Building on cognitive models of information processing, knowledge can be understood as information that is stored in long-term memory after it has actively been processed in working memory (Aamodt and Nygård, 1995; Renkl, 2009). Scientific knowledge about classroom management is stored information about what theory and empirical research suggest to be effective classroom management (Emmer and Stough, 2001; Korpershoek et al., 2016). According to scientific theory, classroom management comprises different management areas that teachers should know about. These areas are (1) the instructional and organizational management, (2) the behavioral management and (3) the social and interactional management of the classroom (Marzano et al., 2003; Everton and Poole, 2008; Piwowar, 2014). Across these areas, classroom management strategies can be categorized along a timeline as to when they are taken, namely preventively or reactively (Everton and Poole, 2008) and as to whether they are acute short-term or long-term actions inside or outside the classroom (Piwowar, 2014).

Scientific knowledge about (1) instructional and organizational management entails knowing a great variety of preventive teacher actions that have been backed up by empirical evidence (Kounin, 1970; Marzano et al., 2003). Teachers must know how to mobilize the whole learning group and ensure smooth transitions between working phases (Balli, 2011). They must continuously scan the classroom and monitor each student’s learning (withitness, overlapping; Kounin, 1970; Piwowar et al., 2013). Procedures give students safety and help to organize classroom activities (Bohn et al., 2004; Everton and Poole, 2008).

The area of (2) behavioral management also comprises preventive strategies that teachers should know about such as setting rules and reinforcing positive behavior (Everton and Poole, 2008; Alter and Haydon, 2017). When disruptive behavior occurs, teachers should first use minimal interventions such as non-verbal actions (e.g., moving closer to the student) before they use reactive strategies (e.g., verbal warnings) that directly disrupt the instructional process (Kounin, 1970; Everton and Poole, 2008; Hue and Li, 2008). Teachers should avoid harsh punishment whenever possible and the sanctions they use should be fair (Everton and Poole, 2008).

Research has also provided valuable insights into what teachers should know about (3) social and interactional management. To build a positive teacher-student-relationship, teachers must know how to demonstrate an adequate level of dominance and an adequate level of cooperation (Evertson and Weinstein, 2006; Wubbels et al., 2006). Being dominant implies having high expectations and being consequent while being cooperative implies having a concern for the students’ needs (Marzano et al., 2003). Teachers should emphasize students’ responsibility in classroom management and rely on personal rapport to influence student behavior (e.g., private discussions; Glasser, 1990; Everton and Poole, 2008; Balli, 2011). Furthermore, teachers should avoid opposing behavior, this means being overly authoritarian (e.g., get angry easily) but also laissez-faire behavior, this means being overly submissive (e.g., being uncertain; Marzano et al., 2003; Wubbels et al., 2006).

Knowledge about classroom management gained from university courses is thought to be scientific knowledge and thus represent the evidence-based contents described in the previous section (Emmer and Stough, 2001; Slavin, 2002; Merk et al., 2017). However, when it comes to real classroom teaching, beginning teachers often do not act according to what is typically taught at university courses (e.g., Allen, 2009; Franke and Wecker, 2017; Merk et al., 2017). Only individual, specific formal teacher education programs seem to succeed in doing so as shown by longitudinal case studies (e.g., Levin and Ammon, 1996). The general lack of university-studies-knowledge-use in the classroom may have several reasons.

One reason could be that pre-service teachers may neither very frequently encounter scientific information about effective classroom management in their studies (only in a few selected courses) nor repeat already encountered information (Jones, 2006; O'Neill and Stephenson, 2011; Adams et al., 2020). Thus, the evidence-based knowledge they gain throughout their formal studies does not become automated knowledge (De Jong and Ferguson-Hessler, 1996; Renkl et al., 1996). Being automated, however, is an important criterion of high-quality knowledge besides being deep level and well-structured (i.e., information being meaningfully grouped together; De Jong and Ferguson-Hessler, 1996). If knowledge does not become automated knowledge, it has to be consciously and costly retrieved from long-term memory before it can be used in a (real) classroom setting (Gaissmaier et al., 2008).

