3. Classroom management

Courtney A. Bell
Katherine E. Castellano
Eckhard Klieme

Classroom management refers to the range of structures and practices that help teachers manage classrooms successfully, facilitate high levels of student attention for mathematics and avoid disruptions. Teachers use varied practices that range from overt to subtle in order to manage the classroom. A teacher reminding students of the classroom rules is more overt. While a teacher leading whole group work while also moving to stand next to a student who appears ready to disrupt the room with off-task behaviour is more subtle. Student grouping structures are another way teachers manage classrooms to achieve instructional goals. For example, a teacher who is knowledgeable about the relationships among students might deliberately separate students who tend to “chat” with one another for pair-based work. Teachers’ classroom management practices allow them to use time effectively and those practices have frequently been related to student achievement (Baumert et al., 2010[1]; Kane and Staiger, 2012[2]; van Tartwijk and Hammerness, 2011[3]).

Classroom management is not just about what teachers do. Students also contribute to managing the classroom through their behaviour. If, for example, there is a loud noise in the hallway while a teacher is explaining something, students might react in different ways. On the one hand, they might laugh or ask what is happening or become distracted; on the other hand, they might ignore the noise and continue listening to the teacher. Thus, students’ and teacher’s behaviours together will determine if the noise causes the teacher and students to interrupt the lesson or simply causes the teacher to repeat her explanation. To understand classroom management, it is important to take account of both teacher and student behaviours.

This chapter reports findings on the observed quality of classroom management; including the extent to which lessons were focused on mathematical learning, the prevailing types of activity structures, and teachers’ use of routines, monitoring of the class and handling of disruptions. It also reports on teachers’ and students’ perceptions on how well classrooms are managed and the disciplinary climate in class.

To measure the quality of classroom management, observers holistically noted how teachers handled disruptions, the efficiency and organisation of classroom routines, and the degree of classroom monitoring carried out by the teacher. These are aggregated into an overall classroom management domain score, which ranges from 1 (lowest presence or quality) to 4 (highest presence or quality) (for the domain aggregation method see Chapter 2).1

The vast majority of classrooms observed in every country/economy were well managed. Furthermore, classroom management practices were the strongest teaching practices, when compared to social-emotional and instructional practices (Figure 3.1). On average, teachers had organised and efficient routines in place, frequently engaged in monitoring, and handled disruptions quickly and effectively. All country/economy means are equal or above 3.49: K-S-T (Japan) (3.81), Shanghai (China) (3.75), England (UK) (3.74), Madrid (Spain) (3.72), Colombia (3.70), Germany*2 (3.67), Mexico (3.58), and Biobío, Metropolitana and Valparaíso (Chile) (hereafter “B-M-V [Chile]”) (3.49). Annex 3.A, Tables 3.A.1 and 3.A.2 show descriptive statistics for each country/economy.

Most countries/economies had uniformly high levels of classroom management, with most or all classrooms scoring between a 3 and 4. There was, however, a small amount of variation within countries/economies. Variation within countries/economies is shown in Figure 3.1, which plots classrooms’ mean classroom management score in a density curve. The figure shows that all countries/economies have peaked-shaped curves, meaning classrooms were similar to one another. B-M-V (Chile)’s classrooms had some variation in the mean scores (a distribution concentrated between 3 and 4) and Shanghai (China)’s classrooms had very little variation in mean scores (a distribution concentrated between 3.5 and 4). In K-S-T (Japan) and Shanghai (China) no classrooms had a mean score of 3; almost every classroom’s mean was above 3.5 in each of those countries/economies. High levels of classroom management practices are consistent with patterns found in other observational research (e.g. (Kane and Staiger, 2012[2])).

One of the main reasons it is important to manage classrooms efficiently is so that students can spend as much time as possible learning mathematics and developing valuable social-emotional skills. Research shows that lesson time can have a significant impact on student academic outcomes (Schmidt, Zoido and Cogan, 2014[4]). Opportunity to learn is discussed from a curricular perspective in Chapter 6 of this report. Here we consider how time is spent on mathematics during the observed lessons.

