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Thematische Bibliographien / Engineering mathematics / Zeitschriftenartikel

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Zeitschriftenartikel zum Thema „Engineering mathematics“

Autor: Grafiati

Veröffentlicht am 4. Juni 2021

Zuletzt aktualisiert am 29. Juli 2024

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1

Molina, J. A. López, und M. Trujillo. „Mathematica Software in Engineering Mathematics Classes“. International Journal of Mechanical Engineering Education 33, Nr. 3 (Juli 2005): 244–50. http://dx.doi.org/10.7227/ijmee.33.3.6.

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In this paper we show the advantages of using Mathematica software in engineering mathematics classes through the study of an example problem concerning heat conduction in a slab. Firstly the problem is solved from the point of view of a parabolic model of heat conduction, and secondly from the viewpoint of a hyperbolic model.

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2

Hussin, Husnira Binti, Marina Binti Majid und Rohayu Binti Ab Wahab. „Relationship of Secondary School Mathematics Achievement with Engineering Mathematics 2 in Polytechnics“. Jurnal Konseling dan Pendidikan 6, Nr. 3 (30.11.2018): 160. http://dx.doi.org/10.29210/128300.

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Engineering Mathematics 2 is one of the core courses for all diploma-level engineering students in Malaysian Polytechnic. From the statistics obtained, students achievement in the Engineering Mathematics 2 course (DBM2013) is still moderate and less satisfactory. This is because the subject of Engineering Mathematics 2 is mostly related to calculus and only students who have taken Additional Mathematics subject during secondary school had a basic in the Engineering Mathematics 2. Thus, this research was developed to see the relationship and influence of Mathematics subject during secondary school level, especially Additional Mathematics with the subject of Engineering Mathematics 2 in Polytechnic. High school achievement was measured using the Sijil Pelajaran Malaysia (SPM) examination results in Additional and Modern Mathematic subjects. Meanwhile, the results in the polytechnic level were measured from the final result of the Engineering Mathematics 2 course. The research used secondary data obtained from the examination unit from 2442 students of Semester 2 of Diploma in Civil Engineering (JKA), Diploma in Electrical Engineering (JKE) and Diploma in Mechanical Engineering JKM) at Polytechnic Sultan Mizan Zainal Abidin (PSMZA). Data obtained were processed and analyzed using Microsoft Excel 2010 and Statistical Packages For Social Sciences (SPSS) version 23.0 through Easy Linear Regression Analysis. The findings from the regression analysis showed that there was a significant positive correlation between the achievement of Mathematics during secondary schools with the achievement of Engineering Mathematics 2 in polytechnics and it also proved that Additional Mathematics is one of the medium for student’s excellence in Engineering Mathematics 2 at polytechnics.

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3

Middleton, D., A. C. Bajpai, L. R. Mustoe und D. Walker. „Engineering Mathematics“. Mathematical Gazette 74, Nr. 468 (Juni 1990): 188. http://dx.doi.org/10.2307/3619395.

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4

Gonthier, Georges. „Engineering mathematics“. ACM SIGPLAN Notices 48, Nr. 1 (23.01.2013): 1–2. http://dx.doi.org/10.1145/2480359.2429071.

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5

Rismayanti, Afriliani, Sudi Prayitno, Muhammad Turmuzi und Hapipi Hapipi. „Pengaruh Kemampuan Penalaran dan Representasi Matematis terhadap Hasil Belajar Matematika Kelas VIII di SMP“. Griya Journal of Mathematics Education and Application 1, Nr. 3 (30.09.2021): 448–54. http://dx.doi.org/10.29303/griya.v1i3.64.

