- Email: [email protected]
Forty years of measuring quality with the Environment Rating Scales
Early Childhood Research Quarterly 51 (2020) 164–166
Contents lists available at ScienceDirect
Early Childhood Research Quarterly
Forty years of measuring quality with the Environment Rating Scales Richard M. Clifford a,∗ , Noreen Yazejian a , Debby Cryer b , Thelma Harms b a b
University of North Carolina at Chapel Hill, United States Environment Rating Scales Institute, Inc., United States
a r t i c l e
i n f o
Article history: Received 23 July 2019 Accepted 27 August 2019 Keywords: Early education Child care Quality Measurement
a b s t r a c t Early childhood classroom quality can be viewed from multiple perspectives—including parents, teachers, administrators, researchers, policymakers, and politicians. From the beginning of our work in the 1970s, we have defined and measured the quality of early learning environments with the Environment Rating Scales (ERS) from the perspective of the children in those environments. As quality definitions and measurement have changed through the decades since then, we have retained a focus on children’s perspectives and have continued to revise the ERS to better capture aspects of caregiver–child interactions and particularly language interactions as research has shown these to be particularly important for children’s development. We have maintained our view of the centrality of children’s needs across a wide range of developmental and personal health and safety domains so that teachers, directors, homebased providers, technical assistance personnel, policymakers, researchers, and others interested in high quality programming have tools to guide their work. © 2019 Elsevier Inc. All rights reserved.
Quality in early childhood classrooms can be measured and viewed from a variety of perspectives. What do parents most want? What do teachers want? How about administrators? Or kindergarten teachers? Then, there are researchers, policymakers and politicians. From the very beginning of our work in the mid-1970s, we chose to look at learning environments from the perspective of the children who are spending a large proportion of their lives – more than 50% of their waking time for some – in these environments. From the perspective of a child, important questions about quality include the following:
• • • •
Is this a safe place for me? Am I getting a healthy and nourishing experience? Is the environment stimulating for me cognitively? Do I have opportunities to develop healthy relationships with other children and with adults? • Am I being provided with enough guidance and freedom to help me become an independent and self-sufficient individual?
∗ Corresponding author at: Research Scientist Emeritus, 750 Weaver Dairy Rd. Apt 178, Chapel Hill, NC 27514, United States. E-mail addresses: [email protected], [email protected] (R.M. Clifford). https://doi.org/10.1016/j.ecresq.2019.08.006 0885-2006/© 2019 Elsevier Inc. All rights reserved.
• Am I exposed to a wide range of ideas, ways of thinking, approaches to problem solving and to a diverse world and people? From this point of view, teachers/caregivers and children work together and respect one another, in turn teaching and learning together. There are millions upon millions of teaching and learning opportunities in early childhood programs. We can look at only a tiny fraction of these opportunities to estimate the degree to which they together create a healthy environment for our children. In our own work with the Environment Rating Scales (ERS), we have used a 1–7 point Likert-type scoring approach ranging from inadequate to excellent, anchored by sets of descriptors (indicators) along the scale to judge levels of quality. We do not expect any classroom to perfectly meet all of the 400–500 indicators in a given scale. Teachers and administrators must use their deep understanding of the children in their programs and the resources available to them to make good choices. Vygotsky (1978) argues that learning takes place with a crisis of some type. That is, children have to move out of their comfort zone, but not so far as to be overwhelmed. Children need some exposure to risk in order to test their limits. So for teachers, choices are often in conflict with one another. Sometimes it is in the best interests of children for a caregiver to be a little lax on handwashing hygiene in order to provide the needed social and emotional support to infants and toddlers. One of us (Cryer) has a favorite saying from her experience as a program director. She says
R.M. Clifford et al. / Early Childhood Research Quarterly 51 (2020) 164–166
“I had to learn to take my ones (meaning a score of inadequate) on some indicators of quality to achieve what was best in the big picture for the children in my program.” So, to us, quality should always be judged from the perspective of the children in the environment. Are we giving them the opportunities and help to be safe and secure, healthy, knowledgeable about the world and their own capabilities, to be able to learn throughout life, to be ethical and caring and to enjoy life? It is a tough order to figure out if our programs and teachers are doing all these things. We have worked on these measurement issues for most of our lives and still are learning how to do it. When we first started this work in the 1970s and 1980s, women were entering the workforce in great numbers, and thus early care and education was viewed primarily as a basic employment support for young families and only as secondarily as a place for cognitive and social learning. Our first instrument was essentially a checklist for county child care coordinators as they sought to improve child care in their communities. We were