Peer Reviewed Article on Collaborative Strategies for Effective Literacy Teamwork
Introduction
Collaboration amid teachers is a force that positively influences the whole school community. DuFour et al. (2005) advocate to increment collaborative activities in the form of professional person learning communities, stating that such collaborative communities "concord out immense, unprecedented hope for schools and the improvement of pedagogy" (p. 128). Positive effects for teachers were found in improved self-efficacy (cf. Puchner and Taylor, 2006), increased teaching effectiveness (cf. Graham, 2007), and improvement of instructional quality (cf. Jackson and Bruegmann, 2009; Hochweber et al., 2012). These positive furnishings will amend their quality equally professionals and as Hattie (2003) suggests, instructor quality alone accounts for thirty% of the variance in student performance. The communities that will be formed by working collaboratively will enhance teacher effectiveness and expertise (Hattie, 2015).
The positive influence of teacher collaboration transcend the teacher community; research has shown that professional collaborative activities might take a positive outcome on educatee achievement (cf. Lee and Smith, 1996; Louis et al., 2010; Dumay et al., 2013). Goddard et al. (2010) found a significant straight positive issue on student achievement while Lara-Alecio et al. (2012) found that students whose teachers participated in collaborative activities, such as instruction strategies, scored higher in science and reading achievement than students whose teachers did not attend such professional development activities. All the same, considering of its relatively contempo emergence, empirical evidence of the furnishings of instructor collaboration on pupil achievement is limited (Moolenaar et al., 2012). Enquiry tends to investigate teacher collaboration as a unmarried construct and thus, information about the benefits that can be drawn from specifics form of collaboration are unknown (Reeves et al., 2017). Furthermore, Scheerens (2000) points out that almost of the information on schoolhouse effectiveness has been gathered in American simple schools (p. 44).
In this paper, past using the representative German language data from PISA-2012 (Prenzel et al., 2015), we investigate the extent to which three dissimilar forms of teacher collaboration, namely instruction- project- and organization-related, influence student achievement. We use the students' grades retrieved in the first one-half yr of the academic catamenia 2011/2012 in the subjects of mathematics, German language, biology, physics, and chemistry. To our knowledge, this is the only study that has used this dataset in society to investigate these variables.
Theoretical Background
Given the huge touch on that teachers play in the performance of their students and the continual acknowledgment of teacher collaboration as a cadre element for the professional development of the school and its members, information technology is not surprising that many official policies and education reforms around the world plead for more collaborative practices amidst teachers. Countries like Denmark, Republic of finland, Kingdom of norway, and Hungary, among others, dedicate a fair amount of fourth dimension to activities of teacher collaboration (OECD, 2004). In Finland, for instance, the curriculum reform of 2016 stated that a "collaborative temper" (Halinen, 2015) is a key aim for school improvement, given that by working together across school subjects the objectives of the new curriculum, such as teacher competence development, tin can be met. Another example of the loftier value placed on teacher collaboration can be constitute in the The states; Melanie Hirsh states that: "the system at the schoolhouse level is supported past state and federal policies that encourage regular instructor collaboration […] and provides needed resource to give teachers time and opportunity to make this happen" (Darling-Hammond et al., 2009, p. 3).
Research has besides establish a positive and significant association between teacher collaboration and job satisfaction (cf. OECD, 2014; Mostafa and Pál, 2018), which is a core element of an effective teacher. In fact, Johnson (2003) found "important emotional and psychological benefits associated with working closely with colleagues in teams" (p. 343) when planning, discussing, and working in collaborative teams (ibid, p. 344). One reason for this might be that when teachers interact, feelings of isolation are mitigated. According to Lortie (1975) isolation is a defining characteristic of the teaching profession which ultimately tin can lead to a series of negative aspects such equally job dissatisfaction and exhaustion (Gaikwad and Brantly, 1992) equally well as a sense of being completely lonely (Fimian, 1982; Eisner, 1992). Because through collaboration joint work is fostered to achieve specific educatee learning goals, contest among colleagues is prevented (Williams, 2010).
Additionally, some studies have plant a positive effect of instructor collaboration on student accomplishment (cf. Lee and Smith, 1996; Borko, 2004; Louis et al., 2010; Dumay et al., 2013). For instance, Goddard et al. (2010) plant a significant directly positive effect on student accomplishment in the subjects of mathematics and reading equally well as an indirect outcome of shared instructional leadership on educatee accomplishment only when mediated through collaboration. Vincent-Lancrin et al. (2017), as office of the OECD projection Measuring Innovation in Education identified teacher collaboration (measured in forms of peer ascertainment and discussion with peers) equally a factor that fosters student scores. Hargreaves and Fullan (2012) argue that "a more collaborative and collegial profession improves student learning and achievement" (p. xii). Darling-Hammond et al. (2017) take a similar stance, as they have shown that pupil achievement tin be positively influenced when "effective collaborative structures for teachers to problem-solve and learn together are utilized" (p. x). In their research review (ibid), they identified instructor collaboration as 1 of seven factors that plant effective professional development stating that, "by working collaboratively, teachers can create communities that positively change the culture and education of their entire grade level, department, school, and/or district" (p. 5). This has also been suggested for general and special pedagogy teachers in inclusive classrooms, where collaboration has been identified as an important factor for the inherent challenges that educators in such environments find (Gebhardt et al., 2015). Schwab (2017) has also establish that students in inclusive classrooms adopt teachers that piece of work in teams (co-teaching) because they feel more than supported. Given that "collaboration make teaching less stressful and more than satisfying" (Burns and Darling-Hammond, 2014, p. two) arguably teachers tin focus on other aspects such equally teaching practices, which in turn have considerable positive effects on educatee achievement (cf. Schacter and Thum, 2004; Hidalgo-Cabrillana and Lopez-Mayan, 2015). For example, Reeves et al. (2017) suggest that through collaboration, teachers may have more time to reflect on their didactics practices and thus, assess if what they are doing works and accordingly change or reinforce their actions and behaviors in the classroom. In a study conducted in three schools in Norway over a single year, Svendsen (2016) found out that through collaboration practices, teachers were able to adopt a new teaching form chosen "inquiry-based science instruction," which in turn allowed teachers to gain confidence, think critically and reflect near their teaching practices. The results of a study conducted past Ronfeldt et al. (2015) in 336 Miami-Dade Canton public schools indicated strong correlational and possibly causal effects "of collaboration on teachers' and schools' effectiveness at improving student achievement" (p. 508). They argued that an increment in the quality of collaboration can lead to schoolhouse improvement and showed that student achievement is higher in schools with strong collaborative environments. Ronfeldt's findings showed that teachers and students benefited from collaboration in the areas of instructional strategies and curriculum, instructional approaches to groups or individuals, and approaches to cess.