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This Research aims to know about the reasoning ability and mathematic representation ability to the results of mathematic lesson in students grade VIII SMP Negeri 1 Batulayar year academic 2019/2020. This research used quantitative approach with ex post facto research type. The population of this research is the eighth grade students of SMP Negeri 1 Batulayar. In determining the sample, probability sampling technique with the type of cluster sampling was used. The sample in this research is the students of class VIII B SMP Negeri 1 Batulayar amounted to 22 students. Data analysis used was multiple linear regression analysis. From the result of the data analysis we found the significant influence between reasoning ability and representative mathematic’s ability to the mathematics learning result of mathematic lesson in students grade viii smp negeri 1 batulayar year academic 2019/2020 with Fcount = 78,812 > F(2,19) = 3,52. The data we wroute as the same regration that Ŷ=-2,452+0,466X1+0,575X2. The equation show us that reasoning ability and the representative mathematic’s ability increase 1 unit and the learning result will increase to 0,466 from reasoning mathematics ability plus 0,575 representative mathematic’s ability.

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6

Lohgheswary, N., Z. M. Nopiah, E. Zakaria, A. A. Aziz und F. N. D. A. Samah. „Development of the Engineering Mathematics Lab Module with Mathematica“. Journal of Engineering and Applied Sciences 14, Nr. 6 (31.12.2019): 1840–46. http://dx.doi.org/10.36478/jeasci.2019.1840.1846.

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7

Grady, Allan, und Ladis D. Kovach. „Advanced Engineering Mathematics“. Mathematical Gazette 69, Nr. 448 (Juni 1985): 155. http://dx.doi.org/10.2307/3616964.

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8

Harding, A. T., J. A. Cochran, H. C. Wiser und B. J. Rice. „Advanced Engineering Mathematics“. Mathematical Gazette 72, Nr. 460 (Juni 1988): 154. http://dx.doi.org/10.2307/3618955.

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9

Chorlton, Frank, und K. A. Stroud. „Further Engineering Mathematics“. Mathematical Gazette 75, Nr. 473 (Oktober 1991): 383. http://dx.doi.org/10.2307/3619541.

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10

Stern, Martin D., A. C. Bajpai, L. R. Mustoe und D. Walker. „Advanced Engineering Mathematics“. Mathematical Gazette 75, Nr. 472 (Juni 1991): 246. http://dx.doi.org/10.2307/3620303.

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11

Holland, F. „Advanced Engineering Mathematics“. Irish Mathematical Society Bulletin 0016 (1986): 82–85. http://dx.doi.org/10.33232/bims.0016.82.85.

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12

Sollero, P. „Advanced engineering mathematics“. Engineering Analysis with Boundary Elements 9, Nr. 2 (Januar 1992): 190. http://dx.doi.org/10.1016/0955-7997(92)90066-g.

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13

Hall, Anthony. „Software engineering mathematics“. Science of Computer Programming 12, Nr. 2 (Juli 1989): 168–70. http://dx.doi.org/10.1016/0167-6423(89)90045-2.

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14

More, M. „Mathematics and engineering in real life through mathematical competitions“. International Journal of Mathematical Education in Science and Technology 49, Nr. 2 (27.10.2017): 305–21. http://dx.doi.org/10.1080/0020739x.2017.1387297.

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15

Gayoso Martínez, Víctor, Luis Hernández Encinas, Agustín Martín Muñoz und Araceli Queiruga Dios. „Using Free Mathematical Software in Engineering Classes“. Axioms 10, Nr. 4 (12.10.2021): 253. http://dx.doi.org/10.3390/axioms10040253.

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There are many computational applications and engines used in mathematics, with some of the best-known arguably being Maple, Mathematica, MATLAB, and Mathcad. However, although they are very complete and powerful, they demand the use of commercial licences, which can be a problem for some education institutions or in cases where students desire to use the software on an unlimited number of devices or to access it from several of them simultaneously. In this contribution, we show how GeoGebra, WolframAlpha, Python, and SageMath can be applied to the teaching of different mathematical courses in engineering studies, as they are some of the most interesting representatives of free (and mostly open source) mathematical software. As the best way to show a topic in mathematics is by providing examples, this article explains how to make calculations for some of the main topics associated with Calculus, Algebra, and Coding theories. In addition to this, we provide some results associated with the usage of Mathematica in different graded activities. Moreover, the comparison between the results from students that use Mathematica and students that participate in a “traditional” course, solving problems and attending to master classes, is shown.