trying to provide guidance on aspects of the classroom environment to look for as indicators of quality. We soon expanded the checklist into the 7point scale that is familiar today. The availability of process quality tools during the 1980s (ours was not the only one, but was the one most widely used) propelled the study of early education program quality forward during this time. The major study to come out of this decade was the National Child Care Staffing Study (Whitebook, Howes, & Phillips, 1989), which found that teacher wages were the strongest predictor of structural and process (global) quality. That study also highlighted associations between higher quality programming and lower teacher turnover as well as between quality and auspice — with nonprofit centers generally rated as higher quality. By the 1990s, researchers were using broad theoretical perspectives (e.g., Bronfenbrenner & Morris, 2006) to examine children’s outcomes. It was recognized that quality of early care settings as measured with tools like the ERS was one aspect of microsystems in which children develop, and that systems beyond these settings also exerted influence. The Cost, Quality, and Outcomes Study (CQO Study Team, 1995); Study of Early Child Care and Youth Development (e.g., NICHD ECCRN, 2000); and federal Head Start studies, including the Head Start Family and Child Experiences Study (Moiduddin, Aikens, Tarullo, West, & Xue, 2012); consortium of Head Start Quality Research Centers (1995–2000, 2001–2006; e.g., Dickinson & Sprague, 2001), and the Early Head Start Research and Evaluation Project (1996 to present; e.g., Love, Chazan-Cohen, Raikes, & Brooks-Gunn, 2013) all found evidence of links between quality and child outcomes. In the 2000s, the evidence of the previous decades of research was used to support the development of statewide Quality Rating and Improvement Systems (QRISs), program and accreditation standards. But much more research is needed to understand how best to set benchmarks, measure and monitor programs to ensure the best outcomes for children and families. Toward the end of this decade and into the next, the field also saw additional tools developed to measure more discrete aspects of children’s experiences. For example, the Classroom Assessment Scoring System Pre-K (Pianta, La Paro, & Hamre, 2008) focuses on teacher–child interactions; the LENA focuses on the language environment and specifically numbers of words and conversational turns in children’s environments; and the Quality of Caregiver–Child Interactions for Infants and Toddlers (Q-CCIIT; Atkins-Burnett et al., 2015) examines the interactional and language environments for children under age 3. Throughout these decades we continued to revise the ERS to better capture aspects of caregiver–child interactions and particularly language interactions as research has shown these to be particularly important for children’s cognitive development. With
165
these revisions, we have not abandoned the centrality of the children’s developmental needs in the measurement of quality nor the view that global quality – including aspects of health/safety, activities, and language/interactions – is important in understanding the multiple facets of environments that influence children. Going forward, we hope to continue to revisit and revise our measures to best capture those aspects of the environment that are important for optimizing children’s development so that teachers, directors, home-based providers, technical assistance personnel, policymakers, researchers, and others interested in high quality programming have tools to guide their work. Two recent meta-analyses of the older versions of ERS for preschool classrooms (Brunsek et al., 2017; Ulferts, Wolf and Anders (2019) found significant but weak associations between quality and child outcomes, with Ulferts, et al. finding that the effects last over children’s school career. The newer versions, as noted above, attempt to better capture aspects of caregiver–child interactions and particularly language interactions to strengthen associations with outcomes. There are measurement limits to our ability to achieve our goals related to predictive validity. First, measures of child outcomes in the early years are only moderately associated with achievement and well-being in later life (Duncan et al., 2007; Jones, Greenberg, & Crowley, 2015). New and more predictive instruments are needed to further our understanding of the influences of early learning environments, including measures of biological processes (Granger & Kivlighan, 2003; Shonkoff, 2010). Second, our analytic and statistical tools are only roughly able to control for the many other influences on outcomes beyond the classroom and program domains (NICHD ECCRN, 2002). Third, we lack adequate theory testing and replication. A cornerstone of scientific study is replication of findings, yet there are few incentives in our field for doing such work. Replication is particularly significant since most of us as researchers have some form of conflict of interest in our studies and because multiple replications are needed to identify true effects (Maxwell, Lau, & Howard, 2015). As researchers, we each have our own special interests in understanding how environments affect various aspects of children’s development. This means our work can, as a whole, develop a more thorough understanding of the child-environment interaction that leads to successful and well-adjusted adults. We are fortunate to live in a time in history that is seeing new forms of families and roles of parents in rearing their children, with resulting new roles for our institutions in supporting those families as we transmit our culture and knowledge to the next generation.