However, every bit Friend and Melt (2009) point, in order to create thriving collaboration communities, specification of goals, and outcomes is necessary equally well as the allocation of fourth dimension to interact. According to Dufour et al. (2006) a lack of fourth dimension and a lack of leadership support are amidst the factors that tin can cause a Professional person Learning Communities (PLC) to autumn apart. Research has shown that goals and outcomes must exist set from both principals and teachers in lodge to avoid hierarchical systems of control which according to Hargreaves (2003) are paths which will ultimately lead to "bogus collaboration." Additionally, studies concerning the influence of teacher collaboration on pupil accomplishment are insufficient (cf. Goddard et al., 2007; Desimone, 2009; Meirink et al., 2010; Kullmann, 2013). Goddard et al. (2010) argue that the bulk of the existing literature investigates the effects on teachers and not on students. Because research on teacher collaboration and its furnishings on student accomplishment is still in an emerging phase, farther examination is essential to sympathise its connections and to expand related findings (ibid).
This is, yet, a complicated task given the definitional inconsistencies of teacher collaboration. Woodland et al. (2013) write that a definition of teacher collaboration "is elusive, inconsistent, and often theoretical" (p. 443). The demand to reach a consistent definition is well-documented in the literature (cf. Bondorf, 2013; Aldorf, 2016), for instance Kelchtermans (2006) highlight the importance and necessity of further definition and specification of teacher collaboration, in society to "properly discuss the issue" (p. 220). The absence of a unified theory on the furnishings of teacher collaboration, equally well equally a consistent definition of the construct, atomic number 82 to mixed and inconsistent results which could brand their interpretation very difficult. Although originally denominated "collaborative consultation" and aimed specifically for interactions between general and special educators, Idol et al. (every bit cited in Luster, 1993) provide i of the first operationalized definitions: "an interactive process that enables people with diverse expertise to generate artistic solutions to mutually defined problems" (p. 1). This definition lays the foundations for later on expanded definitions such as occupational and organizational psychology (Piepenburg, 1991; Spieß, 2004), political pedagogy (Reinhardt, 2000), or pedagogic-oriented (Esslinger, 2002). Taking as a starting betoken these different approaches to the definition, Mora-Ruano et al. (2018) provide one definition aimed exclusively at the teacher level in which aspects such as relational trust, schoolhouse administration, as well equally coordination and exchange of ideas and materials between teachers play a central role for the educational activity effectiveness.
The structural characteristics of teacher collaboration are also manifold. Friend and Cook (1992) listed six defining features of collaboration: is voluntary; requires parity among participants; is based on mutual goals; depends on shared responsibility for participation and decision-making; individuals who collaborate share their resources, and individuals who collaborate share accountability for outcomes. Trivial (1990) identified four unlike types of collaborative elements, including storytelling and scanning for ideas, aid and assistance, sharing, and joint work. The seminal work from Gräsel et al. (2006) propose a model of teacher collaboration with three specific forms of collaboration: commutation, synchronization, and co-construction. Finally, the Leibniz Plant for the Education of Natural Sciences and Mathematics (IPN) constructed iii dissimilar forms of collaboration from the questionnaire for teachers used in PISA 2012 namely:
Teaching-related (IRC) which involve elements related to the grooming and development of didactical skills. This form is measured with questions referring to the frequency with which teachers exchange pedagogy materials, exam questions and work together for the preparation of individual and follow-upwardly lessons. Project-related (PRC) which include aspects related to the planning of lessons as well as the preparation of written exams and the joint planning and implementation of lessons which encompasses peer observation as well. System, performance, and problems related (ORC) covering aspects such equally strategies to help students based on their academic performance inside and across subjects equally well as strategies to dealing with homework (Frey et al., 2009; Mora-Ruano et al., 2018).
For the German language context which this paper addresses, Drossel (2015) states that findings apropos teacher collaboration in Federal republic of germany are "inconsistent and partially contradictory" (p. 55), although in Germany, collaboration is considered a fundamental office of schoolhouse development (Kultusministerkonferenz, 2003; Kulturministerkonferenz, 2014), and a primal aspect of models of professional person learning which endeavour to close the achievement gap. Furthermore, it is considered a key element for the effective implementation of educational standards (Trumpa et al., 2016). Although the focus of this paper lies on the German context, the results that we present tin can assistance researchers and practitioners alike make up one's mind if a particular form of collaboration can influence educatee achievement in other contexts.
