Paper ID #36831Using Observational Learning Theory to Interpret HowEngineering and Computer Science Faculty Learn to MentorPostdoctoral ScholarsMatthew Bahnson Postdoc in Engineering Education at Penn State with Catherine Berdanier.Catherine G.p. Berdanier Catherine G.P. Berdanier is an Assistant Professor of Mechanical Engineering at Pennsylvania State University and is the Director of the online Master of Science in Mechanical Engineering Program at Penn State. Her research interests include graduate-and postdoctoral-level engineering education; attrition and persistence mechanisms, metrics, policy, and
Paper ID #21015Enhancing Freshman Learning Experience in Computer Aided Drafting andDesign (CADD) Through Applied Learning Experiences: Connecting the DotsDr. Gonca Altuger-Genc, State University of New York, Farmingdale Dr. Gonca Altuger-Genc is an Assistant Professor at State University of New York - Farmingdale State College in the Mechanical Engineering Technology Department. She is serving as the K-12 STEM Out- reach Research and Training Coordinator at Renewable Energy and Sustainability Center at Farmingdale State College. Her research interests are engineering education, self-directed lifelong learning, virtual
Paper ID #22817Evaluating Learning Engagement Strategies in a Cyber Learning Environ-ment during Introductory Computer Programming Courses – an EmpiricalInvestigationMrs. Mourya Reddy Narasareddygari I am Ph.D student at North Dakota State University. My research work is to see how different Learning strategies affect the student learning.Dr. Gursimran Singh Walia Gursimran S. Walia is an associate professor of Computer Science at North Dakota State University. His main research interests include empirical software engineering, software engineering education, human factors in software engineering, and software quality. He is a
AC 2009-10: DISTANCE LEARNING AND COGNITIVE LOAD THEORY TOIMPROVE TRADITIONAL AND NON-TRADITIONAL STUDENT LEARNING OFCOMPUTER PROGRAMMING FOR MECHANICAL ENGINEERS:QUANTITATIVE ASSESSMENTThomas Impelluso, San Diego State University Dr. Impelluso received his BA in Liberal Arts from Columbia University. This was followed by two MS degrees in Civil Engineering and Biomechanics, also from Columbia. He received his doctorate in Computational Mechanics from the University of California, San Diego. Following this, he worked for three years in the software industry, writing code for seismic data acquisition, visualization, and analysis. He then commenced post-doctoral studies at UCSD, wherein he secured
Paper ID #22813Using Gamification and Cyber Learning Environment to Improve Students’Learning in an Introductory Computer Programming Course: An EmpiricalCase StudyMrs. Mourya Reddy Narasareddy Gari, North Dakota State University I am Ph.D student at North Dakota State University. My research work is to see how different Learning strategies affect the student learning.Dr. Gursimran Singh Walia, North Dakota State University Gursimran S. Walia is an associate professor of Computer Science at North Dakota State University. His main research interests include empirical software engineering, software engineering education, human
Computer Simulation and a Realistic Simulator in Conjunction with the New Educational Style How People Learn (HPL) to Improve Learning Achievements Tilo Winkler, Ph.D., Rudolph Mitchell, Ed.D., and Jose G. Venegas, Ph.D. Harvard Medical School / Harvard-MIT Division of Health Sciences & Technology (HST) / Massachusetts Institute of Technology (MIT)INTRODUCTIONTraditional lectures are well suited to teaching of systematic content but lack active hands-onexperience. The NSF publication “How People Learn” (HPL) suggests that challenging studentswith realistic problems and high levels of freedom for problem solving motivates students andsupports learning. In the case
Paper ID #7137Work-in-Progress: The Impact of MatLab Marina - A Virtual Learning En-vironment on Student Learning in a Computing for Engineers CourseDr. Priya T Goeser, Armstrong Atlantic State University Dr. Priya T. Goeser is an associate professor of Engineering Studies at Armstrong Atlantic State Univer- sity in Savannah. She received her Ph.D. in Mechanical Engineering from the University of Delaware. Her current research interests are structural health monitoring, functionally graded materials and innovative teaching methods in engineering education.Dr. Wayne Johnson, Armstrong Atlantic State UniversityDr. Shonda L
tools to quickly generatedesigns, an FPGA platform provides the necessary flexibility to quickly produce a workingsystem. Students are able to easily modify and adapt their designs for a specific application. Wedemonstrate that multiprocessor systems can be developed, implemented and studied byundergraduate students due to the availability and accessibility of design tools and FPGAdevelopment boards. Further, these systems enhance the learning of multiprocessors and aptlycompliment advanced computer architecture courses covering topics to include shared memory,synchronization, sequential consistency, and memory coherency.1. IntroductionThe last few years have seen a dramatic increase in the capabilities and performance of softprocessor cores in
