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Teaching and Teacher Education 33 (2013) 56e68Contents lists availableTeaching and Teacher Education

journal homepage: www.elsevier .com/locate/ tateError management behavior in classrooms: Teachers responses to studentmistakes

Maria Tulis*

Department of Psychology, University of Augsburg, Universittsstr. 10, 86159 Augsburg, Germany

h i g h l i g h t s< Observational data and questionnaires are combined to investigate error climate.< Classroom routines are dominated by adaptive error management behavior.< Only few interactions include emphasizing mistakes as learning opportunities.< More maladaptive patterns of mistake-handling activities in mathematics were found.< Teachers dealing with errors influences students error attitudes and emotions.a r t i c l e i n f o

Article history:Received 24 May 2012Received in revised form1 February 2013Accepted 7 February 2013

Keywords:MistakesError management cultureError climateObservationTeacherestudent interactionEmotions* Tel.: 49 821 598 5610; fax: 49 821 598 5289.E-mail address: maria.tulis@phil.uni-augsburg.de.

0742-051X/$ e see front matter 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.tate.2013.02.003a b s t r a c t

Only a few studies have focused on how teachers deal with mistakes in actual classroom settings.Teachers error management behavior was analyzed based on data obtained from direct (Study 1) andvideotaped systematic observation (Study 2), and students self-reports. In Study 3 associations betweenstudents and teachers attitudes towards mistakes and their impact on students domain specificemotions were investigated. Together, the presented studies contribute to the understanding of theinterplay between teachers everyday instructional routines surrounding mistakes and students beliefsabout (learning from) errors. The findings also emphasize the relevance of how students perceive theirteachers attitudes towards mistakes.

2013 Elsevier Ltd. All rights reserved.1. Introduction

Makingmistakes and overcoming failure are natural elements oflearning processes for all students. A knowledge-based, cognitive-constructivist perspective on learning and instruction presupposesadaptive ways of dealing with errors and learning from mistakes(cf. Hiebert & Carpenter, 1992; Reusser, 2000). If learning isconsidered as an active process that requires practice for bothprocedural as well as conceptual learning, classroom learning en-vironments should encourage students to explore and discuss their(mis-)conceptions. However, little is known about adaptive class-room practices for dealing with errors and the reciprocal effects ofstudents and teachers attitudes towards learning from mistakes.All rights reserved.Research on classroom goal structures (e.g., Gonida, Voulala, &Kiosseoglou, 2009; Roeser, Midgley, & Urdan, 1996) has shownimpressively that classroom practices have an impact on studentsindividual orientations and attitudes. In this sense, it can beassumed that teachers error management behavior in the class-room is likely to influence students attitudes towards learningfrom mistakes (Steuer & Dresel, 2011). For example, teachersmaladaptive ways of handling students mistakes are likely to in-crease students fear of failure and may foster maladaptive moti-vational patterns, such as avoiding academically challengingcourses or experiencing generalized negative emotions in relationto the school subject (e.g., Dweck, 1986; Goetz, Pekrun, Hall, &Haag, 2006). Research on organizational error management sup-ports these assumptions (Degen-Hientz, 2008; Van Dyck, Frese,Baer, & Sonnentag, 2005).

Consequently, teachers need to be sensitive to students errorsand should establish a positive error climate which is constitutedby the quality of everyday classroom experiences within mistake

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M. Tulis / Teaching and Teacher Education 33 (2013) 56e68 57situations. However, there is little empirical research addressinghow teachers respond to student mistakes in classrooms. Althougheveryday classroom situations can be observed systematically,relatively few studies have focused on observations of teacherestudent interactions surrounding mistakes in actual classroom set-tings (cf. Wuttke, Seifried, & Mindnich, 2008). The following ques-tions remain unanswered: Which mistake-handling activities areadaptive, which are maladaptive? Are there domain specific dif-ferences or similarities between teachers? How does teacherseveryday error management behavior influence students subse-quent attitudes towards errors and domain-related emotions?

The goal of this article is to provide first answers to thesequestions. Therefore, patterns of teachers responses to studentmistakes were observed and combined with students self-reports.In particular, three studies are presented: Study 1 aimed to identifyteachers error management behavior in regular everyday class-rooms in three different domains. The purpose of Study 2 was toreplicate the findings of Study 1 for one specific domain in whichthe most adaptive error management behavior was found. In thisStudy, nine videotaped economics lessons were examined andthese observations were combined with students self-reports oftheir perceived error climate in the classroom. Finally, the focus ofStudy 3 was to analyze the impact of teachers error managementbehavior on students own attitudes towards learning from mis-takes as well as associations with students more generalizeddomain specific emotions.

1.1. Error management culture in the classroom

Classroom settings in which constructivist learning approachesare utilized allow for open communication about different solu-tions and, as a result, sharing of error knowledge (i.e., knowledge,how something does not work and what someone does not know).As a consequence, students are able to recognize their mis-conceptions and therefore initiate learning processes. These set-tings are characterized by a positive error culture (Oser &Spychiger, 2005; for an English book review see Minnameier,2006). In contrast, a negative error management culture, whichgenerally eliminates communication about errors and learningfrom mistakes, emerges when students suspect to be negativelyevaluated for their mistakes or when students expect that errorswill be attributed to a lack of skills. For both examples, cultureimplies that there is a system of shared norms and values and a setof common practices (Reichers & Schneider, 1990). The ways inwhich teachers handle mistakes may be nationally embedded andmay differ between countries (Li & Shimizu, 2009; Osborn & Planel,1999; Santagata, 2005; Schleppenbach, Flevares, Sims, & Perry,2007; Stevenson & Stigler, 1992; Stigler & Hiebert, 1999). Forexample, U.S. students produce similar mathematical errors andthe same number of errors as Chinese students, but teachers re-sponses differ significantly (Schleppenbach et al., 2007). U.S.teachers were more likely to follow errors with statements or im-mediate corrections, whereas Chinese teachers asked follow-upquestions to prompt student discussion. Similar to these findings,Stigler and Hiebert (1999) reported that Japanese teachersemphasize the positive function of mistakes and encourage theirstudents to discuss misconceptions.

