EPAAv18n32 Manuscript received: 1/10/2010 Revisions received: 8/20/2010 Accepted: 10/01/2010 education policy analysis archives A peer-reviewed, independent, open access, multilingual journal Arizona State University Volume 18 Number 32 30th of December 2010 ISSN 1068-2341 Rethinking Mentoring: Comparing Policy and Practice in Special and General Education Leah Washburn-Moses Miami University Citation: Wasburn-Moses, L. (2010) “Rethinking Mentoring: Comparing Policy and Practice in Special and General Education” Educational Policy Analysis Archives, Vol 18 (32). Retrieved [date], from http://epaa.asu.edu/ojs/article/view/716 Abstract: Although teacher mentoring is now mandated in most states, high quality research in mentoring remains scarce (Rockoff, 2008). There is a great need to understand how such policies are implemented (Smith, 2007), particularly in teaching areas with high shortages. The purpose of this study is to compare state and district mentoring policies with practices in special and general education. Survey data were collected from 232 teachers in one state and compared with policy information from the Teacher Rules, Roles, and Rights (TR3) database. Results indicated uneven implementation of policy, in that some stated policy was not adhered to consistently, and consistency in practices was seen in the absence of other policy. Further, special education teachers reported less compliance with some mentoring policies than general education teachers. A new model is proposed to encourage implementation of research-validated practices in teacher mentoring. Keywords: educational policy; mentors; special education teachers epaa aape Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 2 Repensando las tutorías: Comparando políticas y prácticas en educación especial y general Resumen: A pesar de que los programas de tutorías (mentores) de orientación profesional para docentes son obligatorias en la mayoría de los estados, investigaciones de calidad sobre este tema son escasas (Rockoff, 2008). En este sentido, es necesario entender cómo esas políticas se aplican (Smith, 2007), especialmente en las zonas donde faltan docentes. El propósito de este estudio es comparar las políticas sobre tutorías de orientación profesional implementadas en los estados y distritos escolares tanto para los sistemas de educación especial y educación general. Se utilizó una encuesta con 232 maestros en un estado y se compararon los resultados con la información en la base de datos Normas, Funciones y Deberes de los Docentes (TR3). Los resultados indican un desequilibrio en la aplicación de políticas, en el sentido de que algunas políticas no se aplicaban constantemente, y ciertas prácticas se consolidaron en ausencia de políticas explícitas. Además, los maestros de educación especial mencionaron mayor falta de cumplimiento con las políticas de tutoría de orientación profesional que los profesores de educación general. Este trabajo propone un nuevo modelo basado en propuestas metodológicamente validadas en investigaciones para estimular la aplicación de tutorías de orientación profesional con docentes. Palabras clave: política educacional; mentores, docentes de educación especial Repensando as tutorias: Comparando políticas e práticas em educação especial e geral Resumo: Embora as tutorias (mentores) de orientação profissional para professores sejam obrigatórias na maioria dos estados, pesquisas de qualidade sobre o tema são escassas (Rockoff, 2008). Nesse sentido, faz-se necessário entender como tais políticas são implementadas (Smith, 2007) especialmente em áreas onde faltam professores. O propósito deste estudo é comparar as políticas de tutorias de orientação profissional praticadas por estados e distritos escolares no que tange a educação especial e a educação geral. Foi realizado um questionário com 232 professores em um estado e seus resultados foram comparados com as informações presentes da base de dados Normas, funções e direitos dos professores (TR3). Os resultados da pesquisa indicaram um desequilíbrio na implementação das políticas, no sentido de que algumas políticas não foram respeitadas de forma consistente, e consistência nas práticas aparecia na ausência de outras políticas. Além disso, professores de educação especial mencionaram menor cumprimento de algumas políticas de tutorias de orientação profissional do que professores de educação geral. Um novo modelo é proposto para encorajar a implementação de práticas de pesquisa metodologicamente válidas sobre tutorias de orientação profissional para professores. Palavras-chave: política educacional; mentores, professores de educação especial Introduction For years, the field of education has attempted to increase teacher retention and bolster teacher quality through a variety of means. Teacher mentoring is one such strategy, as quality mentoring is thought to be related to both retention and increased teacher quality, particularly in hard-to-staff areas such as special education. Although teacher mentoring policies are now mandated in most states, the implementation of these policies varies (Carver & Feiman-Nemser, 2009; Whitaker, 2000). Further complicating this issue is that practices in special education commonly differ from formal policy, due to the unique conditions in the Educational Policy Analysis Archives Vol. 18 No. 32 3 field (Coleman, 2001). Very little is known about either mentoring policies or practices, particularly in special education (Billingsley, Griffin, Smith, Kamman, & Israel, 2009; Gehrke & McCoy, 2006). At issue is whether practices in both special and general education teacher mentoring follow formal policies. This new knowledge can inform policymakers attempting to create and revise policies in such a way as to assist all teachers (Smith, 2007). Mentoring Policy Pervasive teacher attrition and concerns about teacher quality have plagued the field of education for years. In special education, teacher shortages have have been characterized as “chronic, increasing, and serious” (Boe & Cook, 2006, p. 455). Overall, national estimates of the percent of special education teaching positions each year that remain unfilled have ranged from 9 to 11 percent. These conditions have forced the field into a situation in which the majority of its novice teachers are hired from other teaching fields or otherwise lacking sufficient preparation (Boe & Cook, 2006). Further, the continued growth of alternative licensure programs in special education has contributed to a general consensus that teacher preparation in a complex field is too often deficient, and that the need for quality research is great (McLeskey & Ross, 2004). One way in which the field has attempted to address these concerns is through teacher mentoring. An international review of the literature defined mentoring as “as “the one-to-one support of a novice or less experienced practitioner by a more experienced practitioner, designed primarily to assist the development of the mentee’s expertise and to facilitate their introduction into the culture of the profession [teaching] and into the specific local context [the school]” (Hobson, Ashby, Malderez, & Tomlinson, 2009), p. 207. Typically, mentoring means the establishment of a formal relationship between one novice and one experienced teacher that provides the novice with various kinds of supports (Education Commission of the States, 1999). Supports can take a variety of forms, from observation of the novice’s teaching to co-planning to discussing beliefs about teaching and learning (Hirsch, Rorrer, Sindelar, Dawson, Heretick, & Jia, 2009). Some also see mentoring as a way to reward and retain veteran teachers through development of leadership opportunities (Hobson et al., 2009). As such, truly “successful” mentoring would be effective at retaining both novice and experienced teachers and improve teacher quality. Widespread beliefs about the positive outcomes of mentoring have prompted states and districts to enact mentoring policies. As of 2007, at least 45 states had mandated mentoring for novice teachers (NCTQ, 2007). Of these, at least 31 required mentor training and at least 21 required some type of observation of the novice’s teaching. The latest Schools and Staffing Survey (SASS) shows that