- Year 2016
- NSF Noyce Award # 1439763
- First Name Joseph
- Last Name Travis
- Discipline N/A
Chiang Shih, Florida State University, firstname.lastname@example.org
Alec Kercheval, Florida State University, email@example.com
Christine Andrews-Larson, Florida State University, firstname.lastname@example.org
Karen Rose, Florida State University, email@example.com
Sherry Southerland, Florida State University, firstname.lastname@example.org
Kirby Whittington, Florida State University, email@example.com
Students of color and low-income students are less likely to be taught by experienced teachers and are less likely to be engaged in ambitious STEM instruction than their more affluent peers. This lack of opportunity limits their future STEM potential. It is well documented that low-income students are more likely than their more affluent peers to be taught by teachers not certified in their field (Chambers et al., 2010), and this is particularly true in STEM fields (Haycock, 2001). Although the limited number of STEM teachers is in part due to the lack of teacher production, many argue that the problem is not teacher production but teacher attrition. One third of all novice teachers leave the profession within 3 years, and the turnover by year 5 is 50% (Darling-Hammond & Sykes, 2003). These figures are higher in the STEM disciplines where the attrition rate is increased by 33% (Ingersoll & May, 2010). Ingersoll and Perda (2010) report that this attrition is greater in schools with limited resources (which influence new teacher support, salary, student discipline, administrative effectiveness, and instructional supplies); schools serving large percentages of nonmainstream learners often fall into this category. Further, the crisis of teacher turnover is almost twice as prominent in high-poverty schools as it is in low-poverty schools (Kersaint et al., 2007). The high rate of teacher turnover becomes particularly pernicious considering that most novice teachers are not as effective as their more experienced peers. That is, experience does matter, as teachers are the least effective during their first two years of teaching (National Commission on Teaching & America’s Future, 2003), and with novices attaining maximum effectiveness between years 5–10 (Darling-Hammond, 2010). Thus, these learners rarely have access to experienced, effective STEM teachers. The FSU-Teach Noyce Phase II Program is designed to address two of the most central factors influencing the “opportunity gap”—access to effective STEM teachers and engagement in challenging instruction..
The FSU-Teach Noyce Phase II project has three interconnected areas of action, the recruitment, preparation and support of effective STEM teachers in high needs settings. FSU-Teach’s Noyce Phase II Project has leveraged STEM students interest in working with experts in their field to attract these students to explore teaching in their field through STEM faculty’s outreach efforts. The 15, year-long internships to be offered each year will be conducted with STEM faculty who are engaged in offering outreach to the local community. The internships encompass roughly 100 hours spread over a year (with timing dependent on the faculty and students’ schedules). These internships are situated in a variety of STEM settings: FSU/FAMU College of Engineering (robotics, modeling fluid flow), the High Magnetic Field Laboratory (Electricity, Static & Currents, Taming Eddy Currents), FSU Mathematics Department (seeking patterns in phenomena, building mathematical models), the FSU Physics Department (conceptual problem solving in the studio format), FSU Chemistry Department (Developing physical models of natural phenomena), FSU’s Office of Science Teaching (Physical Science on the Move, Sea to See, Saturday-at-the Sea camp), Tallahassee Community College (TCC) (Aquatic horticulture, environmental science, designing investigations in chemistry, arguing from evidence). Each of these outreach opportunities is particularly focused on working with the local community and students in high needs settings.
Noyce Phase II preparation efforts support the development of Noyce scholars’ analytical lens for understanding the limitations of the rote, drill-based approach to instruction employed in the vast majority of high needs settings (Banilower et al., 2013). In the Noyce Scholar Preparation Program, students receiving a scholarship work with program mentors, Karen Rose, Wilbert Butler, and Jacqueline Goodman with whom they meet on a monthly basis to participate in seminars and field experiences. Scholars also volunteer in local high needs schools with additional mentors. In terms of induction support, Noyce graduates are visited by Noyce mentors with additional supports provided through the Noyce website.
Finally, an annual STEM Equity Conference has served as a recruitment, development, and support function. For this conference, Noyce interns and the STEM faculty with whom they work, current and past Noyce Scholars, local teachers and other STEM educators from the university and community college participate in a poster session once each spring semester to share the results of their efforts to engage in STEM teaching in high needs settings. The purpose of this conference is to foster an awareness of equitable STEM teaching practices and the challenges of implementing such approaches in the K-12 settings. This conference provides a venue for Noyce participants to describe and understand their efforts in STEM education through sharing “lessons learned”.
