1
Although teacher education research comprises a relatively newly developed field (Grossman & McDonald, 2008), it has often been under attack for being underdeveloped, small scale, undertheorised, fragmentary, and somewhat parochial (Mayer, 2021; Mayer & Oancea, 2021). Critics of this field often lament that it has failed to reveal how teacher education can uplift teacher quality, which in turn, is assumed to lead to better teaching quality, and eventually to raise student learning (cf. Cochran-Smith, 2021; Tatto & Pippin, 2017). As accountability pressures increase, and as voices about the importance of “fixing” teacher education become more intense, calls have repeatedly been made to conduct large-scale studies and longitudinal studies that can track the impact of different teacher education programs on teacher quality (cf. Grossman & McDonald, 2008; Mayer & Oancea, 2021).
Unsurprisingly, during the last 15 years, some large-scale studies that aimed to examine the outcomes of teacher education on prospective and practicing teachers have been undertaken. For example, starting in 2008 and being conducted every five years, the Teaching and Learning International Study (TALIS) aims to investigate the perceptions of teachers worldwide about their preparation and job satisfaction (OECD, 2009, 2014, 2019). Similarly, focusing on mathematics, the Teacher Education and Development Study in Mathematics (TEDS-M, Tatto et al., 2012) explored the mathematics preparation of teachers at the primary and lower secondary levels in 17 participating countries. Another large-scale study conducted in Australia, Studying the Effectiveness of Teacher Education (cited in Mayer, 2021), examined the effectiveness of teacher education for early career teachers in Australia by following over 5000 graduates from teacher education programs into their early years of teaching. Taken together, these studies have provided important insights into teachers’ perceptions of their preparation and their sense of preparedness. Their importance notwithstanding, these studies do not meet one of the key concerns echoed by accountability critiques: no actual links are made between the aspects studied and their contribution to student learning outcomes. Aiming to address this limitation, this chapter focuses on and reviews large-scale studies that examined the contribution of different aspects of teacher quality to student learning.
The remainder of this chapter is organised into three sections. The first section provides an overview of the results of such large-scale studies. Critically reflecting on these findings, in the next section we discuss four lessons learned that pertain to how the limitations of such large-scale studies can be turned into affordances in future research. In the last section, we consider the
2 Using Large-Scale Studies to Examine the Contribution of Teacher Quality to Student Learning
2.1 Defining Terms
Teacher quality captures “teacher qualifications and characteristics (inputs) that are assumed to influence teaching and student outcomes” (Nilsen et al., 2016, p. 5). Our focus on teacher as opposed to teaching quality in this chapter hinges on that the first term directly corresponds to aspects of teacher education, which are the focus of this book, whereas the second term probes on teachers’ practice, without necessarily exploring the inputs contributing to the quality of teachers’ work (Nilsen et al., 2016).
Large-scale studies have been influential in examining how different teacher-quality attributes contribute to student learning. As Kyriakides and Charalambous (2014) point out, such studies have provided the means to start understanding how different factors – in our case relating to teacher characteristics and qualifications – support different types of student learning (cognitive, metacognitive, affective, and psychomotor). In addition, such studies become even more pivotal when conducted at an international level. As Nielsen and colleagues (2016) explain, by “using the world as a global educational laboratory” international large-scale studies “may contribute toward an international understanding of teacher quality […] and establish their importance for student learning outcomes across and within countries and over time” (p. 2).
But what exactly are “large-scale” studies? Attempting to bring some consensus on this issue, Middleton and colleagues (2015) list four criteria (by drawing on a list of criteria originally proposed by Anderson and Postlethwaite, 2007): (a) sample size, (b) purpose of the research, (c) generalisability of results, and (d) type and complexity of data analysis. In terms of sample size, they propose that studies should include sample sizes of at least 2500 participants for national studies or at least 7500 participants for international studies. In terms of their purpose, large-scale studies should aspire to examine and understand systems and phenomena more broadly rather than focusing on very specific aspects of them. Generalisability of results captures the goal of producing findings that are transferable beyond the local context examined, whereas the type and complexity of data analysis stipulates that more advanced and complex methods are utilised to analyse the data collected.
