework by Wang et al. (1993) 228 variables are grouped into six broad theoretical constructs. The six theoretical constructs used to organize the framework are (1) State and District Governance and Organization; (2) Home and Community Educational Contexts; (3) School Demographics, Culture, Climate, Policies, and Practices; (4) Design and Delivery of Curriculum and Instruction; (5) Classroom Practices; and (6) Student Characteristics. The prominent overview study by Hattie (2009) on the most important determinants of academic achievement is also rooted in this tradition. A second form of integrative frameworks describes the process of learning and development as an interplay of individual characteristics and learning environments whose form may be different across different ages, schools, and school systems (“differential learning and developmental milieu” or “schools as multilevel social organizations”; Baumert et al., 2006; Eccles and Roeser, 2011). This second form of integrative models is typically less exhaustive in terms of variables, but rich in its theoretical foundation and more specific in explaining learning processes and the development of achievement and motivation.
Effects of Schooling: Early Findings and Current Wisdom To the shock of many politicians, educators, and teachers, the influential Coleman Report (Coleman et al., 1966) concluded “that school brings little influence to bear on a child’s achievement that is independent of his background and social context” (p. 325). Along similar lines, Jencks et al. (1972) stated a few years later “that the character of schools’ output depends largely on a single input, namely, the characteristics of the entering children. Everything else – the schools’ budget, its policies, the characteristics of the teachers – is either secondary or completely irrelevant” (p. 256). The early accounts of the effects of schooling are likely to have underestimated the role of differential learning
environments for several reasons. First, reading competence was the most important outcome in the Coleman report. However, as is known by now, differential learning effects in reading are smaller than in, for instance, mathematics. Second, the sample of schools used in the Coleman report was less diverse than it could have been, and this might have led to the observation of smaller effects. It should also be noted that the understanding of what is to be considered a small/meaningful effect has changed over the years. In contrast to the earlier studies, contemporary wisdom on the effects of schooling emphasizes systematic differences in cognitive and motivational outcomes that can be traced back to differential schooling quality. At the same time, recent research clearly highlights the need to differentiate between various factors at several levels, different domains, and multiple outcomes when gauging the effects of schooling. The main findings from recent research on the impact of schooling on children’s cognitive and motivational development are summarized next.
Differential Impact of Schooling on Cognitive Development Schools are expected to teach students knowledge and skills in a number of different subjects, such as languages, mathematics, or science, which students need in later life. In recent years, both in practice as well as in research, there has been a shift in the educational objectives of schools. Whereas the focus used to be on the acquisition and reproduction of subjectspecific knowledge, students are now expected to “apply knowledge and skills in key subject areas and to analyze, reason and communicate effectively as they pose, interpret and solve problems in a variety of situations” (OECD, 2010a, p. 18). Against this backdrop, the concept of competence – similar to the concept of literacy used by the OECD and the IEA – has become prominent in studies assessing the impact of schooling on cognitive development. Competencies can be defined as context-specific cognitive dispositions for achievement which are acquired through learning and are needed to successfully cope with situations and tasks in specific domains (Klieme et al., 2008). In most studies on the impact of schooling, domain-specific competencies such as reading literacy, mathematical competence, or scientific competence are assessed. Whereas competence tests used in national studies focus more on specific school subjects and usually have higher curricular validity (therefore oftentimes called ‘academic achievement tests’), the assessment of more broadly defined key competencies such as problem-solving skills or information and communication technology (ICT) literacy in addition to subject-specific competencies is becoming increasingly important in international large-scale assessment studies. Characterized by its context specificity and its focus on ‘real life’ situations, the concept of competence is to be distinguished from general cognitive abilities such as intelligence. The concept of intelligence refers to the “relatively decontextualized ability to reason and to address new problems without contentspecific knowledge” (Baumert et al., 2009). Whereas competencies have to be acquired through learning, intelligence can be learned only to a certain extent and is usually understood as a relatively stable characteristic of a person. In that sense, intelligence can be seen as an important determinant of the
Schooling: Impact on Cognitive and Motivational Development
development of domain-specific competencies (Baumert et al., 2009; Klieme et al., 2008). Even though intelligence is, consequently, oftentimes used as a predictor or a control variable in studies investigating the impact of schooling on students’ competence development, there is evidence showing that intelligence is also affected by schooling (Becker et al., 2012; Ceci, 1991). However, in the following, we will focus on empirical studies investigating schooling effects on students’ academic competencies. How large are differences in students’ competencies across schools and school systems? When comparing different countries in cross-national studies as those conducted by the IEA or the OECD, massive effects of the quantity and quality of schooling can be ascertained, in particular when comparing developed countries with developing countries. In PISA 2009, for instance, the gap in reading literacy between the highest and the lowest performing country was 242 score points, which is the equivalent of more than 6 years of formal schooling (OECD, 2010a). Similarly, in within-country analyses, substantial differences between mean scores in the best-achieving schools and the worst-achieving schools can be observed. In addition, even when controlling for differential intake (e.g., prior achievement and social background of students), longitudinal studies document substantial differences across schools and classes in cognitive development. What aspects of schooling lead to these observable differences? In the classic review by Wang et al. (1993), “the theoretical construct with the greatest effect was Student Characteristics, followed by Classroom Practices, and Home and Community Educational Contexts. Having less effect were Design and Delivery of Curriculum and Instruction and School Demographics, Culture, Climate, Policies, and Practices, while State and District Governance and Organization had the least effect” (p. 270). This main conclusion is also echoed in more recent accounts. Drawing on Hattie’s (2009) extensive synopsis of empirical findings on what affects students’ academic achievement, which is based on over 800 metaanalyses, as well as other research reviews on what constitutes student learning (e.g., Eccles and Roeser, 2011), there is now a large consensus among educational researchers that proximal variables such as the instructional quality provided by the teacher exert a much stronger influence on students’ competencies than distal variables such as school resources. Or put differently, general characteristics of the school environment do not necessarily impact student learning, they only do so when they reach down to the classroom level and affect teachers’ instructional practices. This general result will next be illustrated with respect to three frequently discussed aspects of schooling (school resources, tracking effects, and teaching quality). School resources: One characteristic of schools, which is often subject of many debates among parents, teachers, and policy makers, is the amount of resources available. Overall, the combined effects of resources are often overestimated (Hanushek and Lindseth, 2009). Whereas few researchers would argue that money does not matter at all, its impact clearly depends on the way it is spent. For instance, if a school uses additional resources to hire qualified teachers, the positive effect that school resources can have on student outcomes is evident. On the other hand, using more resources to reduce
