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It is indicated that research on professional development programmes (PDPs) for mathematics teachers mostly concerns whether a programme affects the teachers’ practice or student learning, while the teachers’ learning is treated as a black box. Calls have been made for a shared body of knowledge on teachers’ professional learning and what supports such learning. In this article, 84 articles from mathematics education journals are examined with respect to facilities and catalysts for teacher learning from PDPs for mathematics teachers. Two main types of PDPs were identified—those that target teacher knowledge growth and those that target changed instruction—and it was determined that the types of facilities for catalysing learning linked to them differ. Typical of PDPs targeting teacher knowledge growth is that they emphasise knowledge of content and teaching, knowledge of content and students and specialised content knowledge; following insight and/or body of knowledge as facilities for catalysing the learning. Typical of PDPs targeting changed instruction is that they use more time and have a larger time span than PDPs targeting teacher knowledge growth, emphasise knowledge of content and teaching; and follow strategies by doing/experimenting when establishing them in the classroom as facilities for catalysing the learning.

An important aspect of reform-based mathematics teaching is how students’ errors are handled in the classroom. This study aims to investigate the relation between mathematics teachers’ beliefs, mathematical knowledge for teaching (MKT) and error-handling practices in the classroom. Using an abductive approach based on 51 lessons with 12 teachers in Grades 4–6, we analysed 469 episodes containing error-handling practices. Patterns in the 12 teachers’ error-handling practices were found in relation to their MKT and belief profiles. The most important dimension in the patterns found is that teachers’ MKT seems to determine their possibilities to act according to their beliefs. That is, the results of the study show that high MKT makes it possible to handle students’ errors in accordance with the teacher’s beliefs (regardless of whether or not they hold more reform-oriented beliefs), while lower MKT seems to constrain their possibilities to explain and discuss students’ errors in conceptually grounded ways and act in reform-based ways.

Curriculum implementations in mathematics education around the world are aimed at supporting students’ attainment of increasingly rigorous learning goals, and teachers play a key role in establishing and acting within such instructional practices. Therefore, teachers’ learning and how to support it are pressing issues, and research on the professional development of teachers is a growing field within mathematics education. Within this dynamic and developing research field, there are different perspectives, conceptualizations, and critical discussions. In this chapter, we will elaborate on challenges within making professional programs drivers of improvement in implemented curricula by focusing on research on the establishment of professional development programs in diverse contexts and at large scale. We elaborate on recent developments within strands of research regarding aspects of how to adapt professional development programs to contexts and at large scale, and conclude by pointing out important directions for future research.

We examine the effects of a year-long national-scale professional development (PD) program on mathematics instructional quality. In contrast to previous studies examining the effects of this program on instruction by comparing before and after participation or participants and non-participants, we examine whether instructional quality changed during the program. More specifically, we conduct an analysis of 174 video-recorded mathematics lessons given by 52 teachers during their year of participation. Contrary to previous studies, the results demonstrate that the instructional quality did not improve over the course of the PD. We suggest that the explanations for the diverging results concern how, when, and to what extent instructional quality changes in PD programs. Specifically, we discuss how the explanations may illuminate the significance of PD duration for PD effects, and how these effects may be mediated by features concerning the PD content and the scale at which the program is implemented.

This study examines the effect of teachers’ participation in mathematics and science professional development (PD) on student achievement in nationally representative settings. We use data from all OECD countries in the 2003 through 2019 cycles of the Trends in International Mathematics and Science Study (TIMSS) and apply student fixed effects to control for unobserved student characteristics and school quality. We find a small negative average effect of PD participation, with negative effects concentrated among high-performing students. We discuss potential explanations of these results and suggest ways PD studies may inform the PD in which teachers typically participate.