Whereas a body of empirical research has demonstrated dif-ferences on the macro level, i.e., between countries, there is lessresearch focusing on differences between teachers and betweenschool domains within the same country. It can be assumed thatthe variation of teaching patterns following errors depends on theindividual perception and shared perception of errors in the sociallearning environment of the classroom (e.g., Clarke, Emanuelsson,Jablonka, & Mok, 2006; Givvin, Hiebert, Jacobs, Hollingsworth, &Gallimore, 2005; Le Tendre, Baker, Akiba, Goesling & Wiseman,2001; Pauli & Reusser, 2003; Seidel & Prenzel, 2006). Theoriesand research on classroom goal structures (Ames,1990,1992) provethat actual classroom practices influence students attitudes andbeliefs. A large body of empirical findings demonstrated thatteachers mastery or performance goal directed instructionalpractices influence students individual goal orientations. Consis-tent with this theoretical framework, it is assumed that teacherseveryday error related practices have a substantial impact on errorclimate in the classroom which in turn has an influence on stu-dents attitudes towards mistakes. Teachers attitudes towards(learning from) mistakes establish a positive or negative errorculture in the classroom by determining the kinds of mistake-handling activities that are expected and supported (Cobb,Stephan, McClain, & Gravemeijer, 2001; Depaepe, DeCorte, &Verschaffel, 2006). For example, teachers who provide opportu-nities to discuss students misconceptions and encourage studentsto learn from errors by correcting errors themselves may fosteradaptive ways of dealing with mistakes (Anderson, Hamilton, &Hattie, 2004; Heimbeck, Frese, Sonnentag, & Keith, 2003; Meyer,Seidel, & Prenzel, 2006). Furthermore, it has been shown thatclear standards in the classroom and a trustful and emotionally-safe learning environment are associated with a positive errorculture (Goldin, Epstein, & Schorr, 2007; Spychiger, Kuster, & Oser,2006). Students who are confident that they will not be ridiculedwhen making a mistake are more likely to develop positive atti-tudes towards mistakes and report less negative emotions (e.g.,Edmondson, 1999; Malmivouri, 2006; Tulis & Riemenschneider,2008). In contrast, if teachers ignore or punish students errors,students will avoid taking risks and be more likely to hide theirerrors instead of communicate their misconceptions (Rybowiak,Garst, Frese, & Batinic, 1999).

Reciprocally, teachers (and students) responses to errors arelikely to be influenced by their attitudes towards errors (Rybowiaket al., 1999). A positive attitude towards making mistakes is char-acterized by adaptive affective-motivational, cognitive and behav-ioral approaches to learning from errors (cf. Steuer & Dresel, 2011;Tulis & Ainley, 2011), such as openness to feedback, adaptiveemotional responses to errors, facing and communicating diffi-culties and misconceptions, and failure tolerance (Cannon &Edmondson, 2001; Clifford, 1991; Keith & Frese, 2005; Rybowiaket al., 1999). Similar to the concept of mastery orientation, failuretolerance (Clifford, 1984; Clifford, Kim, & McDonald, 1988) is char-acterized by treating mistakes as learning opportunities andexperiencing less negative affect after failure (Boekaerts, 1993;Diener & Dweck, 1980; Meyer & Turner, 2006; Tulis & Ainley, 2011;Turner, Thorpe, & Meyer, 1998). It can be assumed that teacherserror management behavior has an impact on students individualerror attitudes (Steuer & Dresel, 2011). However, no theoreticalconsensus has yet been reached regarding the conceptualization ofadaptive or maladaptive error management behavior, or di-mensions of a positive error climate, respectively.

The literature on error climate, which includes both teachersbehavior and how individuals deal with errors and social in-teractions, suggests a number of interrelated, but neverthelessdistinguishable aspects of an adaptive learning environment. Inparticular, four teacher-specific error management behaviors areconsidered adaptive. The first, error tolerance by the teacher, in-volves teachers willingness to acknowledge and discuss studentsmistakes. The second, irrelevance of errors for assessment, refers toregarding students mistakes as learning opportunities rather thanas negative indicators for performance. In this sense, errors are notbeing punished but are discussed with the student or with thewhole class in order to use the mistake as a learning opportunity.Third, teacher support following errors includes teachers patience

M. Tulis / Teaching and Teacher Education 33 (2013) 56e6858and support of the student to correct the error by him- or herself.Finally, an absence of negative teacher reactions (verbal and non-verbal) implies that teachers do not express annoyance or ridi-culing students if they make an error (Oser & Spychiger, 2005).Despite this knowledge of best practices, remaining issues includethe occurrence and frequencies of these responses to studentsmistakes, their postulated adaptive or maladaptive nature, andtheir consequences for students individual attitudes towardslearning from errors and emotions. With respect to the first issue, afew observational studies, which are reviewed in the next section,provide first evidence for the frequency of response patterns.

1.2. Empirical findings on teachers responses to student mistakes

Empirical studies concerning teachers error managementbehavior include classroom observations as well as students andteachers self-reports (Heinze, 2005; Santagata, 2005; Spychiger,Mahler, Hascher, & Oser, 1998; Stigler, Gonzales, Kawanaka, Knoll,& Serrano, 1999). Because whole-class discourse situations repre-sent a dominant classroom activity inmany countries (Hiebert et al.,2003), this form of instructional practice has been the focus of moststudies. Video studies, such as TIMSS (Stigler et al., 1999) identifieddifferent teaching patterns regarding students errors in the domainof mathematics (see also Hugener et al., 2009). For example, almost27% of student mistakes in German math lessons (grade 8) weredirectly solved by the teacher, about 48% were returned by theteacher to the students as a challenge and about 10% of themistakeswere ignored (Hiebert et al., 2003; Stigler et al.,1999). Similarly, Oserand Spychiger (2005) found that Swiss teachers, in multiple subjectareas, often try to evade mistakes beforehand or simply correctstudents errors by stating the correct answer. The authors describea common instructional practice, labeled the Bermuda triangle oferror correction (see also Brophy & Evertson, 1974), during whichanother student is asked to answer the question or correct thewrong answer of the first student who responded incorrectly. Thelatter is left behindwithout having the chance to think about and re-correct the error (see Fig.1). Based on data from60 videotapedmathlessons, Santagata (2005) reported that teachers often correct stu-dents mistakes (31% of the time in Italy; 25% of the time in theUnited States). Approximately 30e40% of the time, the student whomade themistakewas asked to correct his error. However, less thanone fourth of the teachers in both countries gave a hint to the stu-dent in order to direct him to the right answer. The phenomenon ofFig. 1. Bermuda triangle of error correction (Oser & Spychiger, 2005).Osers Bermuda triangle of error correction, with teachers redi-recting an incorrectly answered question to another student, wasidentified as one of the most common strategies of U.S. teachers.This response pattern was observed more than 30% of the time.