2.2 Sampling Teacher Characteristics and Qualifications
In one of the earliest meta-analyses of studies published between 1960 and 1976, Begle (1979) examined the contribution of several teacher characteristics and qualifications on students’ mathematics learning. Given the inconsistent results yielded from this meta-analysis, Begle urged researchers to channel their efforts to other directions. He lamented (pp. 54–55, emphasis added):
We are no nearer any answers to questions about teacher effectiveness than our predecessors were some generations ago. What is worse, no promising lines of further research have been opened up. Evidently our attempts to improve mathematics education would not profit from further studies of teachers and their characteristics. Our efforts should be pointed in other directions.
Nonetheless, contrary to Begle’s plea, scholars in the following years have continued examining a gamut of teacher characteristics and qualifications. From this wide array, for the purposes of this chapter, we focus on four such characteristics and qualifications that are related to teacher education: (a)
2.3 Large-Scale Studies on the Effect of Selected Teacher Characteristics and Qualifications: A Brief Overview
2.3.1 Teacher Preparation and Qualifications
From the indicators examined in this category, we focus on the following three: (a) college quality, (b) certification, and (c) coursework and degrees obtained.
Research findings seem to converge on the first two indicators. In particular, meta-analyses suggest a positive correlation between college ratings and student learning since students of teachers who attended more competitive colleges were found to perform better than students of teachers who attended less competitive colleges (Coenen et al., 2018; Wayne & Youngs, 2003). Subject-matter certification also appears to matter, particularly with respect to subject matters like mathematics and language arts; however, it has not been positively related to student learning for other subject matters (Coenen et al., 2018; Wayne & Youngs, 2003).
Study findings, however, seem to diverge when it comes to coursework and the degrees obtained. Whereas some studies (Çakır & Bichelmeyer, 2016; Canales & Maldonado, 2018) showed no effects on student learning, others (Goldhaber & Brewer, 1997; Harris & Sass, 2011; Toropova et al., 2019) reported positive effects, especially for middle-school mathematics. Harris and Sass (2011) also showed that the timing of acquiring an advanced degree appears to matter. Furthermore, mixed results have also been yielded from meta-analyses. For example, in Greenwald et al. (1996), 15% of the studies reported positive significant effects, 13% negative significant effects, and 72% no significant effects. No significant effects were also found in two other meta-analyses (Coenen et al., 2018; Wayne & Youngs, 2003) for degrees or coursework in different subject matters, with the exception of mathematics and, to some extent, science. Hence, it seems that subject-matter specificity appears to moderate the effect of coursework and degrees obtained on student learning.
2.3.2 Teaching Experience
Research findings appear to be equally inconclusive regarding the contribution of teaching experience to student learning. Whereas a number of studies (e.g., Çakır & Bichelmeyer, 2016; Jung et al., 2014; Wenglinsky, 2002) reported
Meta-analyses do not appear to shed more light on the effect of teaching experience on student learning either. For instance, in Greenwald et al. (1996) only 29% of the studies reported positive significant effects, whereas in 3% of the studies negative significant effects were reported; in most of the studies (68%), no significant effects were yielded. Other meta-analyses that were published during the last two decades (Coenen et al., 2018; Wayne & Youngs, 2003) found positive effects more consistently but in the latter one results were difficult to interpret because of different confounding factors. In the former one, findings diverged as some studies reported a positive effect only for the first three to five years and others a continuous beneficial effect of teaching experience, even up to 27 years.
In sum, although research findings provide some warrants that teaching experience appears to matter for student learning, the mixed study findings suggest that more work is needed to understand in what particular ways and under what specific conditions teaching experience does so.
