Areas of Expertise
University of North Florida, Associate Professor, Dept. of Childhood Education, Literacy, and TESOL, College of Education and Human Services; August 2010present. Appointed to Graduate Faculty in November 2011. Awarded Tenure & Promotion to Associate Professor in March 2016.

Mathematics for Elementary Teachers (Graduate) [3 credits]

Mathematics Methods for Elementary School Teachers (Undergraduate) [4 credits]

Science Methods for Elementary School Teachers [3 credits]

Methods of Conceptual Teaching [3 credits]

Professor in Residence at Kings Trail Elementary School, an Urban Professional Development School

UNF Intern Supervision
University of Central Florida, Adjunct, Dept. of Educational Studies and Dept. of Teaching and Learning, College of Education; January 2009June 2010.

Principles of Instruction and Classroom Management [3 credits]

How Children Learn Mathematics [3 credits]
Tropical Elementary School, Brevard County, FL, taught 5th grade mathematics and science in an inclusion classroom to heterogeneously grouped students; July 2005July 2010.
Gardendale Elementary Magnet School, Brevard County, FL, taught 4th grade in all subject areas in the Magnet School of Microsociety; July 1999June 2005.
Interlachen Elementary School, Putnam County, FL, ran the 4th and 5th grade DropOut Prevention Program; remediated 32 low performing students using a C.E.I. (Creative Education Institute) computer lab; August 1998 – June 1999.
Interlachen Elementary School, Putnam County, FL, 4th grade teacher, taught 24 heterogeneously grouped students in all subject areas; June 1996August 1998.
Education
Ed.D., University of Central Florida, College of Education; Doctoral dissertation title: Levels of line graph question interpretation with intermediate elementary students of varying scientific and mathematical knowledge and ability: A think aloud study; 2008.
Ed.S., University of Central Florida, Lockheed Martin Academy of Mathematics and Science; 2007.
M.Ed., University of Florida, College of Education, PROTEACH Program; 1996.
B.A.E. with High Honors, University of Florida, College of Education, PROTEACH Program; 1995.
State of Florida, Department of Education Professional Educator’s Certificate, # 767761, Elementary Education (16) & ESOL (K12); Expires on June 30, 2018.
Biography
When I joined the UNF faculty in Fall 2010, I had already established mathematical problem solving as my research and scholarship line of inquiry. I am especially interested in how models affect the way students comprehend and solve mathematical problems. How people represent their thinking during problem solving using different models fascinates me. As a result, my research includes the study of three types of models—mental, semiotic, and physical—and how the choice of model affects understanding and learning. By investigating the use of these models with different types of problems, I am learning how the choice of representation both supports and hinders problem comprehension.
From analyses of think aloud data collected for my dissertation (Boote, 2014; Keller, 2008) to written interactions of line graphs (Boote & Boote, in press) to think aloud data currently being collected with MBA students, I have identified a number of factors that affect problem comprehension. Background knowledge, problem context, and assessment format impacts a person’s ability to interpret a graph, an example of a problem type that I have studied extensively. One thing, in particular, that makes graph interpretation so challenging is translating the semiotic model (the graph) (Roth & Bowen, 2001) into an accurate mental model (Meyer & Hegarty, 1996). Additionally, understanding problem context is critical to solving intentionally misleading problems (Boote & Boote, 2016). When learners habitually use mathematical procedures without first understanding the scenario of a problem, comprehension and selfcorrection suffers. My studies have also explored interactions between problem solvers and specific attributes of models they use (Boote & Boote, 2016). From studying these interactions across problem types and populations, these studies’ findings suggest the importance of model choice to support and connect conceptual and procedural comprehension.
Think aloud interview data from 6th graders interpreting science line graphs was the focus of my dissertation (Keller, 2008), yielding two empirical articles, one published (Boote, 2014) and one accepted with the Elementary School Journal (Boote & Boote, in press). One of the most engaging aspects of doing this project was the literature I synthesized during my review. Graph question levels (Bertin, 1967/1983) provided the perfect framework for organizing factors previously cited that inhibit graph interpretation. My dissertation has been downloaded over 350 times by researchers around the world (ResearchGate, n.d.).
