13th IEEE Integrated STEM Education Conference — 9 AM - 5 PM EDT, Saturday, March 11 Onsite Venue - Kossiakoff Center - 11100 Johns Hopkins Road, Laurel, Maryland
Full Papers
Session Full-01
Track 1 — Full Papers 1
Conference
2:50 PM
—
4:50 PM EST
Local
Mar 11 Sat, 2:50 PM
—
4:50 PM EST
Location
Room Number: K-3 (Downstairs, First Floor)
MATLAB Image Processing for Plasma-Wound Interaction to Accelerate Healing and Sterilization
Akhil Agarwal (IntelliScience Institute & Research Intern at San Jose State University, USA); Aahan R Patel (IntelliScience Institute, USA)
1
Plasma healing has been found to be a very powerful technique to accelerate wound healing. Through this research conducted at San Jose State University, this process was automated in an attempt to make plasma healing more efficient in material usage and cost while allowing widespread usage by reducing the need for specialists. The plasma torch was held by a 2D-traversing arm system, which used two stepper motors, each attached to a set of linear slides, for movement. Motor drivers and a Raspberry Pi microcontroller were used to control the stepper motors. The Raspberry Pi was also connected to a USB Logitech camera module, which would take pictures of the wound. In this work, a pictorial version of the wound was provided to the camera to take images and process them accordingly. A MATLAB program was used to control the arm system. The MATLAB program wirelessly received the image from the Raspberry Pi and detected the wound by scanning for the most-red area of the image. It identified the most efficient way for the arm to move by placing the tightest possible bounding box around the wound. The MATLAB program then moved the arm around this bounding box, pausing at approximately 1.5 cm intervals for around 30 seconds generally required for wound exposure. The hardware and software systems are discussed further in the following sections.
Speaker
Speaker biography is not available.
Flexible Submission Policy and Its Impact on Student Learning
Wenbing Zhao and Xiongyi Liu (Cleveland State University, USA)
0
In STEM higher education, the practice of setting hard deadlines for assignments without the possibility of late submission or with harsh penalties for late submissions is mainstream and rarely challenged. In this paper, we present arguments in favor of implementing a flexible late submission policy, and share our experiences in implementing a no-late-submission-penalty policy in two courses. Students are overwhelmingly supportive of the policy. In addition to presenting the anecdotal evidence, we analyze theoretical foundation for the submission policy. It appears that the traditional hard deadline submission policy is influenced by behaviorism in which the learner is modeled as a passive entity that is molded by operand conditioning. However, newer learning theories, including cognitivism, constructivism, and humanism, are treating the learner as an active agent that is influenced not just by external stimulus and conditioning, but also by the individual's affection, motivation, culture, as well as past knowledge and experiences. As such, assignment submission policy must be designed accordingly so that it is conducive for learning.
Speaker
Speaker biography is not available.
Design and Implementation of a Time Management Self-Help Mobile App for College Students
Wenbing Zhao (Cleveland State University, USA); Hanna Harb (Garfield Heights High School, USA)
1
College students, particularly students in the STEM disciplines, are facing huge challenges in time management, juggling between classes, part-time or full-time jobs, extracurricular activities, and social activities. Evidence has shown that academic success in college students is directly associated with their time management skills. Furthermore, a significant fraction of students suffer from procrastination issues. Unfortunately, such students are not receiving adequate help despite the fact that virtually every college in the US provides a suite of student-centered services such as counseling services. In this paper, we review studies related to academic procrastination, identify primary factors associated with academic procrastination, and major interventions towards reducing academic procrastination. Furthermore, we describe the design and implementation of a time management self-help mobile app to help college students manage their time and overcome issues that lead to procrastination. The self-help app facilitates a student to set goals on time allocation, organize tasks, enter progress made, review history of performance, and get help (such as available student services) via a local chatbot. The app incorporates several well-known mechanisms for reducing academic procrastination.
Speaker
Speaker biography is not available.
Integrating Multi-Professional Principles and Practices into the Medical Education Curriculum
Milan Toma, Faiz Syed and Lise McCoy (New York Institute of Technology College of Osteopathic Medicine, USA)
1
Purpose: Due to the advances in healthcare technology, it has become increasingly obvious that engineering is becoming more integral to the process of providing care to people. For engineering and medical students to be able to take electives related to healthcare technology within an interdisciplinary context, the engineering and medical programs must work closely together. Through the implementation of these innovative projects, the students are exposed to new ways of co-designing and interacting with each other. Methods: Medical students were required to collaborate with engineers, architects, and artists as part of a program that was offered to them to create new assistive medical devices. It was asked of participants during the ideation phase of their project to complete a questionnaire in order to assess compassion satisfaction and burnout metrics. Results: On average, the combined compassion satisfaction score was high for both medical students (42/50) and non-medical students (43/50). In terms of burnout, 77% of medical students and 81% of non-medical students reported low burnout; the average burnout score for medical students was 19/50, and for non-medical students 17/50. Only one statement produced a statistically significant difference between groups. For the statement, "I am a caring person", only 31% of medical students self-described as being a very caring person ‘very often' as opposed to 62% of non-medical students. Conclusion: A critical component of this innovative curriculum was determining whether students had a high degree of compassion satisfaction and if they were at risk of burnout as a result of it. The service-learning experience through prototyping allowed students to bridge the gap between science and practice in health care, which in turn contributed to student development, pride, and well-being.
Speaker
Speaker biography is not available.
Developing a Lab Experiment for Demonstrating the Performance of an Off-Grid Solar Array
Bryson Castaneda (BCIT), Paul Cornean (BCIT), Nhat Hoang Dau (BCIT), and Pooya Taheri (BCIT & SFU, Canada)
1
The proliferation of photovoltaic (PV) systems in the last decade demands skilled technologists familiar with the theoretical and practical aspects of solar system technology. Hands-on experiments play a key role in the development of students' creativity and the instinctive understanding of concepts. In this paper, we explain the process of developing a lab manual to introduce diploma-level undergraduate students to power-electronics aspects of solar systems. Experimental test setup and different equipment used for data acquisition purposes are detailed first. We then briefly explain theoretical concepts such as solar panel modeling, maximum power point tracking (MPPT), total harmonic distortion (THD), pulse width modulation (PWM), and filter design. MATLAB/SIMULINK is used as the simulation platform for virtual experiments due to its user friendliness and capabilities. Hands-on and simulation-based experiments and the results are explained and analyzed. This steppingstone project is aimed to solidify students' learning of practical aspects of solar energy harvesting through experimental learning.
Speaker
Speaker biography is not available.
A Sustainable Development Goal for a Campus: LED Vertical Illumination for a Classroom
Enrique C Pajardo, Antony Kinyua and Dong H Kang (Morgan State University, USA)
0
Despite the vast research in Sustainable Development (SD), very little is known about providing "sustainable Light Emitting Diode (LED) lighting" for a campus. The overall image that emerges from advertisements is upgrading to LED's will last a long time. This is a simplistic view of understanding a Sustainable Development Goal (SDG). This misunderstanding is the motivation for this study is to help new graduate students build knowledge about sustainable lighting. Establishing sustainable LED lighting can increase students' well-being, which is a gap in most past research [14]. The primary objective of this study was proven after evaluating the lighting in two classrooms for; (1) economic growth, (2) environmental benefits, (3) and improving students' well-being. A LEED-certified classroom met all objectives with the lighting levels, mood, and reduced cost. Whereas the non-LEED-certified classroom did not meet any objectives or compliance. The larger implications of the findings are that sustainable LED lighting can benefit any size campus.
Speaker
Speaker biography is not available.