nearly 70% of novice teachers report having a mentor (K. Gruber, personal communication, September 30, 2009). Other common mandates included release time, payment for mentors, and requirements as to who assigns the mentor to a new teacher. Some states also specify a minimum amount of time the novice and mentor will meet (NCTQ, 2007). In special education, nearly all teachers participate in the same mentoring programs as their general education colleagues (Müller & Burdette, 2007), despite the fact that many believe these teachers have unique mentoring needs (Billingsley et al., 2009). Unfortunately, common problems of practice often result in a gap between the intent of the mentoring policy and practices in schools. “It is clear that good policy does not guarantee faithful program implementation, much less increased retention and improved teacher quality” (Hirsch et al., 2009, p. 23). Some of these issues unclear definitions of Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 4 mentoring and lack of guidance in policy as to how to create the conditions that will result in effective mentoring (Hobson et al., 2007). This policy to practice gap is so common that Youngs (2007) notes “little understanding in the research literature of the relationship between district induction policy and the nature and quality of the support experienced by beginning teachers” (p. 797). In sum, although mentoring policies are now widespread, what counts as “mentoring” still varies widely in practice, from a few required meetings with an assigned colleague to an in-depth relationship involving critical feedback and mutual support. As such, it is difficult to characterize and study mentoring programs in a consistent manner (Griffin et al., 2003). Research on Teacher Mentoring Due in part to some of the issues discussed above, few controlled studies have been conducted on the effects of such statewide policies, or on the relationship between local and state mentoring policies. As a result, strong empirical data on the effects of mentoring is lacking (Grossman, Thompson, & Valencia, 2001; Smith, 2007). However, several recent studies do provide some insight into the status of research and practice in this area. In 2004, Ingersoll and Kralik reviewed 150 studies on teacher mentoring, only ten of which met their criteria for high quality research. From the results of these ten studies, the authors concluded that they could not support the claim that mentoring programs have a positive impact on retention or teacher quality, but they cautioned that these findings were “seriously limited by the fact that most of [the studies] were not able to control completely for other factors that also might have affected the outcomes noted” (p. 1). These factors include school characteristics, criteria for mentor selection, and program participation (i.e., some programs were voluntary), and content and duration of programs. In 2007, Smith examined pre-existing databases in order to determine the relationship between state-level induction policy and both type of mentorship and teacher turnover. Results indicated that mentoring is indeed more common in states in which it is mandated, and that such mandates may improve the quality of the mentorship. Although states requiring a mentor/novice match by subject, grade, or school were no more likely than other states to succeed in these efforts, these states do have mentoring programs that appear to be more effective at reducing turnover (Smith, 2007). At the local level, “while studies of educational change have largely ignored districts … a number of researchers believe that districts can play a pivotal role in facilitating the implementation of state policies” (Grossman et al., 2001, p. 3). In one of the only carefully controlled studies on teacher mentoring at the district level, Rockoff (2008) investigated the effects of mentoring policy on teacher turnover and teacher quality on New York City teachers. He found strong relationships between quality of mentoring and novices’ ratings of self-efficacy as teachers, but weaker relationships between quality of mentoring and teacher absences, teacher retention, and student achievement. Hours of mentoring did appear to be positively related to student achievement However, the strongest, most consistent finding was that teacher retention within a particular school was higher when a mentor had previous experience working at that same school. The author concluded that, although “time spent with a mentor does appear to improve teaching skills” (Rockoff, 2008, p. 1), the lack of quality research renders judgment about the impact of mentoring policy difficult. Finally, another recent study used random assignment to create a one-year experiment designed to investigate the differences between teachers involved a comprehensive induction program and teachers who were provided with a district’s typical Educational Policy Analysis Archives Vol. 18 No. 32 5 induction program. The comprehensive induction program involved carefully selected and trained full-time mentors; a curriculum of intensive and structured support for beginning teachers; a focus on instruction, with opportunities for novice teachers to observe experienced teachers; formative assessment tools that permit evaluation of practice on an ongoing basis and require observations and constructive feedback; and outreach to district and school-based administrators to educate them about program goals and to garner their systemic support for the program (Glazerman, Dolfin, Bleeker, Johnson, Isenberg, et al., 2008, p. xii). Findings indicated that although the treatment group did receive more mentoring and participate in more mentoring activities than did the control group, no differences were found after the first year of treatment between the two groups in terms of student achievement, teachers’ classroom practices, or teacher retention (Glazerman et al., 2008). Mentoring in Special Education Despite the proliferation of mentoring policies that apply to both general and special educators, even less is known about mentoring in special education (Billingsley et al., 2009; Gehrke & McCoy, 2006). A comprehensive review of the literature on new teacher induction in special education found only ten studies conducted between 1991 and 2001 that met the criteria of “systematically documenting and analyzing (programmatic) features and outcomes” (p. 21). These studies suggest that effective components of teacher mentoring programs include: (1) frequent face-to-face contact between mentor and mentee; (2) similar positions of mentor and mentee; (3) a non-evaluative role of the mentor; (4) an understanding of the mentoring process on the part of both parties; (5) a type of support that matches the novices’ needs (Griffin et al., 2002). In particular, novice teachers in special education appear to find “emotional, procedural, curricular, and instructional information” from a teacher with a similar assignment to be most beneficial (Gehrke & McCoy, 2007, p. 497). A more recent review of the same literature concluded that there are differences in needs between novice general and special educators. This review organizes the unique needs of special educators in three broad categories: “inclusion, collaboration, and interaction with adults; pedagogical concerns, and managing roles” (Billingsley et al., 2009, p. 16). Finally, a 2009 review of induction policy in special education reiterates several of the same themes as the general education literature. The authors of this review conclude a need for mentor training, release time, and a careful novice-mentor match (Hirsch et al., 2009). Although the literature in special education is replete with such suggestions for mentoring as a way to improve teacher quality and increase teacher retention in special education (Griffin et al., 2003; White & Mason, 2006), these findings are based primarily on survey data rather than larger and/or controlled studies connecting mentoring to teacher retention or student achievement (Griffin et al., 2003). Further complicating the issues of how to provide special educators with quality mentoring is the knowledge that programs intended to improve teacher quality (e.g. professional development) and provided to all teachers