Both of my articles from the dissertation focus on students’ abilities to solve graph interpretation problems involving science line graphs, an important topic emphasized in data modeling within Common Core State Standards Mathematics (CCSSM) (2010) and Next Generation Science Standards (NGSS) (2013). The first article (Boote, 2014a) was published online in 2012 with the Journal of Science Teacher Education (JSTE) [h5index: 25], the flagship journal of the Association for Science Teacher Education and published in print in 2014. In this article, I used Bertin’s (1967/1983) semiotic theory of graph interpretation and analyzed think aloud protocols using a data collection instrument I designed for the study. I developed the Graph Interpretation Scoring Rubric (Boote, 2014) from my synthesis of prior graph interpretation literature using Bertin’s graph question levels (1967/1983) as an organizing framework. My analysis revealed that participants interacted differently with line graphs depending on the level of graph question. The analysis also revealed two distinct patterns of graph interpretation behavior for Intermediate Level Questions. Both of these findings added to the literature on graph interpretation.
“Leaping from Discrete to Continuous Independent Variables: Sixth Graders' Science Line Graph Interpretations” is slated to be published March 2017 in The Elementary School Journal [h5index: 27]. In this article, my coauthor and I used three graph component processes (Carpenter & Shah, 1998; Shah & Hoeffner, 2002) as our theoretical framework. We found that participants’ difficulties with continuous data were the result of their “mismodeling” continuous independent variables using their background knowledge of discrete independent variables. Most participants used procedural approaches even for questions that elicited science background knowledge. We argued that mismodeling and an overreliance on procedures were the result of subtle gaps between the 35 and 68 grade bands in both the CCSSM (2010) and NGSS (2013).
Issues of mismodeling and ignoring problem context have also emerged from my research with older learners engaging with different problem types. Over a span of four years, I collected and analyzed data from problem solving journals (n=121), an assignment in my elementary mathematics methods course. Each semester I have been fascinated to see problem solving trends across different groups of learners. These rich data are the focus of a manuscript published with the Journal of Mathematics Teacher Education (h5index: 20) (Boote & Boote, 2016). In this paper, my coauthor and I used mixedmethods content analysis to understand the mathematical habits of preservice teachers (PSTs) across six semesters. We selected one of the most provocative problems to analyze from their journals, The Log Problem, a problem type we classified as “intentionally misleading.” Our analysis revealed that 66% of PSTs answered incorrectly, because they ignored the problem context and modeled the scenario using arithmetic or algebra. The overreliance on using mathematical procedures without connecting them to conceptual understanding is one of the largest problems in mathematics education (National Council of Teachers of Mathematics, 2014).
My developing expertise in graph interpretation has led to opportunities to collaborate with other researchers. In two different studies, I have contributed my expertise in problem solving and modeling to analyze the effects of item format and media on the validity of items assessing quantitative reasoning in Physics and Business Education. In both research projects, we are interested in participants’ efforts to move from semiotic models to mental models and how their cognition is affected by graph question type and assessment format.
“Format Effects of EmpiricallyDerived MultipleChoice Versus FreeResponse Instruments when Assessing Graphing Abilities,” published in the International Journal of Science and Mathematics Education (h5index: 21), presents data questioning the validity of multiplechoice items for assessing graph interpretation ability (Berg & Boote, 2015). I was ecstatic when Professor Craig Berg contacted me to ask if I may be interested in collaborating on a research project using data he had collected from over 700 middle and high school students. Without hesitation, I said yes. In our article, we compare students’ performance on freeresponse and multiplechoice science graphing tests and argue that multiplechoice type question items inadvertently “prime” (Kahneman, 2011) testtakers to mismodel kinematics graphs.
Dr. Craig Berg is Director of the Milwaukee Collaborative Science and Mathematics Teacher Education Program at the University of Wisconsin, Milwaukee. He has been studying graph interpretation for over 20 years, and two of his previous articles in this area have been cited over 100 times each. He extended the invitation to collaborate after reading my dissertation and JSTE article on the networking website, ResearchGate.
My expertise in problem solving and modeling also led to my collaboration with Dr. Steven Williamson. Professor Williamson’s expertise is Management. He teaches in UNF’s Coggin College of Business and is Director of UNF’s PAPER Institute. Using think aloud interviews, we are investigating possible differences in MBA students’ GMAT graph interpretation performance due to test format. Preliminary data suggest that MBA students’ ability to model correctly and solve these difficult GMATtype questions is impaired while answering test items using an electronic format compared to a paper format. Our study uses a convergent mixed methods design (Creswell & Plano Clark, 2007) with randomized item sequences and a think aloud protocol (Ericsson & Simon, 1993).
Two articles in NCTM’s Teaching Children Mathematics focus on the pedagogy of mathematical problem solving. This professional journal has a circulation of over 30,000 and is very influential in elementary mathematics across the US and around the world. The first (Keller, 2011) persuades educators to use what we know about effective game design when teaching problem solving. This article encourages the use of physical models and children’s literature to create a classroom environment that fosters a love of solving mathematical problems. The second (Boote, 2016) uses a groupable model (i.e., grouped craft sticks) to explain BaseTen concepts embedded within the oftenchallenging long division algorithm. This article exemplifies my interest in aligning mathematical models, concepts, and procedures with curriculum materials and instructional methods.