The Impact of Credits on Student Performance: A Case Study of Sri Lanka
Jagodage Dulangi Kanchana Rathnapala (University of Moratuwa & NONE, Sri Lanka); Amal Perera (University of Moratuwa, Sri Lanka); Vishaka Nanayakkara (Chalmers University of Technology, Sweden); Gayashan Amarasinghe (University of Moratuwa, Sri Lanka)
0
A proper curriculum is needed to enable students to have a healthy academic life either in school, college, or university, which helps to balance their academic work and their extracurricular activities. This research was conducted using data of university students from the department of computer science to study the influence of credit on semester-wise student academic performance. After performing feature engineering on the data, different machine learning algorithms such as decision trees, random forest, and support vector machines were applied to the data, with the inclusion and exclusion of credit load per semester, to identify the effect of the credits on the students' academic performance (semester end Grade Point Average). From this study, the relationship between credit and semester-wise student performance is found to be a weak correlation. This may be due to the fact that students get adapted to the heavy academic load from schooling. This study needs to be conducted using school students' data. It is further recommended to balance out the academic work load so that there is little or no difference in the number of credits registered per semester, so students can get sufficient time to engage in other activities.
Speaker
Speaker biography is not available.
Development and Implementation of Natural Language Processing Communication and Virtual Reality-Based Technologies in Educational Applications
Saurabh Sanjay Saindhane (Indian Institute of Information Technology, Tiruchirappalli (IIITT), India); Venkanna U (Teacher, India); Debanjan Das (IIIT Naya Raipur, India)
15
Introduction of Automated speech recognition (ASR) and Virtual Reality and its interpretation for children of underprivileged backgrounds and rural India, in a way as affordable and accessible as possible. Response Learning App is a research project . This is an artificial educational system for presenting students with a real-life situation that they have to understand and answer using acquired theoretical information, for making the students enhance their capacities that until that moment were underdeveloped or nonexistent. Today's education systems across the globe are accelerating in technological advancement. A supportable and strategic academic platform for children of rural India is necessary with an assessment of the study by the latest cybernetics and scientific approach for the adoption of Automatic Speech Recognition (ASR), Natural language processing (NLP) and 3D technology in an effective and affordable way. Conjecture related to the use of technology, engrossment, educational attainment and its effectiveness on the users were examined through various interrogations. Formulate a variety of teaching methods, design and implement interactive artificial intelligence, and verbally communicate with students as if they were someone else. A survey was conducted in which respondents (N = 47 participants) expressed their views on artificial intelligence technologies and their adoption in education. This paper concludes by highlighting the possibilities of using virtual technologies and natural language processing, and how this project increased student's degree of attention, engagement, and how captivating environments can be for encouraging students to become high-spirited pupils.
Speaker
Speaker biography is not available.
Session Chair
Barin Nag (Towson University), Ashutosh Dutta (JHU/APL)
Session Full-02
Track 2 — Full Papers 2
Conference
2:50 PM
—
4:50 PM EST
Local
Mar 11 Sat, 2:50 PM
—
4:50 PM EST
Location
Room Number: K-4 (Downstairs, First Floor)
Successful Model for a Course-based Undergraduate Research Experience (CURE) in Mathematics and STEM during the First Two Years of College
Guillermo Alvarez Pardo (Cuesta College, San Luis Obispo, California, USA)
0
The importance of undergraduate research experiences (UREs) has been increasingly defended and documented in the last decades. As a consequence of its popularity, internships, summer camps and other types of UREs have become more competitive and harder for students to access, and, in the last years, colleges, universities and educative centers have developed an interest in offering their own opportunities in the form of Course-based Undergraduate Research Experiences (CUREs). This paper introduces a model for an accessible, low-cost, high-efficiency CURE in Mathematics with the involvement of collateral STEM disciplines like Statistics, Data Science or Business. The model is a work-in-progress that has been offered and tested for two academic years (2021-22 and 2022-23), with the course delivered in the fall and its fruits coming throughout the whole year. This paper presents a justification of the CURE and its design and a description of the methodology used, the challenges surpassed and the results obtained during those first two editions or iterations, including sample deliverables, publications, exposure in national conferences and other success data. It emphasizes the key aspects that make the course simple and exportable, so the reader acquires the know-how and can easily instrument the course at their own institution. The CURE was developed at a two-year college as part of a larger NSF-awarded project, and has established connections with four-year institutions, high schools, national and international professional associations, journals and conferences, employers, private investors and government agencies.
Speaker
Speaker biography is not available.
Active Learning on Neural Networks through Interactive Generation of Digit Patterns and Visual Representation
Dong Jeong (University of the District of Columbia, USA); Jin-Hee Cho (Virginia Tech, USA); Feng Chen (University of Texas at Dallas, USA); Audun Jøsang (University of Oslo, Norway); Soo-Yeon Ji (Bowie State University, USA)
0
Artificial neural networks (ANNs) have been broadly utilized to analyze various data and solve different domain problems. However, neural networks (NNs) have been considered a black box operation for years because their underlying computation and meaning are hidden. Due to this nature, users often face difficulties in interpreting the underlying mechanism of the NNs and the benefits of using them. In this paper, to improve users' learning and understanding of NNs, an interactive learning system is designed to create digit patterns and recognize them in real time. To help users clearly understand the visual differences of digit patterns (i.e., 0 ~ 9) and their results with an NN, integrating visualization is considered to present all digit patterns in a two-dimensional display space with supporting multiple user interactions. An evaluation with multiple datasets is conducted to determine its usability for active learning. In addition, informal user testing is managed during a summer workshop by asking students to use the system.
Speaker
Speaker biography is not available.
Review of Integrated STEM+C e-Learning Platforms to Support Underrepresented Students
Ella Neading, Teresa M. Ober and Paul R Brenner (University of Notre Dame, USA)
0
Despite initiatives to promote broader participation within the workforce, the science, technology, engineering, mathematics, and computer science (STEM+C) fields still lack diversity. The underrepresentation of historically marginalized students in STEM+C fields may be caused by several factors. Such factors may include but are not limited to, a lack of exposure in their early childhood education, lack of confidence, and gender stereotypes that are perpetuated by society. While a systemic issue, the availability of e-learning platforms has the potential to provide low-stakes opportunities for historically marginalized students in STEM+C to explore subject areas and develop an interest. There is also the added benefit that such platforms are highly scalable. This paper offers a review and synthesis of the effectiveness of current e-learning platforms for promoting historically marginalized students' participation in STEM+C focusing specifically on female students' participation and e-learning platforms that teach STEM+C content. The benefits of such platforms, along with the limitations (e.g., cost, learner motivation, lack of social interaction and technical skills, etc.) are taken into consideration. However, based on the findings described in this review paper, such limitations ultimately do not undermine the benefits e-learning platforms may have in supporting students' interest in pursuing STEM+C and promoting broader participation.
Speaker
Speaker biography is not available.
Examining the impact of experiment-centric pedagogy on students' critical thinking, test anxiety, and motivation while using hands-on technology through pre- and post-activity questionnaires
Frank Efe (Morgan State University, Baltimore, MD, USA.); Antony Kinyua, Ezana Negusse, Krishna. Bista, Gaulee Uttam, Oludare Owolabi, Pelumi Abiodun, Adebayo Olude, Opeyemi Adeniran, Neda Bazyar Shourabi and Chukwuemeka Duru (Morgan State University, USA)
0
This study aims to present a summary of the positive effects that Experiment-Centric Pedagogy (ECP) hands-on tools can have on students' ability to think critically, test anxiety, and motivation rate. Using survey-monkey and IBM SPSS, data was gathered, examined, and cleaned. Both remote and classroom lab experiments were used in this study. Thirty undergraduate physics students served as the subjects. The results include analyzed data, photographs, and feedback from students gathered through observation and oral defense of their reports. The study demonstrated that the introduction of the ECP hands-on device changed the learning environment, resulting in (1) an increase in the positive impact of the survey constructs of critical learning and test anxiety, (2) an enhancement of learning enthusiasm, and (3) an increase in motivation rate that enhances their academic performance. There was a significant difference in the pre- and post-test scores of critical thinking and test anxiety (p<0.05). All these observations account for the high impact of ECP on students' critical thinking, test anxiety, and motivation via hands-on devices.
