32 SES 12 B, Learning Communities and more
Recent literature reviews and meta-analytic findings indicate that high-performing schools feature complex forms of teacher cooperation such as professional learning communities (PLCs) (Fulton & Britton, 2011; Lomos, Hofman & Bosker, 2011b; Scheerens, 2014). However, despite converging evidence regarding the impact of PLCs on important outcomes of pedagogical activities, as measured by student achievement, comparably little is known about how PLC membership affects pedagogical activities per se, as reflected in indicators of instructional quality (Stoll, Bolam, McMahon, Wallace & Thomas, 2006; Vangrieken, Dochy, Raes & Kyndt, 2015). Investigations of teachers’ instructional practices and methods that are associated with working in a PLC thus present a largely missing but highly relevant piece of empirical knowledge, because “[a]t its core, the concept of a PLC rests on the premise of improving student learning by improving teaching practice” (Vescio, Ross & Adams, 2008, 82; Supovitz, 2002).
Against this background, our paper pursues two objectives. The first is to explore if and to what extent departments in German vocational schools operate as PLCs, i.e., in accordance with generic features of PLCs. We do so by adopting a profiling approach and examining profile composition and occurrence. The second objective is to analyse if and to what extent teacher membership in different PLC profiles explains differences in instructional quality.
Core dimensions of professional learning communities
Professional communities represent conceptually and operationally heterogeneous fields of research. Whereas some studies focus on small teams that evolve outside formal organizational structures (e.g., Owen, 2014), others consider the entire staff of schools (e.g., Bolam et al., 2005) or distinct organizational sub-units (e.g., Hallam et al., 2015). Against this background, the present study concentrates on dimensions which describe the way collective professional practice is orchestrated within a PLC, and which should all be pronounced in strong, fully developed PLCs.
Collaborative development denotes the behavioural dimension of a PLC, as PLC members engage in genuinely collaborative efforts to improve pedagogical processes (Little, 2012). This means that teachers not only occasionally exchange instructional materials, but also co-constructively design and consistently implement instructional units (e.g., Bolam et al., 2005). Moreover, PLC members exercise activities of continuous collective inquiry (Hord, 1997) and, thus, cultivate processes of teacher learning (Little, 2012). These activities often include reflective dialogue about instructional issues (Kruse et al., 1995; Penner-Williams, Diaz & Gonzales Worthen, 2017) but also mutual visits and consultation, peer coaching, or joint evaluation of instructional processes and outcomes (e.g., Hipp & Huffman, 2010; Stegall, 2011; Visscher & Witziers, 2004).
Normative agreement describes the ideational dimension of a PLC, as collaborative efforts need to serve shared purposes and to be closely aligned with consented standards of professional conduct to be successful and enduring. Therefore, teachers who work together in a PLC hold a common set of pedagogical values and goals and strongly agree in their personal beliefs about effective teaching and learning (e.g., Andrews & Lewis, 2007; Kruse et al., 1995; Stoll et al., 2006).
Supportive infrastructure depicts the structural dimension of a PLC, as substantial collaborative activities necessitate operational structures that facilitate and promote them (e.g., Hord, 1997). A unit’s “organizational capacity” (Mitchell & Sackney, 2007, 630; Sleegers et al., 2013, 7) may again include a wide range of aspects but two of them are particularly prominent in the literature. Firstly, operational routines as well as project workflows should run smoothly and be closely coordinated, which requires clear rules, procedures and responsibilities, adequate information supply, and fast and transparent communication channels. Secondly, sufficient timely and spatial resources should be available to meet and work in teams (ibid.; Hipp & Hufmann, 2010; Stegall, 2011).
This paper investigates two sub-goals. The first is to empirically explore departmental PLC profiles, using dimensional scores on collaborative development, normative agreement, and supportive infrastructure as classification criteria. This allows us to investigate to which extent and in which combination of dimensional scores departments operate in accordance with generic features of a PLC. We employ multilevel latent profile analysis and evaluate the fit indices of alternative profile solutions to identify characteristic patterns in teacher ratings of core PLC dimensions at the department level (Study 1). The second goal is to examine to what extent variations in instructional quality are attributable to teachers’ membership in distinct PLC profiles. Following extant findings reported in the previous sections, we expect teachers who belong to (comparably) strong PLCs, indicated by (comparably) high scores in all dimensions, to provide students with better opportunities to acquire occupational knowledge and skills. Multilevel multiple group analyses serve to test this assumption. We draw on student assessments of the degree to which teachers demonstrate effective classroom management, individual learning support, and application-oriented teaching, and of the frequency in which teachers employ action- and application-oriented methods such as problem-solving (Study 2). Study 1: The present sample includes schools in Bavaria/Germany. We collected responses from 395 teachers (45.5 % female; 17 years of teaching experience on average, SD = 10.7 years). They belong to 47 departments that are specialized in different vocational domains, i.e., in the technical-industrial (11), social (10), commercial (20), and technological (6) sectors of VET. To assess the degree to which departments display core PLC dimensions, teachers were asked to rate 21 items pertaining to collaborative development (CD), normative agreement (NA), and supportive infrastructure (SI). Items were adapted from school quality research in Germany (Ditton, n.d.; Steinert et al., 2003) because scales for measuring PLCs are missing (Vangrieken et al., 2015). Study 2: We asked students to answer 15 items that serve as indicators of instructional quality. These items stem from previous research on instructional quality (Ditton, n.d.; Gruehn, 2000; Seeber & Squarra, 2003). Twelve items tap teacher's individual learning support (5 items), effective classroom management (4 items), and application orientation (3 items). Three items measure the frequency in which the teacher implements action- and application-oriented instructional methods. Student ratings are available for teachers from 34 of the 47 departments. On average, two classes per department completed the questionnaires (61 classes, 1,243 students, male: 41.8 %, age groups: 15-19).