References Atkins-Burnett, S., Monahan, S., Tarullo, L., Xue, Y., Cavadel, E., Malone, L., et al. (2015). Measuring the quality of caregiver–child interactions for infants and toddlers (Q-CCIIT). OPRE report 2015-13. Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner (Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human development (6th ed., pp. 793–828). New York: Wiley. Brunsek, A., Perlman, M., Falenchuk, O., McMullen, E., Fletcher, B., & Shah, P. S. (2017). The relationship between the Early Childhood Environment Rating Scale and its revised form and child outcomes: A systematic review and meta-analysis. PLoS One, 12, e0178512 http://dx.doi.org/10.1371/journal.pone. 0178512 CQO Study Team. (1995). Cost, quality, and child outcomes in child care centers [Technical report]. Denver: Department of Economics, Center for Research in Economic and Social Policy, University of Colorado at Denver. Dickinson, D. K., & Sprague, K. (2001). The nature and impact of early childhood care environments on the language and early literacy development of children from low-income families. In D. K. Dickinson, & S. Neuman (Eds.), Handbook of research on early literacy. New York: Guilford Press. Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., et al. (2007). School readiness and later achievement. Developmental Psychology, 43, 1428–1446. http://dx.doi.org/10.1037/0012-1649.43.6.1428
166
R.M. Clifford et al. / Early Childhood Research Quarterly 51 (2020) 164–166
Granger, D. A., & Kivlighan, K. T. (2003). Integrating biological, behavioral, and social levels of analysis in early child development: Progress, problems, and prospects. Child Development, 74, 1058–1063. http://dx.doi.org/10.1111/14678624.00590 Jones, D. E., Greenberg, M., & Crowley, M. (2015). Early social-emotional functioning and public health: The relationship between kindergarten social competence and future wellness. American Journal of Public Health, 105, 2283–2290. http://dx.doi.org/10.2105/AJPH.2015.302630 Love, J. M., Chazan-Cohen, R., Raikes, H. A., & Brooks-Gunn, J. (2013). What makes a difference: Early Head Start evaluation findings in a developmental context. Monographs of the Society for Research in Child Development, 78(1), vii–viii, 1–173. Maxwell, S. E., Lau, M. Y., & Howard, G. S. (2015). Is psychology suffering from a replication crisis? What does “failure to replicate” really mean? American Psychologist, 70, 487–498. http://dx.doi.org/10.1037/a0039400 Moiduddin, E., Aikens, N., Tarullo, L., West, J., & Xue, Y. (2012). Child Outcomes and Classroom Quality in FACES 2009. In OPRE Report 2012-37a. Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services.
NICHD Early Child Care Research Network. (2000). The relation of child care to cognitive and language development. Child Development, 71(4), 960–980. NICHD Early Child Care Research Network. (2002). Early child care and children’s development prior to school entry: Results from the NICHD Study of Early Child Care. American Educational Research Journal, 39, 133–164. http://dx.doi. org/10.3102/00028312039001133 Pianta, R. C., La Paro, K. M., & Hamre, B. K. (2008). Classroom assessment scoring system (CLASS) manual, pre-K. Baltimore, MD: Brookes Publishing. Ulferts, H., Wolf, K. M., & Anders, Y. (2019). Impact of process quality in early childhood education and care on academic outcomes: Longitudinal meta-analysis. Child Development, 90, 1474–1489. http://dx.doi.org/10.1111/ cdev.13296 Shonkoff, J. P. (2010). Building a new biodevelopmental framework to guide the future of early childhood policy. Child Development, 81, 357–367. http://dx.doi. org/10.1111/j.1467-8624.2009.01399.x Vygotsky, L. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press. Whitebook, M., Howes, C., & Phillips, D. (1989). Who cares? Child care teachers and the quality of care in America. Oakland, CA: Child Care Employee Project.