Speaker
Speaker biography is not available.
A Collaborative Learning and Support System for STEM Education and Learning Analytics
Qizhi Xu and Beijia Zhang (University of Science and Technology of China, China); Jing Wang (Anhui Xiyue Educational Technology Co. Ltd., China); Xiang Liu (Educational Testing Service, USA); Mengxiao Zhu (University of Science and Technology of China, China)
0
STEM education encourages students to collaborate in learning. With the rapid progress of information technology, computer-supported collaborative learning becomes a powerful method to facilitate STEM education with promising learning outcomes. However, researchers and teachers lack an integrated CSCL system able to meet the following needs: (1) an integrated and ready-to-use instant messenger that can support a large number of users stably, (2) a secured and robust framework that allow embedding third-party learning tasks, (3) support for researchers to design research plans and for teachers to manage classes, (4) power mechanisms to capture, store and export learning process data. To address these requirements. This paper presents a powerful collaborative learning and support system (called CLASS) specifically designed to support learning, teaching, and research in collaborative learning. The CLASS system is web-based, and is compatible with third-party HTML5 applications, which can be embedded safely and smoothly into the system, communicate with the server, and interact with other interface elements. It has also integrated an instant messaging service that can support millions of users simultaneously with text, audio, and video conversations. Assessment data and learning process data are automatically recorded at the server, and can be easily exported for learning analytics research. Internationalizing functions are also employed for users with different language preferences.
Speaker
Speaker biography is not available.
Quantum Serious Games to Enhance Quantum Literacy within Computational Thinking 2.0 Framework
Apostolos Xenakis, Ilias K. Savvas, Costas Chaikalis, Maria Avramouli, Kalliopi Theodoropoulou and Maria Sabani (University of Thessaly, Greece)
0
Quantum mechanics is a revolutionary scientific field, which lies at the crossroad section of Physics, Mathematics, Computer and Computational Science. In essence, it is considered a cross - disciplinary STEM field, advancing the philosophy of Quantum Literacy (QL), which addresses the transdisciplinary nature of real world complex problems. QL addresses the challenges of learning and skills acquisition, through specific computing activities, within a highly bounded discipline and of access to the kind of powerful knowledge that should be more accessible to a wide group of learners. It is therefore important that quantum computing and quantum technologies knowledge is accessible to students and teachers who work with real problems, in a more inclusive and interactive way. In this paper, we argue for the necessity of exposing students to new and powerful quantum tools, as provided by innovative quantum computing technologies. We do that by proposing contemporary and STEM related activities and gamification scenarios, in which they acquire stronger mathematical and computational - problem decomposition and modelling skills, working as real researchers. By engaging students in games and activities related to quantum computing and quantum information processing, they acquire all necessary knowledge related to: superposition, teleportation, entanglement, quantum gates and quantum information. The serious games proposed in this paper relates to quantum strategic games, necessary for STEM activities to train students within the computational thinking 2.0 framework. All scenarios are implemented using the didactic model of game-based inquiry learning using Python libraries.
Speaker
Speaker biography is not available.
A Sustainable Development Goal: A SMART Sustainable Electrical System for an Urban Community
Enrique C Pajardo and Dong H Kang (Morgan State University, USA)
0
Despite the vast research in Sustainable Development (SD), very little is known about having a sustainable electrical system for an urban community. The overall image that emerges from past literature is that obtaining a new electrical system, such as installing a new circuit breaker panel is safer and more convenient then replacing fuses. This is a very a simplistic view of achieving a Sustainable Development Goal (SDG). The motivation for this study is to develop the concept of a sustainable electrical goal for an urban community. Establishing an SDG can increase an urban community wellbeing, which is a gap in most past research. The primary objective of this paper is to provide an electrical system that addresses economic, environmental, and social elements of sustainable development for any urban community. A task was completed to develop a basic sustainable "Self-Monitoring, Analysis and Reporting Technology" (SMART) electrical system. This study evaluated the community of Edmondson Village electrical systems for three reasons: (1) promote economic growth, (2) environmental benefits, (3) and improve communities well-being. The study was conducted at Morgan State University (MSU) in Baltimore, Maryland. The existing electrical systems in Edmondson Village were observed from site visits, local zoning permit office, and "Google Earth Pro" for Baltimore city. After an intense quantitative and qualitative analysis, it revealed majority of community's electrical system were deemed missing, unsustainable, inadequate, and unsafe. An application of the three elements of the "Nested Development" provided the foundation for a sustainable electrical system. This system was developed to be installed for any residential and local business in an urban community. The larger implications of the findings were that an SDG can benefit any size urban community. However, other lower budget communities interested in initiating sustainable goals might benefit from undertaking low-cost educational strategies and techniques.
Speaker
Speaker biography is not available.
Teaching Scientific Experiments through Online Video Lectures: An Eye-Tracking Research
Qizhi Xu, Nuo Chen and Juanjuan Tu (University of Science and Technology of China, China); Xiang Liu (Educational Testing Service, USA); Mengxiao Zhu (University of Science and Technology of China, China)
1
Online video lectures have been promoted by technological advances as a beneficial tool for learning scientific experiments and were proved valuable in the COVID-19 pandemic numerous times when millions of students were forced to be home-schooled. Therefore, the urgency of studying the effects and various factors influencing online scientific experiment teaching is highlighted to enhance students' learning outcomes. This research aims to explore how online video lectures influence procedural and declarative knowledge and to determine whether instructor presence and other visual elements have specific effects on students' learning. In this study, seventy-eight students were randomly assigned to two groups for the controlled experiment. Students' eye movement data were collected to analyze visual attention distributions. Data analysis shows that (1) online video lectures significantly impact the retention of knowledge but have little effect on knowledge transfer; (2) instructor presence has no significant effect on students' learning performance; and (3) complex visual elements such as instructor appearance, tags, and dynamic images compete for students' exogenous attention and significantly affect learning. These findings uncover various factors influencing learning in online video lectures and suggest solutions for proper video design to facilitate students' learning.
Speaker
Speaker biography is not available.
Session Chair
Olu Shonubi (Apex Clean Energy), Brian Choi (JHU/APL)
Session Full-03
Track 3 — Full Papers 3
Conference
2:50 PM
—
4:50 PM EST
Local
Mar 11 Sat, 2:50 PM
—
4:50 PM EST
Location
Room Number: K-5 (Downstairs, First Floor)
Challenges and Applications of AI in Healthcare: A Review
Arav Kumar (Monroe Township High School 200 Schoolhouse Rd Monroe Township NJ 08831, USA); Savya Vats (Bergenfield High School 80 S Prospect Ave Bergenfield NJ 07621, USA); Anvi Kumar (Monroe Township High School 200 Schoolhouse Rd Monroe Township NJ 08831, USA); Avimanyou K Vatsa (Fairleigh Dickinson University, Teaneck, USA)
0
In this fast-paced automated digital world, people's feelings about Artificial Intelligence (AI) applications in healthcare depend on the diverse attitudes of the patients. It also depends on reliable sources and anxiety about healthcare and AI. However, healthcare faces many challenges in trying to achieve its goals. The four main goals of healthcare are to improve population health, patients' experience, and caregiver experience and to reduce the rising cost of care. Although people are getting a better understanding of healthcare situations and are encouraged to broaden their thoughts on the potential computerized technologies, people are still concerned about the effect of AI in the medical domain.