Page 22.437.12each student at the beginning and end of the course, significant improvement in student learning(and understanding of microcontroller-based concepts and their integration into embeddedsystems) was noted. Integrating PSoC devices into microcontroller coursework appears to be ofgreat benefit in electrical and computer engineering education.References[1] Mar, M., Sullam, B., and Blom, E., “An Architecture for a Configurable Mixed-Signal Device”, IEEE Journal ofSolid-State Circuits, Vol. 38, pp. 565-568, March 2003.[2] Fang, W., Kedar, S., Owen, S., Wei, G., and Brooks, D., “System-on-Chip Architecture for Intelligent SensorNetworks,” Proceedings of the 2006 International Conference on Intelligent Information Hiding and
NSF sponsoredproject, entitled “Enhance Computer Network Curriculum using Remote Collaborative Project-based Learning”. The focus of the project is to explore Collaborative Project-based Learning(CPBL) as a pedagogical approach to address the learning issues of under-prepared minoritystudents, and seek effective implementation strategy to extend the pedagogy beyond theclassroom through a remote learning structure. During the three-year project course, a newpedagogical model named as CPBL-beyond-Classroom was developed and its effectiveness hasbeen thoroughly evaluated in iterative classroom implementation. In this paper, we will analyzethis pedagogical model to illustrate how it can address the learning needs of minority students ona commuter
the necessary instructional changes to provide educational frameworks for educators of formal and informal learning environments.Edwin Garcia, Purdue University R. EDWIN GARCIA is Assistant Professor at the School of Materials Engineering at Purdue University West Lafayette. His research interest revolve around the application of theoretical and computational methods to understand the relations between material properties and microstructure. Edwin has also developed new analytical tools, algorithms, and codes for improving materials performance to better understand the relation between processing, structure, and properties of materials
and CS education efforts.Dr. Alejandra J. Magana, Purdue University at West Lafayette Alejandra J. Magana, Ph.D., is the W.C. Furnas Professor in Enterprise Excellence in the Department of Computer and Information Technology with a courtesy appointment at the School of Engineering Education at Purdue University. She holds a B.E. in Informa ©American Society for Engineering Education, 2023 Evaluating Self-paced Computational Notebooks vs. Instructor- Led Online Lectures for Introductory Computer ProgrammingAbstractTeaching a new programming language to computer science students ischallenging, time consuming, and fraught with error. Students face manychallenges while attempting to learn a new language
Paper ID #36361Full Paper: First-Year Computing Course with Multiple ComputingEnvironments - Integrating Excel, Python and MATLABDr. Sean P Brophy, Purdue University at West Lafayette (COE) Dr. Sean Brophy is a learning scientist, computer scientist and mechanical engineer with expertise in developing and research effective learning environments. His research centers on developing engineering students’ expertise to adapt to new problem solving contexts.Dr. John H Cole, Purdue University John H. Cole (S’10–M’12) received the B.S.E.E. and Ph.D. degrees in electrical engineering from Purdue University, West Lafayette, IN, USA
function of the real timephysical system from measurement data and learn the process of computer simulation modeling.The lab provides students a powerful experience to model, analyze, and test the real system withthe computer simulation. The computer simulation constantly interfaces in real time with the DCmotor.The processes of computer simulations in this laboratory are summarized in five steps. First,students collect sample data frequency and step responses of the system to realize it. Next, thedata acquisition is introduced to students. They look at the collection of data stored in thecomputer, identify the statistics, and make a proper representation of the system. After modelingthe system with the computer simulation, students utilize a
This work describes and analyzes a set of state-of-the-art artificial intelligence (AI)hardware kits created for education and research that can be used in undergraduate AI labs. AIcloud-based computing devices and solutions like the Arduino-based Tiny Machine Learning kitsor the mobile app by Edge Impulse, Raspberry Pi-based AIY Voice kits by Google, Quad-core ArmCortex-A53 and Cortex-M4F-based Google Coral Dev Boards, as well as the more powerful JetsonAGX Xavier (512-core NVIDIA Ampere architecture GPU), and Jetson AGX Orin (2048-coreNVIDIA Ampere architecture GPU) Developer kits, are compared using published characteristicsand direct experiments. The comparison criteria used are (1) ease of setup and first use, (2) learningcurve and
