Conference Session

Mathematics Division Technical Session 4

Collection

2018 ASEE Annual Conference & Exposition

Authors

Gianluca Guadagni, University of Virginia; Hui Ma, University of Virginia; Lindsay Wheeler, University of Virginia

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Diversity

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Mathematics

participant in the course.Below we describe the course and modifications we have made through our second iteration.Pilot ULA course The class provides tools and support for UTAs to reflect on the several aspectsof their activity, from the most effective teaching practices, such as student-centered and inquirybased, to relevant educational methods, grading techniques, and including tips to improveinterpersonal skills. Topics covered include: Constructivism, Motivation, Problem solving,Engaging with Groups, Grading and Feedback, and Metacognition (see Appendix A for fullcourse syllabus)These topics are organized around three main modules during the semester. The first one is basedon understanding the learning process as an elaborated process where

Conference Session

Mathematics Division Technical Session 3

Collection

2015 ASEE Annual Conference & Exposition

Authors

Eliud Quintero, Tecnologico de Monterrey (ITESM); Patricia Salinas, Tecnologico de Monterrey (ITESM)

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Diversity

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Mathematics

described by text or bya graphic. Application of the instrument lead us to reflect that, once the appropriation is achievedthrough the motion context, it could be easier for students to apply it without connection with areal context. It also reveals the difficulties for interpreting graphical information based on thederivative function. These findings are part of the overall results of a doctoral dissertationconcerning with the use of digital technologies for the learning of Calculus.Keywords: Calculus learning, digital technologies, linear motion, real context, mediation.BackgroundDigital technologies are important tools in our daily activities, and it looks easy to use them inclassroom to support learning. According to Hillman1, a lot of research

Conference Session

Mathematics Division Technical Session 2

Collection

2017 ASEE Annual Conference & Exposition

Authors

Angeles Dominguez, Tecnologico de Monterrey, Monterrey, Mexico, and Universidad Andres Bello, Santiago, Chile; Genaro Zavala, Tecnologico de Monterrey, Monterrey, Mexico, and Universidad Andres Bello, Santiago, Chile; Maria Elena Truyol, Universidad Andrés Bello, Santiago, Chile

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Mathematics

first day of class (text in black) and follow-up process during the entire semester (text in green). Adapted from [11].The PD process (Figure 2) is called a cycle because it consists of a few elements that arerepeated11. The description of each element is taken from Ho et al (2001, p.147)12:  Self-reflections: Instructors “undergo self-reflection and clarify personal conceptions.” In this study, all three reflections occurred prior to the first day of class.  Exposures: Workshop facilitators “provide a direction and a model for improvement.” Exposure 1 and Exposure 2 occurred prior to the first day of class, whereas Exposure 3 occurred during the semester.  Confrontations: Instructors “are brought to realize

Conference Session

Mathematics Division Technical Session 1

Collection

2015 ASEE Annual Conference & Exposition

Authors

Janet Callahan, Boise State University; Judith A. Garzolini, Boise State University

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Diversity

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Mathematics

levelwhich significantly exceeded the fall, 2013 female STEM enrollment figure (26.5%). In addition,13.4% of awards went to underrepresented minority students. These also significantly exceededthe fall, 2013 URM STEM enrollment figures which reflect a student body consisting of 9.2%URM. When awards were evaluated in terms of student enrollment category we found that 40%of awards went to first-time, full-time students, 28% went to transfer students, 22% to returningstudents and 10% to second degree seeking students.When the retention of FTFT students who received awards was examined, we found that 71.4%of awardees were retained in STEM one year later, and 81.6% were retained here in any major.This favorably compares with STEM FTFT retention figures

Conference Session

Mathematics Division Technical Session 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Rebecca Machen, University of Colorado Boulder; Wysheka Austin, Clemson University; Matthew K. Voigt, Clemson University

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Diversity

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Mathematics

malintent, thatassociate people of color with negative concepts, even though most people self-report havingminimal to no bias (Greenwald et al., 1998). These unintentional beliefs, often referred to asracial microaggressions, communicate hostility toward people of color. Pierce (1974)conceptualized microaggressions as subtle, cumulative mini-assaults. Sue and colleagues (2007)define microaggressions as "brief and commonplace daily verbal, behavioral, or environmentalindignities, whether intentional or unintentional, that communicate hostile, derogatory, ornegative racial slights and insults toward persons of color" (p. 271). The current literatureexpands the definition of microaggressions to include "acts that reflect superiority, hostility