Therefore, applying technology and AI in healthcare can help hospitals, especially when viruses like COVID reduce the workforce. As a result, if AI is successfully implemented, we could see a rapid change in the hospital experience, reduce the amount of work needed in the hospital, protect healthcare professionals from life-threatening viruses or infections, and diagnosis would be efficient, effective, fast, and accurate.
Therefore, applying technology and AI in healthcare can help hospitals, especially when viruses like COVID reduce the workforce. As a result, if AI is successfully implemented, we could see a rapid change in the hospital experience, reduce the amount of work needed in the hospital, protect healthcare professionals from life-threatening viruses or infections, and diagnosis would be efficient, effective, fast, and accurate.
Speaker
Speaker biography is not available.
Enumeration of Birds using Video Segmentation for a Better Understanding of Bird Behaviors
Avimanyou K Vatsa (Fairleigh Dickinson University, Teaneck, USA); Dohyun Lee, Benen Sullivan, Daniel Hogan and Amishi Mittal (Bergen County Academies 200 Hackensack Ave Hackensack NJ 07601, USA); Elise Morton and Harald Parzer (Fairleigh Dickinson University, USA)
0
The State of the World's Birds 2022 report estimated a decline in 30% of the world's birds since 1970, largely attributed to habitat loss, climate change, and other anthropogenic factors [1, 3]. Chimney swifts are aerial insectivores that forage during the day and commonly roost in large colonies inside hollow vertical human-made structures such as chimneys. Signaled by sunset, large groups of this species, sometimes comprised of thousands of individuals, exhibit an impressive display of coordinated entry into their roosting sites. Despite this striking behavior and close relationship with humans, the factors influencing this collective behavior are poorly understood. To understand how anthropogenic and environmental factors influence the population health of this (and other species), reliable methods for counting individuals are required. The purpose of this study is to develop an automated method to accurately count the number of birds over a given period at the roosting site.
To understand the behavior of colonially roosting species such as the Chimney swift, we proposed a methodology in which we collect and analyze videos of birds at roosting sites to understand their behaviors. The proposed approach consists of two steps: physically gathering the video with cameras perched at optimal locations [2] and utilizing video segmentation algorithms to count the number of birds at roosting sites over time.
The final goal of this research is to build useful data for ecologists that can be utilized to fill critical gaps in knowledge. To achieve this, the number of birds counted over time will be analyzed with ambient weather datasets at different geographical locations. Therefore, in this paper, we use four video segmentation algorithms to detect and track the movement of birds, count the number of birds at certain intervals, and then compare the performance of the algorithms.
To understand the behavior of colonially roosting species such as the Chimney swift, we proposed a methodology in which we collect and analyze videos of birds at roosting sites to understand their behaviors. The proposed approach consists of two steps: physically gathering the video with cameras perched at optimal locations [2] and utilizing video segmentation algorithms to count the number of birds at roosting sites over time.
The final goal of this research is to build useful data for ecologists that can be utilized to fill critical gaps in knowledge. To achieve this, the number of birds counted over time will be analyzed with ambient weather datasets at different geographical locations. Therefore, in this paper, we use four video segmentation algorithms to detect and track the movement of birds, count the number of birds at certain intervals, and then compare the performance of the algorithms.
Speaker
Speaker biography is not available.
Teaching an Introductory Programming Course with Project Based Collaborative Learning in a Virtual Learning Environment
Mahmudur Rahman and Roshan Paudel (Morgan State University, USA)
0
Computer programming is one of the most challenging subjects in the computer science curriculum, particularly for the freshmen without any programming background. This work presents our experience and approaches of teaching an introductory computer programming class virtually using Python programming in Fall 2020. Without reinventing the wheel and without missing out the benefits of hands-on learning, project based collaborative learning was infused and assessed with well-defined rubrics to create a dynamic remote classroom environment. To keep the structure of the session much like an in person learning experience, the synchronous session included whole group instruction in Zoom led by the instructor and small group (breakout room) based lab work in Repl.it amongst the learners. Both interactive and collaborative learning are infused in pedagogy effectively so that students can learn using interactive platforms, tools, technologies, systems, and services as available to them and collaborate within and among groups. To evaluate the impact of the infusion, a pre- and post- performance survey were conducted on a student cohort of 4 sections taught by 3 different instructors. In addition, final project scores and final grades for Fall'2020 semester and enrollment number and final grade distributions from Fall'2017 to Fall'2020 were also available for analysis. The initial evaluation of the survey results and student's performances based on quality point scores show evidence to conclude that the proposed pedagogical approach increased student motivation and engagement and facilitated learning to entry-level computer science students.
Speaker
Speaker biography is not available.
Realistic Examples of Mathematical Physics at the Civil Engineering Program
Huber Nieto-Chaupis (Peru & Universidad Autónoma del Perú, Peru)
1
As commonly known, a first course of physics at the civil engineering program is planned to expose classical mechanics with applications to concrete examples of real life. The lack of a sustainable mathematical level emerges a first obstruction to go through a deeply treatment of cases that might be an important motivation to enrich the theoretical component of program towards a solid professional formation as well as in the territory of research. This paper tries to present some methodologies from the Mathematical Physics with concrete examples in the manner as seismic waves can affect large buildings. The case of shear stress and the possible solutions by employing novel versions of Internet are presented as a sequence of topics. The Bessel polynomias are introduced to model the generated S-wave that are released after a random shear stress. These prospects of topics might be included in a modern curricula of civil engineering program with a view in next decade.
Speaker
Speaker biography is not available.
On enabling remote hands-on Computer Networking Education: the NITOS testbed approach
Nikos Makris and Virgilios Passas (University of Thessaly & CERTH, Greece); Apostolos Apostolaras (University of Thessaly & The Centre for Research & Technology Hellas, CERTH, Greece); Theodoros Tsourdinis (University of Thessaly, Greece & Sorbonne University, France); Ilias Chatzistefanidis and Thanasis Korakis (University of Thessaly, Greece)
0
Education in recent years has slowly transitioned to an online model, allowing massive access to online courses virtually from anywhere. The adoption of such educational models was boosted by the global pandemic in 2020, with universities and other degree programs quickly transitioning to such schemes. Although such a model is apt for lecture-based courses, hands-on training remains a puzzle on how it can transition to remote learning. In this work, we describe and evaluate our scheme for integrating testbed resources in online-taught networking-related courses in University of Thessaly, Greece. The framework is based on Kubernetes and is able to deliver hands-on labs related to networking as micro-services over the testbed architecture with minimal overhead on the lab setup from the instructor. The proposed approach has been applied in the networking-related courses of the curriculum during the 2020-2021 and 2021-2022 academic years, educating more than 800 students on computer networking concepts in practice. The paper describes the framework and a benchmarking evaluation, which proves the capacity of the framework to serve up to 5 times higher numbers of students, compared to prior methodologies and practices, without any infrastructure upgrades.
Speaker
Speaker biography is not available.