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class size is not by itself going to have a positive impact on student outcomes; its impact depends on the instructional quality provided. Merely reducing the number of children in a learning group does not necessarily lead to different and more effective instructional strategies of teachers (for a summary, see Hattie, 2009). Tracking/composition: Another practice in many school systems around the world is tracking, that is grouping students into different courses, study programs, or schools according to their achievement. Even though a large amount of research has been conducted on the effects of tracking on students’ achievement in recent years, few strong and definitive answers have emerged. One general conclusion, which can be drawn, is that grouping students by ability has an effect insofar as it determines the curriculum and instruction students receive and exposes them to different peers. More specifically, it has been shown that students in higher tracks may develop higher competencies than students in lower tracks because they receive a different type of instruction and curriculum. Tracking also exerts an effect on students’ competence development by determining the composition of the student body. There is strong evidence showing that being surrounded by high achieving students has a positive effect on students’ competence development. But not only the mean achievement level of a school or a class is of importance, the social and – to a lesser degree – the ethnic composition of the student body has also been shown to impact students’ learning: As the ratio of students from disadvantaged families goes up, the achievement of students goes down. These effects of the composition of the student body are again assumed to be mediated by more proximal variables, such as teachers’ practices and daily interactions between students. To that effect, the composition of the class has a greater influence than the composition of the school. Teaching quality: Generally, the instruction a teacher provides needs to be intellectually challenging and cognitively stimulating for students by paying close attention to the prior knowledge of students (Kunter et al., 2013). This may be achieved by many different practices and strategies such as cooperative learning, direct instruction, concept mapping, reciprocal teaching, or formative assessment. Whatever may be the specific strategy, close attention must be paid to the domain specificity of the competence that is to be learned. At the same time, teachers need to transport clear guidelines, communicate their expectations, and provide students with regular feedback. It is evident that this kind of instruction can be more easily given by teachers who have higher levels of teacher qualifications, more knowledge in the subject matter as well as more pedagogical content knowledge. But not only characteristics of the teachers themselves are important, there is also evidence showing that principals or school leaders may play an important role in the development of students’ competencies when they show strong instructional leadership, including a learning climate free of disruption, a system of clear teaching objectives, and high expectations for teachers and students.
Impact of Schooling on Motivational Development A positive development in motivation is seen as both a goal of schooling in itself and a strong determinant of academic
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achievement and students’ educational choices. Whereas student motivation was understood to be externally driven within the behaviorist tradition of the early twentieth century, current theorizing understands student motivation as a socialcognitive process. Student motivation is, thus, determined by students’ subjective beliefs and attitudes toward schooling, which are developed in response to their social surroundings. Motivation has more stable and more variable, that is more situation-specific, elements. Because of space restrictions, our emphasis in this article is on interindividual differences in relatively enduring motivational predispositions to engage in academic activities. Pintrich (2003) differentiated among five central motivational constructs: competence beliefs, control beliefs, interest, value, and goals. This article exemplarily focuses on two of these constructs – competence beliefs and value – which have been prevalent in motivational education research in the last few decades. Students’ self-beliefs about their own abilities, capabilities, and competencies in certain areas, such as specific subjects and tasks, do influence the strength of their engagement with these specific tasks. The higher students’ subjective expectancies to successfully engage in and master a specific situation are, the stronger their motivation will be to engage in this specific situation will be. Similarly, students’ motivation to engage within the school context is seen to depend on the extent to which the specific context matches their values, needs, and goals. In addition, the subjectively perceived usefulness of a specific task in terms of accomplishing one’s personal goals and the perceived enjoyment while performing that task is seen to increase the likelihood of students’ engagement (Eccles and Wigfield, 2002). Summarizing a huge number of studies, several characteristics of the learning environment are substantially associated with motivational development. As with achievement, classroom processes are closely associated with motivational development, whereas somewhat ‘paradoxical’ effects are found at the level of schools/tracks. Tracking/classroom composition: The composition of the student body with regard to its academic achievement levels has been found to be one important contextual influence. In particular, students’ self-beliefs about their ability are strongly affected by the achievement levels of their immediate classmates (Marsh et al., 2008). When assessing their own abilities and academic standing, students will naturally use the achievement levels of their immediate classmates as a frame of reference. Thus, equally able students have been found to report lower confidence in their academic competencies if they are attending schools with higher average levels of ability, a phenomenon that is commonly described as the big-fishlittle-pond-effect. Further research suggests that students’ valuing and enjoyment of school, e.g., their interests, might potentially be affected in a similar way. Selective schooling thus might produce negative motivational patterns for students of high ability. To fully depict the complexity of the influence of peers’ ability levels on individual student motivation, however, the type of ability tracking needs to be taken into account as well (Chmielewski et al., 2013). Teaching quality: The type of classroom environment that is created by teachers has been shown to be particularly influential to the development of student motivation. Teachers influence the development of student motivation in multiple