2.3.3 Professional Development
A similar picture of mixed findings is also depicted in previous studies regarding the effect of professional development on student learning. Whereas no studies have been found to report negative effects, findings again range with some studies (e.g., Jacob & Lefgren, 2004; Loyalka et al., 2019) reporting no effects and others positive, albeit small effects (e.g., Wallace, 2009). Yet, there are nuances even in studies that paint a favourable picture of the contribution of professional development to student learning.
Specifically, it was shown that this effect is only present for particular grade levels and particular subject matters. For instance, Harris and Sass (2011) reported positive effects only for middle and high school mathematics teachers. Additionally, other studies showed that the content of professional development matters. For example, Wenglinsky (2002) found positive effects of professional development programs focusing on higher-order thinking skills and diversity. Desimone and colleagues (2010) went further by listing a set of
In conclusion, despite inconclusive findings, there seems to be a pattern of positive findings especially when adding the content of the professional development programs into the equation. Nevertheless, future studies are needed to further explore how exactly specific aspects of professional development programs contribute to their effectiveness in terms of supporting student learning.
2.3.4 Teacher Knowledge
An increasingly growing body of studies has focused on the effects of teacher knowledge on student learning, examining different aspects of teacher knowledge, including content knowledge (CK) and pedagogical content knowledge (PCK). To a great extent, these studies support that teacher knowledge has a positive effect on student learning as different types of teacher knowledge have been examined. For example, positive associations between students’ performance and teachers’ CK were identified (e.g., Metzler & Woessman, 2012). Moreover, studies have shown teachers’ PCK to be a better predictor of student learning compared to teachers’ CK (e.g., Baumert et al., 2010; Campbell et al., 2014; see also the meta-analysis by Depaepe et al., 2013).1 Hence, these positive findings are important for teacher education, especially when taking into consideration that PCK can be developed during initial or ongoing teacher education.
2.4 Summarising Existing Evidence
Summarising the findings reported above and seeing the glass half empty, one could wonder whether we have really made any progress or whether we are more or less where Begle had arrived more than 40 years ago. In fact, a cynical critic might even argue that the inconclusiveness in the findings reported actually vindicates Begle’s admonition that scholarly attention should be directed to other, more productive, paths. Yet, seeing the glass half full, one could argue that we are now aware of certain teacher characteristics for which there seems to be a positive pattern of contribution (e.g., teacher knowledge
3 Four Lessons Learned from the Results of Large-Scale Studies Focusing on Teacher Quality
3.1 Seeing the Bigger Picture
Several of the studies reviewed above have considered the focal teacher characteristics and qualifications mostly in isolation, without any of them bringing different characteristics together. It is thus necessary to explore teacher quality characteristics more comprehensively as some of the disparate findings reported above can be attributed to omitted variable bias (cf. Hill et al., 2019).
At least five studies attempted to examine the contribution of teacher quality characteristics more comprehensively (Boonen et al., 2014; Campbell et al., 2014; Grubb, 2008; Hill et al., 2019; Palardy & Rumberger, 2008). In addition to the four categories of teacher qualifications and characteristics explored above, these studies also examined teacher attitudes and beliefs. For example, by focusing on teacher preparation and experience as well as teacher attitudes, Palardy and Rumberger (2008) found that whereas preparation and experience did not explain student learning, teacher attitudes, and in particular, teachers’ efficacy beliefs did. Grubb (2008) reported positive relationships between student outcomes in mathematics in the NELS:88 data and a variety of teacher background and preparation characteristics (e.g., experience, teaching in-field, education track), along with teacher efficacy beliefs. In Boonen and colleagues’ (2014) work, teaching experience and job satisfaction – a background characteristic and attitude respectively – predicted Flemish students’ mathematics outcomes. Lastly, Campbell et al. (2014) found that teacher knowledge was positively associated with student outcomes in contrast to special education certification which was negatively associated with them. Teacher attitudes and beliefs largely had no effects outside interactions with knowledge itself.