Over the last decade, I have focused on naturalistic and clinical investigations of students’ problem solving behaviors and the effects of model choice on problem comprehension. By doing so, I have uncovered some of the factors that prevent elementary and University students from correctly modeling problem scenarios. I am looking forward to continue my collaborations with Professors Berg and Williamson. These writing projects have great promise to contribute to the literature on graph interpretation and accompanying assessment formats. I am also excited to analyze the next set of journal problems from my large data set. The analysis of their solution methods to answering addition problems in a different Base will supplement the professional scholarship I have already contributed to mathematics education.
In addition, the next phase of my research will attempt to ameliorate factors identified in earlier studies by designing educational materials for elementary students and educative curriculum materials for PSTs (Davis & Krajcik, 2005). My data collection and analysis will include systematically studying the effects and effectiveness of these interventions.
References
Berg, C. A., & Boote, S. K. (2015). Format effects of empiricallyderived multiplechoice versus freeresponse instruments when assessing graphing abilities. International Journal of Science and Mathematics Education, Springer Online First. doi:10.1007/s1076301596786
Bertin, J. (1967/1983). Semiology of graphics: Diagrams, networks, maps (W. J. Berg, Trans.). Madison, WI: The University of Wisconsin Press, Ltd.
Boote, S. K. (2016). Choosing the right tool. Teaching Children Mathematics, 22(8), 476486.
Boote, S. K. (2014). Assessing and understanding line graph interpretations using a scoring rubric of organized cited factors. Journal of Science Teacher Education, 25(3), 333354.
Boote, S.K., & Boote, D.N. (in press). Leaping from discrete to continuous independent variables: Sixth graders' science line graph interpretations. The Elementary School Journal. [Scheduled for publication in March 2017]
Boote, S.K., & Boote, D.N. (2016). ABC problem in elementary mathematics education: Arithmetic before comprehension. Journal of Mathematics Teacher Education, p.124. Springer First Online: May 25, 2016; doi 10.1007/s1085701693502
Carpenter, P. A., & Shah, P. (1998). A model of the perceptual and conceptual processes in graph comprehension. Journal of Experimental Psychology Applied, 4(2), 75100.
Common Core State Standards Initiative. (2010). Common Core State Standards for Mathematics (CCSSM). Washington, DC: National Governors Association Center for Best Practices and the Council of Chief State School Officers.
Common Core State Standards Initiative (CCSSI). (2010). Common core state standards for mathematics. Washington, DC: National Governors Association Center for Best Practices and the Council of Chief State School Officers.
Creswell, J. W., & Plano Clark, V. L. (2007). Designing and conducting mixed methods research. New York: Wiley.
Davis, E. A., & Krajcik, J. S. (2005). Designing educative curriculum materials to promote teacher learning. Educational Researcher, 34(3), 314.
Kahneman, D. (2011). Thinking, fast and slow. New York: Farrah, Strauss, and Giroux.
Keller, S. K. (2008). Levels of line graph question interpretation with intermediate elementary students of varying scientific and mathematical knowledge and ability: A think aloud study. (Doctoral Dissertation), Retrieved from ProQuest LLC. (UMI Microform 3340991)
Keller, S. K. (2011). Make 'em want to be there! Teaching Children Mathematics, 18(1), 610.
Meyer, R. E., & Hegarty, M. (1996). The process of understanding mathematics problems. In R. J. Sternberg & T. BenZeev (Eds.), The nature of mathematical thinking. Mahwah, New Jersey: Lawrence Erlbaum Associates, Inc.
National Council of Teachers of Mathematics. (2000). Principles & standards for school mathematics. Reston, VA: National Council of Teachers of Mathematics.
National Council of Teachers of Mathematics. (2014). Principles to actions: Ensuring mathematical success for all. Reston, VA: National Council of Teachers of Mathematics.
NGSS Lead States. (2013). Next generation science standards: For states, by states. Washington, DC: The National Academies Press.
ResearchGate. (n.d.). Stacy K. BooteResearchGate. Retrieved from https://researchgate.net/profile/Stacy_Boote
Roth, W. M., & Bowen, G. M. (2001). Professionals read graphs: A semiotic analysis. Journal for Research in Mathematics Education, 32(2), 159194.
Shah, P., & Hoeffner, J. (2002). Review of graph comprehension research: Implications for instruction. Educational Psychology Review, 14(1), 4769.