Research Question and Hypothesis
Our review of the literature has identified concrete aspects that can exist positively influenced through teacher collaboration. Some of these aspects, such equally student accomplishment, are currently in an emergence phase and thus crave more investigation to expand the cognition base of operations about which specifics forms of collaboration can influence them. Therefore, in this study we would like to know to what extent teacher collaboration influences student achievement (measured in the subjects of mathematics, High german, biology, physics, and chemistry) dependent on the course of collaboration. To our knowledge, no other report has investigated the aforementioned variables with the representative dataset from PISA 2012 in Federal republic of germany. We hypothesize that student achievement will only be positively influenced by the third form of collaboration (organization, operation, and problem-related, ORC), because this is the only grade of collaboration that is explicitly focused on educatee achievement. The other two forms, IRC (instruction related) and PRC (project related) may accept an influence on other aspects simply not on student achievement.
Methods
Design
PISA employs a multi-layered (stratified) probability sample from a list of all schools provided by the fourteen Land Statistical Offices in Germany. This sample is drawn from two steps: starting time, schools are randomly selected, so within each selected schoolhouse, classes, students or teachers are randomly selected (Sälzer and Prenzel, 2013). For a detailed explanation of the design used in PISA 2012, see (ibid).
Participants
To investigate the extent to which instructor collaboration influences student achievement, we carry out a secondary analysis of the representative German PISA 2012 information. In order to properly appraise these effects, ii datasets (teacher and student) were matched, resulting in a subsample of 869 schoolteachers (44.5% female, 55.5% male person) with a hateful age of 47.3 and in a corresponding subsample of 869 students.
Measures
In PISA 2012 frequency of teacher collaboration is measured through question 21 in the in the National Questionnaire for Teachers (past Bosker and Hendriks, 1997, run into Table Appendix A) and investigated through three different forms of collaboration from the IPN: instruction-, project- and arrangement, performance, and bug related. Student accomplishment is measured through the retrieved students' grades in the first one-half yr of the bookish menstruation 2011/2012 in the subjects of mathematics, High german linguistic communication, biology, physics, and chemistry. In order to provide a valid framework we will use on the i mitt, the definition of teacher collaboration from Mora-Ruano et al. (2018) and on the other hand, the three forms of collaboration described above.
Assay
All analyses were conducted using the software packages SPSS 25 and AMOS 25. A full structural equation model was run to investigate the impact that teacher collaboration has on pupil achievement. Structural equation modeling allows to test statistically if there are "causal processes that generate observations on multiple variables [and] to hypothesize and specify in detail the procedure of interrelated effects operating among variables" (Bentler, 1988, p. 317). This is carried out through simultaneous analyses such as confirmatory gene analysis, linear regression and path estimates (cf. Bollen, 1989; Byrne, 2016). All this is in particular appropriate for our study, given that we desire to investigate the furnishings that teacher collaboration has on educatee achievement.
Before modeling the final structural model and matching the two datasets, we conducted a confirmatory get-go order factor analysis in order to test the factorial validity of the proposed model from PISA (Figure 1) and to verify if model re-specification was required. Anderson and Gerbing (1988) suggested that earlier examining the structural relationships in a model, a starting time step in grade of a confirmatory factor assay is preferred considering it ensures that the latent constructs are adequately measured. Nosotros used the Maximum Likelihood (ML) estimator considering it uses all the available information for each person, estimating missing information from relations among variables in the full sample (Schafer and Graham, 2002). Hypothesis testing was conducted at significance level of p < 0.05. Table i shows a comparing of the model fit results between the original hypothesized model and the two re-specifications which were conducted because the initial model proved to be ill-fitting. They were fabricated with the solely purpose to find a scale and an instrument that actually fit the data. Reasons and theoretical basis are also provided justifying every pace in the re-specifications.
Figure 1. Initial hypothesized measurement model.
Table 1. Comparison of model fit values between original and respecified measurement models.
In the literature, several recommendations take been made for the number of fit indices to be reported (c.f., Bollen, 1990, Fan et al., 1999, Hu and Bentler, 1999, Schumacker and Lomax, 1996). Brown (2006) recommended the use of fit indices from each of the 3 categories of fit estimates: (a) an index for a model's absolute fit, (b) an index for fit adjusting for model parsimony, and (c) an index for comparative or incremental fit. Post-obit this recommendation, we selected the following fit indices: the standardized root mean square (SRMR), the Tucker-Lewis Alphabetize (TLI; Tucker and Lewis, 1973), the root mean-foursquare error of approximation (RMSEA; Steiger and Lind, 1980), and the comparative fit index (CFI; Bentler, 1990). We report the chi-square and its significance value as information technology is the original fit index and the footing for near other fit indices. Still, it is worth noting that the chi-square is no longer relied upon every bit a basis for credence or rejection because it is very sensitive to sample size (Schermelleh-Engel et al., 2003; Vandenberg, 2006), and it is affected past several factors similar model size, normal distribution of the variables likewise every bit omission of variables (Newsom, 2018). Additionally several recommendations about the cutting-off values to decide goodness-of-fit have been suggested and although this has been an object of study for a long fourth dimension, there is still some disagreement every bit to the cut-off values for fit indices (Marsh et al., 2004, 2005). For our written report, the recommended joint criteria to retain a model by Hu and Bentler (1999) and past MacCallum et al. (1996) are used. Hu and Bentler (1999) suggested values for the CFI and TLI above 0.95 and values below 0.05 for the SRMR, whereas MacCallum et al. (1996) defined RMSEA values of 0.01, 0.05, and 0.08 to indicate excellent, practiced, and mediocre fit, respectively.
Exploratory Gene Analysis
Given that the proposed construction resulted in an sick-fitting model, an exploratory gene analysis (EFA) was conducted to farther investigate the adequate number of constructs and construction of this measure. This assay is intended to explore the data when the links between the observed and latent variables are unknown or uncertain (Pilus et al., 2014; Byrne, 2016). In other words, this immune us to organize the items of the questionnaire better in relation to the three proposed forms of collaboration.