Another explanation could be the way scientific knowledge is taught at university. University teacher education may not show by means of examples or cases how scientific knowledge translates into actual classroom behavior (Zottmann et al., 2013). This may lead to knowledge compartmentalization. In particular, pre-service teachers are not able to connect what they have learned in formal teacher education about classroom management to real teaching situations because the two aspects are stored in different memory compartments (Renkl et al., 1996).

Besides these gaps in the quality of the knowledge, pre-service teachers may not be motivated to use the scientific knowledge that they acquire through their formal university courses. Possibly, they do not perceive its value for practical classroom teaching when it has not been connected to authentic examples from teaching (Wubbels, 1992; Renkl et al., 1996; Siebert, 2005).

Over and above the described explanations, knowledge about classroom management from university studies has to compete with knowledge derived from other sources when it comes to quick decision making in everyday teaching (Korthagen and Kessels, 1999; Allen, 2009). For example, it has to compete with teachers’ practical experiences from their own teaching or from observing that of others.

In contrast to knowledge gained from university studies, knowledge from own (K-12) schooling experiences is knowledge that can be but does not have to be in line with scientific evidence (Zeichner, 1980; Krause and Stark, 2006; Leikin and Levav-Waynberg, 2007). It is knowledge that usually has not systematically been tested or verified by the person who holds it (Fenstermacher, 1994). Real world classroom teaching comprises a great variety of situations that are usually selectively attended to (Balli, 2011). For example, reactive classroom management strategies are more salient than proactive strategies and therefore may more easily be observed and remembered from a student/novice perspective (Balli, 2011; Stahnke and Blömeke, 2021). The actual content of pre-service teachers’ knowledge from their own K-12 schooling experiences, that is what they remember and consider useful classroom management strategies based on their experiences as school students, has rarely been investigated in quantitative empirical studies. An exception presents the study by Balli (2011). The author investigated whether pre-service teachers’ memories of an excellent teacher (whereby excellent was not further specified) from their own schooling reflect scientific classroom management models [e.g., Assertive Discipline model (Canter and Canter, 1992); Withitness and Group Management model (Kounin, 1970)]. The pre-service teachers had to handwrite their episodic memory on a blank form during an introductory teacher education course. The author showed in their sample of 148 pre-service teachers that own K-12 schooling experiences were most strongly focused on establishing rules (and punishment). Furthermore, they were focused on teachers being firm and strict, partly in an adequate, balanced way. There was a weaker focus on other (preventive) strategies such as smooth transitions or withitness as well as on students’ needs and their active role in classroom management. These findings suggest a rather narrow focus of pre-service teachers’ own K-12 schooling experiences on behavior management through rules and a lack of consideration of other evidence-based strategies. However, except for this study, there is little research that gives insights into the actual content of pre-service teachers’ understanding of classroom management based on their own K-12 schooling experiences.

In contrast to knowledge from university studies, knowledge based on own schooling experiences is claimed to more strongly and implicitly guide (pre-service) teachers’ classroom actions (Goodman, 1988; Calderhead and Robson, 1991). This may be explained by the fact that knowledge gained from own experiences is practical knowledge that was built within the context in which it has to be enacted later on (Renkl et al., 1996). Furthermore, it is knowledge that usually has become automated through repeated use or observation (Wubbels, 1992). During their own K-12 education pre-service teachers had plenty of opportunities to observe their teachers dealing with classroom disruptions (Lortie, 1975; Wubbels, 1992). If the assumption is true that knowledge gained from own schooling experiences is rather selective and does not necessarily correspond to scientific evidence, then it would seem problematic if this knowledge strongly guided (per-service) teachers’ classroom behavior.

In our study, we focus on pre-service teachers’ knowledge about classroom management as derived from two different sources: university studies and own K-12 schooling experiences. Knowledge gained from both sources has repeatedly been the focus of research, though partly for different reasons. Knowledge gained from university studies is seldom used in practice by teachers although it is evidence-based (scientific) knowledge (Franke and Wecker, 2017). Thus, research has been concerned with how its use can be fostered. In our study, we draw on a knowledge mobilization task to investigate whether the use of university studies knowledge can be leveraged by means of systematic prior knowledge activation (RQs 1a-c). The underlying assumption is that pre-service teachers have scientific knowledge about effective classroom management stored in their long-term memory but do not automatically use it.