ways within the classroom setting: through their choice of tasks and materials, the instructional practices they employ, and the type of relationship they foster with their students (Schunk et al., 2008). With regard to the choice of tasks and materials, certain task characteristics have been identified to be beneficial for the development of student motivation. The use of surprising task features, the use of challenging tasks in combination with appropriate instructional support as well as highlighting the relevance of the educational content for students’ lives appear to positively influence students’ enjoyment, their feelings of competence, and the value they attach to school. Considering teachers’ instructional practices in the classroom, several instructional practices have been identified that promote student motivation in the classroom. On the one hand, the application of student-centered classroom practices that support students’ feeling of autonomy such as the provision of choices has been shown to increase student motivation and engagement in the classroom. Additionally, teacher practices that support students’ feelings of competence such as the provision of informative and constructive feedback that focuses on students’ individual improvement over time will increase student motivation. At the same time, teachers’ general classroom management influences student motivation. The use of proactive practices such as communicating clear expectations and rules with regard to classroom conduct has been shown to support students’ commitment and attachment of value to school. Lastly, the type of relationship that teachers foster with the students in their classroom is connected to the development of student motivation (Wentzel, 2009). The provision of an emotionally safe and trusting environment in which teachers act as role models as well as confidantes providing social support has been found to increase student commitment and valuation of school. A supportive relationship with the teacher appears to be instrumental for student motivation over and above the support that is provided by parents and peers in some circumstances. Interest differentiation: Schools are sometimes seen as a killer of student interest rather than a developer (Travers, 1978, p. 125). In fact, the trajectories for motivational dispositions such as self-concept and interest show a decline from school entrance to adolescence, and this decline might be particularly strong under some conditions. For instance, it has been suggested that the decline in student motivation from elementary to secondary schooling commonly found in national and cross-national studies is actually related to systematic changes in the classroom environment. It is assumed that the classroom environment in secondary schools fails to meet the specific developmental needs of students (Eccles et al., 1993). Students’ increase in selfawareness and their increased need for independence during adolescence appear to be mismatched with the organization of the classroom environment that is shaped by a high level of control and promotion of social comparison and competition within secondary schools. At the same time, the overall decline in self-concept and interest may also reflect agenormative developmental trends in terms of intraindividual differentiation across different subjects: Although students partly lose interest in some or the majority of their subjects, most students have stable or even increasing interests in other subjects.
Schooling: Impact on Cognitive and Motivational Development
Persisting Methodological Challenges Because of several methodological challenges, it is too early – and in fact impossible – to make final statements about the size of the effects of differential learning environments. First, it is quite obvious that the size of these effects differs across different samples; for instance, between-school differences may tend to be larger in more differentiated school systems. Moreover, the size of effects is likely to change over time as school environments and societies develop. Second, the outcome variables under study also determine the observed effects (for instance, larger effects have been found for mathematics than for reading). Third, a fundamental challenge for research on schooling effects are problems with ‘differential intake’ or ‘selection.’ In order to come to an accurate estimate of the impact of a certain aspect of schooling (such as the composition of the student body of a school) on students’ competencies, there is a need to (statistically) control for other variables affecting student outcomes, most importantly students’ family background and characteristics of students such as intelligence and their prior knowledge (Scheerens and Bosker, 1997). Unfortunately, not all empirical studies control for these variables when analyzing the impact of schooling on students’ cognitive development. Experimental and quasiexperimental intervention and reform studies are still rare. Fourth, measurement issues are relevant because the restricted reliability and validity of some achievement tests will lead to a downwardly biased estimate of schooling effects. Fifth, there are a number of challenges for data analysis including the handling of hierarchically structured data and the almost inevitable problem of missing values that have not been overcome in a satisfactory way; missing values are particularly troubling if there are differential participation rates/differential attrition across different learning environments.
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aptitude; however, research findings may not unanimously support these claims and thus challenge policy practices in providing each student with equal opportunities. A second implication of the evidence for the existence of differential learning environments is that in most school systems there is considerable room for improvement. Intervening with crucial determinants of cognitive and motivational development will likely have a positive impact. For instance, if all schools within a state became as effective as the most effective schools within this state, the average achievement in this state might increase considerably, especially if their effectiveness was quite different in the beginning. Along these lines, ways to improve the quality of schooling have been discussed in many countries, and several measures have been put in place. An influential, well-known example from the recent past is the No Child Left Behind Act of 2001 in the US which is often referred to as a highly ambitious perspective on how much improvement in educational effectiveness is possible over a short timeframe. For instance, one element of this act is the Adequate Yearly Progress (AYP) in test scores on standardized achievement tests that schools need to ‘produce’ in order to receive federal funding. However, current research does not unanimously support the optimistic view on how much progress can be achieved over a relatively short time span as formulated in this and similar reforms. Importantly, unlike less important factors such as class size and the use of tracking, the most powerful determinants of student achievement are not easily influenced by political interventions. For instance, teaching quality cannot quickly and easily be increased, but rather requires long-term efforts to increase the quality of teacher education and to attract the best candidates to the teaching profession. Moreover, research highlights the fact that – given the huge selectivity effects in school composition – even schools with below-average student achievement can be very effective schools (and therefore may not have much room to improve).