quite often is not appropriate for special educators and does not address their needs (Stodden, Galloway, & Stodden, 2003). Much literature discusses the unique professional development needs of special educators, including time management, assistance with paperwork, stress management, behavioral techniques, and collaboration skills (Griffin et al., 2003; White & Mason, 2006). Common problems such as obtaining appropriate experienced mentors (e.g. special educators with Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 6 similar assignments, working in the same building as the novice) could lead to discrepancies between policy and practice (Hirsch et al., 2009; Whitaker, 2000). Some even advocate dual mentoring to introduce novice special educators to both special and general education systems within the specific school context (Hirsch et al., 2009; Whitaker, 2000). Thus, mentoring may be yet another area in which policy and practice differ, and particularly for special educators. In fact, Billingsley et al. (2009) identified “the relationship between special and general education induction” as “a question that has been largely unaddressed” (p. 3) in the research literature. Again, the lack of research in this important area hinders the ability of school officials and policymakers alike to set appropriate policy and ensure best practices (Smith, 2007). Policy Framework Planning for successful policy implementation begins with careful mobilization of key stakeholders. A strong motive for adoption of any new policy is imperative. Berman & McLaughlin (1978) outline two positive reasons for implementing a new policy: first, in order to solve a legitimate, widely-recognized problem; and second, for capacity-building of leaders as a catalyst of further change. In the case of teacher mentoring, policies are viewed as a way to address longstanding issues with teacher turnover, teacher quality, and lack of preparation for some of the specific context of teaching (Smith, 2007). Assessing support among key stakeholders is another crucial aspect of mobilization, particularly as their resistance can easily derail a new policy (Fullan, 2001). Because top-down implementation efforts are “generally met with indifference or resistance at the school level” (Berman & McLaughlin, 1978, p. 15), the support of school-level leaders for mentoring policies should be addressed. Both states and districts have set mentoring policy (NCTQ, 2007); as such, both play a role in the planning process. Clearly, allocation of resources can make or break any policy (Fullan, 2001). In the case of mentoring policy, resources such as time, money, and appropriate personnel are needed (Hobson et al., 2007). Policy changes are notorious for increasing time demands on personnel (Fullan, 2001). For example, school and district leaders are needed to set up mentoring programs, pair mentors and novices, and oversee implementation. Mentors will spend time with novices and vice versa. Some states and districts have even specified how much time mentors and novices are to meet (Education Week, 2003). Allocation of fiscal resources is another issue with mentoring that is closely tied to the success or failure of policy implementation. Although research has shown that directing funding dollars to multiple individuals in the form of small stipends is not particularly efficient or effective, many states and districts have directed mentoring funds to mentors in this manner. In some states, teacher mentoring is unfunded (Education Week, 2003). Instead, experts recommend paying to provide continuing support and/or to hire individuals to oversee the project (Louis & Miles, 1990). Identification of appropriate personnel to assist in the implementation of mentoring policy has been another stumbling block, particularly in special education (Hirsch et al., 2009). Again, identifying an individual or individuals to implement the project can be an important predictor of success (Louis & Miles, 1990). As the policy moves from the planning stages to full implementation, researchers agree that assistance to implementers is crucial to ensure sustainability, and that the assistance continues throughout implementation (Fullan, 2001; Louis & Miles, 1990). Such assistance must match local needs; as such, it will vary by locale (Louis & Miles, 1990). Educational Policy Analysis Archives Vol. 18 No. 32 7 In sum, when developing mentoring policy, states must consider the support of districts and avoid “top down” programming. The allocation of resources should be considered carefully. In this case, “resources” includes time, money, and personnel. This framework provides a lens through which to consider current issues with mentoring policies. For example, general mentoring policies have been described as “helpful but not sufficient” (Carver & Feiman-Nemser, 2009, p. 323). A policy-to-practice gap in this area has resulted in differences in the mentoring practices in locales (Carver & Feiman-Nemser, 2009; Youngs, 2007). One specific model that takes into account both the influences of states and districts, as well as the influence of resources in the pursuit of successful policy implementation, is the framework developed by Fuhrman and Elmore (1990). They assert that “states that have significant effects on local education agencies rely more on multiple mechanisms of influence than on direct control” (p. 90). They describe several alternative methods of achieving policy implementation, including mobilization of opinion through a variety of means, and using state waivers to encourage creativity in local programming. Others have also cited Fuhrman and Elmore to explain how the effects of state policy can be “mapped” on local schools (Stevenson & Schiller, 1999) and how states can both follow and lead in the sphere of policy enactment (Malen, 2003). In particular, their model has been used to demonstrate the influence of districts “in a variety of state reform efforts” (Weinbaum, 2005, p. 99). Purpose of the Study Clearly, further research in teacher mentoring in both special and general education is crucial. Although debate continues regarding the possible impact of teacher mentoring, recent studies have shown that mentoring quality may be related to both increased student achievement and teacher retention (Rockoff, 2008; Smith, 2007). States have already invested heavily in setting and overseeing mentoring policy, yet little is known about policy enactment in this area. Further, the relationship between formal mentoring policies and mentoring practices in special education remains virtually unexplored, and there is no published research about effectiveness of common mentoring programs on novice special education teachers (Billingsley et al., 2009; Griffin et al., 2003). The purpose of this study is to compare official state and district mentoring policies and practices, in both special and general education. This knowledge is imperative in order to guide policymakers in revisiting and revising current mentoring policy in such a way as to maximize potential to improve teacher quality and increase retention (Smith, 2007). Therefore, this study examines two research questions: 1. Are there differences between formal teacher mentoring policies and reported mentoring practices in two large urban districts in one state? 