Conference Session

Mathematics Division Technical Session 2

Collection

2019 ASEE Annual Conference & Exposition

Authors

Cathy Poliak, University of Houston

Tagged Topics

Diversity

Tagged Divisions

Mathematics

= 0.00245). Figure 2: Q-Q Plot ExampleR syntax: coffee=c(9.9, 9.7, 10.0, 10.1, 9.9, 9.6, 9.8, 9.8, 10.0, 9.5, 9.7, 10.1, 9.9, 9.6, 10.2, 9.8, 10.0, 9.9, 9.5, 9.9) qqnorm(coffee) qqline(coffee) t.test(coffee,mu=10)Example 2:A study was conducted to examine the effect of pets in stressful situations. Subjects wererandomly assigned to each of three groups to do a stressful task alone (the control group), with agood friend present, or with their dog present. The subject’s mean heart rate (in beats perminutes) during the task is one measure of the effect of stress. The data has the mean heart ratesduring stress with a pet (P), with a friend (F) and for the control group (C).Result: The

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

Tagged Topics

Diversity

Tagged Divisions

Mathematics

class review/Q&A online Station #1 Station #2 online quiz quiz Three-station 10 min 10 min 40 min 40 min 40 min 10 min class review/Q&A online Station #1 Station #2 Station #3 online quiz (workshop) quizFigure 3. Class timeline (150 minutes)Learning Assistant Classroom SupportAn important part of the rotating station design was the availability of an undergraduate LearningAssistant (LA) provided by the University. Undergraduate students who qualify to become anLA have earned an A or B+ in the course they are an LA for, successfully

Conference Session

Mathematics Division Technical Session 1

Collection

2019 ASEE Annual Conference & Exposition

Authors

Rebecca George, University of Houston

Tagged Topics

Diversity

Tagged Divisions

Mathematics

: Yij = β0j + β1j X1ij + β2j X2ij + β3j X3ij + β4j X4ij + ijwhere β0j is the intercept for the level 1 equation and β1j , β2j , β3j , β4j are the level 1 coeffi-cients of each X. Also, ij represents the level 1 random effect. The level 1 coefficients andintercept become the outcome variables for the level 2 variables. The level 2 model is βqj = γq0 + γq1 W1j + γq2 W2j + γq3 W3j + γq4 W4j + uqjwhere γqj , q = 0..4, are the level 2 coefficients of each W and uij represents the level 2random effect.The first step in the analysis is to run the empty or unconditional model (Model 1) and com-pute the intraclass correlation coefficient (ICC) in order to compute the proportion of the totalvariance in each class. For this

Conference Session

Mathematics Division Technical Session 4

Collection

2018 ASEE Annual Conference & Exposition

Authors

Emre Tokgoz, Quinnipiac University; Hazal Ceyhan, Ankara University

Tagged Topics

Diversity

Tagged Divisions

Mathematics

) > 0 when x > 2 , f ′′( c ) = 0 for an x = c such that − 1 < c < 1 .A similar research question in the literature was used to understand STEM undergraduate and graduate students’ability to answer the following research question19:Q. Please draw the graph of f ( x ) = x x +1 at (e) below by finding and applying each of the following information ifthey are applicable.a) Vertical and horizontal asymptotes of f(x) and limiting values of f(x) at the vertical asymptotes if there exists any vertical asymptote.b) Local maximum, local minimum and inflection

Conference Session

Mathematics Division Technical Session 3: Diversity in Mathematics Education

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Shuvra Das, University of Detroit Mercy; Kirstie A. Plantenberg, University of Detroit Mercy

Tagged Topics

Diversity

Tagged Divisions

Mathematics

questions are summarized in Figures 8 through 13. The responseshighlight the impact of the course. Here are some of the conclusions that can be drawn from thedata: • ENGR1234 has a stronger impact on student performance in Physics I (Mechanics) than in Physics II (Electricity and Magnetism) • ENGR1234 has a very strong positive impact on student performance in Statics and Dynamics • ENGR1234 seems to have a strong positive influence on students’ ability to perform well in other Mathematics courses • As per the response to Q#6 ENGR1234 was a valuable addition to the curriculum and students feel the course is helping them a lot STRONGLY DISAGREE 1 DISAGREE 2 NEUTRAL