your department chair (or advisor) called… · •female students are 1.5 times as likely to...

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…to say that you will be teaching a class next semester that you have never taught before. What do you want to know so you can plan and offer an effective course? (Alternative phrasing: If you HAD taught the course before, what useful knowledge would you already possess?) Your department chair (or advisor) called…

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Page 1: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

…to say that you will be teaching a class next semester that you have never taught before.

What do you want to know so you can plan and offer an effective course? (Alternative phrasing: If you HAD taught the course before, what useful knowledge would you already possess?)

Your department chair (or advisor) called…

Page 2: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Why did they think that? The use and development of mathematical

knowledge for teaching at the undergraduate level

Natasha SpeerDepartment of Mathematics & StatisticsCenter for Research in STEM Education

The University of Maine

Page 3: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

…to say that you will be teaching a class next semester that you have never taught before.

What do you want to know so you can plan and offer an effective course? (Alternative phrasing: If you HAD taught the course before, what useful knowledge would you already possess?)

Discuss this with the people seated near you. We will share out ideas in a few minutes.

Your department chair (or advisor) called…

Page 4: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

• Overview of research on knowledge used in teaching mathematics

• Connections to improving teaching and learning of undergraduate mathematics

• Example of research designed to inform these efforts

• Implications for supporting novice instructors and further research

… with “work of teaching” tasks scattered throughout

Today

Page 5: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Ball, Hoover Thames, & Phelps (2008)

Page 6: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Ball, Hoover Thames, & Phelps (2008)

Page 7: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Common Content Knowledge

“knowledge of a kind used in a wide variety of settings – in other words not unique to teaching”; these are not specialized understandings but are questions that typically would be answerable by others who know mathematics” (Ball, Hoover Thames, & Phelps, 2008, p. 399)

472− 295=177If f(x) = 3sin(x), y’ = 3cos(x)

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Knowledge used to do mathematics• Necessary, but not sufficient for teaching (Ball &

Bass, 2000; Hill, Rowan, & Ball, 2005; Hill, Sleep, Lewis, & Ball, D., 2007; Monk, 1994)

• More courses in content are not strongly correlated with higher student achievement (Begle, 1979; Monk, 1994)

Page 9: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Ball, Hoover Thames, & Phelps (2008)

Page 10: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Ball, Hoover Thames, & Phelps (2008)

Page 11: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

On a pre-calculus test, students need to expand the following expression:

(x + 3)2

• What are some answers students might produce?

• What might students be thinking as they produce the incorrect answers?

Teaching task #1

Page 12: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Typical ways students think (productively and unproductively), common student strategies, especially useful examples, organization of content in a course, relative difficulty of topics

(Shulman, 1986)

– influences practices (Carpenter et al., 1988, 1989)

– influences student learning (e.g., Fennema et al., 1996; Franke et al., 2001; 1997)

Pedagogical Content Knowledge (PCK)

Page 13: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)
Page 14: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

This question was on a calculus quiz:If y = (5 + x2)7, what is the derivative of y?

Several students gave this answer:y’ = 7(5 + x2)6 (2x) (2)

What might the students have been thinking?

Bonus problem: What’s the thinking here?

Teaching Task #2

472– 295223

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• Used to – do the “mathematical work” of teaching– follow and understand students’ mathematical thinking– evaluate the validity of student-generated strategies

• Shown to play a role in teachers’ practices and correlate with students’ learning

(Ball & Bass, 2000; Hill et al 2004, 2005; Ma, 1999)

Is important and distinct from “common”content knowledge

Specialized Content Knowledge (SCK)

Page 16: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

…and that class you will be teaching for the first time uses collaborative groupwork, inquiry-based instruction and other active learning approaches. • Are there types of knowledge that would be especially

important/valuable for this instructional approach?

• What are some types of knowledge that might be important in this situation that would be less crucial in an all-lecture format?

Discuss.

Your dept. chair (or advisor) called AGAIN…

Page 17: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Using “engaged student learning” approaches

• is challenging– requires facilitating discussion and progression

of ideas (Stein et al., 2006)– often means adopting new practices

• places different demands on instructors’ knowledge than traditional lecture (Speer & Wagner, 2009; Wagner, Speer & Rosa, 2007)

So, why should we bother?