Prior to conducting the EFA a bivariate correlation was carried out in order to exam the factorability of the items. No signs of multicollinearity were found as none of the items correlated more than the threshold of 0.8 suggested past Field (2013). Nine items were eliminated because they did not contribute to a simple cistron structure and failed to meet a minimum criteria of having a principal cistron loading of 0.4 or higher up, and no cross-loading of 0.2 or to a higher place as suggested by Nunnally and Bernstein (1994). Furthermore, because their communalities were lower than 0.3 or only marginally higher up (Item 11) and thus were not explained adequately by the factors (see Table ii).
Table ii. EFA of forms of teacher collaboration.
Secondly, the Kaiser-Meyer-Olkin measure of sampling capability was 0.916 falling in the range that Kaiser (1974) defined as "marvelous." The Bartlett's test of sphericity was significant, χtwo (136) = 10,297.8, p < 0.05. The diagonals of the anti-image correlation matrix were also all over 0.5. Reliability of the scales were measured through Cronbach's α and all of them resulted in an acceptable value. Pilus et al. (2014) deemed values of 0.threescore–0.70 the lower limit of acceptability. IRC α = 0.63; Red china α = 0.seventy, and ORC α = 0.71. All items appeared to be worthy of memory.
Confirmatory Factor Assay
Afterwards, a confirmatory factor analysis was conducted in order to test the factorial validity of the re-specified instrument, resulting in a better model than the original. Notwithstanding, this model but partially fulfilled the required criteria to be retained (encounter Table 2). Subsequently an inspection of the regression weights, the error terms of the items vi and viii were correlated because they had an unusually big value in comparison to the other items, contributing to a misspecification of the model. "Correlated error terms in measurement models correspond the hypothesis that the unique variances of the associated indicators overlap; that is, they measure something in mutual other than the latent constructs that are represented in the model" (Dattalo, 2013, p. 118). Given that these two items take a similar wording, i can infer that they share something in common; although the specific nature of the "something" is unknown, 1 can argue that ane central aspect in both cases changes, namely: the teachers are no longer alone and are accompanied past a colleague in the classroom. Therefore, the correlation of these error terms is supported by what we consider a substantive rationale and not only because of statistical reasons or for purposes of achieving a better plumbing fixtures model. Effigy 2 shows the final measurement model with its standardized values and regression weights. This model will exist used to perform our chief analyses.
Effigy 2. Last measurement model with standardized values and regression weights.
Results
After validation of the measurement model, the human relationship between the three forms of collaboration and educatee achievement was estimated through a structural equation model (see Figure 3). It consists of a measurement model that defines the latent constructs and a structural model that defines the relationships amidst the latent variables (Bollen, 1989). The measurement model specifies the outcomes variables measured. Overall, the model produced a good fit of the data, χ2 = 139,513 (p ≤ 0.05), df = 58, CFI = 0.975, TLI = 0.960, RMSEA = 0.040 (90% CI = 0.032–0.049) PCLOSE = 0.970. Given that pupil achievement information contained missing values and that AMOS does non provide the total information maximum likelihood interpretation, the SRMR was not calculated for the concluding model. Nonetheless, all values are well within the threshold for a good fit.
Effigy iii. Structural model of 3 forms of collaboration and student achievement (SA).
Gene loadings for the complete model tin can exist seen in Table 3. The tertiary form of collaboration [organization, performance, and issues related (ORC)] was the only class that had a positive influence on student achievement (SA) (standardized coefficient = 0.06). The other two forms, Teaching-related (IRC) and Project-related (PRC) collaboration, did not have an upshot on pupil achievement (standardized coefficients = −0.03 and 0.00, respectively). Nonetheless, these effects were non-significant.
Table 3. Gene loadings and significance values of the final model.
Discussion
The central role that teachers play every day at school is well documented in the literature. For instance, Kunter and Pohlmann (2009) write that "teachers are largely responsible for the success of education" (pp. 262), thus it is of disquisitional importance to investigate which factors can positively influence them as professionals and as individuals. Teacher collaboration is 1 gene that is consistently presented as decisive for the comeback of the schoolhouse and its members. Ditton (2000) places teacher collaboration (at the instruction level) every bit a cistron in a model for school quality. Previous research has found positive furnishings of teacher collaboration on student achievement (cf. Goddard et al., 2010; Lara-Alecio et al., 2012). Reeves et al. (2017) argue that related findings are limited, given the trend to investigate teacher collaboration as a single construct instead of using unlike forms. Thus, by analyzing the representative German sample from PISA 2012, we expand the existing literature by investigating the effects that 3 forms of collaboration [pedagogy-related (IRC), project-related (People's republic of china) and organization, operation, and problems-related (ORC)] have on pupil achievement as measured past grades from the subjects of mathematics, High german language, biology, physics and chemistry. Although from our analysis, the effects of the three forms of collaboration on student achievement were non-significant, the direction of the relationships were as expected. That is, only the tertiary class of collaboration (ORC) were positive. The other two forms IRC and PRC yielded no direction whatsoever and a negative direction, respectively. Nosotros expected this because the items belonging to the ORC dimension were the simply ones that dealt with outcomes related to student achievement. The fact that the other 2 forms of collaboration (IRC and PRC) have a null and a negative standardized regression weight does non hateful that the more than a teacher collaborates forth these dimensions, the worse the students' accomplishment will exist. These results are an indication that these two forms (IRC and PRC) may have effects on other aspects such as increased job satisfaction and/or decreased teachers' workload, but no effect on student achievement. Additionally, the effects of the forms of collaboration on student accomplishment may be delayed in time.
