Teorías de la variable: Oferta turística

Setting The School District

Sites 1 and 2 belong to a school district that serves over 100,000 students. Within this district, over 15 high schools serve unique learning communities that differ in socio- economic backgrounds, student body demographics, and transient rates. On average, the school district demographics of the student body are Caucasian (45%), African-American (31%), Hispanic (17%), Asian (5%), and Multi-Racial (3%). Nearly 45% of the students in the district qualify for Free/Reduced Lunch, and the transiency rate is 24%. Yet,

schools within the school district vary greatly from this district average. For example, one high school within the school district has a student body of around 1,700 students. The demographic make-up of the student body is African-American (39%), Hispanic (49%), Caucasian (7%), Asian (2%), and Multi-Racial (3%), in which over 80% of the students are eligible for discounted or free lunch. In contrast, the student bodies of Sites 1 and 2 are predominantly Caucasian (over 70% at each site), with a considerably smaller proportion of students who qualify for free and reduced lunch (Site 1 (5%) and Site 2 (14%).

Why are these differences within the school district important to the present study? Each of the participants spoke of their needs or their educational community with respect to other schools in the school district. Participants described their school in terms

of how their school was different from other schools in the district, and also how their professional learning needs were different than teachers at other schools within their district. As teachers discussed learning with other teachers within their school district, these differences became more clearly defined as they either assumed distinctions or experienced them through teaching in other schools themselves.

Site Distinctions

Although both of the sites for the study shared similarities in academic

performance, differences existed regarding administrative involvement, collaboration opportunities, and the mathematics departments themselves. These differences were illuminated by the participant interviews and provide a context for the interaction with other teachers and administrators mentioned by the participants during the interviews. Additionally, collaborative opportunities provided and evaluated by the schools’ administrations also served as a backdrop for the participants’ desires for planning time allocated for professional learning.

Administration and governance. The governance systems at Sites 1 and 2 were

quite different. Site 1 maintained a school governance system of several committees, such as Attendance, Student Climate, or Curriculum and Instruction, in which representatives participated from each department, as well as administrators, parents, and students. Changes within the school were approved after a council comprised of students, parents, community members, administrators, and teachers voted on the issue. However,

participants at Site 2 expressed that their school practiced a more traditional approach to administration and governance. Changes within the school were primarily decided by administrators after consulting with department chairs. These differences also influenced

the initiatives in professional learning that took place within the school, as well as the ways these initiatives were annually evaluated for effectiveness.

Time to work with peers. Both sites implemented different systems to allow

teachers to purposefully collaborate. Site 1 actively supported a teacher Peer Coaching program, through which teachers who were trained in peer coaching could collaborate with one or more teachers from within or outside of their department. These teachers went through coaching cycles with a peer in which they gave and received coaching. During the coaching process, teachers would set professional learning goals and develop data collection instruments to be used when their peers observed them teaching. Coaches recorded data relevant to the teachers’ developed learning goals. At the end of the

process, each teacher wrote a reflection of their goals, process, and thoughts to be

submitted to the administrators. The administrators then conferred with the peer coaching team to discuss their findings. Those involved in peer coaching had to apply through an application process to participate, and administrators chose which applicants would participate.

Although the participants at Site 2 discussed observing teachers in and out of their department, no formal peer coaching system was in place. However, unlike Site 1, Site 2 teachers noted that their administrators provided a common planning period for each department. Specifically, administrators deliberately scheduled teachers from the same department to have a common planning period. Some of the participants discussed how this planning period was used, misused, or ignored by their peers. One participant in particular noted that administrators would “stop by” once a month to check their progress.

Relationships within each department. It is also important to keep in mind the

relationships among the participants. Betty, Lucy, and Mary all taught at Site 1. All three taught 9th grade mathematics, and work together occasionally to plan the sequencing of the units, the assessments, or the activities for the course. Unlike Betty and Mary, Lucy also taught a brand new senior course with other members in the department. As part of a departmental policy, teachers within like subject areas were expected to be in “lock-step” with each other in terms of pacing, assignments, and assessments. Although they were allowed to vary with respect to how they teach mathematics, what they taught and when they taught it was expected to be uniform. As with Site 2, teachers at Site 1 were not expected to turn in lesson plans to their administrators.

Helen, Ed, Ellen, and Laura all taught at Site 2. Ed was the department chair, taught calculus, and collaborated with Laura, who also taught calculus. Ellen, who taught an Honors PreCalculus course, also worked closely with Ed for a couple reasons. First, Ellen vertically collaborated with Ed to ensure that her Honors PreCalculus students were aptly prepared for his calculus class the following year. Second, Ed and Ellen are married (I asked Ed and Ellen for permission to disclose this identifying factor within the study, and they agreed to allow me include this characteristic of their relationship). As I decided whether to include this unique, identifying factor about Ed and Ellen, I determined that their relationship was far too important to omit. As I analyzed their interviews and their stances on education, I realized that their perspectives, experiences, and learning styles were intertwined. Because they are married and have no children together, they had spent a great deal of time together at home, at work, and during professional learning activities. Although Helen did not share any common course with the other participants at her site,

she expressed that she sought out Ellen and Ed for professional guidance. Helen was originally encouraged by both Ed and Ellen to come teach at Site 2. Unlike Site 1’s mathematics department, teaching teams are not expected to give the exact same assessments or follow the same pacing as other like subject area teachers. Teachers at Site 2 collaborated and may still have chosen to work independently from one another regardless of the size of their subject-area team. This increased isolation was evident as teachers from Site 2 spoke of their collaborative relationships with their peers.

Participant Learning Profiles Overview

Ultimately, the purpose of this study was to investigate the professional learning processes of mathematics teachers in high performing schools from the perspectives of teachers themselves. As part of my criterion sample, I chose the participants because they espoused different perspectives of teaching and learning mathematics through the initial survey containing both multiple-choice and free-response items. I collected a variety of additional data through Photo Elicitation Interviews, blog responses, photographs, and Professional Learning Journal responses to anchor their unique perspectives. Each participant recounted how they learned independently, with others, or because of the requirement of others. The Photo Elicitation Interviews with each participant followed a similar pattern. First, the participants spoke about their photographs and their correlation to professional learning. Then each participant discussed their professional goals,

perceptions of expert mathematics teachers, and their learning processes. The participants revealed the sequence of their own learning through the resources they preferred, and discussed how they distinguished between professional learning and professional development. The participants described their favorite and least favorite learning

experiences and then detailed why the experiences were positive or negative. The later blog responses and professional learning journal reflections provided additional details to support these perspectives.

During the analysis process, I found commonalities and differences among the participants’ perspectives on learning. The emerging themes will be discussed after the participants’ Professional Learning Profiles. However, the participants’ unique

personalities, learning needs, and learning motivators emerged through their narratives of professional learning experiences. Thus, in addition to the pseudonym, I assigned a character name, such as Pioneer or Observer, to describe the learning lens through which the participant filtered his or her learning goals and experiences throughout the study. These learning lenses indicated the participant’s underlying perspective, and the multiple data sources used within the study supported this perspective within each case. In the following participant profiles, I present the participants’ background, learning goals, learning processes, and additional significant factors that motivated or deterred the

learners’ professional growth through their own words. Following the profiles, I detail the themes that emerged from the data analysis process and discuss how the participants’ views agreed or diverged along these topics.

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CHAPTER 5: BETTY’S PROFESSIONAL LEARNING PROFILE