The mean lesson length was slightly less than 55 minutes (see Annex 3.A, Table 3.A.5). But lesson length varied by country/economy: Germany* (65 minutes), Colombia (63 minutes), B-M-V (Chile) (62 minutes), Mexico (55 minutes), England (UK) (54 minutes), K-S-T (Japan) (50 minutes), Madrid (Spain) (47 minutes) and Shanghai (China) (42 minutes). Within a country/economy, lessons were sometimes quite a bit longer or shorter than the mean; for example, lesson length ranged from 46 to 80 minutes in Colombia.

During a lesson, teachers and students regularly need to accomplish tasks that might not be strictly mathematical – marking down which students are absent, talking with students about their weekend activities, or moving chairs around to get into small project groups. Not all of this type of off-task behaviour from mathematics is “lost” time. During conversations about students’ weekend activities, for example, teachers convey their interest and care for students thereby developing and maintaining the social relationships that support students’ development.

Observers noted each 8-minute segment in terms of how much time was focused on non-mathematical tasks. Ratings ranged from 1 (four or more minutes out of eight were spent on non-mathematical tasks) to 4 (0-30 seconds was spent on non-mathematical tasks).

Teacher and student time was generally spent on mathematics. All countries/economies had extremely high mean time-on-task lesson ratings. Observers noted ranges of time off-task in segments and therefore calculations of the time off-task in a lesson can only be reported in ranges. To further understand where lesson time was off-task, a lesson analysis was carried out. Lesson segments were grouped into three groups: the first, middle and last. All middle segments were averaged together to produce a “middle segments” mean score. For each kind of segment, the proportion of lessons that had a mean lower than 3.5 was calculated. A mean rating lower than 3.5 means that more than 30 seconds per segment was spent on non-mathematical tasks and that the individual segment spent more time on them than the mean country/economy. All country/economy means were over 3.71 of 4 (see Annex 3.A, Tables 3.A.8 and 3.A.9), suggesting that observers assigned most segments a rating of four, zero to 30 seconds lost in the segment.

With one exception, non-mathematical tasks were most frequent during the first segments of lessons (Figure 3.2). Between 9 and 37% of lessons had at least one observer noting that more than 30 seconds of the first 8-minute segment was not focused on mathematics (K-S-T [Japan] [37%], Mexico [33%], Colombia [31%], B-M-V [Chile] [26%], Germany* [22%], Shanghai [China] [14%], England [UK] [11%], Madrid [Spain] [9%]). In England (UK), non-mathematical tasks were most frequent in the last segments of the lesson (14%).

During the last segments of lessons, a smaller proportion, between 1% and 22% of lessons, spent more than 30 seconds on non-mathematical tasks, depending on the country/economy. The middle segments of lessons were the most focused on mathematical tasks; 0-9% of lessons spent more than 30 seconds per segment on non-mathematical tasks.

All lessons face disruptions - there are loud noises coming from the hallway, power point projectors or smartboards do not work properly, students misbehave. Teachers address these disruptions through their actions, but students also determine whether these disruptions distract them from the mathematics or are ignored. Longer and more sustained disruptions are harder for everyone to ignore and potentially decrease learning time more than shorter disruptions.

Observers noted whether disruptions occurred and how the teacher handled them. The highest rating on the holistic four-point scale meant that either there were no disruptions, or the teachers and class handled them quickly and effectively. Virtually all classrooms in every country/economy received high ratings (above 3.8 out of 4) (Figure 3.3). This means that when disruptions occurred, teachers handled them quickly and effectively, and while students’ focus on mathematics was interrupted momentarily, significant learning time was not lost.

In addition to disruptions threatening to reduce learning time, organisational tasks also can reduce learning time. Each day students and teachers carry out common, repetitive organisational tasks – taking attendance, asking questions of the teacher, passing out books or calculators, or transitioning between whole group and individual work. These tasks can also reduce available learning time. Routines are pedagogical strategies teachers use to carry out these organisational tasks efficiently and minimise the amount of time that is lost to non-mathematical tasks.

Observers noted the organisation and efficiency of classroom routines on a four-point holistic scale. A 1 on the scale means that routines were inefficient and often disorganised. A 4 means that all routines were efficient and organised. Efficiency refers to the use of time.