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16

Lohgheswary, N., Z. M. Nopiah, E. Zakaria, A. A. Aziz und S. Salmaliza. „Identifying Common Engineering Mathematics Topics for Innovative Learning of Engineering Mathematics“. Journal of Engineering and Applied Sciences 14, Nr. 20 (31.10.2019): 7765–70. http://dx.doi.org/10.36478/jeasci.2019.7765.7770.

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17

Chikampa, Victor, Derrick Banda, Jacqueline Siwale, Sheilas C. Kafula, Ireen Moonga, Alfred Daka und Lungowe Chindele. „The Effect of Mathematics Anxiety on Mathematics Self Efficacy and Perceived Mathemathics Achievement“. International Journal of Research and Innovation in Social Science VII, Nr. VI (2023): 1010–17. http://dx.doi.org/10.47772/ijriss.2023.7683.

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This study examined the relationship between mathematics anxiety, mathematics self-efficacy and perceived mathematics success among 131 freshmen Zambian engineering and natural and applied science students. A quantitative ex post facto survey design was used to achieve the research objectives. Negative but statistically significant relationships between mathematics anxiety and self-efficacy as well as perceived mathematics achievement were established. A positive empirical relationship between mathematics self-efficacy and perceived mathematics achievement was supported.

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18

Raveh, Ira, Elena Trotskovsky und Nissim Sabag. „Mathematical Understanding vs. Engineering Understanding: Engineering Students’ Perceptions“. International Research in Higher Education 2, Nr. 2 (26.05.2017): 15. http://dx.doi.org/10.5430/irhe.v2n2p15.

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The current study explores how BSc engineering students at an academic college of engineering perceive engineering and mathematical understanding and the interrelationships between them. The theoretical framework for this research includes three main aspects of engineering and mathematical understanding: procedural, conceptual, and applicable. The participants were thirty BSc students from different engineering disciplines who answered a four-open-items questionnaire that included three questions dealing with specific mathematical and engineering subjects and one general question. Content analysis of the students' answers revealed that all three aspects were reflected in the students' answers. More responses were recognized in student answers to the specific questions than to the general question. The procedural aspect was very prominent among the students’ responses to the specific mathematics and engineering subject. Regarding the answers to the general question, it can be induced that students possess general perceptions of mathematic understanding as procedural and conceptual, but not applicable; and engineering understanding as conceptual and applicable, but not procedural. Concerning relationships between mathematical and engineering understanding, more than one third of the students claimed that mathematics is a tool for engineering; yet, at the same time, not even one student addressed applicable aspects of mathematical understanding in the general question. This fact stresses the students’ detached general perception of mathematical understanding as not applicable.

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19

Nurmasari, Linda, Budiyono, Joko Nurkamto und Murni Ramli. „Realistic Mathematics Engineering for improving elementary school students’ mathematical literacy“. Journal on Mathematics Education 15, Nr. 1 (01.10.2023): 1–26. http://dx.doi.org/10.22342/jme.v15i1.pp1-26.

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Mastery of mathematical literacy is essential for developing life skills in the 21st century. Mathematical literacy is even more critical in elementary schools as it forms the basis for mastery at the junior and senior high school levels. Elementary school students differ in their characteristics from students at the higher education level. They, therefore, require an appropriate learning model to improve their mathematical literacy. This research aims to develop a learning model, termed Realistic Mathematics Engineering (RMEng), that combines the Realistic Mathematics Education approach with the steps of the Engineering Design Process and determines the model’s effectiveness. The model was validated by seven experts from three universities in Indonesia and had an Aiken validity index value of 0.786, indicating that it was valid. The RMEng model contains the following steps: understanding realistic problems, solving problems in informal ways, developing formal mathematics, developing products, and drilling. Discussions and presentations can be incorporated into each of these five steps. The RMEng model was subjected to the stages of preliminary and main field testing and was revised based on the suggestions of teachers and observers. Through experimental research compared to a control group, the RMEng model was proven more effective in increasing elementary school students’ mathematical literacy at the 0.000 significance level.