2. Are there differences between mentoring practices reported by general and special education teachers? Method Participants One Midwestern state was selected purposively for this study because of the availability of personnel data from the state Department of Education website and because Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 8 of accessibility to the researcher, in that potential participants would be familiar with the researcher’s institution. The two largest city school districts in terms of population were selected purposively to correspond with the two districts included in the Teacher Rules, Roles, and Rights (TR3) database. The database provides comprehensive policy information on two selected school districts from each of the 50 states (NCTQ, 2007). “District A” has a graduation rate of 70.6%, and a daily enrollment of approximately 53,000. District A has 2970 teachers. Approximately ! of its students are non-white, and 98.1% qualify for free or reduced lunch. “District B” has a graduation rate of 61.9%, and a daily enrollment of approximately 50,000. Approximately 85% of its students are non-white, and 83.7% qualify for free or reduced lunch. District B has 5378 teachers. The two districts are considered to be “similar districts” in that they received the same rating by the state and are both large, urban districts. Because relatively similar experiences were expected among participants, approximately 210 respondents were required to achieve a 5% sampling error (Salant & Dillman, 1994). Stratified random sampling was used, in that equal numbers of special and general education teachers were selected in order to provide samples of sufficient size for comparison. This type of sampling was selected because special education teachers comprise only about 12% of the K-12 teaching workforce (Bureau of Labor Statistics, 2009). Therefore, disproportionate sampling is necessary if the goal is to obtain sufficient numbers of both general and special education teachers for statistical analysis (Salant & Dillman, 1994). Therefore, four hundred fifty teachers (225 special education and 225 general education) were selected at random from a list of all general and special education teachers teaching in the approximately 200 schools in the two selected districts. The list was obtained from a publicly-available dataset on the state department of education website. The database offered the ability to sort educator names by position and school, and included full addresses. After data collection was complete, responses had been received from 232 teachers, comprising a 51.6% response rate. One hundred twenty-nine teachers (55.6%) who responded were from District A; the remainder were from District B. Of the 232 individuals who returned the survey, 45 indicated having been both novice and mentor in that district. Sixty-eight were neither mentor nor novice. Twenty were mentors and not novices, and 82 were novices and not mentors. Seventeen did not respond to this question. Participants’ average number of years teaching was 16, with a standard deviation of 8.5. On average, they had spent 14 years teaching in their current district. This data compares well to state-level data indicating the average teaching experience of teachers in District A is 14 years, and District B is 15 years. Just under half (48.3%) were special education teachers, and the remainder was general education teachers. Procedure Instrumentation. The majority of questions included in survey instruments used in this study correspond to those asked by researchers compiling the TR3 database (NCTQ, 2007). The TR3 database includes nine questions under the topic of mentors. Participants were asked to provide brief responses to each question, in order to abide by the principles of simplicity and specificity, while maintaining wording developed by the National Council on Teacher Quality (NCTQ). This decision assists with compatibility to the original NCTQ database (Salant & Dillman, 1994). The nine questions were: 1. Is a mentor available to a new teacher? 2. How long is the mentorship program for a new teacher? Educational Policy Analysis Archives Vol. 18 No. 32 9 3. Who selects teachers to be mentors? 4. Is it expected that a mentor will have experience in subject area/grade related to the teacher's teaching assignment? 5. What is the minimum number of years of experience a teacher must have to be eligible to be a mentor? 6. Is a mentor paid? 7. Are mentors provided with training? 8. Does a mentor have reduced teaching responsibilities or release time? 9. Does a mentor observe the teacher teaching? Next, participants were asked: (1) whether they had served as mentors, novices, or neither in that district, in order to determine their familiarity with mentoring; and (2) their number of years of teaching experience, in order to determine representativeness of sample. Finally, participants were asked “how would you describe the quality of your mentorship experience?” in order to provide a basic evaluation of their perceptions of mentoring. They were provided five choices on a Likert-type scale: poor, fair, undecided, good, and excellent. Data collection. The 450 randomly selected teachers were sent a survey invitation via direct mail. A mail survey was selected as a way to minimize sampling error, as the addresses obtained were complete and up to date, and participants were thought to be “likely to respond accurately and completely in writing” (Salant & Dillman, 1994, p. 37). Two one- dollar bills were included in the mailing as an incentive. Following the first mailing, postcard reminders were sent in two weeks. A second complete mailing targeting all non-responders was sent four weeks after the initial mailing. Data analysis. Simple descriptive data (frequencies) was calculated to determine percentages of participants’ responses to yes/no questions. This data was compared to state and district policy reported in the TR3 database. Means were calculated to determine responses to ordinal and continuous data such as participants’ perceptions of their mentoring experiences and their average number of years of teaching experience to yes/no questions. Chi-square tests were used to determine differences in responses between general and special education teachers. Chi-square tests were also used to compare responses across districts, because although both districts were subject to the same state mentoring laws, district rules varied. For ordinal and continuous variables (length of mentorship, years of experience, perceived quality of mentorship), t-tests were used to compare responses between general and special education teachers, and to compare responses by district. The current mentoring laws in the state were implemented in 1996. Because number of years experience might affect participants’ responses on mentoring (i.e. participants’ experiences in mentoring might have taken place before 1996, despite the researcher’s efforts to gain current data through wording of questions), correlations were taken between years teaching experience and responses to the nine mentoring questions asked. Years experience did not correlate significantly with responses to any of the questions asked in the survey. Results In order to compare mentoring policies and practices, participants’ responses were compared to both state and district policy for each of the nine mentoring policies reported in the TR3 database. Two of these policies were required by the state; four were required by one or both districts, but not the state; and three lacked requirements at both levels (NCTQ, Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 10 2007). Responses of general and special education teachers were compared in order to determine whether differences existed between the two groups. Differences between the two districts were also noted. Finally, perceived quality of mentoring was analyzed. A summary of results is shown in Tables 1 – 3. State Policies As shown in Table 1, two of the nine mentoring policies were required by the state. First, the state requires that a mentor be available to new teachers. Overall, 75.7% of the respondents indicated that a mentor was made available to a new teacher in their district. Findings differed both by type of teacher (general education versus special education) and by district. General education teachers were significantly more likely (79.3%) to report availability of a mentor than special education teachers (64.4%), 2 (1) = 49.548, p < .001. More teachers in District A (85.6%) reported availability of a mentor than teachers in District B (65.2%), 2 (1) = 49.548, p < .001. Length of mentorship was also determined by the state, as “up to one year” (NCTQ, 2007). Length of mentoring program was reported as one year by 86.7% of respondents. No significant differences were found either by district or by type of teacher. Table 1 State Policies Question Policy Findings Difference by District Difference by Teacher Type Mentor availability State: yes District A: yes District B: yes 75.7% yes District A: 85.6% yes District B: 65.2% yes General education: 85.6% yes Special education: 64.4% yes Length of mentorship State: up to one year District A: n/a* District B: n/a 86.7% one year n.d. ** n.d. * not specified in the scope of the documents studied by NCTQ (NCTQ, 2007) ** no significant differences District Policies Four of the nine policies were requirements in one or both districts, but not by the state (see Table 2). With respect to selection of mentors, District B required selection by the principal, but no requirements were specified by either District A or the state. Overall, 61.6% of respondents indicated that school administrators selected mentors, and there was no significant difference between responses of special and general education teachers or between responses of participants in District A and District B. Second, both districts required that mentors be paid, although this was not required by the state. However, only 35.1% of participants responded that mentors were compensated for this service. A significant difference was found between responses of special and general education teachers, with 14.9% of special education teachers indicating Educational Policy Analysis Archives Vol. 18 No. 32 11 that mentors were paid, as compared to 40.8% of general education teachers, 2 (1) = 9.993, p = .002. No differences were found by district. Third, district B required “release time… if deemed necessary by the principal” (NCTQ, 2007). Overall, 26.6% of participants indicated that mentors received reduced teaching. Differences were found between responses of special and general education teachers. Only 14.3% of special education teachers reported that mentors received a reduced teaching load, as compared with 29.9% of their general education colleagues. Participants from District A were also more likely to indicate mentors receiving a reduced teaching load (43.5%) than those in District B (12.5%), 2 (1) = 24.429, p < .001. Finally, District A required observation of novice teachers, whereas the state and District B did not have a formal policy regarding observation of novice teachers. Overall, 62.8% of teachers involved in this study reported observation of novices. No differences were found between special and general education teachers. Results did differ by district, showing that teachers in District A did report an observation component (67.6%) more often than teachers in District B (60.3%), 2 (1) = 11.268, p = .001. Table 2 District Policies Question Policy Findings Difference by District Difference by Teacher Type Mentor selection State: n/a District A: n/a District B: principal 61.6% administrator n.d. n.d. Compensation for mentoring State: n/a District A: yes District B: yes 35.1% yes n.d. General education: 40.8% Special education: 14.9% Reduced teaching State: n/a District A: n/a District B: yes, if necessary 26.6% yes District A: 43.5% District B: 12.5% General education: 29.9% Special education: 14.3% Observation of novice State: n/a District A: yes District B: n/a 62.8% yes District A: 67.6% District B: 60.3% n.d. * not specified in the scope of the documents studied by NCTQ (NCTQ, 2007) ** no significant differences No Formal Policies As shown in Table 3, three types of policies were not stated expressly either in state or district documents. Just under half (48.6%) of participants reported that mentors and Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 12 novices were matched by grade or subject. Also, 41.9% indicated the presence of mentor training. The mean number of years experience required for teachers to become mentors was reported as 5.0 years. There were no differences by type of teacher. However, there were differences by district. Participants in District B reported an average of 6.32 years of experience required for mentors, whereas District A’s participants reported an average of 4.36 years. This difference was statistically significant, t(103) = -2.239, p = .03. Table 3 No Policy Specified Question Policy Findings Difference by District Difference by Teacher Type Experience in subject / grade State: n/a District A: n/a District B: n/a 48.6% yes n.d. n.d. Years experience State: n/a District A: n/a District B: n/a 5.0 years District A: 6.32 years District B: 4.36 years n.d. Mentor training State: n/a District A: n/a District B: n/a 41.9% yes n.d. n.d. * not specified in the scope of the documents studied by NCTQ (NCTQ, 2007) ** no significant differences Finally, perceived quality of mentorship was also measured (see Table 4). Overall, participants rated their mentorship experiences as between “undecided” and “good” (3.66/ 5.0). There were no significant differences in ratings by type of teacher. However, significant differences were found between teachers in District A and District B. Teachers in District A rated their mentorship experiences higher (3.85) than their counterparts in district B (3.38), t(192) = 2.626, p = .009. Table 4 Perceived Quality of Mentorship Overall Percentage District A District B Poor 8.9 3.6 15.5 Fair 11.6 11.8 11.9 Undecided 12.6 6.4 20.2 Good 40.5 52.7 23.8 Excellent 26.3 25.5 28.6 Total 100.0 110.0 100.0 Educational Policy Analysis Archives Vol. 18 No. 32 13 Discussion and Implications The results of this study provide some insight into the relationship between state and district mentoring policy and practice in general and special education. In general, it appears as though mentoring practices enacted locally did not always follow policy, either district- or state-mandated policy. State policies appeared to produce greater compliance, in that participants were more likely to report practices that aligned with state policy initiatives than with district initiatives. The results of this study also indicated some significant differences between the mentoring experiences of special and general education teachers. General education teachers reported more availability of mentors, the practice of compensating mentors, and offering reduced teaching for mentors. Knowledge about policy implementation, in conjunction with new information about effective components of mentoring, also provides insight into issues with current mentoring efforts. A new model of implementation of mentoring policy is proposed. Policy Compliance Figure 1 depicts a traditional view of the relationship between policy and practice. Under this model, policies originate at the state and district level and are translated into practice with teachers. State policies have more influence on practice than district policies. Figure 1. Traditional policy model. The top-down model depicts the way in which state and district policy reaches teachers. State policy produces the most compliance, but both state and district policy are diluted as they reach teachers. As Cohen, Moffitt, & Goldin (2007) describe, this simplistic model dates back to the 1950s, when “states contributed to local school funds… It was widely assumed that more money would buy more educational resources, which would create better education, which would enable more learning (p. 63). Even through the 1980s, reforms were intended to work this way: “In virtually every state, the reform movement resulted in new legislation or state board regulation… it appeared that the movement would constitute a marked increase of state power vis-à-vis local districts” (Fuhrman & Elmore, 1990, p, 82). However, districts used this opportunity to shape and add to policies in a way that suited their own needs, Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 14 increasing policymaking at the local level as well (Fuhrman & Elmore, 1990). In the case of mentoring policy, the traditional view would begin with state policy and filter the policy through districts, who could tinker with those policies and/or set their own. However, this model does not appear to hold up in the case of the data presented in this study. Even cases in which both the state and district had very basic rules, such as mandating mentorship of novice teachers, only about three-quarters of participants indicated that mentors were assigned to new teachers, and special education teachers were much less likely to report availability of mentors than their general education counterparts. Further, when one district had a policy but the other did not, this did not appear to predict responses to questions. For example, although District B stipulated reduced teaching for mentors was available