33,315 research outputs found

    Emerging cad and bim trends in the aec education: An analysis from students\u27 perspective

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    As the construction industry is moving towards collaborative design and construction practices globally, training the architecture, engineering, and construction (AEC) students professionally related to CAD and BIM became a necessity rather than an option. The advancement in the industry has led to collaborative modelling environments, such as building information modelling (BIM), as an alternative to computer-aided design (CAD) drafting. Educators have shown interest in integrating BIM into the AEC curriculum, where teaching CAD and BIM simultaneously became a challenge due to the differences of two systems. One of the major challenges was to find the appropriate teaching techniques, as educators were unaware of the AEC students’ learning path in CAD and BIM. In order to make sure students learn and benefit from both CAD and BIM, the learning path should be revealed from students’ perspective. This paper summarizes the background and differences of CAD and BIM education, and how the transition from CAD to BIM can be achieved for collaborative working practices. The analysis was performed on freshman and junior level courses to learn the perception of students about CAD and BIM education. A dual-track survey was used to collect responses from AEC students in four consecutive years. The results showed that students prefer BIM to CAD in terms of the friendliness of the user-interface, help functions, and self-detection of mistakes. The survey also revealed that most of the students believed in the need for a BIM specialty course with Construction Management (CM), Structure, and Mechanical-Electrical-Plumbing (MEP) areas. The benefits and challenges of both CAD and BIM-based software from students’ perspectives helps to improve the learning outcomes of CAD/BIM courses to better help students in their learning process, and works as a guideline for educators on how to design and teach CAD/BIM courses simultaneously by considering the learning process and perspectives of students. © 2018 The autho

    Educating the educators: Incorporating bioinformatics into biological science education in Malaysia

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    Bioinformatics can be defined as a fusion of computational and biological sciences. The urgency to process and analyse the deluge of data created by proteomics and genomics studies has caused bioinformatics to gain prominence and importance. However, its multidisciplinary nature has created a unique demand for specialist trained in both biology and computing. In this review, we described the components that constitute the bioinformatics field and distinctive education criteria that are required to produce individuals with bioinformatics training. This paper will also provide an introduction and overview of bioinformatics in Malaysia. The existing bioinformatics scenario in Malaysia was surveyed to gauge its advancement and to plan for future bioinformatics education strategies. For comparison, we surveyed methods and strategies used in education by other countries so that lessons can be learnt to further improve the implementation of bioinformatics in Malaysia. It is believed that accurate and sufficient steerage from the academia and industry will enable Malaysia to produce quality bioinformaticians in the future

    Business Process Management Education in Academia: Status, challenges, and Recommendations

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    In response to the growing proliferation of Business Process Management (BPM) in industry and the demand this creates for BPM expertise, universities across the globe are at various stages of incorporating knowledge and skills in their teaching offerings. However, there are still only a handful of institutions that offer specialized education in BPM in a systematic and in-depth manner. This article is based on a global educators’ panel discussion held at the 2009 European Conference on Information Systems in Verona, Italy. The article presents the BPM programs of five universities from Australia, Europe, Africa, and North America, describing the BPM content covered, program and course structures, and challenges and lessons learned. The article also provides a comparative content analysis of BPM education programs illustrating a heterogeneous view of BPM. The examples presented demonstrate how different courses and programs can be developed to meet the educational goals of a university department, program, or school. This article contributes insights on how best to continuously sustain and reshape BPM education to ensure it remains dynamic, responsive, and sustainable in light of the evolving and ever-changing marketplace demands for BPM expertise

    Closing the gap between software engineering education and industrial needs

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    According to different reports, many recent software engineering graduates often face difficulties when beginning their professional careers, due to misalignment of the skills learnt in their university education with what is needed in industry. To address that need, many studies have been conducted to align software engineering education with industry needs. To synthesize that body of knowledge, we present in this paper a systematic literature review (SLR) which summarizes the findings of 33 studies in this area. By doing a meta-analysis of all those studies and using data from 12 countries and over 4,000 data points, this study will enable educators and hiring managers to adapt their education / hiring efforts to best prepare the software engineering workforce

    Pervasive Parallel And Distributed Computing In A Liberal Arts College Curriculum

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    We present a model for incorporating parallel and distributed computing (PDC) throughout an undergraduate CS curriculum. Our curriculum is designed to introduce students early to parallel and distributed computing topics and to expose students to these topics repeatedly in the context of a wide variety of CS courses. The key to our approach is the development of a required intermediate-level course that serves as a introduction to computer systems and parallel computing. It serves as a requirement for every CS major and minor and is a prerequisite to upper-level courses that expand on parallel and distributed computing topics in different contexts. With the addition of this new course, we are able to easily make room in upper-level courses to add and expand parallel and distributed computing topics. The goal of our curricular design is to ensure that every graduating CS major has exposure to parallel and distributed computing, with both a breadth and depth of coverage. Our curriculum is particularly designed for the constraints of a small liberal arts college, however, much of its ideas and its design are applicable to any undergraduate CS curriculum

    Multinational perspectives on information technology from academia and industry

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    As the term \u27information technology\u27 has many meanings for various stakeholders and continues to evolve, this work presents a comprehensive approach for developing curriculum guidelines for rigorous, high quality, bachelor\u27s degree programs in information technology (IT) to prepare successful graduates for a future global technological society. The aim is to address three research questions in the context of IT concerning (1) the educational frameworks relevant for academics and students of IT, (2) the pathways into IT programs, and (3) graduates\u27 preparation for meeting future technologies. The analysis of current trends comes from survey data of IT faculty members and professional IT industry leaders. With these analyses, the IT Model Curricula of CC2005, IT2008, IT2017, extensive literature review, and the multinational insights of the authors into the status of IT, this paper presents a comprehensive overview and discussion of future directions of global IT education toward 2025

    Curriculum Guidelines for Undergraduate Programs in Data Science

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    The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program met for the purpose of composing guidelines for undergraduate programs in Data Science. The group consisted of 25 undergraduate faculty from a variety of institutions in the U.S., primarily from the disciplines of mathematics, statistics and computer science. These guidelines are meant to provide some structure for institutions planning for or revising a major in Data Science
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