Edited by: Cheryl J. Craig, Texas A&M University, United States
Reviewed by: Tracy X. P. Zou, The University of Hong Kong, Hong Kong; Eliza Pinnegar, Independent Researcher, Orem, United States
This article was submitted to Teacher Education, a section of the journal Frontiers in Education
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Classroom professional vision is a teaching skill that refers to the ability of teachers to rapidly notice information in class and engage in knowledge-based reasoning about the noticed information. Knowledge-based reasoning includes three interrelated processes: description, explanation, and prediction. The present study aimed to examine how pre-service teachers, in-service teachers, and school principals differed in these three reasoning processes after viewing classroom photographs with varying presentation time and interactional complexity. A 3 × 2 × 4 factorial design was used. Teacher expertise (pre-service teachers vs. in-service teachers vs. school principals) was a between-group factor, presentation time (1 vs. 3 s) and complexity (teacher vs. dyad vs. small group vs. whole class) were within-group factors. Analysis of verbal reports suggested that in-service teachers and school principals used significantly more episodic knowledge, content knowledge, and pedagogical content knowledge in their reasoning than pre-service teachers did. Explanations with mathematical content knowledge were more frequent for in-service teachers, for shorter rather than longer presentation times, and for photographs showing the teacher only. Explanations with pedagogical content knowledge were more frequent for in-service teachers, for shorter rather than longer presentation times, and for photographs showing a small group. Across time and complexity, school principals verbalized less frequently what they noticed. In-service teachers and school principals verbalized significantly more self-monitoring and more predictions of teacher actions than pre-service teachers. The study findings contribute to the growing body of evidence on classroom professional vision, teacher noticing, and visual teacher expertise, and provide initial evidence on expert teachers' frequent metacognitive self-monitoring.
Classroom professional vision is the ability of teachers to rapidly notice information in class and engage in knowledge-based reasoning about the noticed information (Van Es and Sherin,
Charles Goodwin developed the concept of
Even before Goodwin (
These classroom situations can vary in interactional complexity. For example, in mathematics education, sometimes a teacher works closely with a single student, forming a student-teacher dyad. At other times, students work in small groups of four or five. And sometimes the teacher uses direct instruction to teach the whole class simultaneously. These different levels of interactional complexity—teacher, student-teacher dyad, small group, whole class—have different processing demands in working memory. Pre-service teachers in particular are likely to experience cognitive overload in highly complex scenarios given their relative lack of experience (Kim and Klassen,
In conceptualizing professional vision, Seidel and Stürmer (
First, description refers to verbalizing selected information of a given classroom situation and represents the ability to say what is perceptually noticed without additional explanations. For example, teachers might verbalize that they see a small group of students engaged in a mathematical problem-solving task.
Second, explanation refers to verbalizing interpretations of the selected information and represents the meaning making of a classroom situation. Explanation processes include the organization of selected information, professional knowledge, and metacognitive self-monitoring. Particularly, selected pieces of information are organized in working memory into mental models of the perceived classroom situation. These organized mental models are further enriched and integrated with professional knowledge retrieved from long-term memory; types of professional knowledge are, to take the same example, episodic knowledge of previous teaching experiences, content knowledge of mathematics problems, and pedagogical content knowledge of math problem-solving in small student groups. Importantly, processes of organizing selected information and integrating mental models with professional knowledge are supported through self-monitoring. For example, teachers might use metacognitive strategies to monitor and self-evaluate the accuracy of their explanations.
Third, prediction refers to future-oriented consequences of the explained classroom situations. Predictions can be oriented toward consequences for student learning and subsequent actions that might unfold after the observed scene. For example, participants can predict what teachers do next, or offer alternative actions they would take to manage the observed classroom situation.
Seidel and Stürmer (
The aim of this study was to explore knowledge-based reasoning as a component of classroom professional vision. Based on Seidel and Stürmer's (
To answer this research question, we recruited 74 people (43 female, 31 male) on three levels of expertise: 25 pre-service teachers, 24 in-service teachers, and 25 school principals. The pre-service teachers (16 female, nine male) had a mean age of 23.84 years (
Participants viewed a set of photographs showing problem-solving situations in eighth grade mathematics education. The photographs were video stills created from the validated video material of Hugener et al. (
The study included two tasks:
Measures in this study included participants' demographic variables and verbal reports. Demographic variables were measured with a paper-and-pencil questionnaire, with one question each to report participant age (in years) and gender. Additionally, pre-service teachers were asked in which semester they studied while in-service teachers were asked for their years of teaching experience (in years).
