Abstract
Student perceptions of teaching quality have become increasingly important for measuring teaching effectiveness and can be used for the subsequent improvement of teachers’ teaching. However, measuring teaching quality through student perceptions reliably and validly and the subsequent improvement is not guaranteed. On the one hand, students’ teaching quality data are influenced by many characteristics of the students, classes and measurement instruments, and on the other hand, teachers’ use of the feedback data is influenced by factors such as personality, context and data characteristics. This chapter, therefore, provides important insights into measuring teacher effectiveness through student perceptions, risks and opportunities of using these teaching quality perceptions and the effective use of student feedback data for the development of teaching and teachers.
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1 Introduction
Within schools, teaching quality is one of the most important factors in student achievement (Nye et al., 2004; Rivkin et al., 2005). Thus, in order to address the decline in student achievement all over the world (OECD, 2014), increased emphasis has been placed on examining teaching quality and improving teacher effectiveness (Timperley et al., 2007). Teaching quality can be determined in several ways; for example, through lesson observations by external observers to analyze student achievement growth, or by teacher self-evaluation. All of these approaches have their advantages and disadvantages.
In addition to the above-mentioned methods, student perceptions of teaching quality have become increasingly important for measuring teacher effectiveness (Bell & Aldridge, 2014; Ferguson, 2012; Goe et al., 2008). Students’ ratings for a lesson can be used for conducting research on, for example, the effectiveness of classroom interventions, and, to a limited extent (see Part III), for accountability purposes at schools. Moreover, with the student ratings, teachers can identify where improvement of their teaching is still possible and they can make their teaching more effective for student learning (Gärtner, 2014; Peterson et al., 2000). Student perceptions are thus considered very helpful for developing instructional quality. For example, in the early years of teacher effectiveness research, Gage (1960) studied sixth grade teachers receiving information as to how their students described their actual and their ideal teacher. More recently, Bell and Aldridge (2014) investigated the use of student perception data for teacher reflection and classroom improvement, and Mandouit (2018) used action research to investigate the impact of student feedback on teacher practices. A recent meta-analysis of student feedback intervention studies was able to show that, on average, the use of student feedback on teaching can indeed generate a significant, albeit small, positive effect on teaching quality as viewed from the student’s perspective (Röhl, 2021). Notably, the systematic literature search for this meta-analysis revealed that, with the exception of one study from Turkey, only intervention studies from Western countries were found, even though student perceptions are assumed to be as effective for measurements of teaching quality and learning environments in Eastern countries and cultures as well (e.g., Khalil & Aldridge, 2019; Maulana et al., 2012).
Some issues have been raised concerning the reliability and validity of students’ perceptions for assessing teaching quality. Various statistical techniques can be used to correct for these problems, namely, Classical Test Theory, Item Response Theory or Generalizability Theory. These techniques function as being exemplars for the connection between psychometric theories and the different perspectives on the validity of student perceptions (Bijlsma et al., 2021).
However, the arguments for and against the use of student ratings as a basis for improving teaching have been going on for some time now. And even if student ratings were guaranteed to be accurate measures of teaching quality, the ratings cannot in themselves support improvement of individual teaching performance (Loeb, 2013). For improvement to occur, it is also necessary for teachers to meaningfully reflect on the feedback they receive and use it to develop and implement improvement-oriented actions.
Therefore, in this chapter, we first present a process model of the use of student feedback in schools that visualizes its productive use for the improvement of teaching quality. This model illustrates that, on the one hand, the teaching quality data are influenced by several characteristics of the students, classes, and measurement instruments, and, on the other hand, teachers’ use of the feedback data is influenced by factors such as personality, context and data characteristics. The advantage of this model lies in its cyclic way of looking at student feedback utilization by teachers, instead of a linear approach, used, for example, by Gärtner (2014), and which further does not consider factors influencing students’ perceptions and feedback. Following this, we present an overview of the empirical literature on peculiarities of student perception data, especially concerning validity, reliability and potential factors influencing student ratings, and discuss how these measurement characteristics should be considered by teachers when using student ratings of teaching quality for the improvement of their teaching. This is followed by an overview of factors influencing the utilization of student feedback for the improvement of teaching and teachers. Lastly, we consider the conditions under which teachers’ process of collecting, interpreting and accepting the data, and subsequent teaching improvement can be accomplished. Opportunities for further research are presented.
In this chapter, thus, we give an overview of the literature, focussing on what we know about student feedback on teaching and what teachers should keep in mind when they perceive and utilize the feedback for their professional development and improvement of teaching. With this overview, we aim to provide important insights into measuring teacher effectiveness through student perceptions, risks and opportunities of these teaching quality perceptions, and the effective use of student feedback data for the development of teaching and teachers.
2 Process Model of Student Feedback on Teaching
The process of using students’ teaching quality ratings to improve instructional quality has many necessary stages and is influenced by many individual and contextual factors, starting with the specifics of obtaining information about teaching quality using student perception questionnaires. To make sure that the information available in the teaching quality data actually leads to professional development of teaching, the teachers must transform the information into improvement-oriented actions. Such actions include giving special attention to possible areas of improvement during lesson preparation or teaching, attending targeted training courses, asking colleagues for advice, or looking for ways to improve the teaching situation together with the students (for an overview, see Röhl, 2021; Bijlsma et al., 2019b). Unfortunately, receiving feedback does not automatically lead to improvement processes. Röhl et al. (2021) summarized findings from organizational psychology on productive feedback use (Ilgen et al., 1979; Kahmann & Mulder, 2011; Kluger & DeNisi, 1996; Smither et al., 2005) in a model to visualize teachers’ feedback use processes (Fig. 6.1).