Contents lists available at ScienceDirect
Early Childhood Research Quarterly
Forty years of measuring quality with the Environment Rating Scales Richard M. Clifford a,∗ , Noreen Yazejian a , Debby Cryer b , Thelma Harms b a b
University of North Carolina at Chapel Hill, United States Environment Rating Scales Institute, Inc., United States
a r t i c l e
i n f o
Article history: Received 23 July 2019 Accepted 27 August 2019 Keywords: Early education Child care Quality Measurement
a b s t r a c t Early childhood classroom quality can be viewed from multiple perspectives—including parents, teachers, administrators, researchers, policymakers, and politicians. From the beginning of our work in the 1970s, we have defined and measured the quality of early learning environments with the Environment Rating Scales (ERS) from the perspective of the children in those environments. As quality definitions and measurement have changed through the decades since then, we have retained a focus on children’s perspectives and have continued to revise the ERS to better capture aspects of caregiver–child interactions and particularly language interactions as research has shown these to be particularly important for children’s development. We have maintained our view of the centrality of children’s needs across a wide range of developmental and personal health and safety domains so that teachers, directors, homebased providers, technical assistance personnel, policymakers, researchers, and others interested in high quality programming have tools to guide their work. © 2019 Elsevier Inc. All rights reserved.
Quality in early childhood classrooms can be measured and viewed from a variety of perspectives. What do parents most want? What do teachers want? How about administrators? Or kindergarten teachers? Then, there are researchers, policymakers and politicians. From the very beginning of our work in the mid-1970s, we chose to look at learning environments from the perspective of the children who are spending a large proportion of their lives – more than 50% of their waking time for some – in these environments. From the perspective of a child, important questions about quality include the following:
• • • •
Is this a safe place for me? Am I getting a healthy and nourishing experience? Is the environment stimulating for me cognitively? Do I have opportunities to develop healthy relationships with other children and with adults? • Am I being provided with enough guidance and freedom to help me become an independent and self-sufficient individual?
∗ Corresponding author at: Research Scientist Emeritus, 750 Weaver Dairy Rd. Apt 178, Chapel Hill, NC 27514, United States. E-mail addresses: [email protected], [email protected] (R.M. Clifford). https://doi.org/10.1016/j.ecresq.2019.08.006 0885-2006/© 2019 Elsevier Inc. All rights reserved.
• Am I exposed to a wide range of ideas, ways of thinking, approaches to problem solving and to a diverse world and people? From this point of view, teachers/caregivers and children work together and respect one another, in turn teaching and learning together. There are millions upon millions of teaching and learning opportunities in early childhood programs. We can look at only a tiny fraction of these opportunities to estimate the degree to which they together create a healthy environment for our children. In our own work with the Environment Rating Scales (ERS), we have used a 1–7 point Likert-type scoring approach ranging from inadequate to excellent, anchored by sets of descriptors (indicators) along the scale to judge levels of quality. We do not expect any classroom to perfectly meet all of the 400–500 indicators in a given scale. Teachers and administrators must use their deep understanding of the children in their programs and the resources available to them to make good choices. Vygotsky (1978) argues that learning takes place with a crisis of some type. That is, children have to move out of their comfort zone, but not so far as to be overwhelmed. Children need some exposure to risk in order to test their limits. So for teachers, choices are often in conflict with one another. Sometimes it is in the best interests of children for a caregiver to be a little lax on handwashing hygiene in order to provide the needed social and emotional support to infants and toddlers. One of us (Cryer) has a favorite saying from her experience as a program director. She says
R.M. Clifford et al. / Early Childhood Research Quarterly 51 (2020) 164–166
“I had to learn to take my ones (meaning a score of inadequate) on some indicators of quality to achieve what was best in the big picture for the children in my program.” So, to us, quality should always be judged from the perspective of the children in the environment. Are we giving them the opportunities and help to be safe and secure, healthy, knowledgeable about the world and their own capabilities, to be able to learn throughout life, to be ethical and caring and to enjoy life? It is a tough order to figure out if our programs and teachers are doing all these things. We have worked on these measurement issues for most of our lives and still are learning how to do it. When we first started this work in the 1970s and 1980s, women were entering the workforce in great numbers, and thus early care and education was viewed primarily as a basic employment support for young families and only as secondarily as a place for cognitive and social learning. Our first instrument was essentially a checklist for county child care coordinators as they sought to improve child care in their communities. We were trying to provide guidance on aspects of the classroom environment to look