Page 18: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

To have an adequate number of people for STEM jobs, we (universities, colleges) need to produce 1 million ADDITIONAL graduates with STEM degrees over the next decade.

(Holdren & Lander, 2012)

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Part of that reality

Whatpercentoffreshmenwhointend tomajorinSTEM(science,technology,engineering,mathematics)actually finishaSTEMmajor?

(1)>80% (2)60– 80%(3)40– 60% (4)<40%

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Part of that reality

Whatpercentoffreshmenwhointend tomajorinSTEM(science,technology,engineering,mathematics)actually finishaSTEMmajor?

(1)>80% (2)60– 80%(3)40– 60% (4)<40%

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“The first two years of college are the most critical to retention and recruitment of STEM majors.”

Holdren & Lander, 2012, p. 6

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“Thelecturehasbeenamainstayofhighereducationsincetheword‘lecture’wascreatedinthe14thcentury,andtodaymostintroductorySTEMcoursesaretaughtlargelythroughlectures.”

“Extensiveresearchonhowthehumanbrainlearnsindicatesthatdiversifyingteachingmethodsenhancescriticalthinkingskills,long-termretentionofinformation,andstudentretentioninSTEMmajors.”

Holdren &Lander,2012,p.8

Page 23: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Evidence from a meta-analysis*

• 200 studies of undergraduate STEM instruction

• Two categories:– passive lecture– anything else

• Passive lecture courses: 55% higher DFW rates

• Medical metaphor*Freeman,S.,Eddy,S.L.,McDonough,M.,Smith,M.K.,Okoroafor,N.,Jordt,H.,&Wenderoth,M.P.(2014).Activelearningincreasesstudentperformanceinscience,engineering,andmathematics.ProceedingsoftheNationalAcademyofSciences,111(23),8410–8415.

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“…theseactivelearningtechniquesbenefitallstudentsandcanclosetheachievementgapbetweenethnicgroupsandmenandwomen”(Holdren &Lander,2012,p.9)

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Minorities in STEMUSpop:30%

College-agepop:36%

Page 26: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

In mathematics• Inquiry-based learning (IBL) in over 100 course

sections at 4 universities• Despite variation in how IBL was implemented,

student outcomes are better relative to traditionally taught courses

• “The use of IBL eliminates a sizable gender gap that disfavors women students in lecture-based courses.”

Laursen, S. L., Hassi, M.-L., Kogan, M., & Weston, T. J. (2014). Benefits for Women and Men of Inquiry-Based Learning in College Mathematics: A Multi-Institution Study. Journal for Research in Mathematics Education, 45(4), 406–418.

Page 27: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

In calculus• While taking calculus, some students will decide

to switch out of a major that requires the calculus sequence

• Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Ellis, J., Fosdick, B. K., & Rasmussen, C. (2016). Women 1.5 Times More Likely to Leave STEM Pipeline after Calculus Compared to Men: Lack of Mathematical Confidence a Potential Culprit. PLOSONE, 11(7), 1-14.

Page 28: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

What makes it difficult?

“Asignificantbarriertobroadimplementationofevidence-basedteachingapproachesisthatmostfacultylackexperience usingthesemethodsandareunfamiliarwiththevastbodyofresearchindicatingtheirimpactonlearning”(Holdren &Lander,2012,p.iii).

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What makes it difficult?

Preparing the next generation of instructors (graduate students):• Not always possible to provide substantial

pre-service preparation• Professional development concurrent with

teaching sometimes limited• TA professional development is not

typically a primary focus for faculty

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Rest of this talk

• Sample of study examining college instructor MKT

• What knowledge of student thinking do experienced instructors possess? – And how does that compare to novices?