Process model of student feedback on teaching. (Source: Röhl et al., 2021, p. 4)
Once the feedback information is available, the teacher has to perceive, understand, and interpret the data. Teachers need a form of data literacy (Kippers et al., 2018; Mandinach & Gummer, 2013) to interpret the information in feedback reports correctly. Additionally, reactions to received feedback have not only cognitive, but also affective components (Kahmann & Mulder, 2011; Taylor et al., 1984). Therefore, during this interpretation process, positive emotions such as satisfaction and joy, or negative ones such as dissatisfaction or defensiveness can occur as emotional effects. On the cognitive level, knowledge effects can occur when feedback provides the teacher with new information about the students’ view of their teaching or the feedback reinforces their existing knowledge.
The new knowledge is linked to the teacher’s own perceptions and standards for teaching. Any discrepancies must be considered (i.e., the feedback that contradicts one’s own perceptions) in order for the teacher to consider changes in their teaching. This could lead to the teacher’s planning and goal-setting for the elimination of a discrepancy in a possible area of improvement (Smither et al., 2005), which could finally result in improvement-oriented actions as behavioral effects of the feedback. This process on the part of the teacher represents, in a sense, the bottleneck for realizing the potential of student feedback for teaching improvement. This process is influenced by factors concerning the students and classes, the teacher, and the organizational context, the importance of which for the practice of student feedback use we discuss below.
3 Factors Associated with Student Perception Measurements
Perceptions of the quality of the same teaching practices differ between students. These differences are not undesirable per se, because ratings do reflect a student’s personal perspectives on teaching quality, and students do differ (Kenny, 2004). Insight into the extent to which differences in student ratings are related to factors on the student, teacher and class levels is important for evaluating the ratings students give and avoiding any incorrect conclusions. For example, the average teaching quality score can be lower in a class with many low-performing students without the teaching quality actually being lower. Female teachers might receive significantly lower ratings from male students although they are doing as good a job as male teachers do. In the following section, we discuss factors associated with student perceptions of teaching quality on four levels: characteristics of students, teachers, classes and measurements.
3.1 Student Characteristics
Some research has reported that teachers at both the primary and secondary school levels were viewed as more dominant, more positive and more cooperative by girls than by boys (Den Brok et al., 2006; Fisher et al., 2006; Levy et al., 2003; Rickards, 1998; Veldman & Peck, 1969). However, it is not clear to what extent the gender effect is confounded with the effects of other variables, as gender seems to interact with a number of other variables, such as students’ subject preferences (Baker & Leary, 1995; Jones & Kirk, 1990), ethnicity or culturally-related gender role definitions (Levy et al., 2003; Timm, 1999; Worthington, 2002) and level of academic performance (Brophy & Good, 1986; Goh & Fraser, 1995; Levy et al., 2003). Student age was found to be related to student perceptions of their teacher, as older students tend to perceive their teachers as more strict and noted more teacher dominance than their younger peers in some studies (Levy et al., 1997; Levy et al., 2003). Moreover, students with higher general interest in the subject are more likely to give a higher rating of teaching quality than students with lower interest (Cashin, 1988; Fisher et al., 2006). Students’ achievement was also found to be related to their perceptions of their teacher: Students with high prior achievement tend to perceive the quality of their teacher’s teaching more positively than students with low prior achievement (Atlay et al., 2019; Bijlsma et al., 2022; Gärtner & Brunner, 2018; Marsh, 2007). Additionally, the level of parental education and wealth of the students should be considered, as a study by Atlay et al. (2019) pointed towards a negative association of these characteristics with student perceptions of their teachers’ behavior.
3.2 Teacher Characteristics
Mixed results have been found for teacher gender influencing student ratings of teaching quality. Veldman and Peck (1969) found a significant but weak effect of teacher gender, showing that female secondary school teachers tend to receive higher ratings than their male colleagues, but this effect was only found for being ‘friendly and cheerful’ and not for other aspects of teaching quality. Bijlsma et al. (2022) did not find any significant effects of gender on student ratings. They studied effects of teacher popularity on student perceptions of teaching quality and found that the more popular the teacher is according to their students, the higher students’ ratings of their teaching qualities. This relationship was also addressed by Gärtner (2014), Gärtner and Brunner (2018), Clausen (2002), Fauth et al. (2014), Goe et al. (2008) and Donahue (1994). In addition, teachers with more teaching experience receive higher teaching quality ratings from their students than teachers with little teaching experience (Bijlsma et al., 2022; Brekelmans et al., 2002; Day et al., 2008; Kini & Podolsky, 2016; Leigh, 2010; Rowley, 2003). Other variables mentioned in the literature that might influence student ratings of their teacher are teachers’ cultural and ethnic background, whereby teachers from another ethnic background than the student receives lower teaching quality ratings (den Brok et al., 2002; den Brok et al., 2003), teachers’ personality, whereby more stressed teachers are rated as less socially oriented (Klusmann et al., 2006), and teachers’ teaching ability or capacity, whereby lower ability or capacity results in lower teaching quality ratings (Veldman & Peck, 1969).