Evaluating the Effectiveness of Equitable K-12 Professional Learning Access in Computer Science
Jean Chu, Yulia Kumar, Daehan Kwak, James Novotny, Pankati Patel and Patricia A Morreale (Kean University, USA)
1
Computer science professional learning, widely available to 9-12 educators, has increased the number of AP CS courses offered in the U.S. and the number of students taking those courses. However, access to all CS classes remains unequal, dependent on the state, district, counselors, and teachers providing a pathway for K-12 students into the CS classrooms. A 15-month project was undertaken to provide professional learning for K-12 educators to provide broader access for more students. The goal was to increase the knowledge and preparation of teachers in a wide range of school districts, as defined by socioeconomic status (SES), to meet state CS standards. Objectives included increasing the number of educators to teach CS, expanding equitable access to high-quality CS education, and providing resources to school districts to support CS education across the K-12 curriculum. Research questions include determining the most effective professional learning strategy for K-12 educators by grade band and identifying best practices to build a community of educators to support students in CS equitably. Strategies included physical and virtual events, single and multi-day workshops, individual study and out-of-class learning. Results show that 70% of the participants (n=175) came from districts with low SES factors. Short events and peer support enticed educators new to CS. In contrast, experienced CS educators wanted to meet nationally recognized norms, such as the Praxis CS examination, or learn advanced topics. These results can be used to provide more K-12 educators with CS professional learning.
Speaker
Speaker biography is not available.
Environmental Education Through Activities: Teacher Practices of Including Students' Lived Experiences
Tanaya Vyas and Girish Dalvi (Indian Institute of Technology Bombay, India)
0
This paper examines teachers' use of students' lived experiences in primary Environmental Studies (EVS) classrooms of government schools in suburban Mumbai. Data was collected through ethnographic field notes and semi-structured interviews across four schools and fifteen teachers teaching Grades 3 to 5. Environmental Education (EE) is a crucial aspect of the integrated STEM field, for advancing sustainability in a rapidly changing world. EE in primary grades in India is introduced through the subject ‘Environmental Studies' (EVS). EVS integrates the concepts and issues of science (physical, chemical and biological), social studies (history, geography, civics, society, culture) and environment education (protection and conservation). Under efforts to generate quality education, several activities have been introduced to link theoretical concepts and students' real-world scenarios. While the effectiveness of curricular activities and resources for EVS in promoting student learning is often investigated, teachers' implementation of these materials have received less attention. Students bring different lived experiences into the classroom, and we examine what those mean to the teachers. We examine teachers' approaches towards inviting these experiences as part of their process of adapting textbook activities. Episodes of teacher practice illustrate the wide variety in their use of timing and reasons for introducing and sustaining discussions with students. The study also describes how the teachers integrate their own life experiences with those of the students to support meaningful dialogue. Finally, teacher views on limitations and possibilities of using students' lived experiences are discussed.
Speaker
Speaker biography is not available.
Machine Learning-Based Relative Performance Analysis for Breast Cancer Prediction
Ranjit Chandra Das and Fatema Tabassum Liza (Florida State University, USA); Partha Pratim Pandit (Miami University, USA); Afia Farjana (University of South Dakota, USA); Fariha Tabassum (Western Michigan University, USA); Madhab Chandra Das (University of Information Technology and Science, USA)
1
The current high population growth in medical research has made early disease identification an urgent issue. The danger of dying from breast cancer is increasing exponentially along with the rapid population expansion. The second most serious cancer among those that have already been identified is breast cancer. Breast cancer poses a major hazard to women, as it is highly morbid and lethal. Doctors find it challenging to develop a treatment strategy that could increase patient survival time due to the lack of reliable prognostic models. As a result, developing a technique that results in the fewest errors while increasing accuracy takes time. A reliable, effective, and prompt response is offered by an automatic illness detection system, which also helps medical workers identify diseases and reduces the likelihood of fatalities. In this work, we investigate eight machine learning techniques, including GaussianNB, Decision Tree, K-Nearest Neighbor, Random Forest, support vector machine (SVM), XGBoost, LightGBM, AdaBoost. The Wisconsin Breast Cancer dataset was discovered in the UCI machine learning database, a well-known machine learning database. The performance of the study is assessed with relation to accuracy, precision, recall, F1 score, and ROC score. Among the eight-machine learning model, Random Forest and AdaBoost perform best which provides 99.20% accuracy and around 99% ROC curve score.
Speaker
Speaker biography is not available.
Session Chair
Anna Romaniuk (IEEE), Webert Montlouis (JHU/APL)
Session Full-04
Track 4 — Full Papers 4
Conference
2:50 PM
—
4:50 PM EST
Local
Mar 11 Sat, 2:50 PM
—
4:50 PM EST
Location
Room Number: K-6 (Downstairs, First Floor)
An Immersive Curriculum to Develop Computational Science and Research Skills in a Cohort-Based Internship Program
Erik Johnson, Marisel Villafañe-Delgado, Danilo Symonette, Katherine-Ann Carr, Marisa Hughes, Julie Burroughs, Sydney Floryanzia and Martha Cervantes (Johns Hopkins University Applied Physics Laboratory, USA); William Gray-Roncal (Johns Hopkins University Applied Physics Laboratory & Preparation Meets Opportunity Foundation, USA)
0
Workforce education is a key challenge as computational science, including data science and machine learning, increasingly influences critical application spaces such as public health and medicine, space exploration, national security, autonomous systems and cybersecurity. Developing core software development, analysis, and machine learning skills will enable workers to have impact across a range of spaces. These skills are in high demand in industrial research and development, but we do not believe that traditional recruiting and training models in industry (e.g., internships, continuing education) are serving the needs of the diverse populations of students who will be required to revolutionize these fields. To accelerate workforce development in these key areas, we have designed and executed a machine learning and research skills training curriculum for our cohort-based research internship program, the Cohort-based Integrated Research Community for Undergraduate Innovation and Trailblazing (CIRCUIT). The program targets trailblazing, high-achieving students who face barriers in achieving their goals and the training program is aimed at accelerating their growth as leaders in data science, machine learning, and artificial intelligence research. The training curricula and support structure is designed to be flexible to student and research project needs during a research internship. Utilizing both existing online material and custom workshops, this model consists of a compressed data science and machine learning curriculum, a series of professional development training workshops, and team-based challenges. Strategies allow for customization of these training efforts for individual students and projects. Over four cohorts, this training curricula has helped students achieve mastery of data science and machine learning concepts, produce key demonstrations and work products in their cohort research projects, and progress to further internships, graduate school, and employment.
Speaker
Speaker biography is not available.
A Predictive Analysis of Imposter Phenomenon in STEM Education
Katherine-Ann Carr (Johns Hopkins University Applied Physics Laboratory, USA); Aishwarya Jayabharathi (Johns Hopkins University, USA); Jacalynn Sharp (Johns Hopkins Applied Physics Laboratory, USA); Julie Burroughs (Johns Hopkins University Applied Physics Laboratory, USA); Jorge Rivera (Johns Hopkins University, Applied Physics Laboratory, USA); William Gray-Roncal (Johns Hopkins University Applied Physics Laboratory & Preparation Meets Opportunity Foundation, USA)
0
Technology companies across the country have used hackathons to showcase ideas, talents, and collaboration in a time-bound, prompt-driven framework. These hackathons also often act as an informal learning space. We recently implemented an intern hackathon as a tool for engaging students through innovation, technical work, and further exposure to our work culture. We expanded beyond these goals to develop an inclusive and diverse talent identification platform. When considering STEM fields and inclusivity, the concept of imposter phenomenon is often discussed as a barrier through feelings of self-doubt. This topic is based on research that began with particular populations and often did not include the diversity needed to generalize appropriately. Exploring the diverse identities within the intern population during a hackathon, our research seeks to explore the connection between imposter phenomenon and different identifiers. In addition to analyzing these connections, we hope to see whether machine learning approaches may be used to identify these barriers earlier and the effects the environment had on the study results. In this study, we developed a reproducible framework; identified correlations using machine learning; and critically found that many of the demographic correlations expected in a STEM environment were not observed, suggesting that our inclusive environment may limit these negative emotions.