Overall, the reviewed findings of Hiebert et al. (2003), Santagata(2005), and Stigler et al. (1999) indicate four types of teachers errormanagement behavior (in mathematics): ignoring the error,directly solving the error, returning the correction to the studentwho made the mistake, and redirecting the question to anotherstudent. In these studies, ignoring the error was rarely observed.Although a large body of literature supports the usefulness ofstudying the domain specificity of motivational orientations andattitudes (e.g., Bong, 2001), few studies have focused on domainsother than mathematics. In one study, Mindnich, Wuttke, andSeifried (2008) analyzed video-based observational data from 15German economics lessons held by three teachers. They identified85 error management situations. In contrast to mathematics les-sons, teachers ignored students mistakes or failed to pick up thelearning opportunity in 40% of these situations. Observationalfindings reported by Oser and Spychiger (2005) also suggestdomain specific differences with regards to both the frequencies ofstudent errors and teachers error management behaviors. In his-tory classes, error-correction and learning from errors was lesspronounced than in math classes, although maladaptive responseswere observed infrequently in both domains. These findings sug-gest that teachers attitudes and their responses to mistakes maydiffer between domains. Study 1 aimed to provide further un-derstandings of domain-related differences in teachers (mal-)adaptive error management activities.

2. Study 1

2.1. Aim and research questions

In order to gain insight into teachers error management prac-tices, systematic classroom observations were conducted. For thispurpose, a self-developed coding schemewas used by independentobservers (pairs of undergraduate pre-service teachers) duringreal-time naturalistic/direct observations in regular everyday clas-ses. Coding was based on an observation training protocol andinter-coder reliability was tested (Cohens Kappa). The main goalsof Study 1 were to: (a) describe teachers error managementbehavior in everyday classrooms, and (b) explore differences be-tween three subjects: mathematics, German, and economics.

2.2. Method

2.2.1. Coding schemeTeachers responses to students mistakes were coded into 11

categories. Table 1 shows examples according to each category. Toencompass a broad range of responses, including non-verbal re-actions, the categories were distinct but notmutually exclusive. Thetheoretical distinction between adaptive and maladaptive errormanagement behavior (see 1.1) was adopted based on Spychigeret al. (1998) with the exception that correction by the teacherwas not a priori classified as a maladaptive response pattern. Sixcategories of teacher behaviors were derived based on previousobservations on errormanagement behavior (Mindnich et al., 2008;Santagata, 2005; Stigler et al., 1999) and research literature on errorclimate (Oser & Spychiger, 2005): 1) ignoring the mistake; 2)correction by the teacher; 3) correction by the student; 4) redirectingthe question to another student; 5) negative teacher reactions (ex-pressions of annoyance, ridiculing students); and 6) teacher supportfollowing errors. The latter was divided into (a) emphasizing thelearning potential of themistake by encouraging the student, and (b)

Table 1Categories of teacher responses, absolute frequencies and proportions (Study 1).

Category/Type of response Definition/Examples fo %

Maladaptive [1]Ignoring mistake

The teacher ignores the mistake, switches without any comment to another topic 30 4.0

[2]Criticizing student

The teacher is angry, negative evaluation of the students mistake 39 5.3

[3]Redirecting the question to another student

The teacher picks another student to correct the mistake made by the first student(Bermuda triangle of error correction)

109 14.7

[4]Humiliating/laughing

The teacher laughs, makes jokes of the students answer, humiliates the student 28 3.8

[5]Disappointment/Hopelessness

The teacher is upset, shaking his head, grimacing with pain 33 4.5

[6]Correction by the teacher

The teacher states the correct answer e the error is directly solved by the teacher 117 15.8

Adaptive [7]Discussion with whole class

The teacher starts a discussion with the whole class, asking the whole class for(different) solutions

105 14.2

[8]Correction by the student

The teacher repeats the question and/or gives a hint to the student in orderto get the correct answer(error correction is returned to the student who made the mistake)

160 21.6

[9]Waiting

The teacher waits at least 5 s without reformulating the question or giving a hint 72 9.7

[10]Emphasizing the learning potential

The teacher praises the students thought or approach, highlights positively thestudents active contribution, emphasizes the learning potential of the mistake

26 3.5

[11]Impeding negative reactions from class

The teacher stops negative reactions from classmates (e.g. laughing) and turbulences 22 3.0

Notes. fo: absolute frequencies for each category. %: proportions for each category (S 100%).

M. Tulis / Teaching and Teacher Education 33 (2013) 56e68 59providing time for the student to rethink his answer (waiting).Negative teacher reactions were also divided into two sub-categories: (a) humiliating behavior (e.g., laughing), and (b) expres-sions of annoyance, disappointment or hopelessness. Based onprevious findings on error climate (e.g., Oser & Spychiger, 2005) andattribution theory (Weiner, 1985), both of these subcategories wereconsidered maladaptive because teachers communicate maladap-tive attributional information to their students through theexpression of hopelessness or humiliation following students er-rors. Based on the findings of Meyer et al. (2006) that a strict sep-aration of learning situations, inwhich errors are considered helpfulto trigger discussions about misconceptions, from performancesituations, in which errors are punished and negatively evaluated,also the notion of irrelevance of errors for assessment (Spychigeret al., 1998; see also Steuer & Dresel, 2011) was categorized. Thisidea was operationalized by two observation categories: (a) (reco-ded asmaladaptive behavior) criticizing the student (i.e., punishmentof errors, negative evaluation), and (b) discussionwith thewhole classabout misconceptions underlying the error at hand. The last cate-gory was teachers behavior with respect to impeding negative re-actions from classmates. This category referred to teachersresponses to the other students in the class in order to preventmaladaptive reactions (e.g., laughing). The dominant instructionmethod and structure of each observed lesson was also recorded.

2.2.2. Sample and procedureObserver training was conducted during the university course

accompanying the school practice sessions. Trainingwas administeredtwo weeks before the observations took place and involved viewingand coding videotaped sequences. Undergraduate teaching practiceincludes several hours of direct observations in different classes(different grades and subjects) in order to providepre-service teachersinsights into everyday classroom practices of different teachers. Eachpair of trained observers randomly selected one lesson of 45 min(irrespective of the lesson topic) and used the coding scheme. All real-time observations took place in different German schools in andaroundamidsizeBavarian city. Theywere from Gymnasium schools,which is the school typewith the highest teaching level and academicdemands in the German school system. Classes ranged from grade 5(10e11 years old) to grade 13 (18e19 years old).

Codings were carried out on the basis of event sampling, i.e.coding was induced for every error management sequence whichwas defined as the teachers immediate response (verbal and non-verbal) to a students mistake. Thus, every event that was treated asa mistake by the teacher followed by his/her specific reaction wasregarded as an error management sequence (see Santagata, 2005).In other words, emphasis was placed on the strategies teachersused to handle what they considered as mistakes. Students errorswere mainly identified by the teachers verbal comment (e.g., No,that is not correct., Wrong!) and/or indirectly by non-verbalbehavior (e.g., shaking the head). The coding scheme containedthe above described 11 categories and a timeline, divided into se-quences of 5 min each (minute 0e5, 5e10, 10e15 and so on). As allcodings were based on event sampling, the timeline only served asan orienting guideline for the observers during the lesson.