Practical Implications Future Directions How can current research findings on the effects of schooling inform educational policy and practices? First, the research findings which indicate that students’ development differs to a meaningful degree depending on the learning environment they experience highlight issues of distributional justice. Differential outcomes despite similar initial student characteristics are at odds with meritocratic principles embraced in many societies. In fact, in many countries there is the explicit goal and widespread claim that all schools are of comparable quality so that, in general, there are no – or only small – differential effects of schooling, and student development is believed to be similar across different learning environments. In a less strict variation of this approach, in some countries with a rather differentiated school system, it is claimed that although schools differ in some respects, each student is assigned to a school that offers a perfect fit for his or her strengths and needs. At first sight, differential effects of schooling are less of a normative problem in school systems in which differences in cognitive and motivational development as a consequence of differential learning environments are considered to be in line with meritocratic principles because the placement in ‘good’ schools is believed to depend on prior achievement and/or student
Whereas current research allows for a general understanding of the sources of differential cognitive and motivational development, there is a need for ambitious research programs that lead to a better understanding of schooling effects. For instance,more research is needed to understand the seemingly opposing effects of classroom composition on cognitive and motivational development. Moreover, the strength of the association between proficiency and motivation varies considerably between countries, which suggests potential differential influences of the school system on student motivation across different countries. Similarly, we have yet to better understand how student characteristics may moderate the effects of characteristics of the learning environment (i.e., there is a lack of systematic studies of aptitude–treatment interactions). In addition, there is a need for more intervention work. Intervention studies are particularly strong in terms of establishing causality and could also help in finding ways to positively impact students’ cognitive and motivational development. More generally, rather than just ‘predicting’ cognitive and motivational development, there seems to be a need for longitudinal studies with a broad theoretical background encompassing the
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Schooling: Impact on Cognitive and Motivational Development
wisdom of several disciplines in order to better understand the processes underlying cognitive and motivational development. Longitudinal studies will also help to understand the long-term impact of schooling (mediated by cognitive and motivational development) on lifelong learning, educational attainment in higher education, and active participation in society.
See also: Academic Motivation and Performance: Task Value Interventions; Affect-Regulation Motivation; Avoidance and Approach Motivation: A Brief History; Flow in Motivational Psychology; Gender and Academic Motivation; Grit; Interest, Psychology of; Leisure Activities Choices among Adolescents; Mastery Learning; Motivation, Learning, and Instruction; Passion and Motivation; School Achievement: Motivational Determinants and Processes; School Burnout and Engagement: Lessons from a Longitudinal Study in Finland; Self-Determination Theory; Self-Regulated Learning: Theories, Measures, and Outcomes; Self-Regulation in Adulthood; Temperament and Motivation; Test Anxiety and Academic Achievement.
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Abstract How strongly does a student’s cognitive and motivational development depend on various characteristics of schooling? This article describes the origins and developing profile of the field of research on differential effects of learning environments, the current knowledge about central characteristics of schooling, persistent methodological challenges, and implications for educational practice.
How much difference does it make for math achievement if one has the best math teacher in the best school of town rather than an average teacher in a typical school? How strongly is a student’s motivation affected by the students she or he is studying with? These and similar questions are extremely important issues – for both research and practice. Millions of parents around the world think about these issues when they make decisions about their children’s school biographies, and an increasing number of researchers from several different disciplines are busy in finding adequate ways of gauging the effects of schooling. In examining “effects of schooling,” it is important to distinguish between two perspectives. When school versus no school conditions (e.g., “is there an effect of two more years of schooling on cognitive development?”) are compared, one studies ‘general’ or ‘average’ effects of schooling on cognitive or motivational development. When differences among classes, tracks, schools, school systems, and the like are studied (e.g., “how much difference does school quality make?”), the primary focus is on what we will call “differential effects of learning environments.” Learning environments such as school classes, schools, or school types function as differential learning and developmental environments “when young people – independent of, and over and above, their individual intellectual, cultural, social, and economic resources – are afforded different developmental opportunities” depending on the class, school, or school type they attend (adapted from Baumert et al., 2006, p. 99, own translation). This article focuses on the emerging field of research on differential effects of learning environments as evidenced in large-scale school achievement studies.