• Findings can inform design of professional development for novice instructors

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Context: CalculusTask-based interviewsSeven tasks borrowed from or modeled after those used in research on student thinking (e.g., Habre & Abboud, 2006; Kendal & Stacey, 2003; White & Mitchelmore, 1996; Zandieh, 2000).Instructors:• research mathematicians recognized for teaching

excellence• graduate students with fewer than two years of calculus

teaching experience

Research design

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PART 1: Solve task and describe solutionPART 2: Describe how students would solve the task,

including difficulties/mistakes they might make and correct/incorrect ways of thinking they might display

PART 3: Examine and discuss student work samples (that represent typical student difficulties, ways of thinking, etc.) Based on protocol from previous studies (Frank & Speer, 2011, 2012; Speer et al., 2006)

PART 4: Describe what you would do/say to student who produced the work during office hours

Approximately 20 minutes per task.

Four-PART INTERVIEW

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PART 1: Solve task and describe solutionPART 2: Describe how students would solve the task,

including difficulties/mistakes they might make and correct/incorrect ways of thinking they might display

PART 3: Examine and discuss student work samples (that represent typical student difficulties, ways of thinking, etc.) Based on protocol from previous studies (Frank & Speer, 2011, 2012; Speer et al., 2006)

PART 4: Describe what you would do/say to student who produced the work during office hours

Approximately 20 minutes per task.

Four-PART INTERVIEW

Page 34: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

The given graph represents speed vs. time for two cars. (Assume the cars start from the same position and are travelling in the same direction.)

Question: State the relationship between the position of car A and car B at t = 1 hour. Provide an explanation for your answer.

From Carlson (1998)

A task

Page 35: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Experience the interviewThe given graph represents speed vs. time for two cars. (Assume the cars start from the same position and are travelling in the same direction.)

Question: State the relationship between the position of car A and car B at t = 1 hour. Provide an explanation for your answer. • With a neighbor, discuss:

– Your thinking and answer to the question– How students might solve the problem– Typical student productive and unproductive ways of thinking

Page 36: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

1. Distance car A traveled > Distance car B traveled2. Distance car A traveled = Distance car B traveled3. Distance car A traveled < Distance car B traveled

Ways of thinking

Thegivengraphrepresentsspeedvs.timefortwocars.(Assumethecarsstartfromthesamepositionandaretravellinginthesamedirection.)

Question:StatetherelationshipbetweenthepositionofcarAandcarBatt=1hour.Provideanexplanationforyouranswer.

Page 37: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

1. Distance car A traveled > Distance car B traveled2. Distance car A traveled = Distance car B traveled3. Distance car A traveled < Distance car B traveled

Ways of thinking

Thegivengraphrepresentsspeedvs.timefortwocars.(Assumethecarsstartfromthesamepositionandaretravellinginthesamedirection.)

Question:StatetherelationshipbetweenthepositionofcarAandcarBatt=1hour.Provideanexplanationforyouranswer.

Page 38: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Common ways of thinking• Productive:

– Use relative speed– Use the relative areas under the curves

• Unproductive:– Interpret the graphs literally as the paths of the cars,

rather than interpreting the functional information displayed on the graph

• The cars will collide at one hour • “Two different paths to get to the same place”

– Interpret the speed graphs as position graphs– Compare function slopes at t = 1

Page 39: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Examining student work

Student A:

Student B:

Student F:

Page 40: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

• Findings from research on student thinking were used to characterize the extent to which participants were knowledgeable of student thinking

• Methods from Grounded Theory (Strauss & Corbin, 1990) were also used• to identify themes • to detect comparisons/contrasts

Research design: Analysis methods

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Brief overview of findings• All participants gave correct solutions to

the task (some took a little while…). • All participants described some

productive ways of thinking that students might use

• All participants gave some possible unproductive ways of thinking

Page 42: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Findings about the mathematicians• generated more possible ways of thinking• used their (more extensive) set of ways of thinking to

make sense of the written work• PLUS: they were able to figure out (new-to-them) ways of

thinking from examining student workThey learned during the interview!