Observation data for 16 math classes, 17 German classes and 15economics classes were available for further analyses. Fifty-eightpercent of the observed teachers were female (in mathematics:41.7%, in German: 62.5%, in economics: 33.3%). Most of theobserved math classes (46%) were grade 9 and grade 5 (23.1%). Therest of the observedmath lessons were equally distributed over theother grade levels (6, 7, 8, and 10). Most of the German classes weregrade 8 (25%), and grade 5, grade 6, or grade 9 (16.7% each). About12% were grade 11, 8.3% were grade 10 and 4.2% were grade 13. Foreconomics classes, 50% of all lessons were observed in grade 10,with 16.7% in each grade 8, grade 9, and grade 12.

M. Tulis / Teaching and Teacher Education 33 (2013) 56e68602.3. Results

2.3.1. Preliminary analysis and reliabilityInter-coder reliability (Cohens Kappa) was calculated for each

pair of observers. Greve andWentura (1997) report K .75 as goodto excellent, and Landis and Koch (1977) suggest K .80 as almostperfect agreement and .60

Table 2Sample of Study 2.

Teacher Grade/class N students N lessons

A 7 A 30 17 B 30 18 29 1

B 9 A 27 19 B 27 2

C 10 A 17 210 B 16 1

S 176 9

1 Realschule (middle track of the German school system).

M. Tulis / Teaching and Teacher Education 33 (2013) 56e68 61pattern following errors in Study 1, nine videotaped economicslessons (by 3 teachers) were coded by two trained observers toidentify teachers error management behaviors. In addition, to un-derstand the relationship between teachers classroom behaviorand students individual perceptions, questionnaires were used tomeasure students perceptions of their teachers attitudes towardserrors and error climate in the classroom.

Another addition to Study 2 was the observation of studentsaffective responses to their teachers errormanagement behavior. Inparticular, students affective states following the Bermuda triangleof error correctionwere identified using visual cues to examine thepostulated maladaptive effects of this specific teacher responsepattern. We acknowledge that this approach was limited in severalmethodological aspects (e.g., observers were not blind to theteachers responses; observations may be biased because humili-ating teacher behavior is expected to provoke negative affect).However, similar to the category correction by the teacher, bothadaptive and maladaptive effects of redirecting the question toanother student seem plausible. To reduce expectancy bias, ob-servers were not informed about the presumed consequences ofthis response pattern. Analyzing students affective reactions byusing visual cues was perceived as a first attempt to explore theeffects of this specific response pattern. In addition, the followinghypotheses and research questions were addressed in Study 2:

(a) Replication of the findings of Study 1:It was hypothesized that, in general, adaptive teacher responseswould be more frequent than maladaptive responses to studentmistakes.

(b) To what degree do error management patterns vary betweenand within teachers in the same domain (i.e., economics)?It was assumed that errormanagement behavior depends on theinterplay between teachers attitudes towards errors on the onehand and situational/social cues on the other hand. Therefore, itwas hypothesized that the teachers error managementbehavior would differ between classes (see also Stigler et al.,1999). However, as attitudes are often stable, it was expectedthat some responses would be more typical for the teacher and,therefore, more frequently observed than other responses in allclasses taught by the same teacher.

(c) How do observations correspond with students self-reportedperceptions of their teachers error management behavior?It was hypothesized that students self-reports should reflect theobserved error management activities of their teacher. On thebasis of students perceived error tolerance of the teacher (i.e.,the extent of supportive error management behavior by theteacher), we compared the class with the highest values forperceived error tolerance (high error climate class), and theclass reporting the least adaptive mistake-handling activities oftheir teacher (low error climate class). Using ANOVAs, classeswere compared with respect to observational data of theteachers error management behavior, and other dimensions ofstudents perceived error climate, including students own at-titudes towards making mistakes (a detailed description of thequestionnaire follows in 3.2.3). It was hypothesized that adap-tive error responses (correction by the student [6], encouragingstudent [10], waiting [9], and discussion with whole class [7]would be more frequently observed in the high error climateclass. In contrast, maladaptive error management behavior(ignoring mistake [1], criticizing the student [2], redirecting thequestion to another student [3], humiliating/laughing [4], anddisappointment/hopelessness [5] was expected to be observedmore frequently in the low error climate class. Finally, it washypothesized that students in the high error climate classwould have more adaptive error-attitudes.(d) Does redirecting the question to another student have mal-adaptive effects on students subsequent affect?It was hypothesized that the phenomenon Bermuda triangle oferror correctionwould trigger observable negative affect in thestudent who made the mistake.3.2. Method

3.2.1. Sample and procedureThree teachers from a suburban secondary school1 in Bavaria

volunteered for Study 2. They were informed that everydayinstructional practices were the focus of the study. In total, seveneconomics classes from grade 7 to grade 10 were observed; classsizes ranged from 17 up to 30 students (for a detailed descriptionsee Table 2). Nine economics lessons (45 min each) were video-taped. All video datawas coded by two trained observers to identifyteachers error management behavior. In a second analyzing pro-cedure, students affective responses to their teachers error man-agement behavior were coded. In this second observation process,only those students that were addressed by the teachers responsefollowing the error were coded.

3.2.2. Coding schemeThe coding scheme from Study 1 was used. Five categories for

students affective states were also added, coded as positive (thestudents verbal or non-verbal reaction is characterized by a clearlypositive affective state, such as enjoyment, pride, interest or satis-faction), negative (the students verbal or non-verbal reaction ischaracterized by a clearly negative affective state, such as shame,anger, or uncertainty), neutral (no observable reaction), ambig-uous and not observable (e.g., the students face could not beseen or the students verbal response could not be heard).

3.2.3. Error climate questionnaireIn all classes, students perceived error climate was assessed

with a questionnaire comprised of two subscales from the ErrorOrientation Questionnaire (Rybowiak et al., 1999) and four scalesfrom the Error Culture Questionnaire (Spychiger et al., 2006). Intotal, 36 items were rated using a 5-point scale ranging from 1(strongly disagree) to 5 (strongly agree). The following six sub-dimensions of error climate were measured (sample items andinternal consistencies are presented in Table 3): 1) error commu-nication, which assessed students communication and opennessfor discussion of errors and misconceptions with their classmates(three items; Rybowiak et al., 1999); 2) covering up errors, whichmeasured students desire to avoid and hide mistakes (five items;

Table 3Sample items, descriptive statistics and internal consistencies.

Scale Sample items M SD a

Error communication If I cannot rectify an error in economics by myself, I turn to my colleagues. 3.15 .58 .68Covering up errors It is disadvantageous to make ones mistakes public in our economy class. 2.02 .66 .78Error tolerance by the teacher If someone in our economy class does something wrong, the teacher will

patiently explain the problem.In our economy class mistakes are nothing bad for our teacher.

3.17 .50 .73

Error strain/Fear of mistakes I am often afraid of making mistakes in economy.I feel embarrassed when I make an error in my economy class.