students will write simple programsreflective of the material that they have learned during the lectures. This approach can be im-proved by conducting the entire course in a “technology ready” classroom, where lectures and in-class exercises could be designed and delivered, in such a way, to promote an active learning en-vironment. This manner of conducting courses requires a larger investment, time and money, onthe part of the institutions and instructors, than the traditional approach. This work describes ourapproach to teaching undergraduate computer programming courses in a computer laboratory en-vironment at the Delaware County Campus of the Pennsylvania State University. Our objectiveshave been to use the computer and communication
are to work in the earn a graduate degree, work in the renewable energy industry, and promote STEM and engineering education. Page 26.717.1 c American Society for Engineering Education, 2015 Experience-Based Approach for Teaching and Learning Concepts in Digital Signal Processing Daniel Raviv and Juan Ramirez Department of Computer & Electrical Engineering and Computer Science Florida Atlantic University Boca Raton, FL 33431 Tel: (561
(documentaries,newspapers, videos), and computer-aided instruction. Certain teaching strategies are moreeffective at teaching to specific learning domains, and certain teaching strategies aremore appropriate for students who are at a higher developmental level8. Thus, facultymust choose the teaching strategy based upon the learning domain that is being addressedand the developmental level the students are at. The type of teaching strategy chosen willinfluence the administrative structure of the course (schedule, resources, credits awarded)and the organization of the curriculum. Different techniques are more appropriate if thelearning domain is cognitive vs. affective, for example. Figure 6 shows a number oftechniques that are appropriate for these
organizations, he developed an interest in psychology and Affective Computing. Currently, pursuing the Doctoral degree in Engineering Education at Utah State University with focuses in self-regulated learning in engineering design.Dr. Oenardi Lawanto, Utah State University Dr. Oenardi Lawanto is an associate professor in the Department of Engineering Education at Utah State University, USA. He received his B.S.E.E. from Iowa State University, his M.S.E.E. from the University of Dayton, and his Ph.D. from the University of Illinois at Urbana-Champaign. Before coming to Utah State, Dr. Lawanto taught and held several administrative positions at one large private university in In- donesia. He has developed and delivered
,including (1) binary numbers, (2) ASCII code, (3) Caesar Cipher, (4) looping, (5) algorithmwriting, (6) message transmission, (7) computer networking/topology, and (8) computer security.Learning Objectives for Workshop: By the end of this workshop, attendees should be able to: 1. Explain each activity and present them to students 2. Explain that binary is the language of a computer (i.e., letters, numbers, and symbols have a representation in binary) 3. Explain the purpose of encryption in modern networking to students 4. Explain the basic concept behind Public-Key Encryption to studentsBrief DescriptionChildren use electronic devices daily (especially after online learning during the pandemic) buthave little
years to promote computer science skills in the initialschool years. Nowadays, computational thinking has been widely recognized as a fundamentalskill to be used by everyone in the world by the middle of the 21st Century. Computationalthinking is also considered crucial for developing engineering habits of minds and solvingengineering problems [2]. When students work on coding, they can learn how to design acomputer program while developing their computational thinking skills [3]. Computationalthinking (CT) includes the thought processes involved in formulating problems, solvingproblems, building systems, and human behavior through the lens of computer science concepts[4]. However, little is known about how and to what extent children acquire
improving methods of assessment in engineering learning environments and supporting engineering students. ©American Society for Engineering Education, 2021 Computational Thinking frameworks used in Computational Thinking assessment in higher education. A systematized literature review.AbstractThis research paper presents a literature review of Computational Thinking (CT) frameworks andassessment practices. CT is a 21st century way of solving a problem. It refers specifically to theeffective methods when trying to solve a problem with a machine or other computational tools. Inthe past few years, CT researchers and educationists' significant movement started to look for aformal definition and composition of