3.3 Class Characteristics
Compared to the student and teacher factors, less is known about class-level factors influencing students’ perceptions of teaching quality. Class size might be related to differences in student ratings, as teachers might have more difficulty with classroom management in large classes, which is reflected in the students’ teaching quality ratings. In a study by Levy et al. (2003), however, it appeared that class size was negatively related to student perceptions of teacher proximity and unrelated to their perceptions of teacher influence. According to Bijlsma et al. (2022), class size also did not matter for the students’ perception of teaching quality. However, according to Göllner et al. (2020), classes with higher proportions of boys and lower mean achievement levels had lower teacher scores for classroom management. Fisher et al. (2006) found that students in highly motivated classes had more favorable perceptions of their teachers. Moreover, they concluded that class composition variables such as percentage of students with a migration background seemed important for differences in student ratings (on average, those classes rated their teachers lower). Bijlsma et al. (2022) however, did not find an impact of the ethnic make-up of the class on students’ perceptions of teaching quality. Other class-level variables that are related to student perceptions of teaching quality are the subject being taught by the teacher (Gärtner & Brunner, 2018; Veldman & Peck, 1969) and the class’ average level of academic achievement (Bijlsma et al., 2022; Veldman & Peck, 1969).
3.4 Measurement Characteristics
Although a student perception questionnaire can be seen as text material in normal language (i.e., textual information presented in the form of separate items; Tourangeau et al., 2000), existing student perception questionnaires differ fundamentally in their linguistic complexity, which shapes student responses (Göllner et al., 2021; Krosnick & Presser, 2010; Tourangeau et al., 2000). It can therefore be argued that differences in student ratings of their teaching quality arise because students encounter difficulties in comprehending the questionnaire items. For example, items that include many linguistic features, including surface aspects (e.g., the length of words and sentences) and characteristics that require more linguistic analysis (e.g., the number of complex noun phrases) can be difficult to understand. Moreover, an item’s referent (the subject to which an item refers) and addressee are two salient characteristics that might affect the information obtained from student ratings of teaching quality. Measurement characteristics also refer to the frequency of measurements (time between the assessments; Gärtner & Brunner, 2018) and to the anonymity of the ratings (Gärtner, 2014).
4 Interpreting and Analyzing Student Feedback Data
Insight into the factors related to differences in student perceptions of teaching quality as presented in Sect. 3 can strengthen the general awareness among teachers of the required nuanced and careful interpretation of student feedback (Bijlsma et al., 2022; Den Brok et al., 2006). For example, if a teacher receives high teaching quality ratings from their students, it is good to be aware that this could have to do with, for example, being a good teacher, popularity (for some reason), or the fact that there are many high-performing or highly motivated students in the class in question. In lower grades teachers’ interpretation of very positive ratings regarding their teaching quality should be more cautious than in the higher grades, as teachers’ proximity to younger students might be greater than their proximity to older students, which might cause a strong effect on teaching quality ratings. Of course, not all of the factors presented above always represent a bias in reported teaching quality. For example, it is to be expected that teachers with a higher level of experience will also have higher reported teaching quality, and that teachers with a high level of stress will find it more difficult to deliver lessons of a high quality.
In addition to gaining knowledge of the factors influencing student perceptions for the most valid interpretation of the feedback received, it is advisable for teachers to disclose the feedback received to the class. By doing so, the teacher can ask directly about specific conspicuous aspects and how these results are to be interpreted from the class’s point of view. Although this may remove the veil of anonymity for student respondents, the information in the feedback can be exploited, for example, by identifying and clarifying misunderstandings of item formulations and other rating biases.
Scientific findings have indicated that not only the mean values, but also the consensus of students’ ratings on teaching quality within classes is predictive for learning achievement (Schweig, 2016). Thus, if students’ answers to an item differ strongly within a class, this can be seen as an important indication of possibilities for improving one’s own teaching in this respect.
As called for in many places (AERA, APA, & NCME, 2014; Bell, 2019; Hill et al., 2011), the validity of student perception measures should always be considered in light of the purpose of data collection. The following situations can be distinguished: (a) teachers voluntarily searching for feedback on their own initiative, (b) student feedback delivered to teachers as established practice or given by the organization, but without official accountability purpose, and (c) student feedback with accountability purposes (Röhl & Gärtner, 2021). The interpretation and analysis of formative student feedback to teachers with the purpose of professional development must be clearly distinguished from any form of summative evaluation, assessment, or rating that is used for administrative decisions.
5 Relevant Conditions for Teachers’ Utilization of Student Feedback
Careful interpretation of the student feedback data is included in the Process Model of Student Feedback on Teaching (presented in Sect. 2 of the chapter) by teachers’ reflection and action phases and subsequent improvement of teaching quality. In order words, teachers may utilize the feedback data to work on improving their instruction.
Many findings and theories from feedback research point to the relevance of both individual teacher characteristics and organizational characteristics for teachers’ use of student feedback for improving teaching quality. In this section, we will outline relevant factors influencing teachers’ use of student feedback from both an organizational psychology perspective (Ilgen et al., 1979; Smither et al., 2005) and a data-based decision-making perspective (Brunner & Light, 2008; Schildkamp & Lai, 2013; Schildkamp et al., 2013).