3.2 Exploring (In)Consistency
Inconclusive results have often been regarded as problematic and have been associated with the “noise” that exists in a system when studying a phenomenon. Under this assumption, attempts are made to minimise the noise in order to better detect “the signal”. However, several scholars (e.g., Hall et al., 2020; Scheerens, 2015; Scheerens & Blömeke, 2016) increasingly propose adopting a different stance; one that regards such inconclusive results as part of the signal rather than the noise. In this context, they argue that attempts should be made to better understand what contributes to the inconsistencies identified upon examining a particular phenomenon.
About 40 years ago, Shulman (1986) advocated the inclusion of content back in the equation of teaching understanding. Since then, scholars have increasingly attended to the demands that teaching particular subject matters imposes on teachers (see, for example, the emphasis placed on identifying
In addition to considering the role of the content, Hall and colleagues (2020) urge for resisting the “context-stripping” tendency that appears to have permeated research on educational effectiveness during the past decades. Thus, the role of context also needs to be carefully examined as a potential contributor to the results obtained in studies exploring teacher effects. This implies that scholars need to invest in examining the consistency of teacher effects across different educational systems and countries [especially systems and countries that differ in their teacher education policies, see more on those differences in Tatto and Pippin (2017) as well as Brown (2017)]; across different student populations, in terms of their age and other background characteristics; as well as across different levels of schooling (pre-primary, primary, secondary-general, secondary-vocational, and tertiary education).
Research attempts can also be invested in considering different types of student outcomes as in most of the studies examined, scholars have focused on cognitive outcomes. Given that different types of student outcomes can lead to different conclusions about the contribution of teacher quality indicators to student learning (cf. Cappella et al., 2016; Lindorff et al., 2020; Reynolds et al., 2016; Scheerens & Blömeke, 2016) future studies need to broaden the type of outcomes examined to also incorporate non-cognitive outcomes. The results of Hill et al.’s (2019) study recounted above, that showed differences even across dissimilar cognitive outcomes, also underline the value of expanding the examination of both cognitive and non-cognitive types of outcomes, as well as differentiating even within the same type of outcomes.
Two relatively recent large-scale studies (Blömeke et al., 2016; Blömeke & Olsen, 2019) suffice for stressing the importance of emphasising and understanding the inconsistencies found in teacher quality effectiveness research. In the first study, the authors examined five teacher characteristics (teaching experience, teacher education degree, major focus in studies, professional
3.3 Adding Teaching Quality to the Equation
The studies reviewed in Section 2 have mostly considered teacher quality but did not open up the black box of teaching in order to understand how different teacher characteristics and qualifications can contribute to student learning through the improvement of teaching quality. Hence, it is encouraging that over the past two decades scholars within the field of educational effectiveness have not only stressed the importance of bringing together teacher and teaching quality factors – in an attempt to better understand what contributes to student learning – but have also proposed different theoretical frameworks and models for doing so (see, for example, Blömeke et al., 2015; Creemers & Kyriakides, 2008; Nilsen et al., 2016; Scheerens, 2016).
Studies that have explored both teacher and teaching quality effects corroborate the need of adding teaching quality into the equation. This becomes quintessential for at least two reasons. First, teacher characteristics and qualifications might have an indirect effect on student learning through teaching quality. This was suggested, for example, in Blömeke et al.’s (2016) study, which, in addition to the teacher characteristics and qualifications discussed above, also considered teaching quality. In that study, whereas the direct impact of professional development on student performance was not significant in most of the 47 countries examined, professional development turned out to be the
3.4 Capitalising on Complementarity
Large-scale studies – be they national or international – are important for understanding what teacher qualifications and characteristics contribute to student learning. Yet, as suggested by the review of the studies in the previous section, they have their own limitations in shedding light on how and why teacher education can support student learning. This is because, due to their design, such studies cannot provide answers on how teacher and teaching quality can contribute to student learning, how teacher education might support (or not) changes in teaching quality and through that, changes in student learning, and why (in)consistent results emerge.