Speaker
Speaker biography is not available.
Strategies for Enhancing Retention of Information Technology Students
Tacksoo Im, Hyesung Park, Wei Jin, Sonal Dekhane, Sebastien Siva and Rahaf Barakat (Georgia Gwinnett College, USA)
0
In this paper, we describe the retention of students enrolled in an Information Technology undergraduate degree program and the various interventions initiated to improve the result. The success of students in information technology programs can be measured by their graduation rates and outcomes. However, a major challenge for some students is often the first programming course. In this study, we evaluate the effectiveness of our efforts to improve this bottleneck and discuss plans for future improvement. We broadly define our interventions into two categories: curricular and student engagement related. Efforts to decease the cost of textbook, POGIL inspired instruction, media-based instruction and a non-majors course are examples of curricular interventions that were made. Student engagement strategies such as boot camps and peer lead instruction are also discussed. Retention data is also presented which indicate that the preparedness of student is not indicative of student retention and that other factors may be influencing retention.
Speaker
Speaker biography is not available.
Retrocomputing in Contemporary Integrative STEM Education
Zhemin Zhang (Rensselaer Polytechnic Institute, USA)
0
In a world of exponentially growing demand for computing power running into chip technology challenges, it takes both software and hardware backgrounds to design and constructs an optimal system. The existing computer system engineering curricula setting has drawbacks as they cannot reach the equilibrium between the simplicity of theory and complicated real-world practical systems. This article proposes an initiative to introduce retrocomputing to bridge the gap between hardware and software curricula. The core idea is to bring simple yet practical computer systems into the classroom. The retrocomputing activities can be summarized into a three-stage collect-restore-build pathway with progressively demanding knowledge and problem-solving skill requirements to be taught at different levels, from middle school to college. In addition to hands-on experience, introducing retrocomputing as a hobby has several benefits including developing self-motivated students, lifetime learning habits, and sustainability awareness. Challenges such as class organization and insufficient teaching resources exist, but there are workarounds.
Speaker
Speaker biography is not available.
CPS-TR: An Online Training Platform to Address Fourth Industrial Revolution Workforce Needs
Pratik Satam, Carter Philipp, Sicong Shao and Soheil Salehi (University of Arizona, USA)
0
The widespread deployment of 'Smart' Infrastructure, which uses networked computing systems to manage physical processes, has brought the onset of the fourth Industrial Revolution (4IR). The 4IR relies on network interconnectivity, sensing, automation, robotics, and artificial intelligence to improve the productivity of modern manufacturing environments while reducing their workforce needs. Although beneficial, this growing adoption of 4IR has increased the complexity of Industrial Control Systems (ICS), creating a huge workforce skills gap and causing 2.1 million manufacturing jobs to go unfulfilled by 2030. In the context of these challenges, this paper presents Cyber-Physical Systems Training Range (CPS-TR), a cloud-based scalable student training platform to address 4IR needs, especially cybersecurity. The CPS-TR, built on Amazon Web Services (AWS), allows instructors to create experimental scenarios using virtual machines in AWS' Elastic Cloud (EC2), connected via AWS Virtual Private Cloud (VPC) based subnet providing an isolated communication environment. The CPS-TR front-end provides a web application-based interface for students and instructors to design new material and perform experiments. This paper evaluates the performance and efficiency of the CPS-TR environment while showcasing an experiment teaching trainees about the safe use of the MQTT protocol from 4IR infrastructure software updates. The experimental evaluation shows that a trainee's network traffic volume while using the CPS-TR peaks at 2000 packets in a second; the network bandwidth requirements of a basic network connection suited for usage with mobile and tablet devices. The experimental evaluation also shows the VPC subnet communication peaks at eight packets in a second, with a cumulative packet count of fewer than 70 packets. This low VPC subnet utilization is in combination with EC2 T2.Micro VMs allows the CPS-TR operation costs to stay low.
Speaker
Speaker biography is not available.
Virtual Reality Museum Application for the Arts
Joshua Maddy and Husnu S Narman (Marshall University, USA)
1
Most students are monetarily or physically inhibited from visiting private or public institutions. The Metaphysical Exhibit project goal is to give all ages a modern, technological take on the museum experience by providing a Virtual Reality alternative. By lowering the barrier of entry to a one-time purchase for the hardware and free software, any classroom or consumer can experience masterworks in an immersive environment. A rich collection of art pieces across the eras can be displayed under one roof by compiling public information on historical works. By utilizing Virtual Reality, the museum is easily distributed and portable. In this paper, we aim to develop a virtual museum with artworks and observe its effects on users. The developed application is capable of running on modern headsets, specifically the Meta Quest 2. To analyze the viability of the application in a classroom and personal setting, we especially find answers to the following questions: (i) Does experiencing the museum in this format feel analogous to prior exhibit experiences? (ii) What is the level of interest in exploratory, self-guided Virtual Reality content used in education from a student and teacher perspective? (iii) How can the experience be improved? The results show that the project was received positively by students and teachers as an introductory experience for the arts.
Speaker
Speaker biography is not available.
A comparative study of machine learning approaches for heart stroke prediction
Fatema Tabassum Liza (Florida State University, USA); Madhab Chandra Das (University of Information Technology and Science, USA); Partha Pratim Pandit (Miami University, USA); Afia Farjana (University of South Dakota, USA); Fariha Tabassum (Western Michigan University, USA); Md Jahidul Islam (Tuskegee University, USA); Ranjit Chandra Das (Florida State University, USA)
1
The majority of strokes are triggered by the heart and brain blocking expected pathways. Today, it is the most common cause of death in the worldwide. By looking at the people affected, several risk elements that are thought to be connected to the stroke's cause have been determined. Numerous studies have been conducted for the prediction and categorization of stroke diseases using these risk variables. Similar to any diseases, an early diagnosis of a stroke can avert such occurrences and open the door to a healthy life. Machine learning (ML) techniques have been used in this study to accurately determine heart attacks. In order to determine multiple matrices like accuracy, recall, ROC, precision, and F1 score, we used nine different machine learning algorithms in this study, which include support vector machines (SVM), K-nearest neighbor (KNN), XGBoost, AdaBoost, Random Forest (RF), Decision Tree, LightGBM, and Logistic Regression. The results indicate that the Random Forest method outperformed the others with an accuracy of 98.4%.
Speaker
Speaker biography is not available.
Adapting Cybersecurity Teacher Training Camp to Virtual Learning
Joshua Maddy, Eric M Dillon and Husnu S Narman (Marshall University, USA)
1
Over the past couple of years, many summer camps have found it necessary to transition their face-to-face programs into online experiences. When adapting it, it is critical to consider how to best ensure an educational experience similar to preceding programs. This raises two primary questions: what pedagogical tools and methods are supported in an online format that replicate the teachings in a face-to-face experience; and second, how to best maintain the efficacy of the program. We define efficacy as a combination of two measures: first, whether the camp matches the sponsor, GenCyber's, mission of promoting the education of cybersecurity to K-12 students and teachers; and second, whether the camp maintains a high level of participation and reported interest. We evaluated our efficacy by analyzing the report provided by the official GenCyber team as well as by recording hours of participant activity, polling participants on a daily basis, and following up after the program with an additional questionnaire. We determined that the camp was effective due to near-unanimous daily approval, strong interest in repeating the camp, and a significant amount of real-world student exposure to cybersecurity topics. Approximately 65% of the twenty teachers who participated in the camp immediately implemented cybersecurity principles in their respective fields, ranging from subjects in science and mathematics to career education and ROTC. Our result shows that 950 K-12 students exposure to cybersecurity subjects within their course subjects in the first semester after the camp and 800 of those are not in the computer science course subjects.