Verbal reports were measured with a voice recorder. Trained student assistants transcribed the voice recordings verbatim and coded the transcripts. Codes were segmented following Strijbos et al.'s (
Coding scheme.
Selecting information | SI | “I see a teacher and a student talking” | Teachers, students, class, classroom |
Organizing selected information | OI | “The student doesn't seem to understand” | Student understanding, teacher engagement, classroom management |
Retrieving episodic knowledge | RE | “Once I made the same experience” | Once, in my experience, happened in my lessons |
Retrieving content knowledge | RC | “The circular equation is…” | Cuboid, three-dimensional fields, geometry |
Retrieving pedagogical content knowledge | RP | “In math education, you secure the results by…” | Cognitive activation, group work, learning atmosphere, feedback |
Self-monitoring | SM | “I'm not sure, I would like to look at the picture again” | Unsure, look again |
Teaching actions | TA | “Now the teacher can…” / “If I was the teacher, then…” | Predictions of teacher actions |
Before starting data collections, participants signed consent forms and reported their demographic background. Participants were then comfortably seated with ~60–80 cm monitor distance. They were informed that the study included two tasks, that they would be viewing photographs of eighth grade mathematics classes, and that photographs would switch automatically. Participants viewed one photograph as a practice trial before the data collection started, to assure they were familiar and felt comfortable with the procedure; this practice trial was not included in the analysis. At the end, participants were given opportunity to ask questions about the study's aims and background and were thanked for their participation. The data collections were performed in individual sessions and took ~35 min per person.
An alpha level of 0.05 was used for the statistical tests. Three-way analyses of variance with the factors expertise, time, and complexity were performed for all verbal codes.
Means (and standard deviations) of verbal codes.
Overall | 0.93 (1.11) | 1.17 (1.18) | 0.00 (0.06) | 0.05 (0.22) | 0.22 (0.51) | 0.05 (0.22) | 0.01 (0.09) |
All | 1.38 (1.15) | 1.41 (1.14) | 0.00 (0.06) | 0.07 (0.25) | 0.31 (0.58) | 0.05 (0.21) | 0.01 (0.13) |
Teacher | 1.51 (1.27) | 1.12 (1.03) | 0.00 (0.00) | 0.22 (0.42) | 0.15 (0.36) | 0.03 (0.16) | 0.03 (0.23) |
Dyad | 1.15 (1.22) | 1.49 (1.22) | 0.01 (0.12) | 0.04 (0.20) | 0.28 (0.65) | 0.05 (0.23) | 0.00 (0.00) |
Small Group | 1.39 (1.06) | 1.49 (1.23) | 0.00 (0.00) | 0.00 (0.00) | 0.47 (0.68) | 0.04 (0.20) | 0.01 (0.12) |
Whole Class | 1.48 (1.03) | 1.51 (1.03) | 0.00 (0.00) | 0.01 (0.12) | 0.32 (0.55) | 007 (0.25) | 0.00 (0.00) |
All | 0.78 (1.05) | 1.09 (1.19) | 0.00 (0.07) | 0.04 (0.21) | 0.19 (0.48) | 0.04 (0.23) | 0.01 (0.07) |
Teacher | 0.80 (1.05) | 0.61 (0.83) | 0.00 (0.00) | 0.10 (0.33) | 0.10 (0.32) | 0.04 (0.23) | 0.00 (0.07) |
Dyad | 0.79 (1.10) | 1.08 (1.21) | 0.01 (0.09) | 0.02 (0.13) | 0.14 (0.44) | 0.05 (0.23) | 0.00 (0.07) |
Small Group | 0.78 (1.06) | 1.40 (1.18) | 0.00 (0.07) | 0.04 (0.19) | 0.31 (0.58) | 0.03 (0.17) | 0.00 (0.00) |
Whole Class | 0.77 (1.24) | 1.27 (1.31) | 0.00 (0.07) | 0.00 (0.00) | 0.21 (0.53) | 0.05 (0.27) | 0.01 (0.12) |
Overall | 1.00 (1.26) | 1.37 (1.44) | 0.01 (0.12) | 0.09 (0.33) | 0.25 (0.60) | 0.12 (0.36) | 0.02 (0.14) |
All | 1.41 (1.34) | 1.62 (1.41) | 0.03 (0.16) | 0.12 (0.37) | 0.39 (0.87) | 0.10 (0.35) | 0.04 (0.21) |