Shulman, L. S. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 414.
Shulman, L. S. (1987). Knowledge and teaching: Foundations of the new reform. Harvard Educational Review, 57(1), 123.
Awards
Nominated for UNF’s Outstanding Undergraduate Teaching Award; 20142015; 20152016 (Finalist); 20162017.
Pearson Most Valuable Teacher (MVT) Award; Seven recipients were chosen throughout the United States from K12th grades. The award was presented at the 2010 National Science Teacher Association (NSTA) Conference in Philadelphia, PA; March 1820, 2010.
Space Coast Science Education Alliance (SCSEA) 2009 Exemplary Science Teacher Award; Eight teacher winners in Brevard County, FL, were selected from nominations submitted by students, parents, teachers, administrators, and community members. Selection was based upon teacher essays, letters of support, and other evidence of exemplary classroom practices; June 2009.
Alpha Delta Kappa, International Honorary Sorority for Women Educators; Treasurer from 20082010; accepted Spring 2007.
The Honor Society of Phi Kappa Phi; UCF Chapter 232; accepted Spring 2005.
Merit Fellowship by the Office of Graduate Studies, UCF; Spring 2004.
Affiliations
National Council of Teachers of Mathematics (NCTM); 2004present.
Florida Council of Teachers of Mathematics (FCTM); 2010present.
National Science Teachers Association (NSTA); 20102016.
Association of Mathematics Teacher Educators (AMTE); 20142015.
School Science and Mathematics Association (SSMA); 20122015.
National Association of Professional Development Schools (NAPDS); 20112013.
Florida Association of Mathematics Teacher Educators (FAMTE); 20102012.
Florida Association of Science Teachers (FAST); 20062009.
American Educational Research Association (AERA); 20042014.
Grants and Contracts Awarded
Boote, S.K. (October 2012). Improving MAE 6318: Mathematics Methods for Elementary School Teachers. UNF Academic Affairs Teaching Grant for 2013. Amount Requested: 7,500. (Not funded).
Keller, S. K., Ouyang, J., & Boote, D. N. (November 2011). Comparative Study of Elementary Mathematics Education in the US and China. UNF Foundation Board. Amount Requested: $25,000. (Not funded).
Keller, S. K. (September 2011). Modeling Outstanding Mathematics and Science Instruction in a Professional Development (PDS) and ESOL Center School. Dean’s Education Advisory Council
Faculty Initiatives Grant. Amount Requested: $3,000. (Not funded).
Keller, S. K. (November 2009). Max Axiom Scientist to the Rescue! Boeing Employees Community Fund of Florida. Amount Requested: $1029 (Funded for $600).
Keller, S. K. (November 2009). Great Gizmos! Brevard County Educational Technology Grant Program. Amount Funded: $799 (Funded).
Keller, S. K. (October 2009). Read Any Good Mathematics Lately? Brevard Schools Foundation Bright Ideas School Bucks Classroom Grant. Amount Funded: $496.96 (Funded).
Keller, S. K. (October 2008). Problem Solving from the Concrete to the Abstract. Boeing Corporation. Amount Funded: $900 (Funded).
Keller, S. K. (November 2007). Microscopy Mania. Brevard County Educational Technology Grant Program. Amount Funded: $1549.46 (Funded).
Keller, S. K. (October 2007). Fizzin’ for AlkaSeltzer. Florida Association of Science Teachers (FAST). Amount Funded: $500 (Funded).
Keller, S. K., McCluney, C., & Zeak, S. (August 2007). The Metric System Connection. Harris Corporation. Amount Funded: $1000 (Funded).
Keller, S. K., McCluney, C., & Zeak, S. (May 2006). The Metric System. Brevard Schools Foundation Classroom Grant. Amount Requested: $2500 (Not funded).
Keller, S. K. (October 2005). Brevard Schools Foundation Boeing Grant Award. Amount Funded: $750 (Funded).
**Published under S. K. Keller until March 2012.
Publications & Presentations
NATIONAL & INTERNATIONAL JOURNALS
Boote, S.K., & Boote, D.N. (in press). Leaping from discrete to continuous independent variables: Sixth graders' science line graph interpretations. The Elementary School Journal. [Scheduled for publication in March 2017; h5index=24; h5median=31; hindex=52; 10% acceptance rate; 2014 Impact Factor: 1.083]
Boote, S.K., & Boote, D.N. (2016). ABC problem in elementary mathematics education: Arithmetic before comprehension. Journal of Mathematics Teacher Education, p.124. Springer First Online: May 25, 2016. doi 10.1007/s1085701693502
[IRB#10092; 1120% acceptance rate; h5index=20; h5median=30; 2014 Impact Factor: 1.259]
Boote, S.K. (2016). Choosing the right tool. Teaching Children Mathematics, 22(8), 476486.