Schools as Differential Learning Environments: The Emergence of an Interdisciplinary Research Field The starting point of modern empirical research on the impact of schooling on children’s development is typically seen as back in the 1960s when the Coleman report (Coleman et al., 1966) was published and the International Association for the Evaluation of Educational Achievement (IEA) conducted its first study comparing the academic achievement of 13-year-olds in 12 countries (Foshay et al.,
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1962). Since these pioneer studies, empirical research on the impact of schooling has increased tremendously – not only with respect to national studies, but also regarding large-scale cross-national studies: The IEA now conducts several studies with up to 60 participating education systems. The Organization for Economic Development and Cooperation (OECD) has started its own Programme for International Student Assessment (PISA) in 2000 involving more than 70 countries to date. The increasing breadth of the data base also concerns the variables under study. Whereas earlier studies on the effects of schooling (including international school achievement studies) had their main focus on students’ academic achievement, in the last two decades students’ motivational development and their engagement in learning have become a key focus of empirical studies on the impact of schooling. From its beginning, research on the effects of schooling has been a field that attracted researchers with diverse disciplinary backgrounds, and this multidisciplinary background has contributed to the richness of conceptualizations of the effects of schooling. As observed by Wang et al. (1993), researchers from different disciplines typically had a focus on different variables. For instance, sociologists were usually concerned with demographic variables such as social class as well as institutional differences between schools. Political scientists studied the impact of federal, state, and district policy variables. Psychologists typically studied individual characteristics of teachers and learners and the interactions between them. Adding to that list, pedagogical research concentrated on the aims of schooling and the design and content of curriculum. Over the last two decades, new developments can be observed with regard to the disciplinary composition of research on the effects of schooling. Additional disciplines have increased their efforts in this field, making the field more heterogeneous. Notably, economics of education has attracted much interest (e.g., Hanushek et al., 2010) and brought in a focus on efficiency and the so-called ‘returns to education’ (the monetary exchange value of education). Moreover, the field of didactics has become more important, specifically when explaining domain-specific outcomes of teaching. In addition, the construction of standardized achievement tests and decisions about research designs has increasingly been informed by psychometricians. Although currently more
http://dx.doi.org/10.1016/B978-0-08-097086-8.26056-X
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focused on learning processes rather than learning outcomes, the emerging field of ‘neuroeducation’ might also contribute to research on the effects of schooling in the future. On the one hand, these developments have added additional perspectives and methodologies to the study of the effects of schooling; on the other hand, they have helped to move toward more integrative frameworks that bring together the wisdom from various disciplines. In fact research on schooling effects (and, more broadly, effects of educational institutions) has become an interdisciplinary field in itself, to varying degrees across different countries, which brings together different streams of theorizing from disciplines such as educational research, psychology, sociology, economics, statistics, and others. In some countries, the interdisciplinary endeavor to study effects of schooling has become a separate discipline in its own right. Integrative frameworks on the effects of schooling come in different forms. The so-called Educational Effectiveness Models (Creemers, 2009; Scheerens and Bosker, 1997; Wang et al., 1993) integrate the wisdom from various disciplines by systematically collecting variables at various different analytical levels with potential effects on academic outcomes and gauge their relative effect. For instance, in the theoretical framework by Wang et al. (1993) 228 variables are grouped into six broad theoretical constructs. The six theoretical constructs used to organize the framework are (1) State and District Governance and Organization; (2) Home and Community Educational Contexts; (3) School Demographics, Culture, Climate, Policies, and Practices; (4) Design and Delivery of Curriculum and Instruction; (5) Classroom Practices; and (6) Student Characteristics. The prominent overview study by Hattie (2009) on the most important determinants of academic achievement is also rooted in this tradition. A second form of integrative frameworks describes the process of learning and development as an interplay of individual characteristics and learning environments whose form may be different across different ages, schools, and school systems (“differential learning and developmental milieu” or “schools as multilevel social organizations”; Baumert et al., 2006; Eccles and Roeser, 2011). This second form of integrative models is typically less exhaustive in terms of variables, but rich in its theoretical foundation and more specific in explaining learning processes and the development of achievement and motivation.
Effects of Schooling: Early Findings and Current Wisdom To the shock of many politicians, educators, and teachers, the influential Coleman Report (Coleman et al., 1966) concluded “that school brings little influence to bear on a child’s achievement that is independent of his background and social context” (p. 325). Along similar lines, Jencks et al. (1972) stated a few years later “that the character of schools’ output depends largely on a single input, namely, the characteristics of the entering children. Everything else – the schools’ budget, its policies, the characteristics of the teachers – is either secondary or completely irrelevant” (p. 256). The early accounts of the effects of schooling are likely to have underestimated the role of differential learning
environments for several reasons. First, reading competence was the most important outcome in the Coleman report. However, as is known by now, differential learning effects in reading are smaller than in, for instance, mathematics. Second, the sample of schools used in the Coleman report was less diverse than it could have been, and this might have led to the observation of smaller effects. It should also be noted that the understanding of what is to be considered a small/meaningful effect has changed over the years. In contrast to the earlier studies, contemporary wisdom on the effects of schooling emphasizes systematic differences in cognitive and motivational outcomes that can be traced back to differential schooling quality. At the same time, recent research clearly highlights the need to differentiate between various factors at several levels, different domains, and multiple outcomes when gauging the effects of schooling. The main findings from recent research on the impact of schooling on children’s cognitive and motivational development are summarized next.