1.85 .64 .73

Rule clarity If I get an error feedback in my economy class, I often dont know why.I often do not understand what my economy teacher wants me to do.

3.03 .53 .80

Students attitudes towards errors Mistakes help me to improve in economy.When a mistake in economy occurs, I analyze it thoroughly.

2.81 .52 .73

25303540%

M. Tulis / Teaching and Teacher Education 33 (2013) 56e6862Rybowiak et al., 1999); 3) error tolerance by the teacher, whichassessed the extent of supportive error management behavior bythe teacher, including explanations, patience and help (sevenitems; Spychiger et al., 2006) and addressed the attitude of theteacher to avoid and hide his/her own mistakes (two items); 4)error strain/fear of mistakes, which addressed whether students fearthe occurrence of errors or react to errors with anxiety and shame(five items; Spychiger et al., 2006); 5) rule clarity, which measuredperceived transparency of norms versus uncertainty regarding theteachers expectations and standards (eight items; Spychiger et al.,2006); and 6) students own attitudes towards (learning from) errors(eight items; Spychiger et al., 2006).

3.3. Results

3.3.1. Preliminary results and reliabilityInter-coder reliability (Cohens Kappa) for all observations was

K > .85 and therefore satisfactory. Teacher-centered, whole-classinstruction was observed most of the time in all classes, withthe exceptionof a short seatwork sequence inone class and a10-min-phase of collaborativeworkwith pairs of students in another class. Ingeneral, bivariate correlations between the six subdimensions (seeTable 4) were in the expected directions and demonstrated the in-dependence of the selected error climate variables. The highestpositive correlations (r .55) emerged between error tolerance bythe teacher and students attitudes towards (learning from) errorsand rule clarity, respectively. Furthermore, error tolerance by theteacher was positively associated with communication about errorsin the class. Students who reported an adaptive error-attitude re-ported high perceived rule clarity, high communication about errors,and low covering up errors. Rule clarity was negatively associatedwith error strain and with covering up errors, and both latter vari-ables were negatively related to error tolerance by the teacher.However, error strain was not significantly correlated with studentsattitudes towards errors or with communication about errors.

3.3.2. Teachers error management behavior and studentsperceptions

A frequency analysis indicated that a total of 174 teacher re-sponses (Mclass 19.33, SD 4.47) were coded for 118 mistake-

Table 4Bivariate correlations.

(1) (2) (3) (4) (5)

(1) Error communication(2) Covering up error e.12(3) Error tolerance by the teacher .21** e.43**(4) Error strain/Fear of mistakes e.08 .31** e.21**(5) Rule clarity .09 e.51** .55** e.49**(6) Students attitudes towards errors .20** e.46** .55** e.07 .40**

Notes. N 176 students.**p < .01.management sequences (i.e., Mclass 13.11 mistakes occurred ineach class, SD 4.11). Negative reactions of the classmates were notobserved. As depicted in Fig. 3,maladaptive behavior (categories [1]e[5]) was generally observed less frequently than adaptive responsesto studentsmistakes (categories [7]e[10]), except the phenomenonof Bermuda triangle of error correction,which was coded in 35% ofall responses. Correction by the teacher [6] accounted for 15.5% of allcoded responses, followed by correction by the student [8] (12.6%),discussion with whole class [7] (10.3%), waiting [9] (9.8%) andemphasizing the learning potential of the mistake [10] (9.2%).

To address the question of differences in error managementbehavior within teachers, profiles based on relative frequencies foreach teacher were examined (Table 5). Regarding maladaptive re-sponses, all teachers showed a similar patternwith one exception: Inclass 9B (teacher B) 25% of error responseswere coded as criticizingstudent [2] and 10% of the teachers responses to studentsmistakeswere coded as humiliating/laughing [4], as depicted in Fig. 4.Regarding adaptive error management behavior, results indicateddifferences between and within teachers, especially for the cate-gories correction by student [8], waiting [9] and emphasizingthe learning potential [10]. For these categories, percentages ofobserved occurrence varied between classes, ranging from 0 to 27%.

Finally, students attitudes and perceived error climate werecompared between the low and high error climate classes. ANOVAresults revealed differences between class 9B (low error climate)and class 8 (high error climate) in error tolerance by the teacher(F(6, 167) 2.190, p .046, h2partial .07), students attitudes to-wards errors (F(6, 167) 2.243, p .042, h2partial :08), andcovering up errors (F(6, 167) 8.895, p < .001, h2partial :24).Students in class 8 reported little need to avoid or hide errors, andreported feeling supported by the teacher as well as a positiveattitude towards mistakes. This is in line with the observationalfindings, showing that the teacher of class 8 encouraged students to05

101520

[1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11]

Notes. Category numbers are explained in Table 1.Maladaptive responses: categories [1] [5], [3] = Bermuda triangle of error correction.Adaptive responses: categories [7] [11], [6] = Teacher states the correct answer.

Fig. 3. Economics teachers response pattern to students mistakes (% of all responses).

Table 5Proportions of different responses by teacher.

Maladaptive responses (%) Adaptive responses (%)

Teacher [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] S

A 2.0 0.0 27.4 0.0 0.0 19.4 5.1 23.6 8.3 14.2 0.0 100%B 5.4 9.9 33.1 3.3 0.0 13.3 10.3 5.2 7.1 12.4 0.0 100%C 0.0 1.5 41.2 0.0 0.0 16.6 11.9 12.1 14.2 2.5 0.0 100%

Notes. Category numbers are explained in Table 1.Maladaptive responses: categories [1]e[5], [3] Bermuda triangle of error correction.Adaptive responses: categories [7]e[11], [6] Teacher states the correct answer.

M. Tulis / Teaching and Teacher Education 33 (2013) 56e68 63correct the error by themselves by giving a hint or reformulatingthe question more often than the teacher of class 9B. Moreover, inclass 8, error correction was more often returned to the studentwho made the mistake. Twice as much as in class 9B, the teacher ofclass 8 directly corrected the mistake by himself and only in thelow error climate class, negative responses were observed, suchas criticizing, humiliating or laughing by the teacher (Table 6).Interestingly, redirecting the question to another student to correctthe mistake was observed more frequently in class 8 (high errorclimate), whereas discussions with the whole class about themistake and different solutions were coded more than twice inclass 9B.

3.3.3. Students affectFrequency analyses of students affective reactions to their

teachers error management behavior (see Fig. 5) show thatteachers maladaptive responses were consistently followed bynegative affect. As expected, students who were criticized [2], hu-miliated or ridiculed [4] after making a mistake explicitly showednegative reactions. More importantly, redirecting the question toanother student [3] was also commonly followed by negative affectFig. 4. Error response patterns of teaexpressed by the student who made the mistake. These negativereactions were also observed when the whole class was asked tofind the right solution [7]. In contrast, students who were encour-aged to learn from their mistakes [10] or students who were givenmore time to think about the correct answer [9] exclusivelyexpressed positive affective reactions. Interestingly, repeating thequestion to the student who made the mistake and guiding thestudent to find the correct answer [8] triggered both positive andnegative affective reactions. Mixed results were also observedwhen the error was directly corrected by the teacher [6].