• They did more (spontaneous) quantifying/calibrating of how common a particular difficulty might be– “…a lot of students probably would…”– “I would expect many to get it wrong” – “Some students might say…”

Page 43: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Findings about the graduate students• Most generated very few possible ways of thinking• Some answers were fairly general:

– “[they] don’t know how to read this graph I think…so we have this speed and we have time but how can I, how do you represent the distance based on this graph?” (A, graduate student)

• Some focused on small variations to one approach, mostly the way they thought about the problem: – “…So they might make the same mistake as I was by

looking at the slope because for some reasons I keep thinking of this as a position instead of speed…” (C, graduate student)

Page 44: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Closing thoughts• Faculty gain MKT from their experiences • MKT supports effective instruction• Need to leverage this to improve student learning

• How I (and others) use these findings– Design professional development for novice college

mathematics instructors• access to known student ways of thinking• opportunities to learn from examining student work

– Equip the next generation of faculty with knowledge needed to enact active, engaged student learning approaches

– Work toward improved learning, retention, access and opportunity for all students

Page 45: Your department chair (or advisor) called… · •Female students are 1.5 times as likely to decide that as their male classmates (with the same preparedness, career goals, etc.)

Thank you!

Questions and/or comments?

Mathematics Education Research Group

Acknowledgements

my email: [email protected]

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Study math &/or science content and teaching

Conduct original research with faculty

Obtain teaching experience

The Master of Science in Teaching (MST) Programat the University of Maine

www.umaine.edu/center

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Overview of the MST program• 2-year master’s program offered through the

Maine Center for Research in STEM Education (RiSE Center)

• Research & certification opportunities in life science, physical science, earth science, and mathematics

• Unique combination of coursework, thesis, and teaching experience

• Paid assistantships for full time students

• NSF Teaching Fellowship Program for selected MST graduates who choose to teach in high-need Maine districts ($10,000 per year)

Teacher certification

Advanced study for current teachers

Preparation for further graduate

study

www.umaine.edu/center

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ReferencesBall, D. L., & Bass, H. (2000). Interweaving content and pedagogy in teaching and learning to teach: Knowing and using mathematics. In J.

Boaler (Ed.), Multiple perspectives on the teaching and learning of mathematics. Westport, CT: Ablex.Ball, D. L., Hoover Thames, M., & Phelps, G. (2008). Content knowledge for teaching: What makes It special? Journal of Teacher Education,

59(5), 389–407.Begle, E. G. (1979). Critical variables in mathematics education: Findings from a survey of the empirical literature. Washington, DC:

Mathematical Association of American and National Council of Teachers of Mathematics.Carlson, M. (1998). A Cross-Sectional Investigation of the Development of the Function Concept. In E. Dubinsky, A. H. Schoenfeld, & J.

Kaput (Eds.), Research in Collegiate Mathematics Education (Vol. 1, pp. 114-162). Washington, DC: American Mathematical Society.Carlson, M., Oehrtman, M., & Engelke, N. (2010). The Precalculus Concept Assessment: A tool for assessing students’ reasoning abilities

and understandings. Cognition and Instruction28, 28(2), 113–145. doi:10.1080/07370001003676587Carpenter, T., Fennema, E., Peterson, P., & Carey, D. (1988). Teachers’ pedagogical content knowledge of students’ problem solving in

elementary arithmetic. Journal for Research in Mathematics Education, 19, 385–401. Carpenter, T., Fennema, E., Peterson, P., Chiang, C., & Loef, M. (1989). Using knowledge of children’s mathematics thinking in classroom

teaching: An experimental study. American Educational Research Journal, 26(4), 499–531. Ellis, J., Fosdick, B. K., & Rasmussen, C. (2016). Women 1.5 Times More Likely to Leave STEM Pipeline after Calculus Compared to Men:

Lack of Mathematical Confidence a Potential Culprit. PLOS ONE, 11(7), 1–14. http://doi.org/https://doi.org/10.1371/journal.pone.0157447

Fennema, E., Carpenter, T., Franke, M., Levi, L., Jacobs, V. R., & Empson, S. B. (1996). A longitudinal study of learning to use children’s thinking in mathematics Instruction. Journal for Research in Mathematics Education, 27(4), 403–434.