Differential Impact of Schooling on Cognitive Development Schools are expected to teach students knowledge and skills in a number of different subjects, such as languages, mathematics, or science, which students need in later life. In recent years, both in practice as well as in research, there has been a shift in the educational objectives of schools. Whereas the focus used to be on the acquisition and reproduction of subjectspecific knowledge, students are now expected to “apply knowledge and skills in key subject areas and to analyze, reason and communicate effectively as they pose, interpret and solve problems in a variety of situations” (OECD, 2010a, p. 18). Against this backdrop, the concept of competence – similar to the concept of literacy used by the OECD and the IEA – has become prominent in studies assessing the impact of schooling on cognitive development. Competencies can be defined as context-specific cognitive dispositions for achievement which are acquired through learning and are needed to successfully cope with situations and tasks in specific domains (Klieme et al., 2008). In most studies on the impact of schooling, domain-specific competencies such as reading literacy, mathematical competence, or scientific competence are assessed. Whereas competence tests used in national studies focus more on specific school subjects and usually have higher curricular validity (therefore oftentimes called ‘academic achievement tests’), the assessment of more broadly defined key competencies such as problem-solving skills or information and communication technology (ICT) literacy in addition to subject-specific competencies is becoming increasingly important in international large-scale assessment studies. Characterized by its context specificity and its focus on ‘real life’ situations, the concept of competence is to be distinguished from general cognitive abilities such as intelligence. The concept of intelligence refers to the “relatively decontextualized ability to reason and to address new problems without contentspecific knowledge” (Baumert et al., 2009). Whereas competencies have to be acquired through learning, intelligence can be learned only to a certain extent and is usually understood as a relatively stable characteristic of a person. In that sense, intelligence can be seen as an important determinant of the
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development of domain-specific competencies (Baumert et al., 2009; Klieme et al., 2008). Even though intelligence is, consequently, oftentimes used as a predictor or a control variable in studies investigating the impact of schooling on students’ competence development, there is evidence showing that intelligence is also affected by schooling (Becker et al., 2012; Ceci, 1991). However, in the following, we will focus on empirical studies investigating schooling effects on students’ academic competencies. How large are differences in students’ competencies across schools and school systems? When comparing different countries in cross-national studies as those conducted by the IEA or the OECD, massive effects of the quantity and quality of schooling can be ascertained, in particular when comparing developed countries with developing countries. In PISA 2009, for instance, the gap in reading literacy between the highest and the lowest performing country was 242 score points, which is the equivalent of more than 6 years of formal schooling (OECD, 2010a). Similarly, in within-country analyses, substantial differences between mean scores in the best-achieving schools and the worst-achieving schools can be observed. In addition, even when controlling for differential intake (e.g., prior achievement and social background of students), longitudinal studies document substantial differences across schools and classes in cognitive development. What aspects of schooling lead to these observable differences? In the classic review by Wang et al. (1993), “the theoretical construct with the greatest effect was Student Characteristics, followed by Classroom Practices, and Home and Community Educational Contexts. Having less effect were Design and Delivery of Curriculum and Instruction and School Demographics, Culture, Climate, Policies, and Practices, while State and District Governance and Organization had the least effect” (p. 270). This main conclusion is also echoed in more recent accounts. Drawing on Hattie’s (2009) extensive synopsis of empirical findings on what affects students’ academic achievement, which is based on over 800 metaanalyses, as well as other research reviews on what constitutes student learning (e.g., Eccles and Roeser, 2011), there is now a large consensus among educational researchers that proximal variables such as the instructional quality provided by the teacher exert a much stronger influence on students’ competencies than distal variables such as school resources. Or put differently, general characteristics of the school environment do not necessarily impact student learning, they only do so when they reach down to the classroom level and affect teachers’ instructional practices. This general result will next be illustrated with respect to three frequently discussed aspects of schooling (school resources, tracking effects, and teaching quality). School resources: One characteristic of schools, which is often subject of many debates among parents, teachers, and policy makers, is the amount of resources available. Overall, the combined effects of resources are often overestimated (Hanushek and Lindseth, 2009). Whereas few researchers would argue that money does not matter at all, its impact clearly depends on the way it is spent. For instance, if a school uses additional resources to hire qualified teachers, the positive effect that school resources can have on student outcomes is evident. On the other hand, using more resources to reduce
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class size is not by itself going to have a positive impact on student outcomes; its impact depends on the instructional quality provided. Merely reducing the number of children in a learning group does not necessarily lead to different and more effective instructional strategies of teachers (for a summary, see Hattie, 2009). Tracking/composition: Another practice in many school systems around the world is tracking, that is grouping students into different courses, study programs, or schools according to their achievement. Even though a large amount of research has been conducted on the effects of tracking on students’ achievement in recent years, few strong and definitive answers have emerged. One general conclusion, which can be drawn, is that grouping students by ability has an effect insofar as it determines the curriculum and instruction students receive and exposes them to different peers. More specifically, it has been shown that students in higher tracks may develop higher competencies than students in lower tracks because they receive a different type of instruction and curriculum. Tracking also exerts an effect on students’ competence development by determining the composition of the student body. There is strong evidence showing that being surrounded by high achieving students has a positive effect on students’ competence development. But not only the mean achievement level of a school or a class is of importance, the social and – to a lesser degree – the ethnic composition of the student body has also been shown to impact students’ learning: As the ratio of students from disadvantaged families goes up, the achievement of students goes down. These effects of the composition of the student body are again assumed to be mediated by more proximal variables, such as teachers’ practices and daily interactions between students. To that effect, the composition of the class has a greater influence than the composition of the school. Teaching quality: Generally, the instruction a teacher provides needs to be intellectually challenging and cognitively stimulating for students by paying close attention to the prior knowledge of students (Kunter et al., 2013). This may be achieved by many different practices and strategies such as cooperative learning, direct instruction, concept mapping, reciprocal teaching, or formative assessment. Whatever may be the specific strategy, close attention must be paid to the domain specificity of the competence that is to be learned. At the same time, teachers need to transport clear guidelines, communicate their expectations, and provide students with regular feedback. It is evident that this kind of instruction can be more easily given by teachers who have higher levels of teacher qualifications, more knowledge in the subject matter as well as more pedagogical content knowledge. But not only characteristics of the teachers themselves are important, there is also evidence showing that principals or school leaders may play an important role in the development of students’ competencies when they show strong instructional leadership, including a learning climate free of disruption, a system of clear teaching objectives, and high expectations for teachers and students.