Pre-service teachers’ knowledge gained from their own schooling experiences is thought to consist of content that may not be in line with scientific evidence. At the same time, it is thought to be a deeply rooted belief system that implicitly guides teacher action inside the classroom (Wubbels, 1992) although there are also studies that do not support this assumption and show that other sources of knowledge seem more relevant for guiding classroom management behavior (Levin and He, 2008). Exploring the actual content of pre-service teachers’ knowledge gained from own K-12 schooling experiences and contrasting it with that of knowledge gained from their university studies seems highly relevant and is another focus of our study (RQs 2a-b). We seek to extend the findings by Balli (2011) as we do not only compare the content of pre-service teachers’ own schooling experiences with that of scientific theory but also compare it with the pre-service teachers’ individual university-based knowledge. We focus on an early phase in pre-service teachers’ university studies, that is, a phase when they still remember events from their own schooling but at the same time have already acquired some scientific knowledge. It seems sensible to investigate the two knowledge sources at a time point when they both may guide behavior and therefore can fruitfully be taken up for reflection and contrasted with each other by teacher educators.

The two clusters of research questions (RQs 1a-c and RQs 2a-b) will be investigated in the context of a joint experimental study design. By means of a knowledge mobilization task, pre-service teachers will be either asked to activate knowledge about an effective classroom manager from their university studies, their own schooling experiences or they will not be asked to explicitly activate any knowledge prior to being confronted with written classroom problems. The effects of activating knowledge from university studies (vs. no knowledge activation) on its subsequent use to solve the written classroom problems and the quality of solutions provided to these problems will be investigated to answer RQs 1a-b. We will also investigate whether having activated knowledge from own schooling experiences negatively affects the use of knowledge from university studies (RQ1c). To answer RQ2, the products of the knowledge activation task will be examined. In particular, pre-service teachers’ descriptions of an effective classroom manager based on their own schooling experiences will be contrasted with scientific theory (RQ2a) and with descriptions of an effective classroom manager based on knowledge gained from university studies (RQ2b).

We investigate the two described clusters of research questions, which we formulate as follows.

The sample consisted of 93 German pre-service teachers (74% female, 2% diverse). Participants prepared for different school types: 35.48% prepared for primary school, 36.56% prepared for lower and middle secondary track, 17.20% prepared for the highest secondary track and 10.75% prepared for special education. Most participants were enrolled in their third or fourth semester of their university studies (M = 3.47, SD = 1.72). At this point in their studies, the pre-service teachers have already attended a lecture that covers classroom management as one topic among others. Participation in this lecture is obligatory and the lecture must be completed with a written exam. Thus, as the participants study for the exam and attend the lecture they already acquire a fair amount of scientific knowledge about classroom management although they may not have comprehensive knowledge at this stage of their studies.

Participants rated their prior knowledge about classroom management on average to be 41.38% (SD = 22.46%) on a scale ranging from 0 to 100%. In terms of own practical teaching experiences, 15.1% of the participants reported having no prior practical teaching experience, 39.8% reported having teaching experience from school internships, 36.6% reported having both teaching experiences from school internships and a teaching side job (substitute teaching) and 8.6% reported having teaching experiences from a teaching side job (substitute teaching), only.

Data collection consisted of two waves due to organizational reasons. The larger part of the sample (n = 76) was recruited from a course in the context of initial teacher education in a German university in April 2019 (wave 2). The other part of the sample (n = 17) was recruited from the same German university in November and December 2017 but not within the context of a specific teacher education course (wave 1). The study was implemented fully online and took about 30 min. Participants of wave 2 filled in the questionnaire during a session of the mentioned course; participants of wave 1 filled in the questionnaire in a laboratory at the university. Participants taking part in these two different waves of data collection did not differ in terms of their gender: χ²(2) = 0.95, p = 0.62, semester of university study: t(91) = −0.63, p = 0.53, school type: χ²(3) = 0.50, p = 0.92 and their self-rated prior knowledge about classroom management: t(91) = 1.59, p = 0.12.