3.4. Summary of the findings of Study 2

In summary, the results of Study 2 replicated the findings ofStudy 1, identifying more adaptive than maladaptive responses tostudent mistakes by economics teachers. However, a high per-centage of all responses (35%) were categorized as the Bermudatriangle of error correction.Observational results were generally inline with students perceived error climate measured by ques-tionnaire. One exception was that redirecting the question toanother student was observed more frequently in the high errorcher A, teacher B and teacher C.

Table 6Comparison of classes with high- and low error climate.

Dimensions High error climate (class 8) Low error climate (class 9B)

M (SD) M (SD) t(55) pSelf-reports Students attitudes towards errors 3.07 (0.64) 2.63 (0.53) 2.828 .007

Error tolerance by the teacher 3.41 (0.40) 3.03 (0.67) 2.349 .023Covering up errors 1.84 (0.62) 2.57 (0.71) 4.142 .000Error communication 3.20 (0.75) 3.27 (0.57) 0.449 .656Error strain/Fear of mistakes 1.82 (0.61) 1.82 (0.55) 0.048 .962Rule Clarity 3.12 (0.55) 3.03 (0.60) 0.628 .533

% Observed % ObservedObservations [1]

Ignoring mistake4 0

[2]Criticizing student

0 25

[3]Other student/redirecting question

36 25

[4]Humiliating/laughing

0 10

[5]Disappointment/hopelessness

0 0

[6]Correction by the teacher

20 10

[7]Discussion with whole class

4 10

[8]Correction by the student

16 5

[9]Waiting

4 5

[10]Emphasizing the learning potential

16 10

[11]Impeding negative reactions from classmates

0 0

0% 20% 40% 60% 80% 100%

[10][9][8][7][6][5][4][3][2][1]

positive negative neutral, ambiguous or not observable

Notes. % of observed affective reactions.Category numbers are explained in Table 1.Maladaptive responses: categories [1] [5], [3] = Bermuda triangle of error correction.Adaptive responses: categories [7] [11], [6] = Teacher states the correct answer.

Fig. 5. Students affective reactions to teachers error management behavior.

M. Tulis / Teaching and Teacher Education 33 (2013) 56e6864climate class than in the low error climate class, and observa-tional results point to its negative affective consequences. Profilesof error response patterns suggest differences between and withinteachers. Similar to Meyer et al. (2006), maladaptive reactions ofthe classmates did not occur in these observations.4. Study 3

4.1. Aim and hypotheses

The focus of Study 3 was to analyze the impact of perceivederror management behavior on students own attitudes towardslearning frommistakes, as well as associations with studentsmoregeneralized emotions in one specific subject (mathematics).Mathematics was chosen for three reasons. First, mathematics is asubject in which making errors is an essential part of learning, andthe distinction between right and wrong is more pronouncedthan in other subjects. Second, a large body of research has shownthat students report less positive emotions in this domain (e.g.,Middleton & Spanias, 1999). It can be assumed that dealing withmistakes in the mathematics classroom not only has an impact onstudents attitudes towards mistakes but also on students domainspecific emotions. Third, Study 1 revealed more maladaptive errorresponses by math teachers compared to other domains.

Questionnaires were conducted 4 weeks after the beginning ofthe school year (time 1) and 5 months later (time 2). Students self-reported attitudes, perceived error tolerance by the teacher, anddomain specific emotions (anxiety, anger, boredom and enjoy-ment) were assessed at both measurement points. In particular, itwas hypothesized that students error-related attitudes at time 2would be influenced by the perceived attitude and error manage-ment behavior of their teacher at time 1, after controlling for stu-dents attitudes towards mistakes at time 1. Furthermore, it washypothesized that students individual beliefs about making mis-takes at time 1 would impact their math-related emotions at time2. Specifically, an adaptive attitude towards errors was assumed tobe negatively associated with subsequent domain specific anxiety,anger, and boredom, and positively associated with enjoyment.

4.2. Method

As in Study 2, perceived error climate in themath classroomwasassessed using the error tolerance by the teacher scale (seven items;Spychiger et al., 2006). Students attitudes towards errors (eightitems) were also assessed with the same scale used in Study 2. Allitems were presented on a 5-point scale ranging from 1 (stronglydisagree) to 5 (strongly agree). Internal consistencies (Cronbachs

Table 7Hierarchical regression analysis predicting students attitude towards error at time2.

Predictor Model 1 Model 2

B SE b B SE b

Students attitude towardserrors (time 1)

0.59 0.046 .50*** 0.56 0.047 .47***

Error tolerance by theteacher (time 1)

0.15 0.056 .11**

R2/DR2 .25/.25*** .26/.01**

Notes. Dependent variable is students attitude towards errors (time 2), ***p < .001;**p < .01.

M. Tulis / Teaching and Teacher Education 33 (2013) 56e68 65alpha) were satisfactory (a .71 and a .82, respectively). The twosubscales were positively correlated at time 1 (r .29) and time 2(r .36), respectively (p < .01). Students math-related emotions eanxiety (eight items), anger (eight items), boredom (nine items),and enjoyment (six items) e were measured with the AcademicEmotions Questionnaire e Mathematics (Pekrun, Goetz, Titz, &Perry, 2002). Responses were given on a 5-point scale rangingfrom 1 (strongly disagree) to 5 (strongly agree). Internal consis-tencies were satisfactory (.86 < a < .94). Bivariate correlationsshowed the expected directions at both measurement points:Positive associations among all negative emotions (.50 < r < .75)and negative associations between enjoyment and negative emo-tions (.38 < r < .65).

4.2.1. Sample and procedureStudents from 25 fifth grade classrooms (N 685 students) at

25 different schools2 in Bavaria participated in Study 3. The pro-portion of female students was 54% and the average age was 10.4years (SD 0.61). Class size ranged from 19 to 32 students. Studentparticipation was voluntary and with parental agreement. Datawere collected 4 weeks after the beginning of the school year (time1) and at the end of the first term (i.e., after 5 months, time 2). Allmeasurements were operationalized with respect to the subject ofmathematics.4.3. Results

In order to analyze the impact of error management behavior onstudents individual error-related attitudes, hierarchical linearregression analysis was performed. Students attitudes towardserrors at time 2 were used as the dependent variable. Studentsattitudes towards errors at time 1 (model 1) and teachers errormanagement behavior perceived by the students at time 1 (model2) were entered block-wise in the analysis. The results indicate thatteachers dealing with mistakes has a substantial influence onstudents perception of errors as learning opportunities at time 2(see Table 7).

