student skills has itsdrawback.This paper addresses a back-and-forth based pedagogy integrated with the student-centeredlearning for engineering and computer science student curriculum enhancement in ComputerArchitecture course. The objective of this Computer Architecture course offered for electricalengineering, computer engineering, software engineering and computer science students is tocultivate an understanding of modern computing technology through an in-depth study andlearning of the interface between hardware and software. This paper describes a new coursecurriculum development that dedicates to enhancing the quality of student learning by such anintegrated learning pedagogy. In the back-and-forth based learning, course materials
Paper ID #26116An Approach to Integrating Learning and Engagement Strategies (LESs) intoCS Class ActivitiesDr. Peter J. Clarke, Florida International University Peter J. Clarke received his B.Sc. degree in Computer Science and Mathematics from the University of the West Indies (Cave Hill) in 1987, M.S. degree from SUNY Binghamton University in 1996 and Ph.D. in Computer Science from Clemson University in 2003. His research interests are in the areas of software testing, software metrics, model-driven software development, domain-specific modeling languages, and computer science education. He is currently an associate
Paper ID #26981Science and Engineering Courses, Theory and Practice; An ExampleDr. S. ”Hossein” Mousavinezhad P.E., Idaho State University Dr. Mousavinezhad was the principal investigator of the National Science Foundation’s research grant, National Wireless Research Collaboration Symposium 2014; he has published a book (with Dr. Hu of University of North Dakota) on mobile computing in 2013. Professor Mousavinezhad is an active mem- ber of IEEE and ASEE having chaired sessions in national and regional conferences. He has been an ABET Program Evaluator for Electrical Engineering and Computer Engineering as well as
feedback to make updates.References[1]. Sanati-Mehrizy, Reza, Kailee Parkinson, and Afsaneh Minaie. "Integration of data miningcourse in computer science curriculum." Journal of Computing Sciences in Colleges 34.2 (2018):87-98[2]. Romero, Cristobal, and Sebastian Ventura. "Data mining in education." WileyInterdisciplinary Reviews: Data Mining and Knowledge Discovery 3.1 (2013): 12-27.[3]. Chakrabarti, Soumen, et al. "Data mining curriculum: A proposal (Version 1.0)." IntensiveWorking Group of ACM SIGKDD Curriculum Committee 140 (2006).[4]. Anderson, Paul, et al. "An undergraduate degree in data science: curriculum and a decade ofimplementation experience." Proceedings of the 45th ACM technical symposium on Computerscience education. ACM, 2014.[5
software talent training system that is supported byuniversities, governments and enterprises for industrial and practical application needs. The deep convergence of engineering and computing. With the advancement ofscience and technology and the continuous development of the Internet, engineering andcomputing have become an integral whole. It is an inevitable trend to solve engineeringproblems more efficiently and accurately by using computing knowledge and skills. Accelerated integration of hardware and software. The rapid development of artificialintelligence, robotics and other industrial fields put forward requirements to the in-depthintegration of hardware and software. These fields require the use of the knowledge and skillsof diversified
of student feedbackregarding the level of their interest in programming before and after robotic activities, thechallenges of programming a robot, and their overall rating of integrating robotic activities inprogramming classes are presented and discussed.IntroductionIntroductory computer programming is a core subject in the curriculum of computer sciencemajor. The subject is frequently taught in three different courses; namely, CS 0, CS 1, and CS 2.The topics covered in CS 0 are often related to various fundamental concepts in computing andcomputer algorithms. Many computer science programs place a particular emphasis on computeralgorithm in CS 0 to familiarize students with programming logic. In CS 1, students learn towrite computer
-WIE. She is also on the leadership team of the Kentucky Girls STEM collaborative network. c American Society for Engineering Education, 2019 USING A DATA SCIENCE PIPELINE FOR COURSE DATA: A CASE STUDY ANALYZING HETEROGENEOUS STUDENT DATA IN TWO FLIPPED CLASSESAbstractThis study presents a data science methodology to integrate and explore disparate student datafrom an engineering-mathematics course. Our methodology is based on exploratory data miningand visualization for analyzing and visualizing raw student data from multiple data sources. Theexploratory analysis serves two purposes, 1) it supports the instructor's desire to gain insightsinto the implementation of a flipped
otherinstitutions.During these group meetings, and with the consent of all the participants, notes were taken by oneof the researchers, which were later rewritten into summaries and conclusions, that after beingvalidated by all the participants, became formal records kept by the project team.Collecting Internal Data (Step 2)The collection of the necessary data to produce the report was not an easy task. The main reasonsfor these difficulties were related either to bureaucracy or to the non-integration of informationsystems.However, all these problems were minimized by the support of all the working group. Eachmember of this working group has been selected taking into account either his/her position insidethe University, his/ her recognition in the scientific
research. Possible research questions might include:RQ1. What are core computational thinking skills in the context of engineering?RQ2. How to integrate computing in engineering curriculum so as to help engineeringstudents learn computational thinking skills?RQ3. How do engineering students learn computational thinking skills through theeffective engagement in instructional activities?RQ4. What should we endeavor to promote computational thinking for non-CSengineering majors?II. Computational Thinking in Engineering1. Computational Thinking (CT)Computing is an innate capacity of human beings. The term Computational Thinking(CT) has been used in the educational context for quite a long time (Dijkstra, 1976).But the concept has become popular in
,light sensors and LED dot matrix screens to easily realize face recognition, speechrecognition and so on. But there are different kinds of such systems with less systematic de-sign for school students and insufficient well-designed curriculum systems, which make it aheadache for schools to pick. Therefore, it is imperative to develop a convenient and practicalAI teaching systemsto carry out AI education in primary and secondary schools. To this end, this paper develops an AI teaching system for primary and secondary studentsunder iSTREAM (intelligence for Sciences, Technology, Robotics, Engineering, Arts, andManagement) Educational structure, where parallel intelligence theory and ACP framework[3]-[7] are applied. In this system, typical AI