5.1 Characteristics of Feedback Recipients (Teachers)
Empirical findings show that teachers’ age and professional experience affect teachers’ use of student feedback. In general, older teachers seek less collegial feedback (Kunst et al., 2018; Runhaar et al., 2010) and use feedback less often compared to younger teachers (Ditton & Arnold, 2004). Teachers with longer professional experience are more skeptical of the usefulness of feedback (Dretzke et al., 2015). Some findings on gender effects regarding feedback show that female teachers more often seek collegial feedback (Runhaar et al., 2010) and tend to improve their teaching more after receiving and utilizing student feedback (Buurman et al., 2018). Teachers with higher self-efficacy seek more feedback and are more willing to reflect upon it (Ditton & Arnold, 2004; Runhaar et al., 2010). Moreover, teachers’ motivation to use the feedback data for improving teaching quality is a relevant factor (Bijlsma et al., 2019a), as well as teachers’ data literacy (their ability to understand numerical or other data and translate them into actions; Mandinach & Gummer, 2016; Schildkamp et al., 2017). Other individual characteristics of teachers that might foster the processing and use of student feedback are high mastery goal orientation (Elliott & Dweck, 1988), lower level of perceived stress (Ditton & Arnold, 2004; Elstad et al., 2015), and more positive attitude towards students’ trustworthiness or competence as feedback providers (Balch, 2012; Ditton & Arnold, 2004; Elstad et al., 2017; Ilgen et al., 1979).
5.2 Characteristics of the Organization (School)
A feedback culture is generally defined by different organizational characteristics, such as support for giving and interpreting feedback, a non-threatening atmosphere, shared valuing of feedback for improvement, team psychological safety, and support in understanding feedback, setting goals, and implementing them in practice. In general, a well-established feedback culture has proved to be effective for the use of feedback in organizations (London & Smither, 2002). In the context of student feedback, in particular, those intervention studies that provided supportive measures for reflection and teaching development showed significantly higher positive effects (Röhl, 2021). In all of this, leadership plays an important role in feedback usage processes (Röhl & Gärtner, 2021). In an educational setting, it is important that school leaders have a clear vision of the schools’ future, inspire teachers in their work, give the work a greater sense of meaning, and stimulate the questioning of old assumptions (transformational leadership; Bass, 1985; Runhaar et al., 2010). Active encouragement by school leaders to seek student feedback is also supportive, as extrinsically motivated feedback use is as beneficial to reported improvements in teaching as is intrinsically motivated feedback use (Gärtner, 2014; Röhl & Gärtner, 2021). However, it is important to ensure that the use of feedback is communicated as an opportunity for development and not as control or accountability, as the latter can lead to resistance to its use (Elstad et al., 2017). School leaders should also give teachers the feeling of autonomy to make decisions about their instruction in data-use processes in schools (Prenger & Schildkamp, 2018).
5.3 Characteristics of Feedback Information (Data)
With regard to the characteristics of the feedback message, the comprehensibility, valence, specificity and timing of the feedback data are relevant in the processing and use of feedback (Röhl & Gärtner, 2021). The feedback data need to be presented in such a way that teachers understand the results, for example, mean scores in graphs or scale plots, or means for every item. The more positive the feedback, the more precise reception, easier remembering of contents, and better acceptance of the feedback by teachers (Ilgen et al., 1979; Lyden et al., 2002). The literature shows different findings on the specifics of the feedback, ranging from ‘highly specific feedback’ to ‘low specificity or summarized feedback’. High-specificity feedback seems to be more effective for beginners and for short-term learning, whereas low-specificity feedback tends to have a stronger impact on long-term learning performance (Röhl & Gärtner, 2021).
The timing of the feedback refers to the time between the actual act or task and the provision of the feedback. If the feedback is provided to the teacher right after a lesson, the link between the actual actions of the teacher in the classroom and the student feedback is clearer than in the case of feedback on teacher behavior in general (across many lessons; Hattie & Timperley, 2007; Shute, 2008). When feedback is given immediately, it is found to be more effective than when it is postponed (Timmers & Veldkamp, 2011). Teachers might therefore be able to work better on improving their teaching quality when feedback is given immediately (Bijlsma et al., 2019b). Furthermore, a survey instrument that is scientifically and psychometrically validated and reliable should be carefully selected for reliable and valuable use of student feedback data (Bijlsma, 2021).
6 Conclusions and Future Directions
Student feedback can be a valuable tool to improve teaching. However, teachers’ use of feedback data to assist in their professional development does not happen automatically. On the basis of the Process Model of Student Feedback on Teaching (see above, Röhl et al., 2021), we pointed out that on the one hand, student teaching quality perceptions are influenced by several characteristics of the students, classes and measurement instruments, and on the other hand, teachers’ use of the feedback data is influenced by factors such as individual characteristics of the teacher, and context and data characteristics. Insight into these factors can strengthen the general awareness among practitioners of the conditions under which teachers’ process of collecting, interpreting and valuing the results, and the subsequent teaching improvement, can be accomplished successfully.
For future research, an interesting question is how the prerequisites for teacher development based on student feedback can be fulfilled to match with what is possible within the context of schools. From the research on deliberate practice by professionals and experts by Ericsson (2006), we know that improving as a teacher requires a coach who guides the teacher through the improvement process and who knows what ideal teaching behavior looks like, how this behavior can be trained effectively, and what practices are effective if problems occur during the improvement process. From the research on Professional Learning Communities (e.g., Brown & Poortman, 2018), we know that teacher collaboration in improvement processes is a promising way to improve teachers’ teaching, in which the underlying goal is to improve teaching and teacher learning within the school (Blankenship & Ruona, 2007; Prenger et al., 2017). We recommend investigating the role of a coach and the collaborative learning process among teachers when improving teaching quality based on student feedback.