for as indicators of quality. We soon expanded the checklist into the 7point scale that is familiar today. The availability of process quality tools during the 1980s (ours was not the only one, but was the one most widely used) propelled the study of early education program quality forward during this time. The major study to come out of this decade was the National Child Care Staffing Study (Whitebook, Howes, & Phillips, 1989), which found that teacher wages were the strongest predictor of structural and process (global) quality. That study also highlighted associations between higher quality programming and lower teacher turnover as well as between quality and auspice — with nonprofit centers generally rated as higher quality. By the 1990s, researchers were using broad theoretical perspectives (e.g., Bronfenbrenner & Morris, 2006) to examine children’s outcomes. It was recognized that quality of early care settings as measured with tools like the ERS was one aspect of microsystems in which children develop, and that systems beyond these settings also exerted influence. The Cost, Quality, and Outcomes Study (CQO Study Team, 1995); Study of Early Child Care and Youth Development (e.g., NICHD ECCRN, 2000); and federal Head Start studies, including the Head Start Family and Child Experiences Study (Moiduddin, Aikens, Tarullo, West, & Xue, 2012); consortium of Head Start Quality Research Centers (1995–2000, 2001–2006; e.g., Dickinson & Sprague, 2001), and the Early Head Start Research and Evaluation Project (1996 to present; e.g., Love, Chazan-Cohen, Raikes, & Brooks-Gunn, 2013) all found evidence of links between quality and child outcomes. In the 2000s, the evidence of the previous decades of research was used to support the development of statewide Quality Rating and Improvement Systems (QRISs), program and accreditation standards. But much more research is needed to understand how best to set benchmarks, measure and monitor programs to ensure the best outcomes for children and families. Toward the end of this decade and into the next, the field also saw additional tools developed to measure more discrete aspects of children’s experiences. For example, the Classroom Assessment Scoring System Pre-K (Pianta, La Paro, & Hamre, 2008) focuses on teacher–child interactions; the LENA focuses on the language environment and specifically numbers of words and conversational turns in children’s environments; and the Quality of Caregiver–Child Interactions for Infants and Toddlers (Q-CCIIT; Atkins-Burnett et al., 2015) examines the interactional and language environments for children under age 3. Throughout these decades we continued to revise the ERS to better capture aspects of caregiver–child interactions and particularly language interactions as research has shown these to be particularly important for children’s cognitive development. With
165
these revisions, we have not abandoned the centrality of the children’s developmental needs in the measurement of quality nor the view that global quality – including aspects of health/safety, activities, and language/interactions – is important in understanding the multiple facets of environments that influence children. Going forward, we hope to continue to revisit and revise our measures to best capture those aspects of the environment that are important for optimizing children’s development so that teachers, directors, home-based providers, technical assistance personnel, policymakers, researchers, and others interested in high quality programming have tools to guide their work. Two recent meta-analyses of the older versions of ERS for preschool classrooms (Brunsek et al., 2017; Ulferts, Wolf and Anders (2019) found significant but weak associations between quality and child outcomes, with Ulferts, et al. finding that the effects last over children’s school career. The newer versions, as noted above, attempt to better capture aspects of caregiver–child interactions and particularly language interactions to strengthen associations with outcomes. There are measurement limits to our ability to achieve our goals related to predictive validity. First, measures of child outcomes in the early years are only moderately associated with achievement and well-being in later life (Duncan et al., 2007; Jones, Greenberg, & Crowley, 2015). New and more predictive instruments are needed to further our understanding of the influences of early learning environments, including measures of biological processes (Granger & Kivlighan, 2003; Shonkoff, 2010). Second, our analytic and statistical tools are only roughly able to control for the many other influences on outcomes beyond the classroom and program domains (NICHD ECCRN, 2002). Third, we lack adequate theory testing and replication. A cornerstone of scientific study is replication of findings, yet there are few incentives in our field for doing such work. Replication is particularly significant since most of us as researchers have some form of conflict of interest in our studies and because multiple replications are needed to identify true effects (Maxwell, Lau, & Howard, 2015). As researchers, we each have our own special interests in understanding how environments affect various aspects of children’s development. This means our work can, as a whole, develop a more thorough understanding of the child-environment interaction that leads to successful and well-adjusted adults. We are fortunate to live in a time in history that is seeing new forms of families and roles of parents in rearing their children, with resulting new roles for our institutions in supporting those families as we transmit our culture and knowledge to the next generation.