The average classroom observed had well-organised and efficient routines in place. The mean score was very high in all countries/economies: Shanghai (China) (4.00), K-S-T (Japan) (3.92), Madrid (Spain) (3.84), Colombia (3.82), England (UK) (3.78), Germany* (3.74), B-M-V (Chile) (3.57) and Mexico (3.53).

It is also noteworthy that there was little variation across classrooms within countries/economies. All classrooms in K-S-T (Japan) and Shanghai (China), and nearly all of them in Colombia (95%), Madrid (Spain) (94%), England (UK) (93%) and Germany* (88%) had consistently well-organised and efficient routines (score above 3.5) (see Annex 3.A, Tables 3.A.1 and 3.A.2). However, this was the case in only the majority of classrooms in B-M-V (Chile) (69%) and Mexico (64%). In these classrooms, teachers and students carried out routines, such as transitioning between activities or getting the teacher’s attention, quickly and with little guidance.

Effective monitoring can prevent disruptions before they arise and support students by focusing their attention on learning. Monitoring is the idea of noticing what is happening in the whole classroom by, for example, looking out across the students from the front of the room, walking between students’ desks as they work independently and noticing when a small group’s noise level seems to be getting louder than is appropriate for the mathematics they are working on. If most students are focused on learning, then teachers may not need to constantly keep an eye on them.

Observers noted the quality of monitoring on a holistic four-point scale. They focused on the teacher’s physical proximity to students, scanning of the whole classroom, facing the students, calling on a range of students and noticing students’ progress through tasks. The lowest levels of monitoring (score of 1) means that there was no evidence that the teacher engaged in monitoring behaviours, while teachers who frequently and consistently did so were rated at the highest level (score of 4).

Teachers sometimes or frequently engaged in monitoring students’ behaviours in the average classroom observed and did so with few to no inconsistencies. The mean score was above 3 in all countries/economies: England (UK) (3.61), K-S-T (Japan) (3.54), Germany* (3.45), Madrid (Spain) (3.41), Colombia (3.31), Mexico (3.27), Shanghai (China) (3.24) and B-M-V (Chile) (3.06).

Not all teachers within each participating country/economy engaged in monitoring with the same frequency (Figure 3.4). For example, teachers in Germany* and Madrid (Spain) were equally divided between frequently and sometimes. It is worthwhile to note that occasional monitoring (score between 1.5-2.5) was observed in none or very few classrooms, meaning that keeping an eye on students is a very common strategy teachers used to maintain a productive learning environment.

The classroom can take many shapes, from students sitting silently in rows and waiting to be called on by the teacher to groups or U-shaped arrangements of desks and students raising their hands to volunteer. A large body of literature has underlined the importance of effectively managing these classroom structures and transitions for student learning (Allen et al., 2013[5]; Hochweber, Hosenfeld and Klieme, 2014[6]; OECD, 2018[7]).

The structure of the classroom is often influenced by the activities of the lesson. Teachers might ask students to listen as a whole group or ask them to work individually, in pairs or in groups on a lesson problem. Different activity structures are not universally better or worse, rather they have different affordances, constraints and expectations for students and teachers. Further, more than one activity structure is frequently used in rapid succession (e.g. going from whole group to individual seat work and back to whole group). Teachers work with students to create a well-managed classroom within and across those activity structures. To measure what structures are most commonly used, observers recorded the two predominant activities in each 8-minute segment of the lesson.

Whole group instruction (frontal teaching) – a teacher standing at the front of the room in front of a group of students – was observed in over 88% of the lesson segments on average (Figure 3.5). It is worthwhile to note that this structure is prevalent across classrooms within countries/economies. Nine of every ten classrooms made use of it in at least 69% of the lesson segments observed (see Annex 3.A, Table 3.A.7).

Individual seatwork activities was the second most used structure. Students worked individually in a large proportion of lesson segments in England (UK) (84%), K-S-T (Japan) (77%), Shanghai (China) (68%), and in a smaller proportion in B-M-V (Chile) (48%), Mexico (38%), Germany* (36%), Madrid (Spain) (31%) and Colombia (22%).

Student collaboration – either in pairs or in small groups of three or more students – was used in less than 22% of lesson segments in all countries/economies. In B-M-V (Chile) and Shanghai (China), students were almost never seated in small groups or pairs.

