27 SES 06 C, Didactics and Subject Matters
The belief that teachers should adapt their teaching to individual students’ needs is widespread. Such adaptations are seen as crucial for effective teaching and to provide equal learning opportunities for all students in a class (Banks et al., 2005; Tomlinson et al., 2003). Effective teachers seem to possess knowledge about students’ characteristics, subject matter and pedagogy/didactics and use such understandings to enhance the learning of the students by adapting their teaching according to this knowledge (Banks et al., 2005; Halim, Abdullah, & Meerah, 2014).
However, the knowledge teachers have of their students and how such knowledge influences a teacher’s adaptive teaching is not well studied empirically, especially not within the context of secondary education where teachers teach a multitude of students and see their students less frequently. This study aims to gain insight in the relation between teachers’ knowledge of their students and their adaptive teaching.
Teacher knowledge is seen as an umbrella term; incorporating a large variety of teacher cognitions, knowledge, beliefs and thoughts that are inextricably intertwined in the mind of the teacher and guide their actions (Verloop, van Driel, & Meijer, 2001). Scholars divert in their views of what teachers should know, how they should gain such knowledge and how they should use it. For example, Banks and colleagues (2005, p. 233) describe that it is important to know ‘who the students are, what they care about, what languages they speak and what customs and traditions are valued at their homes’. Other authors stress, among others, the need for teachers to know (1) the abilities of their students, their interest and learning profile (Tomlinson et al., 2003), (2) general student characteristics (Halim et al., 2014), (3) pre-conditions for each student’s learning and (4) the individual student’s learning process (Vogt & Rogalla, 2009). These claims are often more conceptually and ideologically warranted than empirically, are rather fixed in that all teachers should possess similar knowledge about every student, are prescriptive in nature and, taken together, set teachers for the seemingly unfeasible task of knowing all about every student.
In contrast to this prescriptive approach, empirical studies that focus on the knowledge of teachers conclude that what a teacher knows is highly context-specific and cannot be prescribed (Mayer & Marland, 1997; Paterson et al., 2002). In these studies it is concluded that the knowledge expert teachers have of their students is diverse and different among teachers. The teachers themselves regarded their personal knowledge as critical for their teaching. In contrast, other studies have shown that teachers have and use more selective knowledge about their students (Blease, 1995; Corno, 2008). Moreover studies have shown that the knowledge teachers have about their students does not necessarily relate to their classroom behaviours (cf. Savage & Desforges, 1995). Empirical investigations into the knowledge teachers have of their students and how they use this knowledge while teaching show mixed results regarding what teachers know, moreover it remains unclear whether and how this knowledge affects their teaching.
Within the adaptive teaching discourse a strong relation between the knowledge that secondary school teachers have of their students and their adaptive teaching is assumed, but empirical evidence for this relation between knowledge and teaching is lacking. To gain more insight in this relation we designed a study with the following research questions:
- What is the knowledge teachers express about each of their students?
- How is this knowledge about students related to teachers’ adaptive teaching practice?
We studied the knowledge of seven teachers teaching the same class of students. The class was a mixed-level, 2nd year secondary school class with 34 students of 12/13 year olds, tracked in the upper-levels of the Dutch educational system. The school is located in a rural area in the south/east of the Netherlands. The teachers that participated in this research taught Dutch, French, English, Math, Science and History, they had a mean age of 40.1 (SD=10.21) and 13.6 years of experience teaching in secondary schools (SD=8.06). This class and its teachers are involved in a project that aims at personalizing education towards the learning needs of the students. Teachers were interviewed about the knowledge of their students approximately 3.5 months after the start of the school year (in November). In these interviews teachers were asked to describe their students and the knowledge they had of the student. A photo of each student was used as a prompt. We built in a time constraint of one minute per student to ensure teachers would express the most relevant knowledge. Teachers’ adaptivity was mapped by asking the students to fill out a questionnaire how they experienced each teacher (cf. Maulana, Helms-Lorenz, & van de Grift, 2015). The qualitative data of the knowledge teachers’ expressed were coded by an iterative process in which student characteristics described in the handbook of educational psychology (Woolfolk, 2013) were used as a coding framework. Next, the codes were quantified by scoring the knowledge domains expressed by teachers and whether students labels were positive (e.g. [student] is highly motivated), neutral (e.g. [student] asks a lot of questions) or negative (e.g. [student] lacks ability). To study to what extent teachers’ knowledge was specific for a teacher or a student, the between- and within-teacher variance were analysed using dyadic data analysis. Intra-class correlations were calculated to give insight in the variability of teachers knowledge. Secondly, these data were analysed using a Multi-Dimensional Scaling technique to map similarities between teachers and students. Thirdly, the relation between teachers’ knowledge and their adaptivity was explored using regression analyses.