Hierarchical linear regression analyses were applied to examineassociations between domain specific emotions at time 2 and at-titudes towards errors (time 1), controlling for students emotionsat time 1. For each emotion, separate regressions were calculated(see Tables 8e11). Even after controlling for students emotions atthe beginning of the school year, students attitude towards mis-takes was a significant negative predictor of all negative emotions(anger: b .08, anxiety: b .17, boredom: b .21) and apositive predictor of enjoyment (b .13) at the end of the first halfof the school year.Table 8Hierarchical regression analysis predicting students anxiety at time 2.

Model 1 Model 2

B SE b B SE b4.4. Summary of the findings of Study 3

In summary, the findings from Study 3 emphasize the positiveimpact of teachers error management behavior on students ownattitudes towards learning from mistakes. Furthermore, associa-tions between these attitudes and domain specific emotions havebeen found. Students who hold an adaptive orientation towardstheir mistakes are more likely to report positive domain specificemotions (and less negative emotions) in mathematics. This is inline with other research findings that highlight the importance of2 Eleven classes from Hauptschule, which is the school type with the lowestacademic demands in the German school system and 14 classes of Gymnasium(with the highest teaching level and academic demands) were involved. It shouldbe noted that in the Bavarian school system, students meet with a new teacher aftertransitioning from grade 4 to grade 5.positive attitudes towards mistakes for positive emotional statesduring learning (Tulis & Ainley, 2011).

5. General discussion

The presented studies aimed to examine an activity funda-mental to students learning and everyday experiences in theclassroom: teachers dealing with mistakes. The three empiricalstudies in this article build upon each other: Study 1 addressed thegeneral occurrence of error management behavior in everydayclasses and focused on the frequency of teachers adaptive andmaladaptive error management activities. On this basis, video ob-servations within one specific domain (economics classes) wereconducted to replicate these findings (Study 2). Observational datawas also combined with students self-reports of perceived errorclimate in Study 2. In addition, the phenomenon called Bermudatriangle of error correction (Oser & Spychiger, 2005) and itspostulated maladaptive effects on students affect was examined.Finally, Study 3 analyzed the impact of students perceived errormanagement behavior of their teacher at the beginning of theschool year on students own attitudes towards learning frommistakes and domain-related emotions at the end of the first term.

The current findings contribute to existing attempts for atheoretical conception of error management behavior and respec-tive error climate in several ways. First, the results provide evidencefor a broad range of adaptive versus maladaptive responses (Oser &Spychiger, 2005; Rybowiak et al., 1999; Steuer & Dresel, 2011).Although limited due tomethodological aspects, findings regardingstudents affective reactions point to the maladaptive nature ofredirecting the question to another student (Bermuda triangle oferror correction, cf. Oser & Spychiger, 2005). However, furtherresearch using enhanced measurements of students emotionsshould explicitly focus on this issue to confirm these findings. Withrespect to adaptive responses, students in all domains were oftenencouraged to correct the mistake by themselves (see also Hiebertet al., 2003; Santagata, 2005). Thus, it seems that adaptive errormanagement behavior is not a question of the school subject.Nevertheless, in all domains and especially in mathematics,teachers place little emphasis on the learning potential of errorsthrough positive acknowledgment of incorrect solution strategies.Anxiety (time 1) 0.61 0.033 .64*** 0.60 0.033 .63***Students attitude towards

errors (time 1)0.12 0.053 .08*

R2/DR2 .40/.40*** .41/.01*

Notes. Dependent variable is students self-reported anxiety in mathematics (time 2),***p < .001; *p < .05.

Table 11Hierarchical regression analysis predicting students enjoyment at time 2.

Model 1 Model 2

B SE b B SE b

Enjoyment (time 1) 0.69 0.035 .65*** 0.62 0.040 .58***Students attitude towards

errors (time 1)0.27 0.076 .13***

R2/DR2 .42/.42*** .43/.01***

Notes. Dependent variable is students self-reported enjoyment in mathematics (time2), ***p < .001.

Table 9Hierarchical regression analysis predicting students anger at time 2.

Model 1 Model 2

B SE b B SE b

Anger (time 1) 0.65 0.036 .63*** 0.61 0.037 .58***Students attitude towards

errors (time 1).30 0.062 .17***

R2/DR2 .39/.39*** .42/.03***

Notes. Dependent variable is students self-reported anger in mathematics (time 2),***p < .001.

M. Tulis / Teaching and Teacher Education 33 (2013) 56e6866These findings, combined with the results of Study 3, highlight theimportance of including these aspects of adaptive error manage-ment into teacher training.

Secondly, the results of Study 3 indicate that how teachersdeal with mistakes has a substantial influence on studentsperception of errors as learning opportunities and, in turn, onstudents domain specific emotions. Together, these findingscontribute to the understanding of the interplay between teach-ers everyday instructional routines surrounding mistakes andstudents beliefs about (learning from) errors. They emphasize therelevance of students perceptions of their teachers error-relatedattitudes. In Study 2, students perceptions of their teachers er-ror tolerance corresponded to observational findings of theteachers actual error management behavior, and error toleranceby the teacher was positively correlated with students attitudestowards errors. On the other hand, both, error tolerance by theteacher and students attitudes were negatively associated withcovering up errors. Thus, the current findings provide evidencethat students adopt error-related attitudes based on theireveryday experiences with their teachers management of mis-takes e similar to how classroom goal structures influence stu-dents individual goal orientations (e.g., Gonida et al., 2009).However, no significant correlation between error strain andstudents attitudes towards learning from errors were found inStudy 2. It is possible that students hold an adaptive view aboutlearning from mistakes but nevertheless try to avoid making(public) errors in order to avoid negative evaluations. Futurestudies are needed to investigate the relationship betweendifferent components of teachers behaviors regarding studentmistakes and students error-related attitudes.

Third, the current findings demonstrate that overall, teachersresponses to students errors are more often adaptive than mal-adaptive (with the exception of the Bermuda triangle of errorcorrection). This is in line with other observational findingsfocusing on mistake-handling activities (e.g., Hiebert et al., 2003;Santagata, 2005). However, previous studies were mainly con-ducted in the domain of mathematics. The current findings suggestthat the dominance of adaptive teacher behavior is also true forother subjects.

Although maladaptive patterns of teacher-responses were lessfrequently observed, they were found more often in mathematicsTable 10Hierarchical regression analysis predicting students boredom at time 2.