Teacher | 1.50 (1.24) | 1.39 (1.24) | 0.00 (0.00) | 0.33 (0.56) | 0.38 (1.29) | 0.13 (0.45) | 0.04 (0.21) |
Dyad | 1.01 (1.13) | 1.57 (1.16) | 0.04 (0.21) | 0.13 (0.38) | 0.35 (0.66) | 0.06 (0.29) | 0.04 (0.21) |
Small Group | 1.51 (1.47) | 1.68 (1.64) | 0.03 (0.17) | 0.00 (0.00) | 0.51 (0.83) | 0.06 (0.24) | 0.04 (0.27) |
Whole Class | 1.64 (1.41) | 1.86 (1.55) | 0.03 (0.17) | 0.01 (0.12) | 0.33 (0.53) | 0.16 (0.37) | 0.01 (0.12) |
All | 0.87 (1.20) | 1.29 (1.44) | 0.01 (0.10) | 0.08 (0.31) | 0.21 (0.48) | 0.13 (0.36) | 0.01 (0.12) |
Teacher | 0.95 (1.20) | 0.65 (0.84) | 0.00 (0.07) | 0.22 (0.50) | 0.11 (0.34) | 0.19 (0.43) | 0.02 (0.14) |
Dyad | 0.84 (1.18) | 1.52 (1.61) | 0.01 (0.12) | 0.05 (0.22) | 0.20 (0.49) | 0.13 (0.39) | 0.02 (0.14) |
Small Group | 0.94 (1.28) | 1.46 (1.58) | 0.00 (0.07) | 0.04 (0.22) | 0.35 (0.57) | 0.09 (0.32) | 0.01 (0.12) |
Whole Class | 0.75 (1.13) | 1.53 (1.41) | 0.02 (0.14) | 0.02 (0.17) | 0.19 (0.46) | 0.10 (0.31) | 0.00 (0.07) |
Overall | 0.61 (0.97) | 1.30 (1.32) | 0.03 (0.16) | 0.04 (0.21) | 0.25 (0.56) | 0.08 (0.29) | 0.04 (0.21) |
All | 0.85 (0.13) | 1.57 (1.25) | 0.03 (0.16) | 0.07 (0.26) | 0.41 (0.70) | 0.06 (0.26) | 0.04 (0.20) |
Teacher | 0.76 (1.04) | 1.09 (0.99) | 0.00 (0.00) | 0.27 (0.45) | 0.24 (0.54) | 0.05 (0.23) | 0.03 (0.16) |
Dyad | 0.73 (1.28) | 1.85 (1.26) | 0.01 (0.12) | 0.03 (0.16) | 0.28 (0.53) | 0.08 (0.32) | 0.04 (0.20) |
Small Group | 0.89 (1.05) | 1.67 (1.31) | 0.04 (0.20) | 0.00 (0.00) | 0.63 (0.85) | 0.03 (0.16) | 0.04 (0.20) |
Whole Class | 1.01 (1.16) | 1.67 (1.31) | 0.05 (0.23) | 0.00 (0.00) | 0.51 (0.74) | 0.07 (0.30) | 0.05 (0.23) |
All | 0.53 (0.90) | 1.21 (1.32) | 0.02 (0.16) | 0.03 (0.19) | 0.20 (0.49) | 0.09 (0.30) | 0.04 (0.21) |
Teacher | 0.61 (0.80) | 0.87 (1.09) | 0.02 (0.15) | 0.09 (0.34) | 0.17 (0.48) | 0.11 (0.32) | 0.05 (0.22) |
Dyad | 0.59 (1.03) | 1.47 (0.56) | 0.01 (0.09) | 0.02 (0.13) | 0.17 (0.44) | 0.08 (0.28) | 0.04 (0.21) |
Small Group | 0.47 (0.90) | 1.20 (1.21) | 0.03 (0.16) | 0.02 (0.13) | 0.28 (0.60) | 0.10 (0.34) | 0.03 (0.19) |
Whole Class | 0.45 (0.84) | 1.26 (1.32) | 0.04 (0.20) | 0.00 (0.00) | 0.16 (0.41) | 0.06 (0.24) | 0.05 (0.24) |
Concerning the code SI (selecting information), there was a significant expertise × time interaction,
Concerning the code OI (organizing selected information), there was a significant main effect of expertise,
Concerning the code EK (retrieving episodic knowledge), there were main effects of expertise,
Concerning the code CK (retrieving content knowledge), there were significant expertise × complexity,
Concerning the code PCK (retrieving pedagogical content knowledge), there were significant main effects of expertise,
Concerning the code SM (self-monitoring), there was a significant main effect of expertise,
Concerning the code TA (teaching actions), there was a significant main effect of expertise,
Based on Seidel and Stürmer's (
The major findings demonstrated, first, that in-service teachers and school principals engaged in more knowledge-driven reasoning than pre-service teachers. Particularly in-service teachers verbalized more instances in which they used episodic knowledge, content knowledge, and pedagogical content knowledge to explain the observed classroom situation (Hypothesis 1b). Both groups of experts also produced a higher number of predictions than pre-service teachers did (Hypothesis 1c). These outcomes are in line with Carter's et al. (