A between-subject experimental design was used to investigate the effects of knowledge mobilization on subsequent university studies knowledge use and the provision of evidence-based solutions to authentic classroom problems (RQs 1a-c). Participants were randomly assigned to one of three different conditions. The pre-service teachers had to activate their knowledge about an effective classroom manager from either what they had learned at their university studies (n = 27), from what they remembered about a specific teacher who had been an effective classroom manager during their own K-12 schooling (n = 37) or they did not activate any kind of knowledge prior to being confronted with text-based classroom problems (control group; n = 29; Figure 1). In order to keep testing time equal between the groups, the control group was asked to activate their knowledge acquired during their university studies at the end of the experiment (see Figure 1). The activation task was implemented in such a way that the pre-service teachers had to write down all of the aspects they remembered about the appearance of an effective classroom manager, the general teaching methods of an effective classroom manager and the way they dealt with classroom disruptions. Afterwards, the pre-service teachers were asked to write down solutions to five text-based authentic classroom situations describing classroom management problems. After this task, participants were asked to self-report what kind of knowledge source they had drawn upon to solve the problems.

To answer the research questions in cluster 2 (RQs 2a-b), the products of the knowledge mobilization task (written descriptions of effective classroom manager) were analyzed by means of content analysis and compared between the university-knowledge-activation group and the own-schooling-experiences-activation group. In particular, participants’ descriptions of the way a classroom manager deals with disruptions was analyzed as it is concerned with classroom management in a narrower sense (see Supplementary material 1.1). Figure 1 gives an overview of the study design.

In order to analyze the effects of university study knowledge activation on the subsequent self-reported use of this knowledge (RQ1a), an independent samples t-test was conducted that compared the knowledge-activation-from-university-studies group with the control group (no prior activation of knowledge). To analyze the effects of university study knowledge activation on evidence-based solutions to the text vignettes (RQ1b), an independent samples t-test was used that compared the knowledge-activation-from-university-studies group with the control group (no prior activation of knowledge). To analyze potential negative effects of activating knowledge from own schooling experiences on the self-reported use of knowledge from university studies (RQ1c) an independent samples t-test was used that compared the knowledge-activation-form-own-schooling group with the control group (no prior activation of knowledge).

Descriptive statistics (category frequencies) and multinomial logistic regression, that compared category frequencies of descriptions of an effective classroom manager between the own-schooling-knowledge-activation group and the university-studies-knowledge-activation group, were used to investigate RQ2a and 2b.

Analyses of variance, chi-squared tests, multinomial logistic regression, an independent samples t-test and a Welch-test were used for the preliminary analyses, that is, randomization and implementation check. We set the significance level (alpha) at 0.05.

The preliminary analyses reported in this chapter serve to rule out potential confounding factors that may limit the valid interpretation of the study’s main results. First of all, the three groups did not differ significantly in their self-reported knowledge (self-efficacy) about classroom management prior to the knowledge activation task: F(2, 90) = 0.08, p = 0.92. Furthermore, the groups did not significantly differ in gender: χ²(4) = 4.64, p = 0.33, semester of university study: F(2, 90) = 1.09, p = 0.34, school type: χ²(6) = 2.58, p = 0.86 and high-school GPA: F(2, 88) = 0.61, p = 0.55.

For RQ1a and RQ1b it seemed important to establish that the university-studies-activation group and the control group had the same amount of university-based knowledge about classroom management. If the university-studies-activation group, for example, had more knowledge, then potential positive effects of the manipulation could also be due to that group generally having more knowledge and not due to the activation of this knowledge. We indirectly checked this by inspecting the content of the descriptions of an effective classroom manager generated in the activation task in the two groups. The control group had filled out the activation task after the experiment so that it could not influence their problem solving in the vignette test but also provided us with some insights into their university-studies knowledge about effective classroom management (see Figure 1). A multinomial logistic regression (with 998 as reference category) showed that the groups did not differ in their answers across categories (model fit, χ²(9) = 8.10, p = 0.52) and in the individual categories. In particular, both groups most often named categories 5 (cooperative behavior) and 6 (dominant behavior) which are important aspects of effective classroom management from a scientific perspective (see Supplementary Table 2.1 for more detailed information). Last, we also checked whether either of the two groups seemed to be more committed/motivated to solve the text vignettes by comparing the total number of words the participants wrote in the vignette test. An independent samples t-test revealed that there was no difference in the number of written words between the university-studies knowledge-activation group and the control group, t(54) = −0.28, p = 0.78.