Two major limitations of our report warrant attending. First, given the inherent limitations of the data nosotros used, but a direct effect of teacher collaboration on pupil accomplishment could exist modeled. Even so, teacher collaboration encompasses very complex forms of interactions among its individuals and therefore, it would be appropriate for future studies to include moderation or mediation variables such as primary leadership, teachers' self-efficacy or student motivation in order to requite a meliorate explanation of the effects of teacher collaboration on pupil achievement. The data from the PISA 2012 German questionnaire had no information regarding these variables, making it impossible to include them in the model. Second, the factorial validity of the original questionnaire proved to be problematic and therefore nosotros conducted ii re-specifications that despite yielding proficient results, had fewer items than the original, and as a result, some data was inevitably lost. It would be advisable to rethink the theory that supports the model as well equally the instrument itself.
From our findings, implications for both the research and praxis tin can be fatigued. Future studies should investigate teacher collaboration as a construct that encompasses more than one form, merely then can precise information exist drawn nigh the structures, mechanisms and effects surrounding these practices, which in turn permit teachers, principals, and other participating actors to develop ameliorate collaborative practices. The implication for praxis is that more attending to aspects regarding students' achievement, such as articulation word and advice betwixt teachers for students with different performance levels, should be made because these collaboration practices tin can positively influence students' achievement.
Conclusion
Our goal was to investigate to what extent the three forms of teacher collaboration proposed past the German teacher questionnaire from PISA 2012 influence pupil achievement. Our results show that a positive consequence on student achievement can exist established only when teachers specifically interact to talk over or advise each other about student performance. However, the inclusion of additional variables in a future model, could meliorate explain these effects.
Data Availability
The datasets generated for this study will not be made publicly available permission to admission and use the data for scientific purposes must be granted through the German Research Information Eye (FDZ) at the Institute for Educational Quality Improvement (IQB).
Ideals Statement
Permission to admission and use the data for scientific purposes was granted through the German Research Data Center (FDZ) at the Institute for Educational Quality Comeback (IQB). Every bit per OECD guidelines and German national regulations (KMK) no new ideals approval was required. The authors did not accept access to identifiable information.
Author Contributions
JM-R drafted the manuscript, wrote the literature background, performed, and interpreted the statistical analyses. J-HH provided expertise on data analysis and performed some of these analyses (i.due east., data matching). MG gave oversight almost writing and provided feedback to the terminal edited manuscript.
Funding
This work was supported by the High german Research Foundation (DFG) and the Technical University of Munich (Tummy) in the framework of the Open Access Publishing Programme.
Disharmonize of Interest Statement
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed equally a potential conflict of interest.
References
Aldorf, A.-M. (2016). Lehrerkooperation und die Effektivität von Lehrerfortbildungen. Wiesbaden: Springer VS. doi: 10.1007/978-3-658-11677-4
CrossRef Full Text | Google Scholar
Anderson, J. C., and Gerbing, D. W. (1988). Structural equation modeling in do: a review and recommended two-step approach. Psychol. Bull. 103, 411–423. doi: 10.1037/0033-2909.103.3.411
CrossRef Total Text | Google Scholar
Bentler, P. M. (1988). "Causal modeling via structural equation systems," in Handbook of Multivariate Experimental Psychology. Perspectives on Private Differences, eds J. R. Nesselroade and R. B. Cattell (Boston, MA: Springer), 317–335. doi: ten.1007/978-1-4613-0893-5_9
CrossRef Full Text | Google Scholar
Bollen, K. A. (1989): Structural Equations with Latent Variables. New York, NY: John Wiley & Sons. doi: 10.1002/9781118619179.
CrossRef Full Text | Google Scholar
Bollen, 1000. A. (1990). Overall fit in covariance structure models: ii types of sample size furnishings. Psychol. Bull. 107, 256–259. doi: x.1037/0033-2909.107.2.256
CrossRef Full Text | Google Scholar
Bondorf, N. (2013): Profession und Kooperation: Eine Verhältnisbestimmung am Beispiel der Lehrerkooperation. [Profession and Cooperation. A Defining Human relationship Using the Case of Instructor Cooperation]. Wiesbaden: Springer VS. doi: 10.1007/978-3-531-19703-six.
CrossRef Full Text | Google Scholar
Borko, H. (2004). Professional development and instructor learning: mapping the terrain. Educ. Res. 33, three–15. doi: 10.3102/0013189X033008003
CrossRef Total Text | Google Scholar
Bosker, R. J., and Hendriks, M. A. (1997). Betrouwbaarheid, Validiteit en Bruikbaarheid van een Instrumentarium X Behoeve van Schoolzelfevaluatie in Het Basisonderwijs. Enschede: Universiteit Twente, Onderzoek Centrum Toegepaste Onderwijskunde.
Google Scholar
Chocolate-brown, T. A. (2006). Confirmatory Factor Analysis for Applied Research. New York, NY: Guilford Press.
Google Scholar
Burns, D., and Darling-Hammond, Fifty. (2014). Education Around the Earth: What Can TALIS Tell United states of america? Stanford, CA: Stanford Center for Opportunity Policy in Education.
Google Scholar
Byrne, B. Thousand. (2016). Structural Equation Modeling with AMOS: Basic Concepts, Applications, and Programming, 3rd Edn. New York, NY: Routledge.
Google Scholar
Darling-Hammond, Fifty., Hyler, M. Due east., and Gardner, One thousand. (2017). Effective Teacher Professional person Evolution. Palo Alto, CA: Learning Policy Establish.
Google Scholar
Darling-Hammond, 50., Wei, R., Adree, A., Richardson, Northward., and Orphanos, S. (2009). Professional person Learning in the Learning Profession: A Status Report on Teacher Development in the Us and Abroad. National Staff Evolution Council. Retrieved from: https://learningforward.org/docs/default-source/pdf/nsdcstudy2009.pdf (accessed April 6, 2019).