Moreover, it would be profitable to investigate the use of student feedback data for improving teaching quality in non-Western cultures. Although student perceptions have mainly been used in Europe, Australia and the USA thus far, we assume that they might also be useful in non-Western school cultures. There are studies on student perceptions of teaching quality in schools and also on its use in higher education, for example in Asian countries (e.g., Maulana et al., 2012). However, to the best of our knowledge, there is a lack of studies dealing with how student perceptions of teaching quality can be used as feedback to teachers for the purpose of improving teaching in primary and secondary schools. Adapting findings from Western cultures to the cultural conditions in non-Western cultures might be necessary here.
Another direction for future research might be to combine different teaching quality measures (e.g., classroom observations, student perceptions and teacher perceptions) to obtain a rich picture of teaching quality. Some aspects of teaching quality, for example, are probably best assessed by students, such as whether students feel that the teacher has high expectations of them, and whether students experience the classroom climate as safe. To understand other teacher quality aspects, other perspectives might be more relevant. For example, does an external observer, based on his or her professional standards, think that the explanation of subject matter by the teacher is correct? Moreover, as far as teachers’ perspectives on their lessons are concerned, it would be interesting to know how they perceive their own teaching quality and compare this with the student perceptions, as this may influence their opinion about the need for improvement of their lessons.
References
American Educational Research Association, American Psychological Association, & National Council on Measurement in Education. (2014). Standards for educational and psychological testing.. American Educational Research Association.
Atlay, C., Tieben, N., Fauth, B., & Hillmert, S. (2019). The role of socioeconomic background and prior achievement for students’ perception of teacher support. British Journal of Sociology of Education, 40(7), 970–991. https://doi.org/10.1080/01425692.2019.1642737
Baker, D., & Leary, R. (1995). Letting girls speak out about science. Journal of Research in Science Teaching, 32, 3–27. https://doi.org/10.1002/tea.3660320104
Balch, R. T. (2012). The validation of a student survey on teacher practice. Doctoral dissertation, Vanderbilt University. Vanderbilt University Institutional Repository Electronic Theses and Dissertations. https://etd.library.vanderbilt.edu/etd-07182012-153440
Bass, B. M. (1985). Leadership and performance beyond expectations. Free Press.
Bell, C. A. (2019). What we see depends on how we look QUINT conference, Oslo.
Bell, C. A., & Aldridge, J. M. (2014). Investigating the use of student perception data for teacher reflection and classroom improvement. Learning Environment Research, 17, 371–388. https://doi.org/10.1007/s10984-014-9164-z
Bijlsma, H. J. E. (2021). The quality of student perception questionnaires: A systematic review. In W. Rollett, H. J. E. Bijlsma, & S. Röhl (Eds.), Student feedback on teaching in schools. Using student perceptions for the development of teaching and teachers (pp. 47–72). Springer. https://doi.org/10.1007/978-3-030-75150-0_3
Bijlsma, H. J. E., Keuning, T., & Visscher, A. J. (2019a, Aug 10–14). A users’ perspective on the use of a digital tool for student feedback about teaching quality.
Bijlsma, H. J. E., Visscher, A. J., Dobbelaer, M. J., & Veldkamp, B. P. (2019b). Does smartphone-assisted student feedback affect teaching quality? Technology, Pedagogy & Education, 28(2), 217–236. https://doi.org/10.1080/1475939X.2019.1572534
Bijlsma, H. J. E., van der Lans, R. M., Mainhard, M. T., & den Brok, P. (2021). A reflection on student perceptions of teaching quality from three psychometric perspectives: CCT, IRT and GT. In W. Rollett, H. J. E. Bijlsma, & S. Röhl (Eds.), Student feedback on teaching in schools. Using student perceptions for the development of teaching and teachers (pp. 15–30). Springer.
Bijlsma, H. J. E., Glas, C. A. W., & Visscher, A. J. (2022). Factors related to differences in digitally measured student perceptions of teaching quality. [Paper accepted]. School Effectiveness and School Improvement., 33, 360–380.
Blankenship, S. S., & Ruona, W. E. (2007). Professional learning communities and communities of practice: A comparison of models, a literature review. Online submission.
Brekelmans, M., Wubbels, T., & den Brok, P. (2002). Teacher experience and the teacher-student relationship in the classroom environment. In S. C. Goh & M. S. Khine (Eds.), Studies in educational learning environments: An international perspective (pp. 73–100). New world scientific. https://doi.org/10.1142/9789812777133_0004
Brophy, J., & Good, T. L. (1986). Teacher behavior and student achievement. In M. Witrock (Ed.), The third handbook of research on teaching (pp. 328–375). Macmillan.
Brown, C., & Poortman, C. L. (2018). Networks for learning: Effective collaboration for teacher, school and system improvement. Routledge Taylor & Francis Group. https://doi.org/10.4324/9781315276649
Brunner, C., & Light, D. (2008). From knowledge management to data-driven instructional decisionmaking in schools: The missing link. In A. Breiter, A. Lange, & E. Stauke (Eds.), School information systems and data-based decision-making (pp. 37–48). Peter Lang.
Buurman, M., Delfgaauw, J. J., Dur, R. A. J., & Zoutenbier, R. (2018). The effects of student feedback to teachers: Evidence from a field experiment. Tinbergen Institute.
Cashin, W. E. (1988). Student ratings of teaching: A summary of the research (IDEA Paper No. 20) (p. 29). Center for Faculty Evaluation and Development, Kansas State University.
Clausen, M. (2002). Qualität von Unterricht: Eine Frage der Perspektive? [Quality of instruction as a question of perspective?]. Waxmann.