Paper ID #27115Using An Engineering Analysis Tool for Department AdministrationDr. Hugh Jack P.E., Western Carolina University Dr. Jack is the Cass Ballenger Distinguished Professor of Engineering and Department Head of the School of Engineering and Technology within Western Carolina University. His interests include robotics, automation, and product design. c American Society for Engineering Education, 2019Using An Engineering Analysis Tool for Department AdministrationAbstractThe paper describes a basic application created using Matlab to assist in academic scheduling oftechnical programs. The work
is essentialfor CT to be included as part of the K-12 curriculum. Furthermore, being able to employ a web-based tool that is a repository of peer reviewed questions that could be used to assess CT skills instudents should enhance the effectiveness of any curriculum incorporating CT [4]. Literatureshows that a number of solutions have been developed but lack standardization, require priorprogramming knowledge, or are too lengthy [5] [6].The tool described in this paper was designed to give users the ability to search for questionsbased on specific attributes. The questions can be rated by experts across the world for eachattribute of CT. The aggregate rating is available to users for each question.TECHFIT, an initiative to introduce and
, electric circuits, signals and systems, engineering economics, electromagnetics, and integrating the entrepreneurial mindset with an engineering mindset in core engineering courses. He received the Professor Henry Horldt Outstanding Teaching Award in 2015.Dr. J. Blake Hylton, Ohio Northern University Dr. Hylton is an Assistant Professor of Mechanical Engineering and Coordinator of the First-Year Engi- neering experience for the T.J. Smull College of Engineering at Ohio Northern University. He previously completed his graduate studies in Mechanical Engineering at Purdue University, where he conducted re- search in both the School of Mechanical Engineering and the School of Engineering Education. Prior to Purdue, he
temperature,light, and vibration.Educational excellence requires exposing students to the current edge of research. To ensure thatstudent projects are along the same trajectory that the industry is moving, educators mustcontinually introduce emerging techniques, practices, and applications into the curriculum. Thefield of wireless sensor networks is growing rapidly, and there is increasing interest in providingundergraduate students with a foundation in the area. It is crucial that the emerging field ofwireless sensor networks be integrated into the undergraduate computer science and engineeringcurricula. This paper presents the details of two WSN projects that our undergraduate computerengineering students have done in their senior capstone
mental models andconnecting the model to prior knowledge. They posit that the ability to extract key ideas fromnew material and integrate it into existing mental models leads to development of mastery overcomplex content.In the context of an undergraduate course on computer networking, topics such as configuring,securing, troubleshooting, and managing routing across subnetworks in the computer networkingarea require the student to develop a practical hands-on understanding of network models,protocols, hardware, cabling, subnetting, routing and switching. This encompasses a large set oftheoretical and practical competencies. While there are several resources available for learningabout these topics, according to [3, p. 9] commenting on the
security problems, balancing business concerns, technical issues and security. ▪ Effectively communicate technical information verbally, in writing, and in presentations. ▪ Use appropriate resources to stay abreast of the latest industry tools and techniques analyzing the impact on existing systems and applying to future situations. ▪ Explain the concepts of confidentiality, availability and integrity in Information Assurance, including physical, software, devices, policies and people. Analyze these factors in an existing system and design implementations.These concentration outcomes enable CAC of ABET learning outcomes for computer science andcybersecurity. Some of the practices that are used in these courses
at Reynolds Community College in Richmond, Virginia in 2009 and moved to VCU in August 2016. Debra has served on the advisory board for Lighthouse for Computer Science (LH4CS). The goal of the Lighthouse project is to improve computer science diversity through faculty professional development. In addition, she is a member of the Advisory Council for the Deep Run High School’s Center for Informa- tion Technology in Glen Allen, Virginia, where she provides program support and assists in curriculum development for their technology-based preparatory program for future computer scientists.Dr. Mandayam Thirunarayanan, Florida International University Mandayam Osuri Thirunarayanan is an associate professor in the School of
experience andprepare them for work. Like many engineering programs, students at Utah Valley University(UVU) complete their requirements for graduation with a semester long capstone design projectcourse. The intention of this course is to apply competencies gained during their first three yearstoward the solution of an embedded system design problem.Educational excellence requires exposing students to the current edge of research. To ensure thatstudent projects are along the same trajectory that the industry is moving, educators continuallyintroduce emerging techniques, practices, and applications into the curriculum. Advances inwireless sensors have opened new opportunities in healthcare systems. Sensor-based technologyhas invaded medical devices
and Tagg’s learning paradigmarticle provides us with a valuable insight about the kind of change that is urgently needed inUniversity Higher Education (Barr & Tagg 1995). The author has previously utilized these ideasin several of his ASEE publications and presentations (Narayanan, 2007 & 2009).Assessment Scholars agree that Assessment is a process in which rich, usable, credible feedback froman act of teaching or curriculum comes to be reflected upon by an academic community, andthen is acted on by that community, a department or college, within its commitment to getsmarter and better at what it does (Marchese, 1997, page 93). The National Research Councilsays that High-quality Mathematics Assessment must focus on the