References Atkins-Burnett, S., Monahan, S., Tarullo, L., Xue, Y., Cavadel, E., Malone, L., et al. (2015). Measuring the quality of caregiver–child interactions for infants and toddlers (Q-CCIIT). OPRE report 2015-13. Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. Bronfenbrenner, U., & Morris, P. A. (2006). The bioecological model of human development. In R. M. Lerner (Ed.), Handbook of child psychology: Vol. 1. Theoretical models of human development (6th ed., pp. 793–828). New York: Wiley. Brunsek, A., Perlman, M., Falenchuk, O., McMullen, E., Fletcher, B., & Shah, P. S. (2017). The relationship between the Early Childhood Environment Rating Scale and its revised form and child outcomes: A systematic review and meta-analysis. PLoS One, 12, e0178512 http://dx.doi.org/10.1371/journal.pone. 0178512 CQO Study Team. (1995). Cost, quality, and child outcomes in child care centers [Technical report]. Denver: Department of Economics, Center for Research in Economic and Social Policy, University of Colorado at Denver. Dickinson, D. K., & Sprague, K. (2001). The nature and impact of early childhood care environments on the language and early literacy development of children from low-income families. In D. K. Dickinson, & S. Neuman (Eds.), Handbook of research on early literacy. New York: Guilford Press. Duncan, G. J., Dowsett, C. J., Claessens, A., Magnuson, K., Huston, A. C., Klebanov, P., et al. (2007). School readiness and later achievement. Developmental Psychology, 43, 1428–1446. http://dx.doi.org/10.1037/0012-1649.43.6.1428
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R.M. Clifford et al. / Early Childhood Research Quarterly 51 (2020) 164–166
Granger, D. A., & Kivlighan, K. T. (2003). Integrating biological, behavioral, and social levels of analysis in early child development: Progress, problems, and prospects. Child Development, 74, 1058–1063. http://dx.doi.org/10.1111/14678624.00590 Jones, D. E., Greenberg, M., & Crowley, M. (2015). Early social-emotional functioning and public health: The relationship between kindergarten social competence and future wellness. American Journal of Public Health, 105, 2283–2290. http://dx.doi.org/10.2105/AJPH.2015.302630 Love, J. M., Chazan-Cohen, R., Raikes, H. A., & Brooks-Gunn, J. (2013). What makes a difference: Early Head Start evaluation findings in a developmental context. Monographs of the Society for Research in Child Development, 78(1), vii–viii, 1–173. Maxwell, S. E., Lau, M. Y., & Howard, G. S. (2015). Is psychology suffering from a replication crisis? What does “failure to replicate” really mean? American Psychologist, 70, 487–498. http://dx.doi.org/10.1037/a0039400 Moiduddin, E., Aikens, N., Tarullo, L., West, J., & Xue, Y. (2012). Child Outcomes and Classroom Quality in FACES 2009. In OPRE Report 2012-37a. Washington, DC: Office of Planning, Research and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services.
NICHD Early Child Care Research Network. (2000). The relation of child care to cognitive and language development. Child Development, 71(4), 960–980. NICHD Early Child Care Research Network. (2002). Early child care and children’s development prior to school entry: Results from the NICHD Study of Early Child Care. American Educational Research Journal, 39, 133–164. http://dx.doi. org/10.3102/00028312039001133 Pianta, R. C., La Paro, K. M., & Hamre, B. K. (2008). Classroom assessment scoring system (CLASS) manual, pre-K. Baltimore, MD: Brookes Publishing. Ulferts, H., Wolf, K. M., & Anders, Y. (2019). Impact of process quality in early childhood education and care on academic outcomes: Longitudinal meta-analysis. Child Development, 90, 1474–1489. http://dx.doi.org/10.1111/ cdev.13296 Shonkoff, J. P. (2010). Building a new biodevelopmental framework to guide the future of early childhood policy. Child Development, 81, 357–367. http://dx.doi. org/10.1111/j.1467-8624.2009.01399.x Vygotsky, L. (1978). Mind in society: The development of higher psychological processes. Cambridge, MA: Harvard University Press. Whitebook, M., Howes, C., & Phillips, D. (1989). Who cares? Child care teachers and the quality of care in America. Oakland, CA: Child Care Employee Project.