Firstly, we identified PLC profiles that exist in vocational school departments without external interventions. Multilevel latent profile analysis reveal three distinct configurations. Structurally strong departments have a highly supportive infrastructure but exhibit only modest levels of collaborative development and normative agreement. Rudimentary PLC departments score comparably low on all PLC dimensions, whereas Advanced PLC departments convey the highest scores. We scrutinized profile composition and prevalence, but could not detect systematic relations with gender or seniority of staff, school type, or vocational domain. Only teachers’ work-related efficacy beliefs proved to be predictive of profile membership. Secondly, we expected teachers from comparably ‘strong’ PLC profiles to provide better opportunities for vocational students to acquire occupational competencies than teachers from ‘weaker’ profiles. Multilevel analyses show, that teachers from Advanced PLC departments demonstrate significantly and substantially higher levels of application-oriented teaching (by offering explanations, examples, and materials that illustrate the practical usefulness of subject matter) than teachers from other profiles. Furthermore, these teachers employ substantially more frequently instructional methods that allow students to actively and cooperatively deal with occupation-specific tasks, instruments and procedures. Teachers from Advanced PLCs score highest on both problem- and simulation-based methods, leading to very consistent deviations from the other profiles, even though statistical significance can be established only when compared to Structurally strong departments. On the one hand, this finding underscores the specific professional demands of teachers in vocational schools, where promoting the employability of graduates has high priority. On the other hand, we need to consider that available studies from the general education system examine a range of different target variables themselves, which limits the comparability of results. Although many of these studies suggest that PLCs foster individually supportive strategies of instruction, there is also evidence for increased levels of student problem solving, particularly in STEM classrooms.
De Bruijn, E., & Leeman, Y. (2011). Authentic and self-directed learning in vocational education: Challenges to vocational educators. Teaching and Teacher Education, 27(4), 694–702. DeMatthews, D. (2014). Principal and teacher collaboration: An exploration of distributed leadership in professional learning communities. International Journal of Educational Leadership and Management, 2(2), 176–206. Ditton, H. (n.d.). QuaSSU – QualitätsSicherung in Schule und Unterricht. (QuaSSU – Quality assurance in schools and instruction.) Retrieved from: http://www.quassu.net/. [19.10.2017]. Fulton, K., & Britton, T. (2011). STEM teachers in professional learning communities: From good teachers to great teaching. Washington: National Commission on Teaching and America’s Future (NCTAF). Gruehn, S. (2000). Unterricht und schulisches Lernen: Schüler als Quellen der Unterrichtsbeschreibung. (Instruction and academic learning: Students as sources for describing instruction.) Münster: Waxmann. Hallam, P. R., Smith, H. R., Hite, J. M., Hite, S. J., & Wilcox, B. R. (2015). Trust and collaboration in PLC teams: Teacher relationships, principal support, and collaborative benefits. NASSP. Bulletin, 99(3), 193–216. Henry, K. L., & Muthén, B. O. (2010). Multilevel latent class analysis: An application of adolescent smoking typologies with individual and contextual predictors. Structural Equation Modeling: A Multidisciplinary Journal, 17(2), 193–215. Lomos, C., Hofman, R. H., & Bosker, R. J. (2011a). The relationship between departments as professional communities and student achievement in secondary schools. Teaching and Teacher Education, 27(4), 722–731. Lomos, C., Hofman, R. H., & Bosker, R. J. (2011b). Professional communities and student achievement – a meta-analysis. School Effectiveness and School Improvement, 22(2), 121–148. Louis, K. S., & Marks, H. M. (1998). Does professional community affect the classroom? Teachers’ work and student experiences in restructuring schools. American Journal of Education, 106(4), 532–575. Owen, S. (2014). Teacher professional learning communities: Going beyond contrived collegiality toward challenging debate and collegial learning and professional growth. Australian Journal of Adult Learning, 54(2), 54–77. Sleegers, P., den Brok, P., Verbiest, E., Moolenaar, N. M., & Daly, A. J. (2013). Toward conceptual clarity. A multidimensional, multilevel model of professional learning communities in Dutch elementary schools. The Elementary School Journal, 114(1), 118–137.
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.