Day, C., Sammons, P., & Kington, A. (2008). Effective classroom practice (ECP): A mixed-method study of influences and outcomes. School of Education, University of Nottingham.
den Brok, P., Levy, J., Rodriguez, R., & Wubbels, T. (2002). Perceptions of Asian- American and Hispanic-American teachers and their students on interpersonal communication style. Teaching and Teacher Education, 18, 447–467. https://doi.org/10.1016/S0742-051X(02)00009-4
den Brok, P., Levy, J., Wubbels, T., & Rodriguez, M. (2003). Cultural influences on students’ perceptions of videotaped lessons. International Journal of Intercultural Relations, 27(3), 355–374. https://doi.org/10.1016/S0147-1767(03)00016-6
Den Brok, P., Fisher, D. L., & Rickards, T. (2006). Factors affecting Australian students’ perceptions of their science teachers’ interpersonal behaviour. In D. L. Fisher & M. S. Khine (Eds.), Contemporary approaches to research on learning environments: World views (pp. 51–74). World Scientific.
Ditton, H., & Arnold, B. (2004). Wirksamkeit von Schülerfeedback zum Fachunterricht [Effectiveness of student feedback on subject teaching]. In J. Doll & M. Prenzel (Eds.), Bildungsqualität von Schule. Lehrerprofessionalisierung, Unterrichtsentwicklung und Schülerförderung als Strategien der Qualitätsentwicklung (pp. 152–172). Waxmann.
Donahue, J. M. (1994). Student perceptions of their teachers, their school, and themselves as learners. Retrospective theses and dissertations.(10694), Retreived from https://lib.dr.iastate.edu/rtd. https://doi.org/10.31274/rtd-180813-9962
Dretzke, B. J., Sheldon, T. D., & Lim, A. (2015). What do K-12 teachers think about including student surveys in their performance ratings? Mid-Western Educational Researcher, 27(3), 185–206.
Elliott, E. S., & Dweck, C. S. (1988). Goals: An approach to motivation and achievement. Journal of Personality and Social Psychology, 54, 5–12. https://doi.org/10.1037/0022-3514.54.1.5
Elstad, E., Lejonberg, E., & Christophersen, K.-A. (2015). Teaching evaluation as a contested practice: Teacher resistance to teaching evaluation schemes in Norway. Education Inquiry, 6, 375–399. https://doi.org/10.3402/edui.v6.27850
Elstad, E., Lejonberg, E., & Christophersen, K.-A. (2017). Student evaluation of high-school teaching: Which factors are associated with teachers’ perception of the usefulness of being evaluated? Journal for Educational Research Online, 9(1), 99–117.
Ericsson, A. (2006). The influence of experience and deliberate practice on the development of superior expert performance. In K. A. Ericsson (Ed.), The Cambridge handbook of expertise and expert performance (Vol. 38, pp. 685–705). https://doi.org/10.1017/CBO9780511816796.038
Fauth, B., Decristan, J., Rieser, S., Klieme, E., & Büttner, G. (2014). Students ratings of teaching quality in primary school: Dimensions and prediction of student outcomes. Learning and Instruction, 29, 1–9. https://doi.org/10.1016/j.learninstruc.2013.07.001
Ferguson, R. (2012). Can student surveys measure teaching quality? Phi Delta Kappan, 94(3), 24–28. https://doi.org/10.2307/41763671
Fisher, D. L., den Brok, P., & Rickards, T. (2006). Factors influencing students’ perceptions of their teachers’ interpersonal behaviour: A multilevel analysis. In D. L. Fisher & M. S. Khine (Eds.), Contemporary approaches to research on learning environments (pp. 51–74). World Scientific Publishing.
Gage, N. L. (1960). Equilibrium theory and behavioral change: An experiment in feedback from pupils to teachers. Illinois University.
Gärtner, H. (2014). Effects of student feedback as a method of self-evaluating the quality of teaching. Studies in Educational Evaluation, 42, 91–99. https://doi.org/10.1016/j.stueduc.2014.04.003
Gärtner, H., & Brunner, M. (2018). Once good teaching, always good teaching? The differential stability of student perceptions of teaching quality. Educational Assessment and Educational Accountability, 30, 159–182. https://doi.org/10.1007/s11092-018-9277-5
Goe, L., Bell, C. A., & Little, O. (2008). Approaches to evaluating teacher effectiveness: A research synthesis. National Comprehensive Center for Teacher Quality.
Goh, S. C., & Fraser, B. J. (1995, April). Learning environment and student outcomes in primary mathematics classrooms in Singapore. Annual meeting of the American Educational Research Association, San Francisco.
Göllner, R., Fauth, B., Lenske, G., Praetorius, A. K., & Wagner, W. (2020). Do student ratings of classroom management tell us more about teachers or about classroom composition? Zeitschrift für Pädagogik, 66, 156–172.
Göllner, R., Fauth, B., & Wagner, W. (2021). Student ratings of teaching quality dimensions: Empirical findings and future directions. In W. Rollett, H. J. E. Bijlsma, & S. Röhl (Eds.), Student feedback in schools. Using student perceptios for improving teaching and teachers (pp. 111–123). Springer.
Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
Hill, H. C., Kapitula, L., & Umland, K. (2011). A validity argument approach to evaluating teacher value-added scores. American Educational Research Journal, 48(3), 794–831. https://doi.org/10.3102/0002831210387916
Ilgen, D. R., Fisher, C. D., & Taylor, M. S. (1979). Consequences of individual feedback on behavior in organizations. Journal of Applied Psychology, 64(4), 349–371. https://doi.org/10.1037/0021-9010.64.4.349
Jones, A. T., & Kirk, C. M. (1990). Gender differences in students’ interests in applications of school physics. Physics Education, 25, 308–313.