Due to these limitations, it is argued that there is significant benefit in combining large-scale with small-scale studies. Indeed, for years, an overemphasis on small-scale studies has been accused of producing results that oftentimes were very particular to the context in which they were generated and could hardly inform broader educational policies. For example, almost thirty years ago, Cooney (1994) bemoaned the limitations of small-scale studies – and particularly case-studies – in teacher education, urging scholars to “move beyond collecting interesting stories” to start seeing “how those stories begin to tell a larger story” (p. 627). However, moving away from small-scale studies completely runs the risk of pushing the pendulum to the exact opposite end (large-scale studies only). Hence, our argument here is that we need to strike a balance between both types of studies, capitalising on the benefits of both, since such complementarity can help better understand the complex phenomena of teaching and student learning.
Small-scale (qualitative) studies have a number of affordances upon which future scholarly work can capitalise. First, they can unravel the mechanisms of how teachers learn and how this learning might affect their teaching, and
To illustrate the promise of these studies, we next briefly share two such studies from our work, one conducted with pre-service teachers and another conducted with in-service teachers. Neither study is meant to be presented as exemplary; rather, both of them illustrate how doing research in and on teacher education can yield important insights into supporting teacher learning.
The first study (Charalambous et al., 2018) focuses on three pre-service teachers who were followed during their practicum and were also supported in their work by being engaged in guided analyses of teaching practice – theirs and that of their colleagues – in a video-club setting (see more on such settings in Sherin & van Es, 2009). The analysis of these pre-service teachers’ lessons during their practicum documented differences in the learning trajectories both in planning and enacting of their lessons. More than suggesting that teachers benefit in different degrees when exposed to particular interventions, these differences challenge a tendency to consider teacher learning on the average – an inherent feature of large-scale studies. As such, these findings illustrate the need to better understand why such differences occur and how pre-service teachers’ characteristics along with the characteristics of the intervention interact, yielding these different learning trajectories.
Utilising the same idea of video-clubs, the second study (Charalambous et al., 2023) examined in-service teachers’ experimentation with ambitious teaching. The study documented how practicing teachers can be scaffolded to materialise such ambitious teaching visions in their practice through the use of certain praxis tools – namely tools that can help them materialise complex theoretical ideas in their practice. By portraying the changes that five practicing teachers introduced in their teaching and the challenges they encountered while trying to teach ambitiously, this study provided an account of what “typical” practicing teachers can achieve in their daily practice. Therefore, such studies can provide what Lampert et al. (2011) called “images and narratives for ambitious teaching that portray how one can be a mere mortal and yet
4 Looking Forward
What was discussed in the previous two sections has important implications for teacher education research. In this last section, we discuss three such implications and conclude by discussing how the value of teacher education research can be enhanced through large-scale studies.
The first implication relates to the value of continuing explorations on the contribution of certain promising teacher characteristics to teaching quality and student learning through large-scale studies. Although studies of this type have been conducted in abundance in the previous decades, we argue that there is merit in continuing this line of work (but also adapting and complementing it as will be discussed next). For example, one of the most promising characteristics yielded from prior research relates to teacher knowledge. Yet, several questions remain unaddressed – or are partly addressed – when it comes to its contribution. For instance, what types of teacher knowledge have larger effects and why? How consistent are the results across different contents and contexts? If inconsistencies arise, what might account for them? Equally critical, if teacher knowledge is so important, how do these types of knowledge develop during initial and ongoing teacher education? As already argued, addressing all these questions only through large-scale studies is impossible given that large-scale studies can, at best, help us address only what works and under which conditions. Hence, there is a need to complement such large-scale studies with small-scale (qualitative studies) that can help unravel how and why things work.