when necessary, teachers in District A were more likely to indicate that the district offered reduced teaching for mentors. Increased levels of compliance were found with state- mandated policies than with either district-mandated policies or policies for which neither state nor district had a stated rule. For example, the state mandated availability of a mentor, compliance appeared to be about 76%. However, district policies such as compensation for mentoring and reduced teaching only showed 26% compliance. Some practices were remarkably consistent in the absence of both state and district policy (e.g. almost half stated that the mentor had experience in the subject and/or grade level as the novice; the majority used observation of the novice). Further, some of these policies and practices appear to be reaching general and special education teachers differentially. Differences In Practice Data also show several differences between special and general education teachers, and between the two districts studied. For example, special education teachers were less likely to report availability of a mentor than general education teachers. This finding is consistent with previous research showing that appropriate mentors can be difficult to identify in special education, in part due to small numbers (Billingsley et al., 2009). Because data do not show a difference between special and general education teachers regarding whether the mentor must have experience in the novice’s subject area and grade of the novice’s teaching assignment, it is possible that when a match is difficult to find, the special educator may not be assigned a mentor. Data also show gaps between special and general education teachers in terms of compensation for mentoring and reduced teaching for mentors. These factors are considered by many as a way to strengthen mentoring, because they can provide the necessary time for planning and observation (Billingsley et al., 2009; Griffin et al., 2003). This finding could have serious implications if indeed mentors in special education are spending less time with novices than their counterparts in general education and/or are not compensated (either with money or time) as are their general education peers. However, it is important to note that the findings of this study showed no differences as to whether the mentor observed the novice. Notable differences were also found between districts. Like the differences between special and general education teachers, in which mentoring practices appeared to favor general education teachers, practices appeared to favor District A over District B. For example, mentor availability appeared to be higher in District A, and reduced teaching and observation of the novice also appeared to be more common in the district. Although it is impossible to tie these differences to one or two district characteristics, it is important to note the inconsistent relationship between policy and practice. For example, only District A requires observation of the novice, and data did show observation of the novice to be higher Educational Policy Analysis Archives Vol. 18 No. 32 15 in District A than District B. However, reduced teaching appeared to work in the opposite way. District B required reduced teaching for the mentor “if necessary,” yet District A’s teachers were more likely to report reduced teaching for mentors than those in District B. Although these findings might follow from the higher availability of a mentor found in District A, it is important to note that no differences were found between districts in other areas, such as mentor training and compensation for mentoring. These between-district differences help illustrate the policy-to-practice gap at both the state and district level, in the inconsistency of application of even a very straightforward mandate such as the existence of a mentoring match. From Policy to Practice As shown above, the findings of this study appear to indicate the need for a more complex understanding of the relationship between state and district policy and practices in mentoring in both general and special education. The data in this study show that simply mandating certain mentoring policies may not be sufficient to ensure compliance (Fullan, 2001; Hirsch et al., 2009). For example, although both states and districts required mentoring, only about 76% of participants (and only 64% of special educators) reported availability of a mentor. For some time, we have known that the relationship between state and local policy is not a simple give-and-take relationship (Fullan, 2001). For example, Spillane (1998) characterizes the school district’s organization as “nonmonolithic,” explaining that its fragmented structure, particularly in large districts (such as the two examined in this study) results in varied policy implementation. This concept can be seen in the mismatch between many of the policies examined in this study and the practices reported by teachers. Others have attributed the differential effects of state policy to political mobilization (or the lack thereof), the use of incentives, and the district’s individual relationship with the state (Cuban, 2003; Cusick, 1992; Sarason, 1990). Arguing that pursuing more state mandates does not provide a realistic solution, particularly as “most states lack the capacity to assure compliance” with reform policies (Furhman & Elmore, 1990, p. 86). The power of the district to implement reform efforts should not be underestimated (Fuhrman & Elmore, 1990), but the vast bureaucracy and “segmented” structure can inhibit large districts from accomplishing policy goals (Spillane, 1998). Based on the results of this study, administrators appeared to be the primary individuals assigning mentors to novices. However, this individual ranged from building- level to district-level personnel to union representatives. Additionally, not every teacher appeared to benefit equally from this mandate, either by district or by teacher type. Perhaps one district official should be assigned to monitor compliance, in an effort to reduce effects of this fragmented structure (Louis & Miles, 1990). Regardless, state and district need to work together to ensure every teacher has a mentor, and the special education infrastructure should partner in these efforts (e.g. special education directors). States can encourage districts’ efforts through financial incentives, but accomplishing policy implementation depends upon local conversation and local efforts, regardless of the origin of the policy (Fullan, 2001; Hirsch et al., 2009). As mentioned previously, new research has attempted to tie mentoring policies to teacher retention and even to the “gold standard” of educational research; namely, student outcomes. However, current policies that are thought to improve mentoring effectiveness may not align well with research outcomes. For example, Rockoff (2008) found evidence that hours of mentoring had a positive impact on student achievement, yet only nine states had a policy mandating a minimum number of hours of mentoring as of 2003, and not all Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 16 states even specify a minimum amount of time for the mentorship program (Education Week, 2003). Other common state policies had no effect on novices’ teaching, including matching by subject area (13 states) and requiring mentors to have a minimum number of years of experience teaching (16 states) (NCTQ, 2007). Rockoff also found that number of years teaching in that particular school on the part of the mentor had a positive impact on the novice’s teaching, yet only one state has that requirement (NCTQ, 2007). Additionally, Smith (2007) found that funding induction and requiring matches by subject area may in fact be reducing mentoring quality, and that other common policies did not contribute to the reduction of teacher turnover. Based solely on the results of this study, one might conclude the need to set goals of tightening policy regarding subject/grade matches or a minimum number of years experienced for mentors. However, given recent research findings, increasing compliance with set policies, or creating new, more specific policies in these areas, might not have the desired outcomes of increasing