Classrooms within the same country/economy did not always use similar student groupings. For example, in K-S-T (Japan), nine in ten classrooms used whole group in almost all (89%) segments recorded (see Annex 3.A, Table 3.A.7). But there was variation in the additional structures used in the same segment as the whole group structure. In half of the classrooms, students worked in pairs for at least 8% of segments, small groups for at least 17% of segments and individually in 82% of segments.

Each activity structure has different affordances and constraints. When students are in a whole group setting, teachers may call on individual students in order to learn what they think. This structure has both the affordance and constraint that the rest of the students listen to those individual students while they speak. This format quickly and efficiently provides the same information to all students, but it also means one person at a time is speaking. Whole group instruction has been criticised for decades with some arguing it does not engage students as well as other methods (Kelly and Turner, 2009[8]). When students are working individually, the teacher might circulate among them, and stop to review and provide feedback on a single student’s work. This practice is defined by both the benefit and constraint that only one student at a time has the teacher’s attention. Pairs and small groups benefit from the fact that students are more able to discuss ideas and compare thinking with a classmate, but they have the constraint that students have to work together equitability to realise the potential impact of those learning opportunities (Boaler and Staples, 2008[9]).

Students and teachers were asked about their perceptions of the quality of classroom management during the teaching of quadratic equations. In particular, they were asked on their level of agreement on a four-point scale with statements related to the disciplinary climate in the class, teachers’ efficiency in handling disruptions and teachers’ awareness of students’ attentiveness. Overall, students and teachers had positive views about how classrooms are managed across countries/economies (Table 3.1).

Teachers were very positive about how they handled disruptions and were aware of inattentive students (Table 3.1). In Germany* and Shanghai (China), between 94% and 98% of the teachers agreed or strongly agreed with the respective statements. In most other countries/economies, agreement rates were around 90%. In K-S-T (Japan) and Mexico, however, only 51% and 78 % of the teachers, respectively, agreed or strongly agreed with the statement “I reacted to disruptions in such a way that students stopped disturbing learning”.

In most countries/economies, students were more sceptical than teachers when judging classroom management practices. They were more likely to report that there was much disruptive noise, and they were relatively less positive than their teachers on teachers’ awareness of inattentive students and their handling of disruptions.

This gap between teachers’ and students’ views existed in every participating country/economy. The difference is particularly large in England (UK) and Germany* on the handling of disruptions and awareness of inattentive students. In B-M-V (Chile), Colombia, Madrid (Spain) and Mexico, nearly half of students believe that there is much disruptive noise, compared to one in five or less of their teachers.

To compare the views of teachers and students of the same classroom, an index for the frequency of perceived disruptions was created. This index summarises their views on the following statements: “When the lesson began, our mathematics teacher (I) had to wait quite a long time for us (these students) to quiet down”; “We (I) lost quite a lot of time because of students interrupting the lesson”; and “There was much disruptive noise in the classroom”. Both the index for teachers and students range from 1 to 4. High values indicate fewer, or less disruptions, hence more efficient classroom management.

When students reported that classrooms had relatively few disruptions, their teacher also tended to do so, and vice versa. The teacher index and the student index were strongly correlated in Germany* (0.66) and England (UK) (0.63), moderately in K-S-T (Japan) (0.49) and B-M-V (Chile) (0.44), and less but still significantly in Colombia (0.35), Shanghai (China) (0.32) and Mexico (0.26). The correlation was statistically not significant in Madrid (Spain) (0.17).

Do teachers and students act differently when they know that they are being observed? It is possible that when a video-recording device is present, teachers and students are on their “best behaviour”. There is mixed evidence on this point (Curby et al., 2016[10]; Praetorius, McIntyre and Klassen, 2017[11]), though where such effects are found they are not large.

In the Study, students were asked whether their teacher’s classroom management during the videotaped lessons differed from regular lessons. Although students on average reported a tendency towards better classroom management for videotaped lessons in all countries and economies, the difference was perceived as being very small (see Chapter 2 for details).

