models pertinent to engineering as the semester unfolds.This course stands out due to its inclusion of weekly 75-minute Peer Learning Group (PLG)sessions. These workshops, led by a teaching assistant, offer hands-on programming practicebeyond lectures, reinforcing core concepts. The PLG is a non-credit corequisite, taught by aproficient former student, with all materials provided by the faculty. There is no direct gradeassigned to the PLG because students are completing their Programming assignments during thePLG. The focus is to give students confidence to start writing code from scratch and let themdevelop their own programming style.In addition to the regular coursework, the curriculum is enriched with challenges and modulesfrom the MathWorks
MATLAB Scripts Write programs in script Logical Arrays Use logical expressions in MATLAB Final Project Bring together the introduced concepts with a project 6 9. Student FeedbackThe feedback from students offered meaningful insights into the course's strengths and opportunities forimprovement. Students largely appreciated the practical focus of the curriculum while providingconstructive suggestions to further improve the learning experience.What Students ValuedStudents highlighted the programming assignments and Peer Learning Group (PLG) sessions as some ofthe most effective components of the course. These
distribute one week to teach a simpleintroduction. The detailed topics about GVS usually are taught for math majors in a secondor an advanced version of a linear algebra course. Considering our audience are engineeringstudents, it is evident that numerical applications are preferred. The discoveries from thementioned peer institutes also validated such revision. Secondly, we add numerical compo-nents, which are not included in PTC . There are four parts for the newly added numericalcomponent: MATLAB live script for instructors to teach, MATLAB practice problems ingroup worksheet during each class meeting, coding basic concepts in MATLAB Grader, andMATLAB application projects in MATLAB Grader. By writing MATLAB programs, stu-dents have to imagine the
classAbstract: A redesigned engineering math sequence was implemented from fall 2016 to spring2020, and the study focused on data collected during fall 2018 and spring 2019 from a singleclass with a sample size of 25. The results of the study suggest that the redesigned sequencepositively impacted students' material mastery, communication, collaboration, andmetacognition. Although the sample size was small, and the results were not statisticallysignificant, it was found that students' view of math and perception of their preparedness mayplay a role in their participation and how they interact with the material, with peers, and with theinstructor and TAs.Keywords: engineering math, Calculus, active learning, redesignIntroductionCore curriculum for
experience withcollege expectations. Like many universities, Drexel University offers many programs to supportstudents academically and personally, including academic coaching and remedial courses onacademic skills, walk-in math tutoring in academic buildings and residence halls; math studysquads; math exam review sessions for high-risk courses, peer tutoring for first-year engineeringcourses and Matlab/Python, and academic /financial counseling for underrepresented minoritySTEM majors. Despite the abundance of student support provided, evidence suggests that theseprograms are not utilized effectively. Academic support staff all report that services are mostfrequently used by high-performing students who seek to improve their grades from B+ to A
seven graduate teaching orlearning assistants assigned each hour of open lab. The coaching staff consists of oneprofessional Senior Academic Success Coach (ASC) and at least three peer coaches per term.With the program set to receive recurring budget from the institution, the coaching team will beexpanded to two professional ASCs and at least five peer coaches per term. Additionally, twofull-time instructor/lecturers dedicated to this program will be joining the lead instructor in Fall2025.3.0 Math Launch PedagogyAddressing diverse learning needs in math classes is challenging as students arrive with variedskills and learning styles [17]. In a traditional classroom, the instructor assumes a central rolewith students becoming passive recipients
improve.Examination of the model’s utilization in empirical research may provide information about howresearchers interpret and draw upon of the publications, as well as the nature of the influence ofthe theoretical model [4], [5], [6]. The peer-reviewed publications will be analyzed for theirpurpose and relation to engineering education. The nature of the citation instances will beanalyzed for their primary purpose in empirical research. This analysis will explore theinterpretation and context of the theoretical model and its relations to mathematics andengineering education. Salient findings from the citation analysis may focus future researchconcerning the transition from high school mathematics to college mathematics.Summary of theoretical framework for
