scholarly journals Engineering Education In Biomimetic Microelectronic Systems: An Urban Engineering Research Center’s Response

2020 ◽  
Author(s):  
Gisele Ragusa ◽  
Michael Khoo ◽  
Ellis Meng

2021 ◽  
Vol 20 (1) ◽  
pp. 247-270
Author(s):  
Krystian Chrzan ◽  
Olena Tverytnykova ◽  
Maryna Gutnyk

The deployment of electrical engineering research in the second half of the 19th and at the beginning of the 20th c. is shown. The great attention is focused on the economic circumstances of the development of theoretical electrical engineering. Emphasis is placed on the leading role of Lviv Polytechnic. The names of professors who were at the origins of electrical engineering education in Lviv, Kyiv, Kharkiv and Odesa are given. It is claimed that the European School of Electrical Engineering directly influenced the development of relevant research in Ukraine.



Author(s):  
Linda Steuer ◽  
Anna Bouffier ◽  
Sonja Gaedicke ◽  
Carmen Leicht-Scholten

Engineers and therefore engineering education are challenged by the increasing complexity of questions to be answered globally. The education of future engineers therefore has to answer with curriculums that build up relevant skills. This chapter will give an example how to bring engineering and social responsibility successful together to build engineers of tomorrow. Through the integration of gender and diversity perspectives, engineering research and teaching is expanded with new perspectives and contents providing an important potential for innovation. Aiming on the enhancement of engineering education with distinctive competencies beyond technical expertise, the teaching approach introduced in the chapter represents key factors to ensure that coming generations of engineers will be able to meet the requirements and challenges a changing globalized world holds for them. The chapter will describe how this approach successfully has been implemented in the curriculum in engineering of a leading technical university in Germany.





2017 ◽  
pp. 922-949
Author(s):  
Linda Steuer ◽  
Anna Bouffier ◽  
Sonja Gaedicke ◽  
Carmen Leicht-Scholten

Engineers and therefore engineering education are challenged by the increasing complexity of questions to be answered globally. The education of future engineers therefore has to answer with curriculums that build up relevant skills. This chapter will give an example how to bring engineering and social responsibility successful together to build engineers of tomorrow. Through the integration of gender and diversity perspectives, engineering research and teaching is expanded with new perspectives and contents providing an important potential for innovation. Aiming on the enhancement of engineering education with distinctive competencies beyond technical expertise, the teaching approach introduced in the chapter represents key factors to ensure that coming generations of engineers will be able to meet the requirements and challenges a changing globalized world holds for them. The chapter will describe how this approach successfully has been implemented in the curriculum in engineering of a leading technical university in Germany.



2021 ◽  
Vol 26 (4) ◽  
Author(s):  
Marian Daun ◽  
Jennifer Brings ◽  
Patricia Aluko Obe ◽  
Viktoria Stenkova

AbstractStudents’ experience is used in empirical software engineering research as well as in software engineering education to group students in either homogeneous or heterogeneous groups. To do so, students are commonly asked to self-rate their experience, as self-rated experience has been shown to be a good predictor for performance in programming tasks. Another experience-related measurement is participants’ confidence (i.e., how confident is the person that their given answer is correct). Hence, self-rated experience and confidence are used as selector or control variables throughout empirical software engineering research and software engineering education. In this paper, we analyze data from several student experiments conducted in the past years to investigate whether self-rated experience and confidence are also good predictors for students’ performance in model comprehension tasks. Our results show that while students can somewhat assess the correctness of a particular answer to one concrete question regarding a conceptual model (i.e., their confidence), their overall self-rated experience does not correlate with their actual performance. Hence, the use of the commonly used measurement of self-rated experience as a selector or control variable must be considered unreliable for model comprehension tasks.



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