Impact of Schooling on Motivational Development A positive development in motivation is seen as both a goal of schooling in itself and a strong determinant of academic
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achievement and students’ educational choices. Whereas student motivation was understood to be externally driven within the behaviorist tradition of the early twentieth century, current theorizing understands student motivation as a socialcognitive process. Student motivation is, thus, determined by students’ subjective beliefs and attitudes toward schooling, which are developed in response to their social surroundings. Motivation has more stable and more variable, that is more situation-specific, elements. Because of space restrictions, our emphasis in this article is on interindividual differences in relatively enduring motivational predispositions to engage in academic activities. Pintrich (2003) differentiated among five central motivational constructs: competence beliefs, control beliefs, interest, value, and goals. This article exemplarily focuses on two of these constructs – competence beliefs and value – which have been prevalent in motivational education research in the last few decades. Students’ self-beliefs about their own abilities, capabilities, and competencies in certain areas, such as specific subjects and tasks, do influence the strength of their engagement with these specific tasks. The higher students’ subjective expectancies to successfully engage in and master a specific situation are, the stronger their motivation will be to engage in this specific situation will be. Similarly, students’ motivation to engage within the school context is seen to depend on the extent to which the specific context matches their values, needs, and goals. In addition, the subjectively perceived usefulness of a specific task in terms of accomplishing one’s personal goals and the perceived enjoyment while performing that task is seen to increase the likelihood of students’ engagement (Eccles and Wigfield, 2002). Summarizing a huge number of studies, several characteristics of the learning environment are substantially associated with motivational development. As with achievement, classroom processes are closely associated with motivational development, whereas somewhat ‘paradoxical’ effects are found at the level of schools/tracks. Tracking/classroom composition: The composition of the student body with regard to its academic achievement levels has been found to be one important contextual influence. In particular, students’ self-beliefs about their ability are strongly affected by the achievement levels of their immediate classmates (Marsh et al., 2008). When assessing their own abilities and academic standing, students will naturally use the achievement levels of their immediate classmates as a frame of reference. Thus, equally able students have been found to report lower confidence in their academic competencies if they are attending schools with higher average levels of ability, a phenomenon that is commonly described as the big-fishlittle-pond-effect. Further research suggests that students’ valuing and enjoyment of school, e.g., their interests, might potentially be affected in a similar way. Selective schooling thus might produce negative motivational patterns for students of high ability. To fully depict the complexity of the influence of peers’ ability levels on individual student motivation, however, the type of ability tracking needs to be taken into account as well (Chmielewski et al., 2013). Teaching quality: The type of classroom environment that is created by teachers has been shown to be particularly influential to the development of student motivation. Teachers influence the development of student motivation in multiple
ways within the classroom setting: through their choice of tasks and materials, the instructional practices they employ, and the type of relationship they foster with their students (Schunk et al., 2008). With regard to the choice of tasks and materials, certain task characteristics have been identified to be beneficial for the development of student motivation. The use of surprising task features, the use of challenging tasks in combination with appropriate instructional support as well as highlighting the relevance of the educational content for students’ lives appear to positively influence students’ enjoyment, their feelings of competence, and the value they attach to school. Considering teachers’ instructional practices in the classroom, several instructional practices have been identified that promote student motivation in the classroom. On the one hand, the application of student-centered classroom practices that support students’ feeling of autonomy such as the provision of choices has been shown to increase student motivation and engagement in the classroom. Additionally, teacher practices that support students’ feelings of competence such as the provision of informative and constructive feedback that focuses on students’ individual improvement over time will increase student motivation. At the same time, teachers’ general classroom management influences student motivation. The use of proactive practices such as communicating clear expectations and rules with regard to classroom conduct has been shown to support students’ commitment and attachment of value to school. Lastly, the type of relationship that teachers foster with the students in their classroom is connected to the development of student motivation (Wentzel, 2009). The provision of an emotionally safe and trusting environment in which teachers act as role models as well as confidantes providing social support has been found to increase student commitment and valuation of school. A supportive relationship with the teacher appears to be instrumental for student motivation over and above the support that is provided by parents and peers in some circumstances. Interest differentiation: Schools are sometimes seen as a killer of student interest rather than a developer (Travers, 1978, p. 125). In fact, the trajectories for motivational dispositions such as self-concept and interest show a decline from school entrance to adolescence, and this decline might be particularly strong under some conditions. For instance, it has been suggested that the decline in student motivation from elementary to secondary schooling commonly found in national and cross-national studies is actually related to systematic changes in the classroom environment. It is assumed that the classroom environment in secondary schools fails to meet the specific developmental needs of students (Eccles et al., 1993). Students’ increase in selfawareness and their increased need for independence during adolescence appear to be mismatched with the organization of the classroom environment that is shaped by a high level of control and promotion of social comparison and competition within secondary schools. At the same time, the overall decline in self-concept and interest may also reflect agenormative developmental trends in terms of intraindividual differentiation across different subjects: Although students partly lose interest in some or the majority of their subjects, most students have stable or even increasing interests in other subjects.