Speaker
Speaker biography is not available.
Session Chair
Chinonso Ezeobi (UMBC), Cleon Davis (JHU/APL)
Session Full-05
Track 5 — Full Papers 5
Conference
2:50 PM
—
4:50 PM EST
Local
Mar 11 Sat, 2:50 PM
—
4:50 PM EST
Location
Room Number: K-7 (Downstairs, First Floor)
Gamification FrAmework for promoting Computational Thinking (GFACT)
Yuri M Bermudez (Universidad del Valle, Colombia); Maria Trujillo (Univerdad del Valle, Colombia); Juan Francisco Díaz Frias (Universidad del Valle, Colombia)
0
Computational Thinking is a skill that has become relevant and necessary to be more competitive in the twenty-first century. Primary and secondary school students are challenged to develop it for solving problems. However, there are two issues to consider. Although, there are proposed methods for teaching Computational Thinking, there is no standardization of the dimensions or aspects that compose Computational Thinking. The lack of standardization makes harder to provide methodological guidance to promote and develop those competences in educational environments. On the other hand, new metaphors are needed for facilitating student's computational thinking learning process. In this paper, we propose a Gamification FrAmework for promoting Computational Thinking, addressing these two issues. Our Framework is composed of a conceptual definition of Computational Thinking along with a gamification strategy for motivating learning Computational Thinking. Our conceptual definition is based on associating learning outcomes to abstraction, decomposition, and algorithmic thinking, as the three core competences of Computational Thinking. The gamification strategy incorporates game elements using learning styles and player types. It can be used by students as a tool for achieving problem solving skills in any context and area of knowledge using Computational Thinking.
Speaker
Speaker biography is not available.
Design and Development of a Sustainability-focused Hybrid Course for Undergraduates Based on Open Educational Resources
Mohammad U. Mahfuz (University of Wisconsin-Green Bay, USA); Agachai Sumalee (Chulalongkorn University, Thailand)
0
In this paper, a complete design of a sustainability-focused hybrid course has been presented for undergraduate curricula. The three remarkable features of this course are the following. Firstly, this is a sustainability-focused course suitable for undergraduate students of any discipline. The course particularly focusses on smart and connected cities and how they can help the vision of smart cities. Secondly, this course is based on hybrid modality, meaning that the course has both face-to-face and virtual lectures and other contents that can be balanced with careful attention to program needs. Thirdly, this course is entirely based upon open educational resources (OER) meaning that students do not have to purchase textbooks but rather rely on open-access (OA) scholarly articles for this course. The course is designed and developed by the first author in his sabbatical leave at Chulalongkorn University in Thailand and has been offered for the first time to the undergraduate students of the School of Integrated Innovation (ScII) at Chulalongkorn University in Thailand.
Speaker
Speaker biography is not available.
A meta-analysis on the effect of internal communication
Jieqi Wang (Nanyang Technological University, Singapore)
0
Internal communication is a necessary factor within any organization in the workplace. It can partly affect the efficiency of how an institution works as well as an organization's achievements and developments. However, how internal communication contributes to the three vital factors - employee satisfaction, employee performance, and employee engagement, is poorly understood. The majority of previous studies only concluded the possible influences of internal communication on one of the factors (i.e. employee satisfaction, employee performance, or employee engagement) or in a single industry (e.g. healthcare). Thus, a meta-analysis was conducted in this research to examine the general influence of internal communication on all these three employee outcomes without the limitation of industries. By using the findings from 33 studies, this research summarized the effect and the most influential characteristics of internal communication on employee performance, employee engagement, and employee satisfaction. The results from the current meta-analysis have theoretical and practical implications for internal communication related research and management within companies, and highlight new directions for future studies.
Speaker
Speaker biography is not available.
Multi-Lingual DALL-E Storytime
Noga Mudrik (Johns Hopkins University, USA); Adam Charles (The Johns Hopkins University, USA)
0
Visualizations are a vital tool in the process of education, playing a critical role in helping individuals comprehend and retain information. With the recent advancements in artificial intelligence and automatic visualization tools, such as OpenAI's DALL-E, the ability to generate images based on text prompts has been greatly improved. However, these advancements present a significant challenge for populations with limited English proficiency, exacerbating the educational divide between children from different backgrounds and limiting their access to new technology. Here, we introduce a DALL-E storytelling framework designed to facilitate the fast and coherent visualization of non-English songs, stories, and biblical texts. Our framework extends the original DALL-E model to handle non-English input and allows users to specify constraints on story elements, such as a specific location or context. The key advantage of our framework over manual editing of DALL-E images is that it offers a more seamless and intuitive experience for the user, as well as automates the process, thus eliminating the time-consuming and technical-expertise-requiring manual editing process. The visualization masks are automatically adjusted to form a coherent story, ensuring that the figures and objects in each frame are consistent and maintain their meaning throughout the visualization, allowing for a much smoother experience for the viewer. Our results demonstrate that our framework is capable of effectively and quickly visualizing stories in a coherent way, conveying changes in the plot over time, and creating a narrative with a consistent style throughout the visualization. By enabling the visualization of non-English texts, our framework
helps bridge the gap between populations and promotes equal access to technology and education, particularly for children and individuals who struggle with understanding complex narrative texts, such as fast-paced songs and biblical stories. This holds the potential to greatly enhance literacy and foster a deeper understanding of these important texts.
helps bridge the gap between populations and promotes equal access to technology and education, particularly for children and individuals who struggle with understanding complex narrative texts, such as fast-paced songs and biblical stories. This holds the potential to greatly enhance literacy and foster a deeper understanding of these important texts.
Speaker
Speaker biography is not available.
Disparities in Digital Access at the Intersectionality of Race and Sexual Orientation
Jeffrey B Chavis (University of South Carolina & Johns Hopkins University Applied Physics Lab, USA)
0
Healthcare and health services research when it pertains to racial or sexual minorities has identified many different factors that lead to a minority group being discriminated against or facing disparities in their care individually. However, there is very little research that examines the intersectionality of race and sexual orientation together. This study seeks to examine the relationship between the two and find if their access to the internet, and then healthcare by proxy, is equal to their racial or sexual orientation counterparts. The hypothesis is that areas with high Lesbian, Gay, Bisexual, Transgender, and Queer (LGBTQ+) and People of Color (POC) populations will have less access to the internet. This is a quantitative study that examines the internet access of the 3225 counties of the United States. Factors such as county, region, race, sexual orientation, age, median income, and population were examined. The results showed that there is a direct correlation between a counties level of LGBTQ+ people and the level of POC residents. A liner regression was done and showed a Multiple R value of 78%, an R squared value of 60.8%, and a P of 1.03712E-91. It was concluded that based on this data, there is not a direct correlation between race and sexual orientation and digital access. However, race and sex orientation showed to be closely tied to each other
Speaker
Speaker biography is not available.
Basic Mathematical Methodologies as Tool to Interpret Pandemic Data on the Sight of Freshman Engineering Students
Huber Nieto-Chaupis (Peru & Universidad Autónoma del Perú, Peru)
0
Along these last years (2020-2022) a lot attention has been paid on all types of information concerning to the pandemic of Corona virus 2019 and recently Monkeypox-2022. Mainly the information about the evolution of pandemics has been resumed in terms of infections and projections from a statistical analysis of world-wide data. However, one can wonder: Which material (or academical topics) and methodology might be of interest to engineering students in order that them can extract their own view and perspective on the pandemic and how it can be valuable for local public health operators? This paper tries to answer this question from the fact that freshman students have taken first courses of mathematics as well as computing. Under the guidance of Professor and Instructor, students can build their basic methodology that can help them to understand data of global pandemic. Some toys models are presented and are interpreted in terms of infections.