Google Scholar
Dattalo, P. (2013). Analysis of Multiple Dependent Variables. London: Oxford Academy Press. doi: ten.1093/acprof:oso/9780199773596.001.0001
CrossRef Total Text | Google Scholar
Desimone, L. M. (2009). Improving impact studies of teachers' professional development: toward better conceptualizations and measures. Educ. Res. 38, 181–199. doi: x.3102/0013189X08331140
CrossRef Full Text | Google Scholar
Ditton, H. (2000). Qualitätskontrolle und qualitätssicherung in schule und unterricht. ein überblick zum stand der empirischen forschung. [Quality command and quality assurance in school and teaching. An overview of the land of empirical research.]. Zeitschrift für Pädagogik 41, 73–92.
Google Scholar
Drossel, Thousand. (2015). Motivationale Bedingungen von Lehrerkooperation. Eine empirische Analyse der Zusammenrarbeit im Projekt "Ganz In". [Motivational Atmospheric condition of Teacher Collaboration. An Empirical Assay of the Collaboration in the Project 'Ganz In']. Münster: Waxmann.
Google Scholar
Dufour, R., Dufour, R., and Eaker, R. (2006). Learning by Doing. Bloomington, IN: Solution Tree.
Google Scholar
DuFour, R., Eaker, R., and Dufour, R. (2005). On Common Footing: The Power of Professional Learning Communities. Bloomington, IN: Solution Tree.
Google Scholar
Dumay, X., Boonen, T., and Van Damme, J. (2013). Principal leadership long-term indirect effects on learning growth in mathematics. Elem. Schoolhouse J. 114, 225–251. doi: 10.1086/673198
CrossRef Full Text | Google Scholar
Eisner, Due east. W. (1992). Educational reform and the ecology of schooling. Teach. Coll. Rec. 93, 610–627.
Google Scholar
Esslinger, I. (2002). Berufsverständnis und Schulentwicklung: ein Passungsverhältnis? [Professional Understanding and Schoolhouse Development: A Match?]. Bad Heilbrunn/Obb.: Klinkhardt.
Google Scholar
Fan, X., Thompson, B., and Wang, 50. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Struct. Equ. Model. 6, 56–83. doi: 10.1080/10705519909540119
CrossRef Full Text | Google Scholar
Field, A. (2013) Discovering Statistics Using IBM SPSS Statistics: And Sex and Drugs and Rock "Due north" Roll, 4th Edn. Los Angeles, CA; London; New Delhi: Sage.
Google Scholar
Frey, A., Taskinen, P., Schütte, Chiliad., Prenzel, Yard., Artelt, C., Baumert, J. (eds). (2009). PISA 2006: Skalenhandbuch. Dokumentation der Erhebungsinstrumente. Münster: Waxmann.
Google Scholar
Friend, Chiliad., and Cook, 50. (2009). Interactions: Collaboration Skills for School Professionals, 6th Edn. Upper Saddle River, NJ: Prentice Hall.
Google Scholar
Gaikwad, Southward., and Brantly, P. (1992). Teacher isolation—loneliness in the classroom. J. Adventist Educ. 54, 14–17.
Google Scholar
Gebhardt, M., Schwab, S., Krammer, M., and Gegenfurtner, A. (2015). General and special pedagogy teachers' perceptions of teamwork in inclusive classrooms at elementary and secondary schools. J. Educ. Res. 7, 129–146.
Google Scholar
Goddard, Y. L., Goddard, R. D., and Tschannen-Moran, M. (2007). A theoretical and empirical investigation of teacher collaboration for school improvement and pupil achievement in public elementary schools. Teach. Coll. Rec. 109, 877–896.
Google Scholar
Goddard, Y. L., Miller, R., Larsen, R., Goddard, 1000., Jacob, R., Madsen, J., et al. (2010). "Connecting principal leadership, teacher collaboration, and student accomplishment," in Paper presented at the American Educational Research Association Annual Meeting (Denver, CO).
Google Scholar
Graham, P. (2007). Improving instructor effectiveness through structured collaboration: a example study of a professional learning customs. Res. Middle Level Educ. 31, i–17. doi: ten.1080/19404476.2007.11462044
CrossRef Full Text | Google Scholar
Gräsel, C., Fussangel, Grand., and Pröbstel, C. (2006). Die Anregung von Lehrkräften zur Kooperation - eine Aufgabe für Sisyphos? [The suggestion of teachers for cooperation - a task for Sisyphos?]. Zeitschrift für Pädagogik 52, 205–219.
Google Scholar
Hair, J. F., Black, W. C., Babin, B. J., and Anderson, R. E. (2014). Multivariate Information Analysis, 7th Edn.New York, NY: Pearson.
Google Scholar
Hargreaves, A. (2003). Education in the Knowledge Society: Education in the Age of Insecurity. New York, NY: Teachers College Press.
Google Scholar
Hargreaves, A., and Fullan, 1000. (2012). Professional Capital: Transforming Teaching in Every School. New York, NY: Teachers College, Columbia University
Google Scholar
Hattie, J. (2015). What Works Best in Instruction: The Politics of Collaborative Expertise. London: Pearson.
Google Scholar
Hochweber, J., Steinert, B., and Klieme, E. (2012). Lehrerkooperation, unterrichtsqualität und lernergebnisse im fach englisch. [The bear on of teacher cooperation and instructional quality on learning in English language as a foreign linguistic communication]. Unterrichtswissenschaft 40, 351–370.
Google Scholar
Hu, 50., and Bentler, P. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. half-dozen, 1–55. doi: 10.1080/10705519909540118
CrossRef Full Text | Google Scholar
Jackson, C. K., and Bruegmann, East. (2009). Teaching students and pedagogy each other: the importance of peer learning for teachers. Am. Econ. J. one, 85–108. doi: 10.3386/w15202
CrossRef Full Text | Google Scholar
Johnson, B. (2003). Instructor collaboration: good for some, not so adept for others. Educ. Stud. 29, 337–350. doi: ten.1080/0305569032000159651
CrossRef Full Text | Google Scholar
Kelchtermans, One thousand. (2006). Teacher collaboration and collegiality as workplace weather: a review. Zeitschrift für Pädagogik 52, 220–237.