For RQ2b, it seemed important to establish that the activation task had the same difficulty for the own-schooling-experiences-activation group and the university-studies-activation group. An independent samples t-test revealed that there was no significant difference between the groups in terms of how difficult they found activating the respective kind of knowledge, t(61) = 1.23, p = 0.23. Participants in the own-schooling-experiences-activation group as well as those in the university-studies-activation group found it fairly easy to describe how an effective classroom manager/the specific teacher they remembered deals/dealt with classroom interruptions (M_{own schooling} = 3.28, SD_{own schooling} = 1.09; M_{university studies} = 2.96, SD_{university studies} = 0.90). Furthermore, a Welch-test revealed no statistically significant difference between the two groups in terms of how many classroom management strategies of an effective classroom manager/their former teacher they listed, t(43.42) = −1.85, p = 0.07. Participants in the own-schooling-experiences-activation group named on average 2.03 (SD = 0.92) different strategies to deal with classroom disruptions and participants in the university-studies-activation group on average 2.59 (SD = 1.37) strategies.

The results of an independent samples t-test revealed that the two groups (activation of knowledge from university studies vs. no prior activation of knowledge) did not significantly differ in their self-reported use of their knowledge from university studies when solving classroom problems, t(54) = 0.14, p = 0.89, d = 0.04. Thus, despite its activation, the university-studies-knowledge-activation group did not report using this knowledge more intensively to solve the problems from everyday classroom teaching (RQ1a). The descriptive results (means and standard deviations) are presented in Table 1. Supplementary Table 2.2 gives an overview of the other knowledge sources that the participants reported having used.

An independent samples t-test was used to test whether the university-studies-knowledge-activation group provided more evidence-based strategies as solutions to the classroom management problems (vignette test) than the no-prior-activation-of-knowledge group (control group; RQ1b). Prior testing revealed two extreme outliers on the sum score in the vignette test in the control group. Therefore, the t-test was conducted with and without the two outliers. The analysis with the two outliers showed that the sum score in the vignette test did not statistically significantly differ between the two groups, t(54) = −0.91, p = 0.37, d = −0.244. The descriptive results (means and standard deviations) are presented in Table 1. The results did not change when the two outliers were excluded from the analysis, t(52) = −0.11, p = 0.92, d = −0.03. The results did also not change when the individual vignettes (1–5) were each used as outcome variable and not the sum score in the vignette test (see Supplementary material 1.2). Thus, activating what was learned about classroom management at university did not lead to employing more evidence-based strategies to solve classroom problems.

However, a further multiple regression analysis revealed that, independent of group membership and the number of words written in the vignette test, self-reported university studies knowledge use predicted higher sum scores in the vignette test, β = 0.26, t = 2.27, p = 0.03, and thus more evidence-based problem solving. This underlines the importance of university studies knowledge for taking evidence-based actions in the face of classroom problems.

An independent samples t-test was used to test whether activating knowledge from own K-12 schooling experiences led to a reduced use of knowledge from university studies as compared to no prior activation of knowledge (RQ1c). In other words, it was tested whether activating a more practical kind of knowledge that has been acquired from everyday classroom situations (own schooling) negatively affects the use of a more scientific kind of knowledge that has been acquired in a formal setting, namely university studies. The results showed no significant differences between the two groups, t(54) = 0.09, p = 0.93, d = 0.02. Thus, activating knowledge from own schooling did not negatively affect the use of knowledge from university studies. The descriptive results are presented in Table 1.