mentoring effectiveness. A New Approach Clearly, teacher mentoring is important. Quality mentoring may be related to improved student achievement, and almost every state has invested in this strategy to enhance teaching quality and increase teacher retention. The results of this and other studies indicate that mentoring mandates are implemented inconsistently, possibly missing groups of teachers who arguably need it most. How, then, can we ensure that research-based mentoring practices are mandated consistently? As stated previously, Fuhrman and Elmore’s (1990) model to encourage local policy implementation provides several ways of achieving this goal through the use of various types of influence. Based on previous research findings, it appears that requiring the assigning of mentors to all novice teachers, and requiring more mentor-novice contact, is important to producing the desired effects (namely, improving teacher quality and reducing turnover). Perhaps these two items should be the focus of mentoring policies, rather than attempting to mandate the array of different areas covered in state and district policy around the country, mandates that appear to have wide variability in implementation. Focusing on these minimum requirements, with attention to ensuring compliance with policy in both general and special education, could allow districts the freedom they need to create programs with a minimum of state intervention (Fuhrman & Elmore, 1990). This model avoids the “top- down” approach to implementation and includes flexibility to address local needs (Louis & Miles, 1990). How can these guidelines for achieving reform be implemented? Figure 2 depicts a new model of mentoring policy and practice, using Fuhrman and Elmore’s guidelines. The state sets minimum policies, as explained above, and then uses indirect measures to influence districts, who are responsible for developing more detailed mentoring programs. The programs have direct influence over the lives of teachers. The “top-down” model presented in Figure 1 becomes more circular, in that districts “fill in the blanks” by assisting states in determining effective elements of mentoring programs, which can then be used in other districts. Educational Policy Analysis Archives Vol. 18 No. 32 17 Figure 2. Proposed mentoring policy model. The state influences mentoring policy indirectly through a variety of measures. The district develops the mentoring models, which reaches teachers. Data collection by the district identifies effective mentoring programs, which in turn influences state policy. The indirect measures taken by the state to increase policy implementation are crucial to the success of any educational reform. Fuhrman and Elmore outline several effective ways to “market” educational reform, including utilizing business influences, publicizing data, and organizing committees of educational experts to oversee implementation. This mobilization results in “highly visible statements of the rationale for educational reform” that are recognized and advocated by all stakeholders (p. 90). For example, a carefully chosen committee of experts can create a plan to market the need for high quality teacher mentoring throughout the state. A minimum state policy provides freedom to the committee as well as to districts and schools to develop and evaluate model programs. States can advertise what is known about effective mentoring programs by highlighting districts’ successes (including both low- and high-achieving schools and the work of both general and special education mentor-novice pairs). Successful mentor- novice pairs could be recruited to speak to stakeholders across the state about their experiences. Pre- and post- performance data on new teachers can be collected and tied to mentoring. Collecting, analyzing, and disseminating this data creates an opportunity for universities and businesses in the area. Additionally, states could provide waivers to existing mentoring requirements to districts who propose creative, data-driven mentoring programs. Thus, the state focuses on improving state-district relations through increased reliance on local efforts, rather than on tightening policy that may be more or less effective. Bringing in a variety of stakeholders capitalizes on the strengths of other disciplines, many of which use mentoring, data, and advertisement in highly effective ways. Policy reformers have always emphasized the strength of community mobilization, warning against attempting educational reform without consideration of factors external to the school system (Sarason, 1990). Further, working Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 18 closely with district-level special education as well as general education professionals can help ensure that implementation is more equitable across teacher type. Research Recommendations Finally, it is important to note the crucial role of research in improving the implementation and the effectiveness of mentoring policy. We are still in the nascent stages of our understanding of the impact of mentoring policy, particularly on student achievement and teacher turnover (Smith, 2007). The results of this study point to a particular need to measure compliance even with the most basic of mentoring mandates, and to determine how mentoring may be implemented differentially with special and general education teachers, and across different districts. More diverse samples are imperative, in order to document the full range of mentoring practices in different districts and schools. More research is needed to determine whether special and general education teachers have different mentoring needs, as tied to student outcomes and teacher retention. Understanding why special education teachers may receive less mentoring than their general education counterparts is also crucial. If it is because of a lack of appropriate mentors, it is perhaps even more important that alternative models of mentorship be created, implemented, and monitored for effectiveness. Because it is possible that mentors in special education are not receiving some of the benefits that their general education counterparts are receiving (e.g. reduced teaching, payment for services as a mentor), implementation should be examined separately for both groups of teachers. Clearly, tying specific mentoring practices to teacher retention and teacher effectiveness is the “gold standard.” Both quantitative and qualitative data are needed for this work. For example, larger databases of teacher experiences, recording data similar to that recorded in this study (e.g. did new teachers have mentors? How often did mentor and novice pairs meet?) can be linked to other teacher data. More in-depth, qualitative studies could involve interviewing or observing mentors and novices in both special and general education to determine what “good” formal and informal mentoring looks like. Together, they could provide a picture of mentoring in practice that could be tied more definitely to local and state policy. Limitations and Conclusion This study has several limitations that affect generalization of results. First, the study was conducted with a relatively small number of participants in one state. Participants were teachers in large, urban districts. Although the two districts were considered to be comparable, they did differ in several important ways, including number of teachers and graduation rate. They were selected by compatibility with another database. As such, they are not representative of other districts in the state, particularly smaller and more affluent districts. Second, the survey instrument itself is a limitation. Forced-choice responses (e.g. yes/no) and the lack of concrete definitions on the survey instrument (e.g. what is meant by mentoring, mentor training, or “available to a new teacher”) might have skewed responses. Further, participants were not asked to comment on their responses, so checking for understanding was not possible. Third, this study is not a controlled, randomized study, and it did not measure experiences or observe participants directly. The limited number of participants who report having direct experiences as a mentor may have affected accuracy of responses. Finally, the Educational Policy