Google Scholar
Kullmann, H. (2013). "Der Zusammenhang von Lehrerkooperation und Schulleistung - Zentrale Befunde und Perspektiven für die Forschung [The human relationship between instructor collaboration and school functioning - primal findings and perspectives for research]," in Professionalität und Kooperation in Schulen. Beiträge zur Diskussion über Schulqualität [Professionalism and cooperation in schools. Contributions to the discussion about schoolhouse quality.], eds M. Keller-Schneider, Southward. Albisser, and J. Wissinger (Bad Heilbrunn: Julius Klinkhardt, 123–137.
Google Scholar
Kunter, G., and Pohlmann, B. (2009). "Lehrer [Instructor]," in Pädagogische Psychologie, eds E. Wild and J. Möller (Berlin; Heidelberg: Springer-Lehrbuch. Springer), 961–288. doi: 10.1007/978-three-540-88573-3_11
CrossRef Total Text | Google Scholar
Lara-Alecio, R., Tong, F., Irby, B. J., Guerrero, C., Huerta, M., and Fan, Y. (2012). The issue of an instructional intervention on middle school English learners' scientific discipline and English reading achievement. J. Res. Sci. Teach. 49, 987–1011. doi: 10.1002/tea.21031
CrossRef Full Text | Google Scholar
Lee, V. Eastward., and Smith, J. B. (1996). Collective responsibility for learning and its effects on gains in accomplishment for early on secondary school students. Am. J. Educ. 104, 103–147. doi: ten.1086/444122
CrossRef Full Text | Google Scholar
Little, J. W. (1990). The persistence of privacy: autonomy and initiative in teachers' professional relations. Teach. College Record 91, 509–536.
Google Scholar
Lortie, D. C. (1975). Schoolteacher: A Sociological Study. Chicago, IL: Academy of Chicago Press.
Google Scholar
Louis, Thousand. S., Dretzke, B., and Wahlstrom, K. (2010). How does leadership affect educatee achievement? Results from a national US survey. School Effect. School Improv. 21, 315–336 doi: 10.1080/09243453.2010.486586
CrossRef Full Text | Google Scholar
MacCallum, R., Browne, One thousand., and Sugawara, H. (1996). Power assay and determination of sample size for covariance structure modeling. Psychol. Methods 1, 130–149. doi: 10.1037/1082-989X.1.two.130
CrossRef Full Text | Google Scholar
Marsh, H. W., Hau, K.-T., and Grayson, D. (2005). "Goodness of fit in structural equation models," in Multivariate Applications Book Series. Contemporary Psychometrics: A Festschrift for Roderick P. McDonald, eds A. Maydeu-Olivares and J. J. McArdle (Mahwah, NJ: Lawrence Erlbaum Associates Publishers, 275–340.
Google Scholar
Marsh, H. W., Hau, K.-T., and Wen, Z. (2004) In search of golden rules: comment on hypothesis-testing approaches to setting cutoff values for fit indexes dangers in over generalizing Hu Bentler'south (1999) findings. Struct. Equ. Model. eleven, 320–341. doi: x.1207/s15328007sem1103_2
CrossRef Full Text | Google Scholar
Meirink, J. A., Imants, J., Meijer, P. C., and Verloop, Due north. (2010). Instructor learning and collaboration in innovative teams. Cambridge J. Educ. 40, 161–181. doi: 10.1080/0305764X.2010.481256
CrossRef Total Text | Google Scholar
Moolenaar, N. M., Sleegers, P. J., and Daly, A. J. (2012). Teaming up: linking collaboration networks, commonage efficacy, and student achievement. Teach. Teach. Educ. 28, 251–262. doi: 10.1016/j.tate.2011.10.001
CrossRef Full Text | Google Scholar
Mora-Ruano, J. G., Gebhardt, 1000., and Wittmann, E. (2018). Teacher Collaboration in german schools: do gender and school type influence the frequency of collaboration among teachers? Front. Educ. iii:55. doi: 10.3389/feduc.2018.00055
CrossRef Full Text | Google Scholar
Mostafa, T., and Pál, J. (2018). "Scientific discipline teachers' satisfaction: evidence from the PISA 2015 teacher survey," in OECD Pedagogy Working Papers, 168 (Paris: OECD Publishing). doi: ten.1787/1ecdb4e3-en
CrossRef Full Text | Google Scholar
Newsom, J. (2018). Some Clarifications and Recommendations on Fit Indices [Class handout]. Psy 523/623: Structural Equation Modeling, Jump 2018. Portlant, OR: Section of Psychology, Portland State Academy. Retrieved from: http://web.pdx.edu/~newsomj/semclass/ (accessed Feb 21, 2019)
Google Scholar
Nunnally, J. C., and Bernstein, I. H. (1994). Psychometric Theory 3rd Edn. New York, NY: McGraw-Colina.