The fewer disruptions students and teachers reported from all lessons on quadratic equations, the fewer disruptions were seen by observers in most countries/economies. As student and teacher judgements referred to the whole unit, not just the two videotaped lessons, this alignment provides further evidence against the assumption of “cheating” when teachers and students know that they are being recorded.

Student reports on disruptions3 were significantly correlated with video ratings on disruptions in all countries/economies except Madrid (Spain). Correlations between observers’ ratings and student reports were highest in England (UK) (0.62) and Germany* (0.55), followed by B-M-V (Chile) (0.35), K-S-T (Japan) (0.28), Mexico (0.26), Colombia (0.10) and Shanghai (China) (0.09). Similarly, teacher reports and video ratings on disruptions were significantly correlated in Madrid (Spain) (0.52), Germany* (0.43), England (UK) (0.38) and B-M-V (Chile) (0.22). 


[5] Allen, J. et al. (2013), “Observations of Effective Teacher-Student Interactions in Secondary School Classrooms: Predicting Student Achievement With the Classroom Assessment Scoring System-Secondary.”, School psychology review.

[1] Baumert, J. et al. (2010), “Teachers’ mathematical knowledge, cognitive activation in the classroom, and student progress”, American Educational Research Journal, Vol. 47/1, pp. 133-180, https://doi.org/10.3102/0002831209345157.

[9] Boaler, J. and M. Staples (2008), “Creating mathematical futures through an equitable teaching approach: The case of Railside School”, Teachers College Record, Vol. 110/3, pp. 608-645.

[10] Curby, T. et al. (2016), “Live Versus Video Observations: Comparing the Reliability and Validity of Two Methods of Assessing Classroom Quality”, Journal of Psychoeducational Assessment, https://doi.org/10.1177/0734282915627115.

[6] Hochweber, J., I. Hosenfeld and E. Klieme (2014), “Classroom composition, classroom management, and the relationship between student attributes and grades”, Journal of Educational Psychology, https://doi.org/10.1037/a0033829.

[2] Kane, T. and D. Staiger (2012), Gathering Feedback for Teaching: Combining High-Quality Observations with Student Surveys and Achievement Gains, Bill & Melinda Gates Foundation.

[8] Kelly, S. and J. Turner (2009), “Rethinking the effects of classroom activity structure on the engagement of low-achieving students”, Teachers College Record.

[7] OECD (2018), “Student behaviour and classroom management”, in TALIS 2018 results (Volume 1): Teachers and school leaders as lifelong learners, OECD Publishing, Paris, https://doi.org/10.1787/1d0bc92a-en.

[11] Praetorius, A., N. McIntyre and R. Klassen (2017), “Reactivity effects in video-based classroom research: an investigation using teacher and student questionnaires as well as teacher eye-tracking”, in Videobasierte Unterrichtsforschung, https://doi.org/10.1007/978-3-658-15739-5_3.

[4] Schmidt, W., P. Zoido and L. Cogan (2014), “Schooling Matters: Opportunity to Learn in PISA 2012”, OECD Education Working Papers, No. 95, OECD Publishing, Paris, https://dx.doi.org/10.1787/5k3v0hldmchl-en.

[3] van Tartwijk, J. and K. Hammerness (2011), “The neglected role of classroom management in teacher education”, Teaching Education, Vol. 22/2, pp. 109-112, https://doi.org/10.1080/10476210.2011.567836.


← 1. The meaning of scale points for disruptions, routines and monitoring are explained in each section. The overall mean classroom management score is an arithmetic mean of the components and therefore, are not anchored by scale point descriptors.

← 2. Germany* refers to a convenience sample of volunteer schools.

← 3. To compare what was observed with what students and teachers reported, the “Index of Disruptions” was created which included the three statements on the frequency of disruptions (recoded so that high scores indicate rare disruptions) plus two statements on how teachers managed disruptions: “Our teacher (I) reacted to disruptions in such a way that the students stopped disturbing lessons” and “Our teacher (I) managed to stop disruptions quickly”.

Metadata, Legal and Rights

This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. Extracts from publications may be subject to additional disclaimers, which are set out in the complete version of the publication, available at the link provided.

© OECD 2020

The use of this work, whether digital or print, is governed by the Terms and Conditions to be found at http://www.oecd.org/termsandconditions.