Model 1 Model 2

B SE b B SE b

Boredom (time 1) 0.62 0.039 .58*** 0.55 0.039 .52***Students attitude towards

errors (time 1)0.38 0.067 .21***

R2/DR2 .33/.33*** .37/.04***

Notes. Dependent variable is students self-reported boredom in mathematics (time 2),***p < .001.than in the other two domains, suggesting domain specific differ-ences. One explanation might be that errors may be more salient inmath classrooms because solutions are either correct or incorrect.Incorrect solutions may be more negatively evaluated in mathe-matics than in other subjects because of this either correct orincorrect view. It has been shown that teachers instructionalpractices are related to their beliefs about their subject (e.g., Staub &Stern, 2002). Another explanation may be that math teachers aremore likely to follow an error prevention approach to avoid therecall of erroneous or misleading information (cf. Ayers & Reder,1998). Further replication of domain specific differences in teach-ersmaladaptive error management behavior is required before anyconclusions can be drawn. However, the presented findings dosuggest that we need to investigate differences in error manage-ment behavior between different school subjects. Results of Study 2emphasize that future studies should also control for context spe-cific (i.e., class specific) differences. Therefore, studies should bedesigned to investigate error management behavior and errorclimate between different subjects but within the same class andteacher. It was also found that most of class time was spent onteacher lecturing and class work discourse. As this instructionalpractice is common in many countries (e.g., Hiebert et al., 2003;Stigler et al., 1999) and teachers error responses are an essentialelement of the classroom climate, the coding scheme developed tomeasure teachers error management behaviors can be applied indifferent countries.

6. Limitations

The presented findings are limited in some aspects. First, videobased observational data were not used in Study 1 for economicand feasibility reasons. Although direct observations demonstratedgood inter-rater reliability, real-time assessments are at risk ofobservation bias. Second, as Study 1 did not focus on a specialschool subject, different domains were analyzed but no detailedinformation about each lesson topic was collected. It could beargued that the lesson topic (e.g., algebra versus geometry inmathematics) may affect the type and frequency of students mis-takes, which might have an impact on teachers error managementbehavior. However, empirical studies point to the likelihood thatteachers everyday error management behavior in classes is notrelated to specific topics or the kind of students mistakes(Santagata, 2005). Third, differences between teachers within thesame domain were not addressed in Study 1. Although this wasconsidered in Study 2, gender-related differences were notaddressed in any of the current studies. Male or female teachersmay differ in their error management behavior, and teachers re-sponses to male or female students errors might also differ. Forexample, studies investigating teachers gender-related beliefs ofstudents success and failure in mathematics indicate disadvan-tages for girls (e.g., Tiedemann, 2000). In addition, students per-ceptions of teachers error management behavior might beinfluenced by individual learner characteristics, such as gender or

M. Tulis / Teaching and Teacher Education 33 (2013) 56e68 67achievement level. For example, there is empirical evidence sug-gesting that low-achieving students perceive their teachers as lesspositive than high-achievers (e.g., Ditton, 2002).

Study 2 investigated video-taped lessons of the same schoolsubject and three lessons of each teacher. However, it is unclear towhat degree these findings generalize to other domains. Moreover,as teachers participation was voluntary in Study 2, the sample isnot representative. It can be assumed that the involved teachers areopen-minded to research studies. However, they had to beconvinced before participating in the study (in consideration ofstrict data privacy). Therefore, an extraordinary selection effect canbe excluded.

Study 3 provided longitudinal data that emphasized the in-fluence of perceived error climate on students attitudes towardslearning from errors. However, these correlational findingsshould be corroborated by more controlled, experimentaldesigns.

7. Implications for practice and future research

Students day-to-day experiences are mainly determined bythe practices commonly used by their teachers. Regarding teach-ers responses to students mistakes, different e but mainlyadaptive practices e were observed. However, teachers conceptsand beliefs of how to deal with students mistakes should beexamined in future research. It can be assumed that teachers donot hold explicit conceptualizations of their error attitudes andrespective error management behavior (Santagata, 2005; VanDyck et al., 2005). For example, they may follow an error pre-vention approach instead of viewing errors as learning opportu-nities. In the current studies, teachers placed little emphasis onthe learning potential of errors. Video-based data could be usedfor teacher professional development and interventions (e.g.,Mason & Scrivani, 2004) to demonstrate different error manage-ment practices in classrooms. For example, Heinze and Reiss(2007) conducted a training program about the productive useof mistakes in the mathematics classroom for students learningfrom mistakes.

Moreover, students should be encouraged to discuss andcommunicate their errors and misconceptions. For example,Spychiger et al. (1998) suggest interventions aiming at the reap-praisal of mistakes to highlight the learning opportunities of errors.Frese and his colleagues also investigated the effects of expliciterror management instructions that emphasized the positivefunction of errors (Heimbeck et al., 2003; Keith & Frese, 2005).Recent research on error training (Bourgeois, 2008; Campbell,2007) has addressed the mediating effects of emotion control onlearning outcomes. Therefore, investigating students emotions andtheir ability to regulate negative emotions after failure is an inter-esting task for future research (see Tulis & Ainley, 2011).

Finally, concern with students mistakes is an importantelement of instructional and teaching competence. Insight intostudents individual misconceptions and positive support after er-rors are necessary for individualized instruction. However, adaptiveerror management provided by teachers is one component ofcreating and sustaining learning situations that support active andindividualized learning processes (De Corte, 2003; De Corte, Greer,& Verschaffel, 1996). Studentsmistakes may serve as guidelines forteachers to adapt instruction to students knowledge (Stern, 2005).Identifying the conditions under which students adaptive attitudestowards errors can be enhanced may help to ensure continuedengagement and deep understanding. Therefore, it is important tofocus on the way teachers deal with mistakes in everyday class-rooms as well as students perceptions of their teachers errormanagement behavior.Acknowledgments

This work was supported by the Department of Psychology,University of Bayreuth. I thank all observers for their assistance incarrying out the studies and I wish to sincerely thank the reviewersfor the comments on the initial submission.References

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Error management behavior in classrooms: Teachers' responses to student mistakes1. Introduction1.1. Error management culture in the classroom1.2. Empirical findings on teachers' responses to student mistakes

2. Study 12.1. Aim and research questions2.2. Method2.2.1. Coding scheme2.2.2. Sample and procedure

2.3. Results2.3.1. Preliminary analysis and reliability2.3.2. Teachers' error management behavior in different school subjects

2.4. Summary of the findings of Study 1

3. Study 23.1. Aim and research questions3.2. Method3.2.1. Sample and procedure3.2.2. Coding scheme3.2.3. Error climate questionnaire

3.3. Results3.3.1. Preliminary results and reliability3.3.2. Teachers' error management behavior and students' perceptions3.3.3. Students' affect

3.4. Summary of the findings of Study 2

4. Study 34.1. Aim and hypotheses4.2. Method4.2.1. Sample and procedure

4.3. Results4.4. Summary of the findings of Study 3

5. General discussion6. Limitations7. Implications for practice and future researchAcknowledgmentsReferences