The research conducted under FSU-Teach Noyce Phase II project builds on past research conducted by project researchers as well as work begun under the Phase I. Prior to Phase I, research was conducted into the interactions of context and emotions during the first year of teaching using in-depth naturalistic observations by Southerland (Co-PI) and colleagues, and the results suggested that novices with a strong need for external validation could be stymied by urban students’ resistance to participating in ambitious STEM instruction, and these researchers describe that these negative interactions between a novice with such a disposition and students can result in the teacher’s abandonment of such practices (Saka et al., 2009, 2013). A later qualitative case study conducted by Rose (2012, 2013a,b) on a Noyce scholar during apprentice teaching revealed a similar pattern. Interactions with mentor faculty were somewhat effective in mitigating this dynamic, suggesting that an awareness of novices’ emotional dispositions can allow for more effective support by mentors (Castro et al., 2010). The Noyce Phase II project builds upon these efforts, bringing in a more systematic analysis of teaching context through Andrews-Larson’s work with mathematics teachers in schools, and Turner’s work in educational psychology to systematize the descriptions of students’ affective characteristics.
1. What constellation of affective dispositions and beliefs position preservice teachers – for success in delivering ambitious STEM instruction in high needs settings during apprentice teaching “During the first year of work”
2. How can STEM teacher preparation programs support preservice teachers whose affect and beliefs do not align with this profile?
3. What factors related to school setting and leadership in high needs settings best support ambitious STEM instruction by all novice Noyce graduates?
Methodology and Analytic Approach. The research approach to be employed in the Noyce Phase II project will build toward quantification of possible relationships. Working in tandem with scholars familiar with more systematic descriptions and measurement of teacher affective dispositions () and systematic characterizations of teaching context and ambitious teaching practices (Andrews-Larson, Co-PI), this research will move beyond the solely in-depth naturalistic methodology employed in earlier research in order to identify patterns across a broader number of participants (35 scholars) to eventually lead to later, predictive quantitative work. To allow for this broadening of focus, this research will employ qualitative comparative analysis (QCA) (Coburn et al., 2012) as the analytical approach. QCA employs set theory to interrogate complex systems, formalizing the logic used in qualitative work, to allow for the identification of ways in which constellations of conditions relate to outcomes of interest. This approach is suited to research that includes a relatively small number of cases and large number of possible relevant conditions. QCA operates from the assumption that target conditions may work differently depending on how particular conditions interact; thus allowing better understanding of how configurations of conditions may relate to the desired outcomes.
The outcome of interest is the delivery of ambitious STEM instruction at the end of the target year. The conditions we consider are affective dispositions that the literature and our past work suggest may be relevant, as well as contextual features of the school setting. The goal is to identify a model that can account for all the cases in the sample. For each analysis (apprentice teaching and first year), software fsOCA will be used to arrange the conditions and outcome in a truth table that will list all logically possible combinations of conditions and outcome. This will provide an assessment of the degree to which the given configuration-of-conditions lead to consistent outcomes (all negative or all positive), known as set-theoretic-consistency. If a configuration of conditions is not associated with consistent outcomes across cases, then the conjecture that this set of conditions is associated with the outcome is not supported. Generally a model – a set of configurations of conditions – is supported if it attains a consistency of .80 or higher (Ragin, 2000). We will also examine the set-theoretical-coverage, a measure of the strength of the model – the degree to which the configurations of conditions can account for all the positive cases. This method has the potential of finding relationships that are important in teacher education research, as seen in Coburn et al. (2012).
Data collection and instrumentation. The research will involve the use of surveys, interviews and classroom observations which began during the Fall 2015 semester. The conditions and outcomes to be included in the QCA analysis for the apprentice teaching year (along with measures and timing of data collection) include:
** Conditions (to be measured at outset of apprenticeship by interviews and surveys): (affect) resilience (Patterson et al., 2004, perfectionism (Slaney et al., 2013), teaching agency (Castro et al., 2010); growth versus fixed mindset , teaching responsibility (Arristia et al. under review), growth seeking versus validation seeking (Dykman, 1998), shame-proneness (Tangney, et al. (2000); (beliefs) beliefs about the discipline, teaching beliefs (TBI, Luft & Roehrig, 2007); (to be measured at end of apprenticeship) instructional vision (Munter, 2009), cooperating teacher support of ambitious instruction.
** Outcome (measured at the end of apprenticeship through observations of teaching): use of ambitious instruction (cognitively demanding tasks and nature of class discussion, as measured by the Instructional Quality Assessment, IQA, Boston & Wolf, 2006)
For the first year of teaching the conditions listed above will be used as well as:
** Conditions (to be measured at end of year) (context characteristics) teacher perceptions of principal support & expectation, textbook/teaching supplies, instructional vision (Munter, 2009), teacher community, novelty of ambitious instruction in the department, planning time, student demographic.
** Outcome (to be measured at end of year): use of ambitious instruction (IQA, Boston & Wolf, 2006).
Sequence of analysis. For research question 1, the QCA analysis for apprentice teachers will be performed in the summer of each year, combining data from across years, until a clear pattern is revealed. For research question 2, in research years after the constellation of dispositions supportive of standards based standards based instruction is identified with sufficient analytical strength (.80 or higher), scholars not displaying this constellation will receive targeted support, the nature of which will be documented by the mentors. The success of these supports will be examined in subsequent years? analyses. For research question 3, the QCA analysis for first year teachers will be performed in the summer of each year beginning with year 2.