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20

Lee, Sang-Gu, Jae Hwa Lee, Jun H. Park und Eung-Ki Kim. „Interactive Engineering Mathematics Laboratory“. Communications of Mathematical Education 30, Nr. 3 (30.09.2016): 281–94. http://dx.doi.org/10.7468/jksmee.2016.30.3.281.

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21

Mustoe, Leslie. „Mathematics in engineering education“. European Journal of Engineering Education 27, Nr. 3 (September 2002): 237–40. http://dx.doi.org/10.1080/0304790210141546.

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22

Bird, John. „Engineering Mathematics, 3rd edn“. Measurement Science and Technology 13, Nr. 4 (19.03.2002): 643. http://dx.doi.org/10.1088/0957-0233/13/4/702.

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23

Boute, Raymond. „Why mathematics needs engineering“. Journal of Logical and Algebraic Methods in Programming 85, Nr. 5 (August 2016): 867–78. http://dx.doi.org/10.1016/j.jlamp.2016.01.001.

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24

Sanders, Sam. „Reverse-engineering Reverse Mathematics“. Annals of Pure and Applied Logic 164, Nr. 5 (Mai 2013): 528–41. http://dx.doi.org/10.1016/j.apal.2012.11.006.

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25

Karamyshev, Anton N., und Zhanna I. Zaytseva. „“MATHEMATICA” IN TEACHING STUDENTS MATHEMATICS“. Práxis Educacional 15, Nr. 36 (04.12.2019): 610. http://dx.doi.org/10.22481/praxisedu.v15i36.5937.

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The relevance of the topic of the article is due to the process of modernization of higher mathematical education in Russia, which has led to a significant change in curricula and the need to look for ways and forms of training that would allow students to learn the necessary material within the time granted for studying, while obtaining the maximum necessary amount of skills, knowledge, and competencies. The objective of the article is to justify the ways and principles of the development and implementation of new pedagogical and information technologies in the educational process, the organization of professional education of students in technical areas based on the integration of mathematics and computer science. The leading method of the study of this problem is the methodological analysis and subsequent synthesis, which, by analyzing the didactic content of the sections in mathematics and the possibilities of the computer mathematical environment called Mathematica, reveals the necessary methods and ways of developing and using modern computer technologies in the mathematical education of engineering students. It is proved that one of the main tools for implementing the methods for solving the indicated problem should be considered a computer, namely, the mathematical environment called Mathematica, and the basic principles of its systemic implementation in the educational process of the university have been identified. The materials of the article may be useful to teachers of mathematical disciplines of higher educational institutions, the computer programs and pedagogical software products created in Mathematica can serve as models for the development of similar pedagogical software products.

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26

Rocha, Helena. „Mathematical proof: from mathematics to school mathematics“. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, Nr. 2140 (21.01.2019): 20180045. http://dx.doi.org/10.1098/rsta.2018.0045.

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Proof plays a central role in developing, establishing and communicating mathematical knowledge. Nevertheless, it is not such a central element in school mathematics. This article discusses some issues involving mathematical proof in school, intending to characterize the understanding of mathematical proof in school, its function and the meaning and relevance attributed to the notion of simple proof. The main conclusions suggest that the idea of addressing mathematical proof at all levels of school is a recent idea that is not yet fully implemented in schools. It requires an adaptation of the understanding of proof to the age of the students, reducing the level of formality and allowing the students to experience the different functions of proof and not only the function of verification. Among the different functions of proof, the function of explanation deserves special attention due to the illumination and empowerment that it can bring to the students and their learning. The way this function of proof relates to the notion of simple proof (and the related aesthetic issues) seems relevant enough to make it, in the future, a focus of attention for the teachers who address mathematical proof in the classroom. This article is part of the theme issue ‘The notion of ‘simple proof’ - Hilbert's 24th problem’.