Frank, B.W., & Speer, N. (2012). Developing knowledge for teaching: Three cases of physics graduate students. In S. Rebello, P. Engelhardt, & A.D. Churukian (Eds.), American Institute of Physics Conference Proceedings, (2012 Physics Education Research Conference). Secaucus: Springer.

Franke, M., Carpenter, T., Levi, L., & Fennema, E. (2001). Capturing teachers’ generative change: A follow-up study of professional development in mathematics. American Educational Research Journal, 38, 653–689.

Franke, M., Fennema, E., & Carpenter, T. (1997). Teachers Creating Change: Examining Evolving Beliefs and Classroom Practice. In E. Fennama & B. Scott Nelson (Eds.), Mathematics Teachers in Transition (pp. 255–282). Book Section, Mahwah, New Jersey: Lawrence Erlbaum Associates.

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410–8415.

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ReferencesHabre, S., & Abboud, M. (2006). Students’ conceptual understanding of a function and its derivative in an experimental calculus course. The

Journal of Mathematical Behavior, 25(1), 57–72.Hill, H., Rowan, B., & Ball, D. L. (2005). Effects of teachers’ mathematical knowledge for teaching on student achievement. American

Educational Research Journal, 42(2), 371–406.Hill, H., Sleep, L., Lewis, J. M., & Ball, D. L. (2007). Assessing teachers’ mathematical knowledge: What knowledge matters and what

evidence counts. In K. F. Lester (Ed.), Second handbook of research on mathematics teaching and learning (pp. 111–155). Reston, VA: NCTM.

Kendal, M., & Stacey, K. (2003). Tracing learning of three representations with the Differentiation Competency Framework. Mathematics Education Research Journal, 15(1), 22-41.

Laursen, S. L., Hassi, M.-L., Kogan, M., & Weston, T. J. (2014). Benefits for Women and Men of Inquiry-Based Learning in College Mathematics: A Multi-Institution Study. Journal for Research in Mathematics Education, 45(4), 406–418. http://doi.org/10.5951/jresematheduc.45.4.0406

Monk, D. (1994). Subject Area Preparation of Secondary Mathematics and Science Teachers and Student Achievement. Economics of Education Review, 13(2), 125–145.

Sadler, P. M., Sonnert, G., Coyle, H. P., Cook-Smith, N., & Miller, J. L. (2013). The Influence of Teachers’ Knowledge on Student Learning in Middle School Physical Science Classrooms. American Educational Research Journal.

Shulman, L. (1986). Those who understand: Knowledge growth in teaching. Educational Researcher, 15(2), 4–14.White, P., & Mitchelmore, M. (1996). Conceptual Knowledge in Introductory Calculus. Journal for Research in Mathematics Education, 27(1),

79–95.Speer, N. & Frank, B. (2013). Building knowledge for teaching rates of change: Three cases of physics graduate students, Proceedings of

the 16th Annual Conference for Research on Undergraduate Mathematics Education, Denver, CO.Speer, N. & Wagner, J. (2009). Knowledge needed by a teacher to provide analytic scaffolding during undergraduate mathematics

classroom discussions, Journal for Research in Mathematics Education, 40(5), 530-565.Stein, M. K., Engle, R. A., Smith, M. S., & Hughes, E. K. (2008). Orchestrating productive mathematical discussions: Five practices for

helping teachers move beyond show and tell. Mathematical Thinking and Learning, 10(4), 313–340.Wagner, J., Speer, N., & Rossa, B. (2007). Beyond mathematical content knowledge: A mathematician’s knowledge needed for teaching an

inquiry-oriented differential equations course. Journal of Mathematical Behavior, 26, 247-266.Wilson, S., Floden, R., & Ferrini-Mundy, J. (2002). Teacher preparation research: An insider’s view from the outside. Journal of Teacher

Education, 53(3), 190–204.Zandieh, M. J. (2000). A theoretical framework for analyzing student understanding of the concept of derivative. In E. Dubinsky, A. H.

Schoenfeld, & J. Kaput (Eds.), CBMS Issues in Mathematics: Research in Collegiate Mathematics Education (Vol. IV(8), pp. 103–127).