Kahmann, K., & Mulder, R. H. (2011). Feedback in organizations: A review of feedback literature and a framework for future research (Research Report No. 6). Retrieved from Institute for Educational Science, Universität Regensburg website: https://www.uni-regensburg.de/psychologie-paedagogik-sport/paedagogik-2/medien/kahmann_mulder_2011.pdf
Kenny, D. A. (2004). PERSON: A general model of interpersonal perception. Personality and Social Psychology Review, 8, 265–280.
Khalil, N., & Aldridge, J. M. (2019). Assessing students’ perceptions of their learning environment in science classes in the United Arab Emirates. Learning Environments Research, 22(3), 365–386. https://doi.org/10.1007/s10984-019-09279-w
Kini, T., & Podolsky, A. (2016). Does teaching experience increase teacher effectiveness? A review of the research. Learning Policy Institute.
Kippers, W. B., Poortman, C. L., Schildkamp, K., & Visscher, A. J. (2018). Data literacy: What do educators learn and struggle with during a data use intervention? Studies in Educational Evaluation, 56, 21–31. https://doi.org/10.1016/j.stueduc.2017.11.001
Kluger, A. N., & DeNisi, A. (1996). The effects of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119(2), 254–284. https://doi.org/10.1037/0033-2909.119.2.254
Klusmann, U., Kunter, M., Trautwein, U., & Baumert, J. (2006). Lehrerbelastung und Unterrichtsqualität aus der Perspektive von Lehrenden und Lernenden. [Teacher stress and teaching quality from the perspective of teachers and learners]. Zeitschrift für Pädagogische Psychologie, 20(3), 161–173. https://doi.org/10.1024/1010-0652.20.3.161
Krosnick, J. A., & Presser, S. (2010). Questionnaire design. In J. D. Wright & P. V. Marsden (Eds.), Handbook of survey research (2nd ed.). Emerald Group.
Kunst, E. M., van Woerkom, M., & Poell, R. F. (2018). Teachers’ goal orientation profiles and participation in professional development activities. Vocations and Learning, 11, 91–111. https://doi.org/10.1007/s12186-017-9182-y
Leigh, A. (2010). Estimating teacher effectiveness from two-year changes in students’ test scores. Economics of Education Review, 29(3), 480–488. https://doi.org/10.1016/j.econedurev.2009.10.010
Levy, J., Wubbels, T., Brekelmans, M., & Morganfield, B. (1997). Language and cultural factors in students’ perceptions of teacher communication style. International Journal of Intercultural Relations, 21(1), 29–56. https://doi.org/10.1016/S0147-1767(96)00005-3
Levy, J., Wubbels, T., den Brok, P., & Brekelmans, M. (2003). Students’ perceptions of interpersonal aspects of the learning environment. Learning Environment Research, 6, 5–36. https://doi.org/10.1023/A:1022967927037
Loeb, S. (2013). How can value-added measures be used for teacher improvement? http://www.carnegieknowledgenetwork.org/briefs/teacher_improvement/
London, M., & Smither, J. W. (2002). Feedback orientation, feedback culture, and the longitudinal performance management process. Human Resource Management Review, 12, 81–100. https://doi.org/10.1016/S1053-4822(01)00043-2
Lyden, J. A., Chaney, L. H., Danehower, V. C., & Houston, D. A. (2002). Anchoring, attributions, and self-efficacy: An examination of interactions. Contemporary Educational Psychology, 27, 99–117. https://doi.org/10.1006/ceps.2001.1080
Mandinach, E. B., & Gummer, E. S. (2013). Defining data literacy: A report on a convening of experts. Journal of Educational Research and Policy Studies, 13(2), 6–28.
Mandinach, E. B., & Gummer, E. S. (2016). Data literacy for educators: Making it count in teacher preparation and practice. Teachers College Press.
Mandouit, L. (2018). Using student feedback to improve teaching. Educational Action Research, 26, 755–769. https://doi.org/10.1080/09650792.2018.1426470
Marsh, H. W. (2007). Students’ evaluations of university teaching: Dimensionality, reliability, validity, potential biases and usefulness. In R. P. Perry & J. C. Smart (Eds.), The scholarship of teaching and learning in higher education: An evidence-based perspective (pp. 319–383). Springer.
Maulana, R., Opdenakker, M. C. J. L., den Brok, P., & Bosker, R. J. (2012). Teacher–student interpersonal relationships in Indonesian lower secondary education: Teacher and student perceptions. Learning Environments Research, 15(2), 251–271. https://doi.org/10.1007/s10984-012-9113-7
Nye, B., Konstantopoulos, S., & Hedges, L. V. (2004). How large are teacher effects? Educational Evaluation and Policy Analysis, 26, 237–257. https://doi.org/10.3102/01623737026003237
OECD. (2014). PISA 2012 results in focus: What 15-year-olds know and what they can do with what they know. https://www.oecd.org/pisa/keyfindings/pisa-2012-results-overview.pdf
Peterson, K. D., Wahlquist, C., & Bone, K. (2000). Student surveys for school teacher evaluation. Journal of Personnel Evaluation in Education, 14(2), 135–153.