Conference Session

Mathematics Division Technical Session 4

Collection

2016 ASEE Annual Conference & Exposition

Authors

Virgil U. Pierce, University of Texas, Rio Grande Valley; Javier Angel Kypuros, University of Texas, Rio Grande Valley; Shirley J. Mills, University of Texas, Rio Grande Valley

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Diversity

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Mathematics

at improving entering students’ college readinessand mathematics placement. The small scale intervention, A Bridge to Calculus, is intended toimprove students’ placement from College Algebra into Calculus 1. The target population forthis effort are students with high school experience in a Calculus course but whose performanceon placement exams does not reflect this experience. At our institution this is a significantnumber of students and the goal of the project is to develop methods to address and acceleratestudents in this category. The course design, to take advantage of the students’ prior experience,emphasizes practice and mastery using a modified emporium course design and the ALEKSsoftware1. This intervention runs as a summer course

Conference Session

Mathematics Division Technical Session 1

Collection

2017 ASEE Annual Conference & Exposition

Authors

Jeffrey Lloyd Hieb, University of Louisville; William B. Corley, University of Louisville; Jaqi C. McNeil, University of Louisville

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Diversity

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Mathematics

negatively skewed.The CA scores were negatively skewed because they are the representation of the class activitiesthe students did in class. The authors corrected these violations by reflecting and square roottransforming the CA scores. The data was tested for normality after reflecting and transformingthe data, and the normality was met to run a regression analysis with the transformed data.CALC-IIICA scores in CALC-III violated the regression assumptions of normality and homoscedasticity.The CA scores were negatively skewed. To correct these violations, the CA scores were reflectedand square root transformed. Normality was met after transforming the data.CALC-II-2TFor this model, the original data for UL scores violated the regression assumption

Conference Session

Mathematics Division Technical Session 1

Collection

2015 ASEE Annual Conference & Exposition

Authors

Gunter Bischof, University of Applied Sciences Joanneum, Graz; Andreas Zwölfer, University of Applied Sciences Joanneum, Graz; Domagoj Rubeša, University of Applied Sciences Joanneum, Graz

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Mathematics

Schuster1). Precollege characteristics - like high school grade pointaverages - as well as university entrance exams have, in general, turned out to be usefulpredictors of student retention.A prior investigation of the drop-out probability at the engineering department of ouruniversity (Andreeva-Moschen2) clearly showed that the university entry scores can be usedto identify groups of students at higher risk of failure. It also turned out that the probabilitydistribution for student drop-out depends on the type of high school the students graduatedfrom, namely secondary colleges of engineering or traditional high schools. Interestingly, theuniversity entry score distribution does not reflect any differences in this respect, which might

Conference Session

Mathematics Division Technical Session 1

Collection

2018 ASEE Annual Conference & Exposition

Authors

Nancy Romance, Florida Atlantic University; Ali Zilouchian, Florida Atlantic University; Michael Vitale, East Carolina University; Lisa Greenberg, Florida Atlantic University

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Diversity

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Mathematics

Each CourseFaculty were divided into three math focus groups (leaving College Algebra for the end) wherethey specifically addressed main learning outcomes for the course, the core ideas upon whicheach course is grounded, and the supporting concepts that make up the core idea(s). Thisapproach builds upon a theoretical framework resulting from the work of numerous groups (i.e.,Mathematical Association of America - [MAA]) and individuals, such as Bransford et al., (2000)who, in his National Research Council commissioned book, How People Learn, providedrecommendations based on extensive work addressing learning and teaching in mathematics.Guiding their discussions were a series of questions such as (a) does the course outline reflect thedesired

Conference Session

Mathematics Division Technical Session 4

Collection

2018 ASEE Annual Conference & Exposition

Authors

Eliza Gallagher, Clemson University; Christy Brown; D. Andrew Brown, Clemson University; Kristin Kelly Frady, Clemson University; Patrick Bass, The Citadel; Michael A. Matthews P.E., University of South Carolina; Thomas T Peters, South Carolina's Coalition for Mathematics & Science; Robert J. Rabb P.E., The Citadel; Ikhalfani Solan; Ronald W. Welch P.E., The Citadel; Anand K. Gramopadhye, Clemson University