Analysis Archives Vol. 18 No. 32 19 sample is not truly random, as it was selected to include equal numbers of special and general education teachers. In conclusion, the results of this study showed great variability in mentoring practices, regardless of state or district policy. State policy appeared to show greater compliance than district policy alone. Special education teachers reported less availability of a mentor and less mentor benefits than their general education peers. There were also significant differences by district. All of these findings can be seen as a call to action to ensure that such policies are carried out, with particular attention to a group of teachers whose needs may not be met at the same rate as others. However, the relationship between state and district policy is not straightforward, and high levels of implementation may not be achieved with a traditional top-down approach. Adopting an alternate model to ensure implementation for all teachers may be a better course of action. A variety of stakeholders need to work together to set good policy, ensure that it is carried out, and evaluate its results in such a way as to create effective mentoring programs that reach all novice teachers. References Berman, P., & McLaughlin, M. W. 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State policy and the non-monolithic nature of the local school district: Organizational and professional considerations. American Educational Research Journal, 35(1), 33-63. Stevenson, D. L., & Schiller, K. S. (1999). State education policies and changing school practices: Evidence from the National Longitudinal Study of Schools, 1980-1993. American Journal of Education, 107, 261-288. Stodden, R. A., Galloway, L. M., & Stodden, N. J. (2003). Secondary school curricula issues: Impact on postsecondary students with disabilities. Exceptional Children, 70, 9-26. Weinbaum, E. H. (2005). Stuck in the middle with you: District responses to state accountability. In B. Gross & M. Goertz (Eds.)., Holding high hopes for policy research in education (pp. 95-121). Philadelphia: Consortium for Policy Research in Education. Whitaker, S. D. (2000). Mentoring Beginning Special Education Teachers and the Relationship to Attrition. Exceptional Children, 66, 546-566. White, M., & Mason, C. Y. (2006). Components of a successful mentoring program for beginning special education teachers: Perspectives from new teachers and mentors. Youngs, P. (2007). District induction policy and new teachers’ experiences: An examination of local policy implementation in Connecticut. Teachers College Record, 109, 797-837. Rethinking Mentoring: Comparing Policy and Practice in Special and General Education 22 About the Author Leah Wasburn-Moses Miami University Email: wasburlh@muohio.edu Leah Wasburn-Moses is Assistant Professor of Educational Psychology at Miami University. Her research interests are in policy and teacher education, particularly within special education. She wishes to acknowledge the National Council on Teacher Quality (NCTQ) for providing funding for this research study. education policy analysis archives Volume 18 Number 32 30th of December 2010 ISSN 1068-2341 Readers are free to copy, display, and distribute this article, as long as the work is attributed to the author(s) and Education Policy Analysis Archives, it is distributed for non-commercial purposes only, and no alteration or transformation is made in the work. More details of this Creative Commons license are available at http://creativecommons.org/licenses/by-nc-sa/3.0/. All other uses must be approved by the author(s) or EPAA. EPAA is published by the Mary Lou Fulton Institute and Graduate School of Education at Arizona State University Articles are indexed EBSCO Education Research Complete, Directory of Open Access Journals, ERIC, H.W. WILSON & Co, QUALIS – A 2 (CAPES, Brazil), SCOPUS, SOCOLAR-China. Please contribute commentaries at http://epaa.info/wordpress/ and send errata notes to Gustavo E. Fischman fischman@asu.edu Educational Policy Analysis Archives Vol. 18 No. 32 23 education policy analysis archives editorial board Editor Gustavo E. Fischman (Arizona State University) Associate Editors: David R. Garcia & Jeanne M. Powers (Arizona State University) Jessica Allen University of Colorado, Boulder Christopher Lubienski University of Illinois, Urbana-Champaign Gary Anderson New York University Sarah Lubienski University of Illinois, Urbana- Champaign Michael W. Apple University of Wisconsin, Madison Samuel R. Lucas University of California, Berkeley Angela Arzubiaga Arizona State University Maria Martinez-Coslo University of Texas, Arlington David C. 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Pereyra Universidad de Granada, España Jose Joaquin Brunner Universidad Diego Portales, Chile Monica Pini Universidad Nacional de San Martín, Argentina Damián Canales Sánchez Instituto Nacional para la Evaluación de la Educación, México Paula Razquin UNESCO, Francia María Caridad García Universidad Católica del Norte, Chile Ignacio Rivas Flores Universidad de Málaga, España Raimundo Cuesta Fernández IES Fray Luis de León, España Daniel Schugurensky Universidad de Toronto- Ontario Institute of Studies in Education, Canadá Marco Antonio Delgado Fuentes Universidad Iberoamericana, México Orlando Pulido Chaves Universidad Pedagógica Nacional, Colombia Inés Dussel FLACSO, Argentina José Gregorio Rodríguez Universidad Nacional de Colombia Rafael Feito Alonso Universidad Complutense de Madrid, España Miriam Rodríguez Vargas Universidad Autónoma de Tamaulipas, México Pedro Flores Crespo Universidad Iberoamericana, México Mario Rueda Beltrán Instituto de Investigaciones sobre la Universidad y la Educación, UNAM México Verónica García Martínez Universidad Juárez Autónoma de Tabasco, México José Luis San Fabián Maroto Universidad de Oviedo, España Francisco F. García Pérez Universidad de Sevilla, España Yengny Marisol Silva Laya Universidad Iberoamericana, México Edna Luna Serrano Universidad Autónoma de Baja California, México Aida Terrón Bañuelos Universidad de Oviedo, España Alma Maldonado Departamento de Investigaciones Educativas, Centro de Investigación y de Estudios Avanzados, México Jurjo Torres Santomé Universidad de la Coruña, España Alejandro Márquez Jiménez Instituto de Investigaciones sobre la Universidad y la Educación, UNAM México Antoni Verger Planells University of Amsterdam, Holanda José Felipe Martínez Fernández University of California Los Angeles, USA Mario Yapu Universidad Para la Investigación Estratégica, Bolivia Educational Policy Analysis Archives Vol. 18 No. 32 25 arquivos analíticos de políticas educativas conselho editorial Editor: Gustavo E. Fischman (Arizona State University) Editores Associados: Rosa Maria Bueno Fisher e Luis A. Gandin (Universidade Federal do Rio Grande do Sul) Dalila Andrade de Oliveira Universidade Federal de Minas Gerais, Brasil Jefferson Mainardes Universidade Estadual de Ponta Grossa, Brasil Paulo Carrano Universidade Federal Fluminense, Brasil Luciano Mendes de Faria Filho Universidade Federal de Minas Gerais, Brasil Alicia Maria Catalano de Bonamino Pontificia Universidade Católica-Rio, Brasil Lia Raquel Moreira Oliveira Universidade do Minho, Portugal Fabiana de Amorim Marcello Universidade Luterana do Brasil, Canoas, Brasil Belmira Oliveira Bueno Universidade de São Paulo, Brasil Alexandre Fernandez Vaz Universidade Federal de Santa Catarina, Brasil António Teodoro Universidade Lusófona, Portugal Gaudêncio Frigotto Universidade do Estado do Rio de Janeiro, Brasil Pia L. Wong California State University Sacramento, U.S.A Alfredo M Gomes Universidade Federal de Pernambuco, Brasil Sandra Regina Sales Universidade Federal Rural do Rio de Janeiro, Brasil Petronilha Beatriz Gonçalves e Silva Universidade Federal de São Carlos, Brasil Elba Siqueira Sá Barreto Fundação Carlos Chagas, Brasil Nadja Herman Pontificia Universidade Católica – Rio Grande do Sul, Brasil Manuela Terrasêca Universidade do Porto, Portugal José Machado Pais Instituto de Ciências Sociais da Universidade de Lisboa, Portugal Robert Verhine Universidade Federal da Bahia, Brasil Wenceslao Machado de Oliveira Jr. Universidade Estadual de Campinas, Brasil Antônio A. S. Zuin Universidade Federal de São Carlos, Brasil