The second implication relates to the importance of continuing the investigations of not so promising characteristics and others for which extant studies have yielded inconclusive and mixed results (e.g., professional development). Future studies should, however, not be geared toward replicating the results of prior research, but largely to help better understand under what conditions the
The third implication relates to using more comprehensive designs in how we examine teacher and teaching effects. The recent OECD (2020) TALIS video-study Global Teaching InSights provides one such example of a large-scale study conducted at an international level. Focusing on eight different countries, in this study, scholars explored different teacher characteristics, aspects of teaching quality, and types of student learning. Such studies, especially when conducted at an international level, can help explore different moderation and mediation effects, thus further enhancing existing knowledge about the contribution of teacher and teaching characteristics to different types of student learning. However, when such comprehensive designs are difficult to run at an international level, national research agencies and centres might complement (international) large-scale studies by adding the missing pieces of the complex chain of associations that links teachers, teaching, and student learning. This is something that, for instance, scholars of the COACTIV project did in the past (see Baumert et al., 2010), when complementing the PISA study with research components that better allowed the concurrent studying of teacher characteristics (such as teacher knowledge), different aspects of teaching quality, and student learning.
At the beginning of this chapter, we referred to critiques often voiced regarding the field of teacher education research – critiques that, to some extent, might be nurtured by the difficulties of this body of research to directly inform policy decisions. Coming full circle, we conclude by discussing how large-scale studies can help enhance the value of this field of research. We see three ways in which this can be done.
First, although generalisations are often particularly desirable for policy making, nowadays it seems to be increasingly understood that generalizable patterns might be neither feasible nor productive to derive, especially when it comes to studying complex phenomena like teaching and learning. By exploring different moderators to the association between teacher characteristics, teaching quality characteristics, and student learning, large-scale studies can produce results that, albeit of limited generalisability than those policymakers might be longing for, take into consideration different contextual factors. Doing so is important not only for further developing teacher education research but
Second, neither large-scale studies nor small-scale studies alone can help us understand comprehensively the complex chain of associations between teacher characteristics, teaching, and student learning. As argued above, a productive combination of large-scale and small-scale (qualitative) studies can help us delve deeper into exploring these associations. This complementarity can contribute toward understanding not only what works and under what conditions, but also how and why things work. We maintain that addressing these different types of questions can help uplift the status of teacher education research since complex educational phenomena require a more comprehensive and holistic approach in studying them. Otherwise, according to the well-known Indian fable of the seven blind men studying an elephant, teacher education researchers run the risk of producing fragmentary knowledge pieces which can hardly move the field really forward.
Finally, another way to elevate the status of teacher education research by producing more consistent and applicable findings, that can inform teacher educators as well as policy makers, lies in combining explorations of teacher effects with teaching quality effects. It is encouraging that during the past years such investigations are observed more frequently than in the past (see, for example, Blömeke et al., 2016; OECD, 2020). We argue, however, that they need to be intensified and that researchers have to experiment with different ways of measuring teacher and teaching quality effects (e.g., teacher reports, principal reports, student reports, classroom observations, teacher logs) to better capture and study these effects. Such explorations are envisioned to produce more nuanced results that better lend themselves to informing the design of different teacher education programs as well as decision-making at different levels.
In conclusion, large-scale studies can uplift the status of teacher education research through their contributions, but only if they are critically examined on what they can help us achieve and how. Despite their shortcomings, when they are used in combination with other types of studies their limitations can be turned into affordances. Thus, upon reflecting on Begle’s (1979) and Scheerens’ (2015) admonitions, it can be argued that there are still very productive research paths on teacher and teaching quality when considering the whole of the moon, looking both at its bright and dark sides.
Note
More recently, positive associations were also yielded between student learning and teachers’ general pedagogical knowledge (GPK) (e.g., König et al., 2021). We do not report on these
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