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Mathematics

author(s) and do not necessarily reflect the views of the National Science Foundation.We also wish to acknowledge the assistance of the Institutional Research Officers at each campusin gathering the data used in this analysis.References [1] X. Chen and M. Soldner, STEM Attrition: College Students’ Paths Into and Out of STEM Fields (Statistical Analysis Report), ser. National Center for Educational Statistics (NCSE) Statistical Analysis Reports. U.S. Department of Education, 2013. [2] J. Levin and J. H. Wyckof, “Predictors of persistence and success in an engineering program,” NACADA Journal, vol. 15, no. 1, pp. 15–21, 1995. [3] J. Middleton, S. Krause, S. Maass, K. Beeley, J. Collofello, and R. Culbertson, “Early course and grade

Conference Session

Mathematics Division Technical Session 3

Collection

2016 ASEE Annual Conference & Exposition

Authors

Doug Bullock, Boise State University; Kathrine E. Johnson; Janet Callahan, Boise State University

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Diversity

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Mathematics

(3) face-to-face but taught in parallel with the online section. 600 500 400 300 Other 200 Reform 100 0Figure 2: Calculus I enrollment by semester.Total students “captured” by the reform project, as a percent of enrollment is shown in Figure 3.It appears to be stabilizing in the low to mid 70’s, which currently reflects the portion of calculusthat Boise State University has chosen to offer as honors, online, or face-to-face but parallel toonline. 100% 90% 80% 70% 60% 50% 40

Conference Session

Mathematics Division Technical Session 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Patricia A. Ralston, University of Louisville; Campbell R. Bego, University of Louisville

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Diversity

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Mathematics

college, so we can more easilyimplement evidence-based practices with potential to improve retention, of which there are several.Recently, we have focused on implementing formative assessment, which has been shown to improveretention of at-risk students and under-represented minorities [3], [4]. This paper presents and reflects onthe implementation of formative assessment in our Calculus I course for engineering students.Theoretical Framework: Formative assessmentFormative assessment is an instructional technique in which teachers quickly assess students during oroutside class for minimal reward/penalty, with emphasis on improving learning. Formative assessmenthelps both students and teachers to identify knowledge gaps and misconceptions, and

Conference Session

Mathematics Division Technical Session 3: Diversity in Mathematics Education

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

John Kerrigan, Rutgers University; Lydia Prendergast, Rutgers University; Jillian A.S. Mellen, Rutgers University; Geraldine L. Cochran; Antonio D. Silva

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Diversity

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Mathematics

Calculus II course? To answer this research question, twelve semi-structuredinterviews [22] were conducted during the last week of class with a focus on gaining a deeperunderstanding of students’ experiences in the flipped classroom. The research team adaptedquestions from a previous study on students’ self-efficacy in calculus [23]. Students names wereneither provided nor were known to the interviewer. Each interview was 10-20 minutes long andallowed students to reflect on their self-efficacy in mathematics (see Appendix B). Examples ofinterview questions included, “How do you rate your confidence in math now? Why?” and“What could make you feel more comfortable about math?” [23]. All interviews were audiorecorded using a digital recorder

Conference Session

Mathematics Division Technical Session 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Rebecca George, University of Houston

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Diversity

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Mathematics

then move to modify place-ment exams, curriculum, faculty attitudes, or pedagogy training as needed.Math PlacementAlthough many universities use SAT, ACT, or some other standardized placement exam todetermine if students will be successful in certain math courses, it has been reported thatthese scores under-predict the grades for female students [1]. In their article, Kessel and Linn[1] claim that college admissions officers may be missing talented females if they are relyingheavily on ACT and SAT scores. Their article points out that “females report spending moretime reflecting on similarities among problems, organizing and linking their ideas, and review-ing material” and because of this, they tend to be less able to demonstrate speed and

Conference Session

Mathematics Division Technical Session 1

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Tyler James Sullivan, Clemson University; Matthew K. Voigt, Clemson University; Naneh Apkarian, Arizona State University; Antonio Estevan Martinez IV, UC San Diego & San Diego State University; Jessica Ellis Hagman, Colorado State University

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Mathematics

effects with care, and the surveyasked students to reflect back to the beginning of the term.Implications and Non-Implications We end by emphasizing some implications of this work, and perhaps more importantly,some non-implications of this work. First, we see an important implication in the hiring of morediverse faculty. In order for students to experience positive MRMEs, there is a need for morefaculty that can serve as role models based on a variety of social markers and personal identities.To draw on the vaccine metaphor, we emphasize that while increasing instructor diversity amongmultiple