.” Accessed: Mar. 26, 2024. [Online]. Available: https://dl.acm.org/doi/abs/10.1145/3610978.3640574[7] S. Dutta, T. Banerjee, N. D. Roy, and B. Chowdhury, “Development of a BCI-Based Application Using EEG to Assess Attentional Control,” in Proceedings of the Global AI Congress 2019, J. K. Mandal and S. Mukhopadhyay, Eds., in Advances in Intelligent Systems and Computing. Singapore: Springer, 2020, pp. 659–670. doi: 10.1007/978-981-15-2188- 1_52.[8] E. H. Houssein, A. Hammad, and A. A. Ali, “Human emotion recognition from EEG-based brain–computer interface using machine learning: a comprehensive review,” Neural Comput & Applic, vol. 34, no. 15, pp. 12527–12557, Aug. 2022, doi
Engineering Education Center, and Caruth Institute of Engineering Education. He specializes in Engineering, STEM, and Project Based Learning instruction. American c Society for Engineering Education, 2021 Computer Science and Computational Thinking Across the Early Elementary Curriculum (Work in Progress)In 2016 Amazon announced an extensive search to identify a home for its second headquarters,HQ2. Our city, Dallas, TX was near the top of the list for most of the competition. However,when the final choice was announced two years ago, Dallas lost to Washington, D.C. and NewYork City. According to the Dallas Mayor, who was an active member of the
provide a broad understanding of computer security issues, from high-level to low leveltopics in security, privacy, ethics and politics. The ten objectives for this course are as follows 1) To be aware of IEEE and ACM ethics codes 2) To understand the impact of social engineering on computer security. 3) To learn the basic computer security principles, terms and concepts. 4) To learn access control concepts and techniques To understand the basic principle of symmetric and asymmetric cryptography, typical Page 13.1141.3 5) applications and their strengths and weakness
Paper ID #27636Exploring Music and Technology through Code and Chords (resource ex-change)Alyssa Marie Eggersgluss, Playful Learning Lab Alyssa Eggersgluss is a K-12 Vocal Music Education Major from the University of St. Thomas. Passionate about interdisciplinary learning, she works as a part of Dr. AnnMarie Thomas’ Playful Learning Lab to create learning opportunities for students. She is currently focused on exploring different ways to engage students with sound.Rachel Farah, University of St. Thomas I am a computer engineering student at the University of Saint Thomas and am a researcher at the Playful Learning Lab
-the-shelf technology (COTS) are the dominant platform.12This increased demand for HPC systems has generated also an increasing demand for skilledpractitioners with the required knowledge and experience to build and utilize HPC systems forproblem solving.The design, construction, and operation of high-performance computing and supercomputingsystems have traditionally been “on the edge” of the field of computer science and informationtechnology; thus limited training and education resources have been available for studentsseeking to learn new skills. The result is a gap that has emerged between supply and demand,one in which the lack of skilled practitioners and available training in the development and use ofHPC systems have become serious
embedded system design, hardware-software interfacing, digital communication, networking, image processing, and biometrics, C++, Python, PHP and Java languages. He has a keen interest in pedagogy and instruction de- livery methods related to distance learning. He has a deep commitment to social justice and in achieving economic and educational equity.Dr. Jai P. Agrawal, Purdue University Northwest Jai P. Agrawal is a professor in electrical and computer engineering technology at Purdue University Northwest. He received his Ph.D. in electrical engineering from University of Illinois, Chicago, in 1991, dissertation in power electronics. He also received M.S. and B.S. degrees in electrical engineering from Indian
Alliance(MESA) to further connect the campus to the community through family engagement and bybuilding and sustaining the connection between students’ families and faculty and staff in thecomputer science and computer engineering departments. Through focus groups and informalinteractions with families, we gained a deeper understanding of what cultivated and sustainedtheir engagement over five years. We ran two focus groups, one in Spanish and one in English;family members self-selected into the focus group based on language affinity. Through thesefocus groups, as well as through informal interactions (at both on and off campus activities,including over meals at local restaurants), we learned about parents’/caregivers’ relationshipswith their
Behavioral Biometrics for Human Identification: Intelligent Applications. Dr. Villani has been actively seeking funding and has been awarded funding both internally and externally to address the gender disparity in the Computing Programs at FSC and is Co-Faculty Advisor to the Supporting Women in Computing Club. Dr. Villani has presented and published in peer reviewed journals regarding initiatives and outcomes addressing the gender disparity in computing disciplines including co-moderated a Birds of a Feather Session at the virtual NY Celebration of Women in Computing at the Spring 2021 Conference entitled: Learning and Sharing from the Decade long Journey of Success and Failures on Women in Computing Initiatives