Table 2 shows the category frequencies for the descriptions of an effective classroom manager by the pre-service teachers. The results of the own-schooling-experiences group are of particular interest here (RQ2a). The category, which was most frequently named in this group, was verbal warning as an acute reactive strategy to classroom disruptions (36.6% of all answers). This was followed by the category punishment comprising 16.9% of all answers. 9.9% of all answers were concerned with some kind of preventive strategy to classroom management and 7% with some kind of opposing behavior. Thus, the answers of the own-schooling-experiences group had a rather strong focus on reactive, opposing and punishing teacher classroom behavior. The answers were less focused on behaviors that are expected to be particularly effective from a scientific theory perspective, that is, preventive strategies of behavioral management including minimal intervention (Korpershoek et al., 2016) and strategies that communicate an adequate level of dominance and cooperation (social and interactional management; Wubbels et al., 2006).

In a further step, the descriptions of an effective classroom manager of the own-schooling-experiences group were compared to those of the knowledge-from-university-studies group (RQ2b). A multinomial logistic regression, in which the two groups were compared (and 998 was used as reference category), showed that the groups differed significantly in their answers (model fit, χ²(9) = 50.62, p = 0.00). Among the different strategies to deal with classroom disruptions significant group differences occurred for the codes verbal warning and dominance. The university-studies group named verbal warning less often (B = −2.34, SE = 0.87, Wald(1) = 7.18, p = 0.01), OR = 0.096 (95%-CI[0.02, 0.53]) and dominance more often (B = 1.90, SE = 0.79, Wald(1) = 5.80, p = 0.02), OR = 6.67 (95%-CI[1.42, 31.23]) than the own-schooling-experiences group. There was no statistically significant difference in any of the other categories between the two groups. For cooperation, the difference between the two groups was only slightly above the significance level, B = 1.32, SE = 0.75, Wald(1) = 3.13, p = 0.08, OR = 3.75 (95%-CI[0.87, 16.22]) with the university-studies group descriptively naming this category more often. The comparison in terms of the category fairness could not be calculated as this category was not mentioned in the own-schooling-experiences group.

In a last step, we wanted to rule out the possibility that the pre-service teachers’ descriptions of an effective classroom manager from what they remembered from their own schooling or their university studies were confounded by their more recent practical teaching experiences (e.g., internships in schools, side jobs). Therefore, we descriptively inspected and contrasted the category frequencies of only those participants who did not report having had any prior practical teaching experiences (n = 13). The results are presented in Supplementary Table 2.3. They align well with the results of the whole sample. The largest descriptive differences between the own-schooling-experiences-group and the university-studies-group showed up in category 2 (verbal warnings) and category 6 (dominant behavior).

A strength of the present study is the application of a knowledge mobilization task to the field of teacher education and testing it in an experimental design. To our knowledge, the suitability of knowledge mobilization tasks to boost performance outcomes (and not the learning process) has so far not been tested in the field of teacher education. Furthermore, the present study is one of the first to investigate the content of pre-service teachers’ knowledge from their own schooling experiences more systematically in a quantitative study. To our knowledge, it is the first study that compares this content with the content of knowledge from university studies.

Despite its strengths, the study has some limitations. First, we did not explicitly assess pre-service teachers’ actual prior knowledge from their university studies, which contrasts with other, related studies (e.g., Kostons and van der Werf, 2015). The pre-service teachers’ knowledge could only be estimated from their answers to the university-studies-knowledge activation task. However, the control group did not work on the activation task until after the vignette task. Thus, their answers might have been influenced by information from the text vignettes.

Another limitation is that the knowledge mobilization task was slightly conceptually different in the two groups. Participants in the own-schooling-experiences-activation group were asked to remember a concrete teacher and their concrete behavior and not a stereotyped image of an effective classroom manager. As there are many different strategies to effectively manage a classroom, this one teacher does not necessarily have to have used all of them. In contrast, describing a generic classroom manager from what was learned at university makes it easier to assemble all aspects of effective classroom management into a complete picture. This should be kept in mind when interpreting the results of the group comparison (RQ2b).

It should be further noted that only the content of pre-service teachers’ knowledge about classroom management was studied and not the type and quality of this knowledge (De Jong and Ferguson-Hessler, 1996). However, different types (e.g., conceptual, procedural, strategic) and qualities (e.g., surface-level, deep-level, declarative, compiled; De Jong and Ferguson-Hessler, 1996) of knowledge may also influence whether the activated piece of knowledge content can productively be applied to a given classroom problem.