the useof effective learning strategies [23]. Therefore, identifying appropriate strategies in the classroomto alleviate anxiety and enhance mathematical achievement is crucial [25]. Classroom-Level Factors Influencing Course Performance In addition to psychosocial factors, classroom-level factors also significantly impactstudents' performance in calculus courses.Active Engagement Practices A growing body of scholarship has advocated for the adoption of active learningstrategies in higher education, especially within STEM disciplines. Active learning refers to aneducational approach where students actively participate in activities such as reading, writing,discussions, or problem-solving that promote analysis
spaces of the mathematicalfunctions, students are asked to write rules to communicate the utility of the models to otherstakeholders including healthcare professionals or basic biomedical scientists.In summary, we have created a unique BME focused text for differential equations and linearalgebra that encourages students to harness their knowledge of physics, biology, physiology,engineering, and mathematics to formulate dynamic models of physiological systems. Our overallaim is to enhance students’ ability to apply and foster a deep appreciation of the power ofmathematics in addressing real-world BME challenges.Background:Ordinary differential equations are ubiquitous for understanding various topics and systemsstudied as part of the
become mathematically impossible to pass the course and subsequentlywithdraw. However, the structure of SBG provides a student in a similarly grim situation aglimmer of hope that he or she can radically change his or her behavior and finish the course witha passing grade. This comeback rarely comes to fruition due to the substantial number ofstandards the student must master on the remaining assessments. While we tell our studentsplainly that this type of comeback is highly improbable, some portion remain undeterred.The second noteworthy trend that we observe is a pronounced improvement of SBG students inthe follow-up math course compared to their peers in WAG courses. Particularly, the percentageof students earning a grade of A or B is
teachingundergraduate courses at the research sites formed the potential participant pool. They wereemailed explaining the purpose of the study and inviting them to participate. All who expressedinterest in participating were recruited. IRB approval was obtained before emailing theparticipants. Data were collected in the form of semi-structured interviews. The interview protocolprobed the participants to reflect on the mathematical concepts used in the engineering coursestaught by them, the readiness of students to apply these concepts, and how they respond tostudents’ math readiness. They were also asked for general recommendations on improvingstudents’ math readiness. These interviews were conducted by the first author. As of writing thispaper, we have
a coursewhich was themed around a three-part core of logic, area under a curve, and limits whileintegrating algebra and trigonometry review. Emphasis is placed on exploration, rigorousderivations, and proofs to develop mathematical thinking.In fall 2022 the pilot was administered to six sections of Precalculus. The progress of thestudents from each section was tracked through the 2022-2023 academic year. Data from examsin their subsequent calculus courses was collected and compared to their peers from non-pilotsections of Precalculus to determine if there were statistically significant differences inperformance. This paper will outline and detail the curriculum. Statistical results from apreliminary study of effectiveness will be presented
experiences. The effort covers various courses, including Physics/Mechanics,Calculus, Statics, Control Systems, Digital Signal Processing, Probability, Estima-tion, and Computer Algorithms. The larger scale project, as it relates to calculusconcepts, intends to develop and integrate engaging games, relevant 3D puzzles andbrain teasers, captivating animations, real-world intuitive illustrations and demon-strations, short video clips, hands-on activities (including virtual reality and aug-mented reality experiences), collaborative teamwork and communication exercises,small-scale inquiry-based research, as well as engaging presentations and peer-basedlearning. It should be noted that this work should be considered as work in progress. Itis intended
) 0.007 Traditional 33.71 (5.82) 33.36 (5.68) 0.301 Self-efficacy Mastery experience (prior success) Mastery 4.10 (0.56) 4.25 (0.66) 0.005 Traditional 4.19 (0.52) 4.12 (0.53) 0.248 Vicarious experience (peer success) Mastery 4.63 (0.71) 4.78 (0.76) 0.012 Traditional 4.46 (0.53) 4.52 (0.63) 0.289 Social Persuasions (support for success) Mastery 4.38 (1.05) 4.54 (0.91) 0.018 Traditional 4.41 (0.92) 4.45 (0.87) 0.388 Physiological State (anxiety) Mastery 2.21 (0.96
problems. They emphasized a preference for teaching styles whereinstructors work through problems step-by-step, taking the time to slow down and providethorough explanations, rather than simply reading from slides. Students also wanted instructorsto avoid assuming prior knowledge and to ensure that they clearly explain concepts from theground up. There was a strong desire for more collaborative problem-solving in class, withplenty of opportunities for students to ask questions and work together with peers. Otherrecommendations included improving the pacing of both lectures and tutorials to prevent rushingthrough material, offering lecture notes in advance for review, and creating a comfortableenvironment for students to ask questions without