and stored in the longitudinal database. (a) (b)Figure 1: A representative question used for formative assessment at the beginning of class in Calculus Ifor engineering students as seen by (a) the instructor, and (b) the student.Data analysisWe first used descriptive statistics to evaluate learner perceptions of usability, engagement, and learningusing responses to the CRiSP questionnaire. We then compared perceptions across genders and socio-economic status using statistical analyses of variance (ANOVAs). Although it is possible to test meandifferences with t-tests, ANOVAs are more robust to normality violations such as kurtosis and skew. ResultsDescriptive
. [5] D. E. Lee, G. Parker, M. E. Ward, R. A. Styron, and K. Shelley, “Katrina and the Schools of Mississippi: An Examination of Emergency and Disaster Preparedness,” J. Educ. Students Placed Risk, vol. 13, no. 2–3, pp. 318–334, 2008. [6] W. C. Chen, A. S. Huang, J. H. Chuang, C. C. Chiu, and H. S. Kuo, “Social and economic impact of school closure resulting from pandemic influenza A/H1N1,” J. Infect., vol. 62, no. 3, pp. 200–203, 2011. [7] D. J. D. Earn, D. He, M. B. Loeb, K. Fonseca, B. E. Lee, and J. Dushoff, “Effects of school closure on incidence of pandemic influenza in Alberta, Canada,” Ann. Intern. Med., vol. 156, no. 3, pp. 173–181, 2012
Paper ID #32891Using Science Concepts in a Mathematics Professional Development ProgramTo Improve Student’s Standardized Test ScoresMr. Allen J. Antoine Jr, Rice University Office of STEM Engagement As Associate Director of Mathematics and Computer Science of the Rice Office of STEM Engagement (R-STEM), Allen provides mathematics and computer science support. In this role, he specializes in providing lesson ideas, professional development, and teacher mentoring in the fields of mathematics and CS. Particular points of emphasis include increasing numeracy, inquiry-based learning and culturally responsive teaching strategies
, D. J., Dubinsky, E., Mathews, D., & Thomas K. (1997). A framework for research and curriculum development in undergraduate mathematics education. In J. Kaput, A. H. Schoenfeld, & E. Dubinsky (Eds.), Research in collegiate mathematics education II (p/. 1-32). Providence, RI: American Mathematical Society and Washington, DC: Mathematical Association of America. 2. Piaget, J. (1971). Psychology and epistemology (A. Rosin, Trans.). London: Routledge and Kegan Paul. (Original Work Published 1970) 3. Tokgöz, E., Tekalp S. B., Tekalp E. N., Tekalp H. A. (2020), Qualitative and Quantitative Analysis of University Students’ Ability to Relate Calculus Knowledge to Function Graphs, 127th Annual ASEE
Paper ID #34208Exploring the Relationship Between Math Anxiety, Working Memory, andExperiencesLuke A. Duncan, Clemson University Luke Duncan is a doctoral student in the Engineering and Science Education Department at Clemson University. His background is in mathematical sciences and mathematics education. Luke’s primary research interests include math anxiety and student success in higher education. He is currently involved in projects surrounding the topics of transfer student success, cognitive and symbol load, math anxiety, and qualitative research methods.Dr. Karen A. High, Clemson University Dr. Karen High holds
to solve related calculus problems [1,3,5,6,8-16]. The results of this work can help developing asuccessful teaching methodology of Taylor series after determining areas that can be used for improving learnersability to respond questions. The same research question is empirically evaluated in [19] to continue investigatingundergraduate STEM students’ ability to respond to the following set of power series questions:Q. In a few sentences legibly answer each of the following questions (a) through (d).a) Describe the difference, if any, that exists between ex and 1 + + ! !b) Describe the difference, if any, that exists between e1 + e1 + e1
Canvas platform. The course intervention modules arecurrently implemented in a section of Calculus I. Based on the mid-term process, more than halfof the students (56%) felt they were properly prepared for the course and (20%) felt that they couldearn an A or B. More students also felt confident that they could conduct an engineering designproject (36%). Many of the students (68%) indicated they liked traditional assignments likelectures, quizzes, and homework embedded in the course. Only a small number of students (8%)indicated the intervention was helpful towards learning calculus. This indicates that many studentsprefer the traditional way of learning calculus and feel confident that they are prepared to engagein these activities.Benefits of
MRME A detectable MRME for Woman+ students with Woman+ instructors occurred for sevenof the items on the survey, including one describing instructional practices, three for thehelpfulness of instructional practices, two for the perceived equity of instruction, and STEMmajor (Table 2). That is, the gender MRME was found to significantly contribute to the model ofresponse outcomes for these seven items. B SE Wald z OR [95%CI] Instructional practices PIPS_ShareIdeas 0.15 0.07 2.16* 1.16 [1.01, 1.33] Helpfulness of instructional practices Helpful_Feedback 0.19 0.09
performance in Calculus I varied (Table 5).Mentees performed below the threshold required to enroll in Calculus I; however, all menteeshad previously passed Pre-Calculus with a “C” or higher, which required that they progress toCalculus I. Overall, the section GPA was 1.60 and only three of the six students earned therequired “C” or higher to progress to Calculus II.Table 5. Mentee math preparedness and Calculus I performance. MPE Score (%) Calculus I Grade Brad N/A B Jack 38.3 D Kyle 52.0
become the engineers that expand theboundary of human knowledge. They look beyond the equations.Bibliography[1] P. Wankat and F. Oreovicz, Teaching Engineering, New York: McGraw-Hill, 1993.[2] R. E. Park, "A Memorandum on Rote Learning," American Journal of Sociology, vol. 42, no. 1, pp. 23-26, 1937.[3] B. N. Geisinger and D. R. Raman, "Why They Leave: Understanding Student Attrition from Engineering Majors," International Journal of Engineering Education, vol. 29, no. 4, pp. 914-925, 2013.[4] W. Zimmerman and S. Cunningham, "Editor's Introduction: What is Mathematical Visualization," Visualization in Teaching and Learning Mathematics, MAA, pp. 1-7, 1991.[5] F. Beer, E. R. J. Johnston, D. Mazurek, P. J. Cornwell and B. P. Self
Paper ID #34390Responding to Microaggressions in the Classroom: Perspectives FromIntroductory Mathematics InstructorsRebecca Machen, University of Colorado Boulder Rebecca Machen is currently a Ph.D. student in Curriculum and Instruction with a focus in STEM at the University of Colorado at Boulder. She is also a full-time staff member in the Student Academic Success Center, a comprehensive academic and social program that serves traditionally underrepresented students in higher education. Her research interests include multicultural communities of practice, the use of predictive analytics for admission and placement into
). Dr. Akcay Ozkan’s research interests include Online Teaching of Mathematics. She has completed several workshops on online teaching since 2016. She mentors fac- ulty members as they develop their online or partially online courses and assesses their courses with the Quality Matters Rubric. She has served in the eLearning Committee of the college in chair and secretary positions. She is a member of the Math Department’s Best Practices in Teaching and Learning Committee since 2017, and served in chair and secretary positions.Dr. Dona Boccio, City University of New York, Queensborough Community College Dr. Dona Boccio has a Ph.D. in Mathematics from the City University of New York Graduate Center, and an M.S. in