Last, the study took place in a university setting. This could have generally increased the use of university studies knowledge in all groups and thus made it more difficult to identify differences between the groups.

The present study revealed that a simple knowledge mobilization task was not effective in increasing pre-service teachers’ use of their knowledge from university studies to solve authentic classroom problems as compared to a control group. As already discussed, one explanation could be that the pre-service teachers may not have had enough knowledge at this point in their studies. Therefore, future research should try to replicate the present study’s findings in a sample of pre-service teachers with a deeper and broader scientific knowledge base and directly assess their degree of prior knowledge some weeks prior to the mobilization task (Kostons and van der Werf, 2015).

Furthermore, future research should find out whether knowledge mobilization is an economic way to increase the ad-hoc use of scientific knowledge in a later stage of teacher training, that is, a teacher’s first weeks of teaching as a full teacher. At this time point, teachers should have already acquired enough scientific knowledge that can be activated but that at the same time can easily become washed out again by forthcoming intensive practical experiences (Allen, 2009). In general, repeated retrieval of university-studies knowledge from memory by means of knowledge activation may possibly increase the use of this knowledge in the long run as the respective information gets consolidated through repeated recall (Tempel and Pastötter, 2021). Furthermore, knowledge mobilization tasks could be investigated as a tool to not only increase pre-service teachers’ use of their classroom management knowledge but also to enhance their learning of new classroom management strategies from texts throughout teacher education. Prior knowledge activation has been demonstrated to increase students’ learning from texts and their acquisition of new knowledge (Renkl, 2009; Gurlitt and Renkl, 2010; Hattan et al., 2023).

The present study has further revealed that pre-service teachers’ knowledge from their own schooling experiences has a rather strong focus on easily observable reactive strategies. Hence, teacher education programs should broaden and complement these strategies by other strategies. A knowledge activation task could, for example, be used in teacher education to make explicit to pre-service teachers the knowledge that they have and compare it to and contrast it with what is learned at university (Goodman, 1988; Balli, 2011). The fact that the pre-service teachers found the knowledge mobilization task easy enough and that it triggered different descriptions based on which kind of knowledge source was activated shows that such a task may principally be used in teacher education to make pre-service teachers reflect upon their activated knowledge.

In order to train pre-service teachers to more strongly focus on preventive classroom management strategies, classroom videos seem suitable (Gaudin and Chaliès, 2015) as they mimic the way in which pre-service teachers have acquired their knowledge during their own schooling, that is through observation. Such videos can be used to explicitly instruct pre-service teachers to either focus on what the teacher in the video did prior to a disruption (preventive strategies) and what they did afterwards (reactive strategies; Kounin, 2006). Thus, an overly strong focus on reactive strategies that may have been built through observation habits during pre-service teachers’ own schooling could be replaced by a professional vision on classroom teaching that more strongly focuses on preventive strategies (Emmer and Stough, 2001; Stahnke and Blömeke, 2021; Wolff et al., 2021). More generally, such videos may help to train the pre-service teachers’ ability to notice and interpret important events in the classroom from an expert perspective (Wolff et al., 2021). They learn to understand and predict how classroom events develop over time and to keep track of multiple events at the same time. In other words, their focus becomes shifted away from single cases of student misbehavior and simply reacting to them (Wolff et al., 2017).

The present study shows that a knowledge mobilization task is not sufficient to increase pre-service teachers’ use of their knowledge from their university studies in critical classroom situations in an early phase of teacher education. However, future research may investigate the suitability of such a knowledge mobilization task to increase scientific knowledge use of (pre-service) teachers that have already acquired a broader knowledge base but that find themselves in critical career phases (e.g., career entry) where knowledge from university studies can easily become washed out again. Furthermore, the present study shows that pre-service teachers’ knowledge about classroom management from their own schooling experiences is rather narrowly focused on easily observable reactive strategies. Therefore, pre-service teachers should critically reflect on it and integrate it with scientific knowledge or other sources of practical knowledge (e.g., own teaching experiences). A better understanding of the actual content of pre-service teachers’ knowledge about classroom management and how the productive use of this knowledge can be fostered holds great potential for increasing future teachers’ classroom management performance.