: The faculty involved in FSU-Teach include a cadre of experienced teacher education researchers who are anxious to pursue the research described above and share their findings with the rest of the teacher education community through the UTeach research network, teacher education networks (e.g., AERA, NCTM, AMTE, NARST, ASTE, NSTA), the national Noyce community, and in the published literature. Indeed, Phase I findings have already been shared in several of these venues (NARST, AERA), with the hopes that the more focused efforts from Phase II will appear in journals such as the Journal of Research in Science Teaching, Journal for Research in Mathematics Education. In addition, FSU-Teach students have had some success in publishing their innovative teaching approaches in teaching journals (e.g., Suco & Samere, 2012), and our students routinely publish their efforts in CPALMS (a State of Florida online repository for lesson plans) for use by other teachers. In Phase II, these activities will continue as vehicles to share the approaches that emerge from the STEM Equity Conferences. FSU-Teach has been a consistent host for other STEM teacher educators in the UTeach network to explore particular courses in the UTeach curriculum (e.g., Knowing & Learning, Classroom Interactions), and we will provide a similar venue for this Phase II Noyce effort. Finally, as we identify useful practices for teacher support, we will share these practices and the design of the website with school administrators, superintendents, and state supervisors for math and science through statewide and nationwide meetings.
: The evaluation effort, to be conducted by Patricia Dixon, will provide information on the effectiveness of the Phase II Noyce Program in attracting, preparing, and retaining effective mathematics and science teachers in high needs setting. These data will be compared with that of the graduates of the Phase I Noyce Program, allowing for a more longitudinal assessment of graduates’ retention (up to 8 years past graduation). The following data will be collected as part of the program, and they will be made available to the outside evaluator on a semi-annual basis.
Recruitment: To evaluate the success of the program in attracting quality candidates, data will be gathered and analyzed that includes a record of recruiting and advertising strategies, the number of applicants, demographic information on the applicant pool, academic qualifications of the applicants, and how they learned about the program. These data will be aggregated for Noyce interns, Noyce Scholars and other students in the FSU-Teach program. This information will be used to evaluate the recruitment efforts to identify the most productive recruitment strategies for various STEM majors and those that help increase the diversity of the intern and scholar pool. In addition to these data that were collected in Phase I, Phase II will include interviews and focus groups with interns and STEM faculty conducted by the evaluator regarding recruiting approaches and experiences.
Preparation: FSU-Teach and the teacher education department at FSU have an extensive internal assessment system that prescribes the collection and analysis of data on each student’s progress in the program. Data include critical tasks from each FSU-Teach course and the instructor evaluation of these tasks, evaluations from all field experiences, disposition evaluations (describing each student’s behaviors and attitudes important to teaching), scores on Certification exams (including an exam for content knowledge), and overall GPA. This comprehensive system of collection and analysis will allow the program and the evaluator to track the progress of Noyce scholars.
Retention and Effectiveness: The associate director will maintain records of who received support, information about their progress, and verify compliance with teaching obligations for students from Phase I and Phase II. Each May, the associate director will send the District Verification form to all Noyce scholars and the evaluator will compare retention rates of Noyce and non-Noyce graduates. The evaluator will interview the Noyce scholar/graduates’ administrators to gain their views of the scholars’/graduates’ effectiveness. In addition, during the years of their service commitment, Noyce program graduates (from Phase I and II) will be interviewed as to their perceived success in the classroom and required to submit a survey addressing questions regarding their post-program teaching experiences, including:
school demographics; demographics of the classes they were assigned to teach;
courses taught and number of students enrolled; leadership roles; professional development experiences ; other degrees and certification; recognitions or awards; conferences attended, presentations made; and, achievement of students on national or state standardized tests (where possible).
Finally, the State of Florida Department of Education collects data from ‘value added measures’ from each first-year teacher working in the state, and all these data will be reviewed compared across the two groups of FSU-Teach graduates (Noyce and Non-Noyce).
The outcomes of the project to date include:
Teacher Recruitment—in the two years of the projects we have funded 16 STEM majors to intern with faculty in designing and delivering STEM outreach projects to local schools.
Teacher Production—in the two years of the project we have funded 14 students, 8 of which have graduated and 2 of which are already teaching in high needs settings.
Teacher Support—During the spring 2016 semester, two of our graduates began teaching in high needs settings. One of the Noyce mentors has visited the school sites, observed the teachers and offered supports regarding classroom management and pedagogy.
Research—Data collection on the Noyce scholars began during their student teaching experience and continues with their local education site.
In the upcoming years of the project, we anticipate placing a total of 75 promising STEM students in internships focused on outreach that engages students from high needs settings in the practices of the discipline, engaging 35 Noyce scholars in STEM, teacher education courses, and field work that emphasize STEM experiences that are rich in terms of the practices of the disciplines. When the 35 Noyce graduates are teaching, the induction program will support them in offering ambitious, standards-based instruction in ways that can be accepted in the communities in which they work.