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27

Ker, H. W. „Engineering Education and Attitudes Toward Mathematics“. International Journal of Quality Assurance in Engineering and Technology Education 2, Nr. 1 (Januar 2012): 63–76. http://dx.doi.org/10.4018/ijqaete.2012010105.

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Research addressed the importance of high abilities in mathematics at secondary school for the well preparation of engineering profession. However, factors influencing mathematics performance like Self-Confidence in Mathematics learning, values on mathematics, and Positive Attitudes toward Mathematics received less attention in research of engineering education. This paper utilized TIMSS 2007 data to conduct a global comparative analysis on these three factors at varied International Benchmark levels. The countries for this comparative study are the United States and the top three Asian countries, Chinese Taipei, Korea and Singapore. Results showed that compared with Chinese Taipei and Korea, Singapore students tend to have high level of Self-Confidence in Mathematics learning, values on mathematics, and Positive Attitudes toward Mathematics. The students of United States, though not ranked high in average mathematics achievement, tend to place good values on mathematics, have self-confidence in learning, and have positive attitudes toward mathematics.

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28

Summit, Raymond. „A computer laboratory program in engineering mathematics to enhance mathematical conceptualisation“. ANZIAM Journal 51 (02.06.2010): 280. http://dx.doi.org/10.21914/anziamj.v51i0.2616.

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29

Maat, Siti Mistima, Effandi Zakaria, Norazah Nordin und Mohamed Amin Embi. „Engineering Technology Students’ Mathematics Beliefs and Attitude towards Mathematics“. International Journal of Learning: Annual Review 17, Nr. 3 (2010): 201–10. http://dx.doi.org/10.18848/1447-9494/cgp/v17i03/46866.

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30

Dékány, Kornélia Éva. „Engineering and Economic Mathematics for Engineering Management Students“. Teaching Mathematics and Computer Science 15, Nr. 1-2 (11.12.2017): 35–50. http://dx.doi.org/10.5485/tmcs.2017.0430.

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31

Prabakaran, R. „Issues in Teaching Engineering Mathematics“. Journal of Statistics and Mathematical Engineering 7, Nr. 1 (29.01.2021): 5–8. http://dx.doi.org/10.46610/josme.2021.v07i01.002.

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32

Gjonbalaj, Qefsere Doko. „Engineering Mathematics and Modern Technology“. International Journal of Educational Technology and Learning 2, Nr. 1 (2018): 8–13. http://dx.doi.org/10.20448/2003.21.8.13.

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33

Beretta, Elena, Alberto Gandolfi und C. C. A. Sastri. „Mathematics and Innovation in Engineering“. Key Engineering Materials 380 (März 2008): 3–14. http://dx.doi.org/10.4028/www.scientific.net/kem.380.3.

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We present some examples of mathematical discoveries whose original import was mainly theoretical but which later ended up triggering extraordinary ad- vances in engineering, sometimes all the way down to technological realizations and market products. The examples we cite include Markov chains and Markov random fields, spin glasses, large deviations and the inverse conductivity problem, and their effects in various areas such as communication and imaging technologies.

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34

Bland, J. A., und L. R. Mustoe. „Worked Examples in Engineering Mathematics“. Mathematical Gazette 71, Nr. 457 (Oktober 1987): 250. http://dx.doi.org/10.2307/3616793.

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35

Chambers, Ll G., L. R. Mustoe und M. D. J. Barry. „Mathematics in Engineering and Science“. Mathematical Gazette 83, Nr. 497 (Juli 1999): 380. http://dx.doi.org/10.2307/3619126.