In this article, we discuss the methodological implications of data and theory integration for Theory-Based Evaluation (TBE). TBE is a family of approaches to program evaluation that use program theories as instruments to answer questions about whether, how, and why a program works. Some of the groundwork about TBE has expressed the idea that a proper program theory should specify the intervening mechanisms underlying the program outcome. In the present article, we discuss in what way data and theory integration can help evaluators in constructing and refining mechanistic program theories. The paper argues that a mechanism is both a network of entities and activities and a network of counterfactual relations. Furthermore, we argue that although data integration typically provides information about different parts of a program, it is the integration of theory that provides the most important mechanistic insights.

In this paper, we discuss a set of procedures for the visualization of conversation data, based on machine learning and text mining algorithms. The methodological function of these visualization methods is to support (rather than substitute) humanistic and interpretive qualitative data analysis. The context of our methodological discussion is the study of teachers’ learning communities. Enabling collegial learning among teachers has been argued to play a pivotal role in both teachers’ professional development and students’ learning. The problem is that the interpretive study of collegial discussions among teachers, which are typically considered a fruitful context for the study of teachers' collegial learning, is both time-consuming and cognitively demanding. Several scholars have discussed the potential of including machine learning and text mining in the toolbox of qualitative data analysis as a way to analyze large qualitative data sets and solve the time demand problem. However, the literature discussing the use of machine learning and text mining for qualitative research typically conceives the algorithms as substitutes for the work of the researcher. These automatized approaches are introduced to categorize the data, substituting the researcher in the analysis process. In contrast, we discuss the potential rewards of using automatized methods to support the analysis of teachers’ collegial discussions. We introduce a set of visualization procedures based on semi-supervised topic modeling and supervised classification algorithms and discuss how these visualizations can provide additional elements useful for the analysis of collegial discussions. Whereas these visualizations do not substitute interpretive analysis, we argue that they can support researchers’ interpretations by reducing data, identifying patterns of interactions, and possibly, visualizing group-level learning.

The number of books at home is commonly used as a proxy for socioeconomic status in educational studies. While both parents’ and students’ reports of the number of books at home are relatively strong predictors of student achievement, they often disagree with each other. When interpreting findings of analyses that measure socioeconomic status using books at home, it is important to understand how findings may be biased by the imperfect reliability of the data. For example, it was recently suggested that especially low-achieving students tend to underestimate the number of books at home, so that use of such data would lead researchers to overestimate the association between books at home and achievement. Here we take a closer look at how students’ and parents’ reports of the number of books at home relate to literacy among fourth grade students, by analyzing data from more than 250,000 students in 47 countries participating in 2011 PIRLS. Contrary to prior claims, we find more downward bias in estimates of books at home among high-achieving students than among low-achieving students, but unsystematic errors appear to be larger among low-achieving students. This holds within almost every country. It also holds between countries, that is, errors in estimates of books at home are larger in low-achieving countries. This has implications for studies of the association between books at home and achievement: the strength of the association will generally be underestimated, and this problem is exacerbated in low-achieving countries and among low-achieving students. 

By examining the effects of a national-scale teacher professional development (PD) program on instructional practices and student mathematics achievement, we contribute to calls for empirical studies investigating the impacts of such programs conducted at scale. The program corresponds well with core critical features of high-quality teacher PD and mathematics instruction identified in the literature, and the results indicate that it has had a small but statistical significant impact on teachers’ instructional practices. However, no effect was found for student achievement. These results raise questions as to the importance of the critical features and how programs incorporating all of them affect instructional practices and student achievement.

There is an increasing movement in education towards closer collaboration between researchers and practitioners and research-practice partnerships (RPPs) are seen as one promising approach. However, some challenges still exist. To work in a new collaborative context such as RPPs, researchers and practitioners must adjust their roles in relation to each other. To better inform this movement, we conducted a systematic literature review of 80 articles investigating what roles researchers and practitioners are described to assume in RPPs. The results demonstrate eight different roles for researchers and practitioners, respectively, which reflect variations in both the main processes and tasks for school improvement in RPPs, as well as how these tasks are divided between the participants. Further, based on how tasks are distributed, the different roles provide varying opportunities to pursue a democratisation of evidence.