First analyses of the knowledge teachers expressed show that some knowledge domains are used by all teachers and for many students, e.g. cognitive abilities and effort, while some domains, for example the students home environment, is scarcely used. In addition, some domains are used only by some teachers and not by others, for example students’ diagnosed learning difficulties, well-being and social skills. Although there seems generality among the teachers in the knowledge they express, there are individual differences. Moreover, of some students the teachers expressed very little knowledge, while other students are described with multiple domains, for example; their personality, motivation, abilities and general classroom behaviour. Although there are some differences between the teachers in the students that are well known, analyses show that the same students are less known (i.e. provided with less labels) among most of their teachers. Analyses with regard to how teacher adaptivity is perceived by their students show the perceived variance within teachers is larger (mean SD=.41, ranging between .36-.45) as the variance between teachers (M=2.88, SD=.35, on a 4-point scale). Between students in the class there are large differences in how adaptive they experience their teacher to be. While teacher adaptivity is assumed to be a ‘teacher factor’, this result indicates that teachers might be more adaptive to some, than other, students. Results of further analyses, for example on the relation between teachers knowledge and their perceived adaptivity, will be presented at the conference. With the results obtained so far, interesting discussions arise regarding the validity and subjectivity of teachers’ knowledge, the influence students themselves have in the extent to which they are ‘known’ by their teachers and what teachers need to know to be adaptive to their students. Such insights should be accounted for in professional development programs and/or teacher education.
Banks, J., Cochran-Smith, M., Moll, L., Richert, A., Zeichner, K., LePage, P, Darling-Hammond, L., Duffy, H., & McDonald, M. (2005). Teaching divers learners. In Darling-Hammond, L., & Bransford, J. (eds). Preparing teachers for a changing world. John Wiley & Sons, Inc. San Fransisco, CA. Blease, D. (1995). Teachers’ judgements of their pupils: broad categories and multiple criteria. Educational Studies, 21, 203-215. http://dx.doi.org/10.1080/0305569950210205 Corno, L. (2008). On teaching adaptively. Educational Psychologist, 43, 161-173. Halim, L., Abdullah, S., & Meerah, T. (2014). Students' perceptions of their science teachers' pedagogical content knowledge. Journal of Science Education and Technology, 23, 227-237. DOI 10.1007/s 10956-013-9484-2 Mayer, D., & Marland, P. (1997). Teachers’ Knowledge of Students: a significant domain of practical knowledge? Asia-Pacific Journal of Teacher Education, 25, 17-34. doi.org/10.1080/1359866970250103 Maulana, R., Helms-Lorenz, M., & Van de Grift, W. (2015). Development and evaluation of a questionnaire measuring pre-service teachers’ teaching behaviour: a Rasch modelling approach. School Effectiveness and School Improvement, 26, 169-194. DOI: 10.1080/09243453.2014.939198 Savage, J., & Desforges, C. (1995). The role of informal assessment in teachers practical action. Educational Studies, 21, 433-446. http://dx.doi.org/10.1080/0305569950210308 Tomlinson, C.A., Brighton, C., Hertberg, H., Callahan, C.M., Moon, T.R., Brimijoin, K., Conover, L.A., & Reynolds, T. (2003). Differentiating instruction in response to student readiness, interest, and learning profile in academically diverse classrooms: a review of literature. Journal for the Education of the Gifted, 27, 119–145. Vogt, F., & Rogalla, M. (2009). Developing adaptive teaching competency through coaching. Teaching and teacher education, 25, 1051-1060. doi:10.1016/j.tate.2009.04.002 Verloop, N., Van Driel, J., Meijer, P. (2001). Teacher knowledge and the knowledge base of teaching. International Journal of Educational Research, 35, pp. 441-461. Woolfolk, A. (2013). Educational Psychology (12th ed). Pearson, international edition.
00. Central Events (Keynotes, EERA-Panel, EERJ Round Table, Invited Sessions)
Network 1. Continuing Professional Development: Learning for Individuals, Leaders, and Organisations
Network 2. Vocational Education and Training (VETNET)
Network 3. Curriculum Innovation
Network 4. Inclusive Education
Network 5. Children and Youth at Risk and Urban Education
Network 6. Open Learning: Media, Environments and Cultures
Network 7. Social Justice and Intercultural Education
Network 8. Research on Health Education
Network 9. Assessment, Evaluation, Testing and Measurement
Network 10. Teacher Education Research
Network 11. Educational Effectiveness and Quality Assurance
Network 12. LISnet - Library and Information Science Network
Network 13. Philosophy of Education
Network 14. Communities, Families and Schooling in Educational Research
Network 15. Research Partnerships in Education
Network 16. ICT in Education and Training
Network 17. Histories of Education
Network 18. Research in Sport Pedagogy
Network 19. Ethnography
Network 20. Research in Innovative Intercultural Learning Environments
Network 22. Research in Higher Education
Network 23. Policy Studies and Politics of Education
Network 24. Mathematics Education Research
Network 25. Research on Children's Rights in Education
Network 26. Educational Leadership
Network 27. Didactics – Learning and Teaching
The programme is updated regularly (each day in the morning)
- Search for keywords and phrases in "Text Search"
- Restrict in which part of the abstracts to search in "Where to search"
- Search for authors and in the respective field.
- For planning your conference attendance you may want to use the conference app, which will be issued some weeks before the conference
- If you are a session chair, best look up your chairing duties in the conference system (Conftool) or the app.