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36

Bultheel, Adhemar, und Marc Van Barel. „Linear prediction: mathematics and engineering“. Bulletin of the Belgian Mathematical Society - Simon Stevin 1, Nr. 1 (1994): 1–58. http://dx.doi.org/10.36045/bbms/1103408452.

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37

O'Connor, J. F. „Mathematics in Food Engineering Research“. Irish Mathematical Society Bulletin 0017 (1986): 36–43. http://dx.doi.org/10.33232/bims.0017.36.43.

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38

Hatziargyriou, N. D. „Book Review: Advanced Engineering Mathematics“. International Journal of Electrical Engineering & Education 30, Nr. 3 (Juli 1993): 287. http://dx.doi.org/10.1177/002072099303000332.

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39

Davies, Alan. „Book Reviews: Further Engineering Mathematics“. International Journal of Electrical Engineering & Education 34, Nr. 2 (April 1997): 174–75. http://dx.doi.org/10.1177/002072099703400209.

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40

Steele, N. „Engineering mathematics--dare to hope?“ Teaching Mathematics and its Applications 22, Nr. 4 (01.12.2003): 199–208. http://dx.doi.org/10.1093/teamat/22.4.199.

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41

Scott, Paul J., und Alistair B. Forbes. „Mathematics for modern precision engineering“. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 370, Nr. 1973 (28.08.2012): 4066–88. http://dx.doi.org/10.1098/rsta.2011.0379.

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The aim of precision engineering is the accurate control of geometry. For this reason, mathematics has a long association with precision engineering: from the calculation and correction of angular scales used in surveying and astronomical instrumentation to statistical averaging techniques used to increase precision. This study illustrates the enabling role the mathematical sciences are playing in precision engineering: modelling physical processes, instruments and complex geometries, statistical characterization of metrology systems and error compensation.

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42

Larcombe, P. J. „Engineering mathematics: the crisis continues“. Engineering Science & Education Journal 7, Nr. 6 (01.12.1998): 273–81. http://dx.doi.org/10.1049/esej:19980609.

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43

Strang, Gilbert. „The Teaching of Engineering Mathematics“. Applied Mechanics Reviews 39, Nr. 9 (01.09.1986): 1319–21. http://dx.doi.org/10.1115/1.3149519.

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44

Henderson, Simi, und Philip Broadbridge. „Engineering Mathematics Education in Australia“. MSOR Connections 9, Nr. 1 (Februar 2009): 12–17. http://dx.doi.org/10.11120/msor.2009.09010012.

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45

Jaworski, Barbara, Janette Matthews, Carol Robinson und Tony Croft. „Engineering Students Understanding Mathematics (ESUM)“. MSOR Connections 11, Nr. 3 (September 2011): 47–48. http://dx.doi.org/10.11120/msor.2011.11030047.

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46

Hamlet, Dick. „Mathematics, Computer Science, Software Engineering“. Electronic Notes in Theoretical Computer Science 40 (März 2001): 186. http://dx.doi.org/10.1016/s1571-0661(05)80044-1.

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47

Chatterjee, Anindya. „Mathematics in engineering—Part II“. Resonance 10, Nr. 5 (Mai 2005): 39–53. http://dx.doi.org/10.1007/bf02871330.

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48

Ghosh, S. K. „ASM handbook of engineering mathematics“. Journal of Mechanical Working Technology 14, Nr. 2 (März 1987): 240. http://dx.doi.org/10.1016/0378-3804(87)90067-2.

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49

Winkelman, Paul. „Perceptions of mathematics in engineering“. European Journal of Engineering Education 34, Nr. 4 (10.07.2009): 305–16. http://dx.doi.org/10.1080/03043790902987378.

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50

Wiryanto, L. H. „Line integral on engineering mathematics“. IOP Conference Series: Materials Science and Engineering 296 (Januar 2018): 012046. http://dx.doi.org/10.1088/1757-899x/296/1/012046.

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