scholarly journals Effects of an Intensive Mathematics Course on Freshmen Engineering Students' Mathematics Anxiety Perceptions

2016 ◽  
Author(s):  
Gustavo Moran ◽  
Lisa Benson
2014 ◽  
Vol 4 (3) ◽  
pp. 11 ◽  
Author(s):  
Isabel Braun ◽  
Stefan Ritter ◽  
Mikko Vasko

The inverted classroom is a teaching model, where the students prepare for classroom by watching video lectures. The classroom time is then dedicated to individual practice. We evaluated a mathematics course for electrical engineering students throughout three semesters, where 20% of the topics were taught using the inverted classroom model. The aim was to find out whether the model can help to better address groups with large differences in prior knowledge in mathematics. We report mainly positive feedback from the students, although the opinions vary greatly between the groups. The students appreciate the increased amount of practice in the classroom as well as the possibility to learn at their own pace. Exam performance remained constant in the topics taught using the inverted classroom compared to previous semesters. The exam performance of weaker students also remained constant.


2010 ◽  
Vol 8 ◽  
pp. 482-489 ◽  
Author(s):  
Prima Vitasari ◽  
Tutut Herawan ◽  
Muhamad Nubli Abdul Wahab ◽  
Ahmad Othman ◽  
Suriya Kumar Sinnadurai

2014 ◽  
Vol 4 (4) ◽  
pp. 51 ◽  
Author(s):  
Nina Kälberer ◽  
Cornelia Böhmer ◽  
Katrin Tschirpke ◽  
Brigitte Petendra ◽  
Eva Maria Beck-Meuth

This paper reports the concept of a preparatory mathematics course for non-traditional students in electrical engineering, and its evaluation. The blended-learning course is part of the initial study phase smoothing the transition to learning at university level. The instructional design of the preparatory course is aligned with that of the Bachelor’s study program. However, it takes place prior to the beginning of the first semester. The initial phase additionally encompasses the whole first semester with different courses meant to help students getting ready for studying. Prospective students indicated that they needed to refresh their knowledge in mathematics. Thus, a preparatory mathematics course was given priority. This course serves several purposes: Students get an impression of the requirements in mathematics necessary for the study program; they refresh their basic knowledge; they make themselves familiar with self-organized learning and the blended-learning concept of the program. Design and implementation were evaluated with a questionnaire at the end of the course and after the first semester. The results show that the course is an appropriate instrument prior to engineering studies in order to prepare and support non-traditional students. In the conclusions potential for improvement is identified.


2015 ◽  
Vol 21 (7) ◽  
pp. 2400-2403
Author(s):  
Fariba Firouzian ◽  
Mohammadreza Fadaei ◽  
Zaleha Ismail ◽  
Soheila Firouzian ◽  
Yudariah Mohammad Yusof

2019 ◽  
Vol 8 (2) ◽  
pp. 179
Author(s):  
Rully Charitas Indra Prahmana ◽  
Tri Sutanti ◽  
Aji Prasetya Wibawa ◽  
Ahmad Muhammad Diponegoro

Mathematical anxiety has a negative relationship with mathematics performance and achievement. Further explained, mathematics anxiety has an indirect effect on mathematics performance. This research explores sources or factors related to mathematics anxiety among engineering students at a private university in Indonesia. A total of 47 engineering students participated in this survey that randomly chosen based on gender, major, and age. Two main factors are affecting the mathematics anxiety of engineering students, namely internal and external factors. The results show that mathematics anxiety among engineering students is manifested into three aspects. Firstly, the home aspects are talking about the influence of parents and sibling. Secondly, society's issues are discussing self-efficacy, social reinforcement to hate mathematics, and social stereotypes. Lastly, the classroom aspects are talking about the traditional mathematics learning process and classroom culture, namely the experience of learning mathematics in classrooms and relationships between friends during learning. The details of the statements under the aspects also highlight unique problems and are not covered by previous research in mathematical anxiety. Next, differences in mathematics anxiety by gender and faculty were examined.


2016 ◽  
Author(s):  
Brooke D'Aloisio

<p>Research reveals that the majority of students are unprepared in making the transition from high school to college mathematics. Many students choose majors outside of STEM and business fields to pursue degrees with less rigorous mathematics requirements. According to recent findings, it is likely that over 25% of all freshmen will fail their first mathematics course. Few studies examine student success in business mathematics courses, and business is currently the most popular major in the United States. Thus, the purpose of this research was to examine what factors predict success in a foundational business mathematics course (BUS 111) at a large Northeastern university. </p> <p>Eight independent variables were examined: gender, high school GPA, mathematics SAT score, score on the university’s placement exam, student attitudes using the Attitudes Towards Mathematics Inventory (ATMI), anxiety using the Mathematics Anxiety Scale (MAS), number of hours per week spent on mathematics, and number of classes missed. The dependent variable was BUS 111 final average. All students (<em>n</em> = 247) enrolled in BUS 111 were invited to participate during the Fall 2015. Upon completion of pre- and post-surveys, multiple regression was used to determine which variables were significant predictors. Statistical findings revealed that placement score, high school GPA, a combination of ATMI/MAS scores, and number of classes missed were the best predictors of BUS 111 average overall (R<sup>2</sup> = 44.2%, <em>p</em> = 0.000). Different models are presented for comparison and examination. Significant correlations found between perceived instructor effectiveness and student attitudes, anxiety, and course grades are also presented. Overall, combinations of non-affective and affective measures serve as the best predictors of success in business mathematics.</p>


2015 ◽  
Vol 24 (4) ◽  
pp. 1009-1030
Author(s):  
Jonas Gallenkämper ◽  
Bernhard Heim ◽  
Judith Kreuzer ◽  
Florian Rupp ◽  
Paul von Stockhausen ◽  
...  

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