Google Scholar
OECD (2004). Completing the Foundation for Lifelong Learning: An OECD Survey of Upper Secondary Schools. Paris: OECD. doi: 10.1787/9789264103733-en
CrossRef Full Text | Google Scholar
OECD (2014). "What helps teachers feel valued and satisfied with their jobs?" Teaching in Focus, No. 5. Paris: OECD Publishing. doi: 10.1787/5jxzbtw4gzg3-en
CrossRef Full Text | Google Scholar
Piepenburg, U. (1991). "Ein Konzept von Kooperation und die technische Unterstützung kooperativer Prozesse in Bürobereichen," in Computergestützte Gruppenarbeit (CSCW) [Computer-aided group piece of work], eds J. Friedrich, and K.-H. Rödiger (Stuttgart: B.M. Teubner), 79–94. doi: 10.1007/978-three-322-92140-6_4
CrossRef Full Text | Google Scholar
Prenzel, M., Sälzer, C., Klieme, East., Köller, O., Mang, J., Heine, J.-H., et al. (2015). Programme for International Student Assessment 2012 (PISA 2012). Version: 2. IQB – Institut zur Qualitätsentwicklung im Bildungswesen. Datensatz. doi: 10.5159/IQB_PISA_2012_v2
CrossRef Full Text | Google Scholar
Puchner, 50. D., and Taylor, A. R. (2006). Lesson written report, collaboration and teacher efficacy: stories from 2 school based math lesson study groups. Teach. Teach. Educ. 22, 922–934. doi: 10.1016/j.tate.2006.04.011
CrossRef Full Text | Google Scholar
Reeves, P., Pun, W., and Chung, K. (2017). Influence of teacher collaboration on job satisfaction and pupil achievement. Teach. Teach. Educ. 67, 227–236. doi: 10.1016/j.tate.2017.06.016
CrossRef Total Text | Google Scholar
Reinhardt, Due south. (2000). "Kooperation," in Lexikon der Politischen Bildung, Vol. 3. [Encyclopedia of political education], ed G. Weißeno (Schwalbach), 91.
Google Scholar
Ronfeldt, Grand., Farmer, S. O., Kiel, M., and Grissom, J. A. (2015). Instructor collaboration in instructional teams and student accomplishment. Am. Educ. Res. J. 52, 475–514. doi: 10.3102/0002831215585562
CrossRef Full Text | Google Scholar
Sälzer, C., and Prenzel, Grand. (2013). "PISA 2012 – eine Einführung in die aktuelle studie [PISA 2012 – an introduction to the electric current study]," in PISA 2012 – Fortschritte und Herausforderungen in Deutschland [PISA 2012 – Advances and Challenges in Germany], eds M. Prenzel, C. Sälzer, E. Klieme, and O. Köller (Münster: Waxmann, 11–43.
Google Scholar
Schacter, J., and Thum, Y. M. (2004). Paying for loftier- and low-quality teaching. Econ. Educ. Rev. 23, 411–430. doi: 10.1016/j.econedurev.2003.08.002
CrossRef Full Text | Google Scholar
Scheerens, J. (2000). Improving School Effectiveness. In: Unesco (Ed.): Fundamentals of Educational Planning, 68. Paris.
Google Scholar
Schermelleh-Engel, One thousand., Moosbrugger, H., and Müller, H. (2003). Evaluating the fit of structural equation models: tests of significance and descriptive goodness-of-fit measures. Methods Psychol. Res. 8, 23–74.
Google Scholar
Schumacker, R. East., and Lomax, R. Yard. (1996). A Beginner's Guide to Structural Equation Modeling. Mahwah, NJ: Lawrence Erlbaum Assembly.
Google Scholar
Schwab, S. (2017). Interprofessionelle Lehrkraftkooperation im inklusiven Unterricht aus der Perspektive der Schülerinnen und Schüler. [Interprofessional teacher cooperation in inclusive pedagogy from the perspective of students.]. Unterrichtswissenschaft 45, 262–279. doi: x.3262/UW1704262
CrossRef Full Text | Google Scholar
Spieß, Due east. (2004). "Kooperation und konflikt," in Organisationspsychologie –Gruppe und Organisation [Organizational Psychology - Group and Organization], ed H Schuler (Göttingen: Hogrefe, 193–247.
Google Scholar
Steiger, J. H., and Lind, J. C. (1980). "Statistically-based tests for the number of common factors," in Paper presented at the Annual Spring Coming together of the Psychometric Society (Iowa City, IA).
Google Scholar
Svendsen, B. (2016) Teachers' experience from a school-based collaborative teacher professional development programme: reported affect on professional evolution. Teach. Dev. 20, 313–328. doi: 10.1080/13664530.2016.1149512.
CrossRef Full Text | Google Scholar
Trumpa, S., Franz, East.-K., and Greiten, S. (2016). Forschungsbefunde zur kooperation von lehrkräften – ein narratives review [Research results on teacher cooperation - a narrative review]. Dice Deutsche Schule 108, 82–94.
Google Scholar
Tucker, L. R., and Lewis, C. (1973). A reliability coefficient for maximum likelihood cistron analysis. Psychometrika 38, ane–10. doi: 10.1007/BF02291170
CrossRef Full Text | Google Scholar
Vandenberg, R. J. (2006). Statistical and methodological myths and urban legends. Org. Res. Methods nine, 194–201. doi: 10.1177/1094428105285506
CrossRef Full Text | Google Scholar
Vincent-Lancrin, S. Yard, Jacotin, J., Urgel, Southward., Kar, C., and González-Sancho (2017). Measuring Innovation in Education: A Journeying to the Future. Paris: OECD Publishing.
Google Scholar
Williams, K. L. (2010). Teacher collaboration equally professional development in a large, suburban high school (Dissertation). Academy of Nebraska, Lincoln, OR; Omaha, NE, United States.
Google Scholar
Woodland, R., Lee, M. Grand., and Randall, J. (2013). A validation report of the teacher collaboration assessment survey. Educ. Res. Evalu. 19, 442–460. doi: 10.1080/13803611.2013.795118
CrossRef Full Text | Google Scholar
Appendix A
Source: https://www.frontiersin.org/articles/10.3389/feduc.2019.00085/full
0 Response to "Peer Reviewed Article on Collaborative Strategies for Effective Literacy Teamwork"
Post a Comment