[h5index=8; h5median=10; 17% acceptance rate; circulation = 25,724]
Berg, C.A., & Boote, S.K. (2015). Format effects of empiricallyderived multiplechoice versus freeresponse instruments when assessing graphing abilities. International Journal of Science and Mathematics Education. SpringerLink Online First. doi 10.1007/s1076301596786
[h5index=21; h5median=27; 30% acceptance rate; 2014 Impact Factor: 0.575]
Boote, S.K. (2014). Assessing and understanding line graph interpretations using a scoring rubric of organized cited factors. Journal of Science Teacher Education, 25(3), 333354. Advance online publication: 2012.
doi 10.1007/s1097201293188
[h5index=22; h5median=26]
Keller, S.K. (2011). Make 'em want to be there! Teaching Children Mathematics, 18(1), 610.
[17% acceptance rate; h5index=8; h5median=10; circulation = 25,724]
STATE & REGIONAL JOURNALS
Boote, S.K. (2014). Who's tutoring who? Reflections from a fieldbased elementary mathematics methods course. Florida Association of Teacher Educators Journal, 1(14), 128. http://www.fate1.org/journals/2014/boote.pdf
Boote, S.K., McCormick, L., Parris, L., & Garner, W. (2013). Modeling partwhole relationships in the classroom: Frog and Toad are Friends, lost buttons, and circle graphs. Dimensions in Mathematics, 33(1), 2125.
Keller, S. K. (2011). Reasoning and proof in the classroom: What's your angle, Pythagoras? A math adventure. Dimensions in Mathematics, 30(2), 2125.
PUBLISHED DISSERTATION
Keller, S. K. (2008). Levels of line graph question interpretation with intermediate elementary
students of varying scientific and mathematical knowledge and ability: A think aloud study (Doctoral dissertation, University of Central Florida, 2008). Available online: http://purl.fcla.edu/fcla/etd/CFE0002356.
PAPERS AND PRESENTATIONS AT REFEREED NATIONAL CONFERENCES
Boote, S.K. (2015, April). Making our base10 number system concrete and comprehensible. A 75minute Gallery Workshop presented at the 2015 National Council of Teachers of Mathematics (NCTM) Annual Meeting in Boston, MA (April 1518, 2015).
Boote, S.K. (2013, April). Making our base10 system concrete and comprehensible. A
75minute Gallery Workshop presented at the 2013 National Council of Teachers of Mathematics (NCTM) Annual Meeting in Denver, CO (April 1720, 2013).
Boote, S.K., & Boote, D.N. (2012, Nov.). Roles of mathematics and science knowledge during linegraph interpretation. Research paper proposal accepted for the 2012 School Science and Mathematics Association (SSMA) Annual Convention in Birmingham, AL (Nov. 810, 2012). (accepted but not able to attend due to financial constraints)
Syverud, S., Reed, D., & Keller, S.K. (2012, March). A continuum of clinical preparation: The urban Professional Development School (PDS) model of the University of North Florida. Presentation at the National Association of Professional Development Schools (NAPDS) in Las Vegas, NV; March 812.
Keller, S.K. (2009, April). The roles of science and mathematics knowledge during line graph interpretation: A think aloud study. Paper presented at the Annual Meeting of the American Educational Research Association (AERA), San Diego, CA.
PAPERS AND PRESENTATIONS AT REFEREED REGIONAL CONFERENCES
Boote, S.K. (2015). Making our base10 number system concrete and comprehensible. A proposal accepted for a 75minute Gallery Workshop at the 2015 National Council of Teachers of Mathematics (NCTM) Regional Meeting in Atlantic City, NJ (Oct. 2123, 2015).
Cheek, K.A., & Boote, S.K. (2014, November). The patterns are in the rocks: A lowcost model to describe changes over time. HandsOn Workshop presented at the 2014 National Science Teachers Association (NSTA) Regional Conference in Orlando, FL; (Nov. 68, 2014).
Boote, S.K. (2013, October). Making our base10 system concrete and comprehensible. A 90minute Gallery Workshop presented at the 2013 National Council of Teachers of Mathematics (NCTM) Regional Meeting in Las Vegas, NV (Oct. 2325, 2013).
Boote, S.K. (2012, October). No more “monkey moves:" Bundling craft sticks to understand division. A 90Minute Gallery Workshop presented at the 2012 National Council of Teachers of Mathematics (NCTM) Regional Meeting in Dallas, TX; Oct. 1012, 2012.