The present study extends Carter et al.'s work because it includes a second expert group: school principals. While in-service teachers and school principals were comparable in many verbal codes, an important difference emerged for selecting information (Hypothesis 1a): school principals verbalized less frequently what they saw than in-service and pre-service teachers. This difference could be attributable to the task of many school principals to evaluate, feedback, and counsel the teaching of their teaching staff in school inspections (Tarelli et al.,
A strong expertise difference emerged for self-monitoring strategies, with more metacognitive verbalisations of in-service teachers and school principals compared with pre-service teachers. Research in related domains indicates that self-monitoring is a characteristic of expertise, for example in sport (MacIntyre et al.,
The findings suggest that presentation time and complexity moderated the reasoning process. Differences were, however, not in the expected direction: while we hypothesized that longer presentation times would result in more verbalizations (Hypothesis 2a), the opposite was the case, with fewer verbal codes in the
Implications of the study are associated with expertise theory and teacher education. In terms of theoretical implications, evidence associated with the coding scheme reported here helps develop finer categories of the three dimensions description, explanation, and prediction (Seidel and Stürmer,
In terms of practical implications, the findings signal that metacognitive self-evaluations are associated with expertise. Teacher education programs in universities and higher education institutes can use this finding to focus not only on developing noticing and reasoning skills, but also on developing self-monitoring skills of pre-service teachers during internships and practical school training (Mertens and Gräsel,
Limitations of the study are associated with the material and verbal report data. First, the material—photographs of classroom situations—copied the material used in Carter's et al. (
In conclusion, this study explored knowledge-based reasoning of pre-service teachers, in-service teachers, and school principals based on their rapid processing of briefly presented classroom scenes situated in eighth grade mathematics education. The significance of the study is associated with (a) identifying metacognitive self-monitoring as an important part of classroom professional vision and (b) comparing the understudied group of school leaders and principals with the frequently studied groups of pre-service and in-service teachers. The study findings contribute to the growing body of evidence on classroom professional vision, teacher noticing, and visual teacher expertise, and provide initial evidence on expert teachers' self-monitoring strategies. Future research is encouraged to extend these first steps reported here to the examination of cognitive and metacognitive processes involved when teachers notice and interpret classroom information.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.
Ethical review and approval was not required for the study on human participants in accordance with the local legislation and institutional requirements. The patients/participants provided their written informed consent to participate in this study.
AG designed the study and drafted the manuscript. AG und MS collected and analyzed the data. AG, DL, EL, and HG edited the manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
1This group included four external evaluators who performed ministerial school inspections. Differences in demographic variables were non-significant, so we grouped the twenty-one principals and four evaluators.