Conference Session

Mathematics Division Technical Session 2

Collection

2021 ASEE Virtual Annual Conference Content Access

Authors

Allen J. Antoine Jr, Rice University Office of STEM Engagement; Carrie A. Obenland, Rice University; Roger Ramirez, Rice University; Christopher Barr, Office of Research, Rice University; Matthew Cushing, Rice University; Carolyn Aitken Nichol, Rice University

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Mathematics

workshop but rather a year-long teacherprofessional development program that provides teachers with 100 contact hours to acquire andapply new knowledge and reflect on their teaching practices. Several studies emphasizecontinuous PD that occurs periodically throughout the school year to best support teachers asthey make adjustments to their lessons and teaching practices. [17,18,19,20]. In addition to PDduration, teachers in AMP! learn how to shift their current lessons to include more effectivestrategies such as inquiry-based and team based lessons [21,22]. Inquiry based teaching can bedescribed as an open communication between teachers and students to freely ask questions topromote conceptual understanding and puts an emphasis on lesson

Conference Session

Mathematics Division Technical Session 3

Collection

2015 ASEE Annual Conference & Exposition

Authors

Ruth Rodríguez-Gallegos, Tecnologico de Monterrey (ITESM); Rafael Ernesto Bourguet-Diaz, Tecnologico de Monterrey (ITESM)

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Diversity

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Mathematics

Page 26.302.2disciplinary skills. In particular, we highlight part of a report [2] which aims to develop theglobal dimension in shaping the future engineer and highlights the need and importance of theseskills in several areas.Generic Skills from [2]: 1. holistic thinking, critical enquiry, analysis and reflection 2. active learning and practical application 3. self-awareness and empathy 4. strong communication and listening skillsHence, the need to develop holistic thinking as an important skill for students and future citizensof the 21st century appears explicitly. Based on this request –to train students from basiceducation in this area- we decided to explore this part. Holistic thinking is also related toSystems Thinking

Conference Session

Mathematics Division Technical Session 4: Assessing Success in Mathematics Education

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Danielle Marie Fredette, Cedarville University

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Diversity

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Mathematics

can to encourage students to become more independent learners.4.2 Independent learners and homeschooling practiceThere is evidence to suggest that the homeschooling lifestyle tends to impart independent learningskills to its students [9, 10], and that engineering freshmen coming from a homeschoolbackground are therefore more likely to take responsibility for their own learning [8]. This is onepossible reason why the homeschooled students from this study succeeded in engineering schoolat a higher rate than their equally mathematically equipped non-homeschooled peers.According to [8] and [11], some important characteristics of an independent learner are: • Critical reflection • Self-awareness (especially related to own learning

Conference Session

Mathematics Division Technical Session 4

Collection

2018 ASEE Annual Conference & Exposition

Authors

Emre Tokgoz, Quinnipiac University; Hazal Ceyhan, Ankara University

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Mathematics

: Responses reflected only one analytical property on the correct interval of independent intervals.The responses in this category indicate mistakes in application of two or more analytical properties in two ormore intervals.Inter-level: Participants were able to apply one or more analytical properties on the correct interval, which mayconsist of the combination of independent intervals; however, the combination of these intervals does not formthe entire domain. The responses in this category indicate application mistakes in only one analytical property ona certain interval.Trans-level: The participants in this category made no mistake in the application of the analytical propertiesthroughout the entire domain of the question. For example, a

Conference Session

Mathematics Division Technical Session 4

Collection

2017 ASEE Annual Conference & Exposition

Authors

Doug Bullock, Boise State University; Janet Callahan, Boise State University; Jocelyn B. S. Cullers, Boise State University

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Diversity

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Mathematics

women and URM, but Pell-eligible students are not as wellserved.6.0 AcknowledgmentsThe authors gratefully acknowledge the support of the National Science Foundation throughGrant No DUE-1347830, and the ongoing support of the Dean of Arts & Sciences and the Officeof the Provost.ReferencesAllexsaht-Snider, M. and Hart, L.E. (2001). Mathematics for All: How do we get there? Theory IntoPractice, 40(2) 93-101.Ames, C. (1992). Classrooms: Goals, structures and student motivation. Journal of EducationalPsychology, 84, 261-271.Bandura, A. (1977). Self-efficacy: Toward a Unifying Theory of Behavioral Change. PsychologicalReview 84 (2), 191-215.Bloom, B. S. (1994). "Reflections on the development and use of the taxonomy". In Rehage, Kenneth J