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Persisting Methodological Challenges Because of several methodological challenges, it is too early – and in fact impossible – to make final statements about the size of the effects of differential learning environments. First, it is quite obvious that the size of these effects differs across different samples; for instance, between-school differences may tend to be larger in more differentiated school systems. Moreover, the size of effects is likely to change over time as school environments and societies develop. Second, the outcome variables under study also determine the observed effects (for instance, larger effects have been found for mathematics than for reading). Third, a fundamental challenge for research on schooling effects are problems with ‘differential intake’ or ‘selection.’ In order to come to an accurate estimate of the impact of a certain aspect of schooling (such as the composition of the student body of a school) on students’ competencies, there is a need to (statistically) control for other variables affecting student outcomes, most importantly students’ family background and characteristics of students such as intelligence and their prior knowledge (Scheerens and Bosker, 1997). Unfortunately, not all empirical studies control for these variables when analyzing the impact of schooling on students’ cognitive development. Experimental and quasiexperimental intervention and reform studies are still rare. Fourth, measurement issues are relevant because the restricted reliability and validity of some achievement tests will lead to a downwardly biased estimate of schooling effects. Fifth, there are a number of challenges for data analysis including the handling of hierarchically structured data and the almost inevitable problem of missing values that have not been overcome in a satisfactory way; missing values are particularly troubling if there are differential participation rates/differential attrition across different learning environments.
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aptitude; however, research findings may not unanimously support these claims and thus challenge policy practices in providing each student with equal opportunities. A second implication of the evidence for the existence of differential learning environments is that in most school systems there is considerable room for improvement. Intervening with crucial determinants of cognitive and motivational development will likely have a positive impact. For instance, if all schools within a state became as effective as the most effective schools within this state, the average achievement in this state might increase considerably, especially if their effectiveness was quite different in the beginning. Along these lines, ways to improve the quality of schooling have been discussed in many countries, and several measures have been put in place. An influential, well-known example from the recent past is the No Child Left Behind Act of 2001 in the US which is often referred to as a highly ambitious perspective on how much improvement in educational effectiveness is possible over a short timeframe. For instance, one element of this act is the Adequate Yearly Progress (AYP) in test scores on standardized achievement tests that schools need to ‘produce’ in order to receive federal funding. However, current research does not unanimously support the optimistic view on how much progress can be achieved over a relatively short time span as formulated in this and similar reforms. Importantly, unlike less important factors such as class size and the use of tracking, the most powerful determinants of student achievement are not easily influenced by political interventions. For instance, teaching quality cannot quickly and easily be increased, but rather requires long-term efforts to increase the quality of teacher education and to attract the best candidates to the teaching profession. Moreover, research highlights the fact that – given the huge selectivity effects in school composition – even schools with below-average student achievement can be very effective schools (and therefore may not have much room to improve).
Practical Implications Future Directions How can current research findings on the effects of schooling inform educational policy and practices? First, the research findings which indicate that students’ development differs to a meaningful degree depending on the learning environment they experience highlight issues of distributional justice. Differential outcomes despite similar initial student characteristics are at odds with meritocratic principles embraced in many societies. In fact, in many countries there is the explicit goal and widespread claim that all schools are of comparable quality so that, in general, there are no – or only small – differential effects of schooling, and student development is believed to be similar across different learning environments. In a less strict variation of this approach, in some countries with a rather differentiated school system, it is claimed that although schools differ in some respects, each student is assigned to a school that offers a perfect fit for his or her strengths and needs. At first sight, differential effects of schooling are less of a normative problem in school systems in which differences in cognitive and motivational development as a consequence of differential learning environments are considered to be in line with meritocratic principles because the placement in ‘good’ schools is believed to depend on prior achievement and/or student
Whereas current research allows for a general understanding of the sources of differential cognitive and motivational development, there is a need for ambitious research programs that lead to a better understanding of schooling effects. For instance,more research is needed to understand the seemingly opposing effects of classroom composition on cognitive and motivational development. Moreover, the strength of the association between proficiency and motivation varies considerably between countries, which suggests potential differential influences of the school system on student motivation across different countries. Similarly, we have yet to better understand how student characteristics may moderate the effects of characteristics of the learning environment (i.e., there is a lack of systematic studies of aptitude–treatment interactions). In addition, there is a need for more intervention work. Intervention studies are particularly strong in terms of establishing causality and could also help in finding ways to positively impact students’ cognitive and motivational development. More generally, rather than just ‘predicting’ cognitive and motivational development, there seems to be a need for longitudinal studies with a broad theoretical background encompassing the
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wisdom of several disciplines in order to better understand the processes underlying cognitive and motivational development. Longitudinal studies will also help to understand the long-term impact of schooling (mediated by cognitive and motivational development) on lifelong learning, educational attainment in higher education, and active participation in society.
See also: Academic Motivation and Performance: Task Value Interventions; Affect-Regulation Motivation; Avoidance and Approach Motivation: A Brief History; Flow in Motivational Psychology; Gender and Academic Motivation; Grit; Interest, Psychology of; Leisure Activities Choices among Adolescents; Mastery Learning; Motivation, Learning, and Instruction; Passion and Motivation; School Achievement: Motivational Determinants and Processes; School Burnout and Engagement: Lessons from a Longitudinal Study in Finland; Self-Determination Theory; Self-Regulated Learning: Theories, Measures, and Outcomes; Self-Regulation in Adulthood; Temperament and Motivation; Test Anxiety and Academic Achievement.
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