Prenger, R., & Schildkamp, K. (2018). Data-based decision making for teacher and student learning: A psychological perspective on the role of the teacher. Educational Psychology in Practice, 38, 734–752. https://doi.org/10.1080/01443410.2018.1426834
Prenger, R., Poortman, C. L., & Handelzalts, A. (2017). Factors influencing teachers’ professional development in networked professional learning communities. Teaching and Teacher Education, 68, 77–90. https://doi.org/10.1016/j.tate.2017.08.014
Rickards, T. (1998). The relationship of teacher-student interpersonal behaviour with student sex, cultural background and student outcome. Perth, Australia.
Rivkin, S. G., Hanushek, E. A., & Kain, J. F. (2005). Teachers, schools, and academic achievement. Econometrica, 73, 417–458.
Röhl, S. (2021). Effects of student feedback on teaching and classes: An overview and meta-analysis on intervention studies. In W. Rollett, H. J. E. Bijlsma, & S. Röhl (Eds.), Student feedback in schools: Using perceptions for the development of teaching and teachers (pp. 139–156). Springer. https://doi.org/10.1007/978-3-030-75150-0_9
Röhl, S., & Gärtner, H. (2021). Relevant conditions for teachers’ use of student feedback. In W. Rollett, H. J. E. Bijlsma, & S. Röhl (Eds.), Student feedback in schools: Using perceptions for the development of teaching and teachers (pp. 157–172). Springer. https://doi.org/10.1007/978-3-030-75150-0_10
Röhl, S., Bijlsma, H. J. E., & Rollett, W. (2021). The process model of student feedback on teaching (SFT): A theoretical framework and introductory remarks. In W. Rollett, H. J. E. Bijlsma, & S. Röhl (Eds.), Student feedback in schools: Using perceptions for the development of teaching and teachers (pp. 1–13). Springer. https://doi.org/10.1007/978-3-030-75150-0_1
Rowley, J. (2003). Designing student feedback questionnaires. Quality Assurance in Education, 11(3), 142–149. https://doi.org/10.1108/09684880310488454
Runhaar, P., Sanders, K., & Yang, H. (2010). Stimulating teachers’ reflection and feedback asking: An interplay of self-efficacy, learning goal orientation, and transformational leadership. Teaching and Teacher Education, 26, 1154–1161. https://doi.org/10.1016/j.tate.2010.02.011
Schildkamp, K., & Lai, M. K. (2013). Conclusions and a data use framework. In K. Schildkamp & M. K. Lai (Eds.), Data-based decision making in education: Challenges and opportunities (pp. 177–191). Springer.
Schildkamp, K., Lai, M. K., & Earl, L. (2013). Data-based decision making in education. Challenges and opportunities. Springer. https://doi.org/10.1007/978-94-007-4816-3
Schildkamp, K., Poortman, C., Luyten, H., & Ebbeler, J. (2017). Factors promoting and hindering databased decision making in schools. School Effectiveness and School Improvement, 28(2), 242–258. https://doi.org/10.1080/09243453.2016.1256901
Schweig, J. D. (2016). Moving beyond means: Revealing features of the learning environment by investigating the consensus among student ratings. Learning Environments Research, 19(3), 441–462. https://doi.org/10.1007/s10984-016-9216-7
Shute, V. J. (2008). Focus on formative feedback. Review of Educational Research, 78, 153–189. https://doi.org/10.3102/0034654307313795
Smither, J. W., London, M., & Reilly, R. R. (2005). Does performance improve following multisource feedback?: A theoretical model, meta-analysis, and review of empirical findings. Personnel Psychology, 58(1), 33–66. https://doi.org/10.1111/j.1744-6570.2005.514_1.x
Taylor, S. M., Fisher, C. D., & Ilgen, D. R. (1984). Individuals’ reactions to performance feedback in organizations: A control theory perspective. In K. M. Rowland & G. R. Ferris (Eds.), Research in personnel and human resources management (pp. 81–124). JAI Press.
Timm, J. T. (1999). The relationship between culture and cognitive style: A review of the evidence and some reflections for the classroom. Mid-Western Educational Researcher, 12(2), 36–44.
Timmers, C. F., & Veldkamp, B. P. (2011). Attention paid to feedback provided by a computer-based assessment for learning on information literacy. Computers in Education, 56(3), 923–930. https://doi.org/10.1016/j.compedu.2010.11.007
Timperley, H., Wilson, A., Barrar, H., & Fung, I. (2007). Teacher professional learning and development: Best evidence synthesis iteration. Ministery of Education. http://www.educationcounts.govt.nz/__data/assets/pdf_file/0017/16901/TPLandDBESentireWeb.pdf
Tourangeau, R., Rips, L. J., & Rasinski, K. (2000). The psychology of survey response. Cambridge University Press. https://doi.org/10.1017/CBO9780511819322
Veldman, D. J., & Peck, R. F. (1969). Influences on pupil evaluations of student teachers. Journal in Educational Psychology, 60(2), 103–108. https://doi.org/10.1037/h0027085
Worthington, A. C. (2002). The impact of student perceptions and characteristics on teaching evaluations: A case study in finance education. Assessment & Evaluation in Higher Education, 27(1), 49–64. https://doi.org/10.1080/02602930120105054
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Bijlsma, H.J.E., Röhl, S. (2023). Fostering Effective Teaching at Schools Through Measurements of Student Perceptions: Processes, Risks and Chances. In: Maulana, R., Helms-Lorenz, M., Klassen, R.M. (eds) Effective Teaching Around the World . Springer, Cham. https://doi.org/10.1007/978-3-031-31678-4_6
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