Speaker
Speaker biography is not available.
Comparing the Performance of Classification Algorithms for Melanoma Skin Cancer
Avimanyou K Vatsa (Fairleigh Dickinson University, Teaneck, USA); Arav Kumar (Monroe Township High School 200 Schoolhouse Rd Monroe Township NJ 08831, USA); Savya Vats (Bergenfield High School 80 S Prospect Ave Bergenfield NJ 07621, USA); Anvi Kumar (Monroe Township High School 200 Schoolhouse Rd Monroe Township NJ 08831, USA)
1
Computer vision plays a beautiful role in the early identification of Melanoma skin cancer. Images are used to classify malignant and benign phenotypes. Also, Dermatologists claim that Melanoma may be diagnosed and cured if it is identified in the early stage. However, selecting an appropriate classification algorithm is essential in early and accurate melanoma detection.
Therefore, inspired and motivated by our previous study outcome, we know that early detection and prediction of melanoma skin cancer may be cured (malignant and benign images are classified using CNN, RNN, and XG-Boost methods) [10, 11, 22, 23, 24, 25]. In this experiment, we compared the performance of supervised learning methods like Linear Regression, Light Gradient Boosting Regression, Random Forest Regression, Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbor (KNN) Classifier, Decision Tree, Passive Aggressive, Multinomial Naïve Bayes, and Bernoulli Naïve Bayes. Moreover, a better and more accurate performing algorithm is used in early melanoma skin cancer detection.
Therefore, inspired and motivated by our previous study outcome, we know that early detection and prediction of melanoma skin cancer may be cured (malignant and benign images are classified using CNN, RNN, and XG-Boost methods) [10, 11, 22, 23, 24, 25]. In this experiment, we compared the performance of supervised learning methods like Linear Regression, Light Gradient Boosting Regression, Random Forest Regression, Logistic Regression, Support Vector Machine (SVM), K-Nearest Neighbor (KNN) Classifier, Decision Tree, Passive Aggressive, Multinomial Naïve Bayes, and Bernoulli Naïve Bayes. Moreover, a better and more accurate performing algorithm is used in early melanoma skin cancer detection.
Speaker
Speaker biography is not available.
Detecting encrypted traffic activities and patterns in ZigBee network Data
Jeffrey S Chavis (Johns Hopkins University Applied Physics Laboratory, USA); Joy Falaye (JHUAPL & Morgan State University, USA); Kevin Kornegay (Morgan State University, USA); Daniel H Simon (Johns Hopkins Applied Physics Lab, USA); Khir Henderson (JHUAPL & Morgan State University, USA)
0
With the increase in data transmissions and network traffic over the years, there has been an increase in concerns about protecting network data and information from snooping. With this concern, encryptions are incorporated into network protocols. From wireless protocols to web and phone applications, systems that handle the going and coming of data on the network have applied different kinds of encryptions to protect the confidentiality and integrity of their data transfers. The addition of encryptions poses a new question. What will be observed from encrypted traffic data? This work in progress research delivers an in-depth overview of the ZigBee protocol and analyzes encrypted ZigBee traffic on the ZigBee network. From our analysis, we developed possible strategies for ZigBee traffic analysis. Adopting the proposed strategy makes it possible to detect encrypted traffic activities and patterns of use on the ZigBee network. To the best of our knowledge, this is the first work that tries to understand encrypted ZigBee traffic. By understanding what can be gained from encrypted traffic, this work will benefit the security and privacy of the ZigBee protocol.
Speaker
Speaker biography is not available.
Session Chair
David Mutschler (USN), Jeffrey S. Chavis (JHU/APL)
Session Full-06
Track 6 — Full Papers 6
Conference
2:50 PM
—
4:50 PM EST
Local
Mar 11 Sat, 2:50 PM
—
4:50 PM EST
Location
Room Number: K-8 (Downstairs, First Floor)
Integrating Scrum Project Management in Information Technology Capstone Course
Shuting Xu, Shuhua Lai and Lissa Pollacia (Georgia Gwinnett College, USA)
0
Agile project management has replaced the traditional Waterfall as the main project management method in IT industry. Scrum is the most popular Agile framework, which may greatly improve productivity. In this paper, we introduce the pedagogical methods applied in teaching Scrum project management in an IT capstone course. We integrate the Waterfall and the Scrum methods in the capstone project procedure, to combine the planning of Waterfall and the agility of Scrum. The hybrid method enables students to experience the benefits and differences of these methods while working on the project. We conducted a pre-survey and a post-survey to assess the outcome of the applied pedagogical methods. Survey results show that using Scrum in students' own capstone projects is an efficient way for them to learn Scrum project management, better than other pedagogical methods. Moreover, using Scrum is helpful in implementing students' projects too. Most students recommend to teach Scrum project management in later IT Project courses.
Speaker
Speaker biography is not available.
System Dynamics Modeling Optimization of STEM Education and Outreach Career Pipelines for Students in Underrepresented Communities
Daniel C Appel (US Air Force Research Laboratory, Kirtland AFB, NM & AEgis Technologies Group Inc., USA); Mo Mansouri (Stevens Institute of Technology & University of South-Eastern Norway, USA)
0
Academic and career achievement in science, technology, engineering, and mathematics, (STEM) for K-12 students remains a key area to advance equity and achievement across society. Developing and exploring system dynamics models of the STEM education and outreach ecosystem to understand phenomena related to pipeline leakage observed in underrepresented demographics provides opportunities to explore and optimize intervention strategies. Correlating outputs of system dynamics modeling and simulation to real-world survey data enabled extensive sensitivity analysis of the feedback-driven model elements to be performed. Modeling the complete outreach-catalyzed education to workforce ecosystem enables testing and optimization of intervention strategies, tailored for underrepresented demographics. Strategies such as prioritizing near-peer and other mentorship initiatives, involving families in activities such as ‘family STEM nights', using field trips to expose students to the diversity of work opportunities, and tailored curriculum including the accomplishments of prominent contributors in STEM fields from diverse backgrounds emerged as key heuristics for closing the representation gap in these fields. The massive improvements and positive feedback mechanisms that reinforce beneficial changes across the ecosystem can benefit all students with their STEM education and career aspirations.
Speaker
Speaker biography is not available.
An Inclusive Approach to Hands-on STEM programs in Underserved Secondary Schools: An Epistemological STEAM Model
Martha Omoekpen Alade (Ambrose Alli University Ekpoma & Women in Technology in Nigeria, Nigeria); Fatai I. Sadiq; Festus O. Ikpotokin
1
Underserved schools globally do not usually have sufficient resources and requisite models to run inclusive and sustainable hands-on STEM programs. This often lead to exclusion of more students from opportunities in STEM, especially those with disabilities and learning difficulties. The marginalization of disadvantaged learners and exclusion of majority of students in resource-poor schools creates an internal STEM gap. Some schools having resources but lacking skilled instructors also face the same challenges. After more than a decade of casual observations, these problems have remained consistent, persistent and widespread; especially in developing countries. This mixed and longitudinal study therefore proposes an inclusive framework to address these inequities in STEM. Our model comprises seven components, after inductive analysis of empirical observations. A survey of 214 participants comprising 36 teachers and 178 students, who have participated in hands-on STEM programs was analyzed using simple statistical method to evaluate their perceptions on our hypothesized propositions. Our findings reveal that teachers’ and students’ responses validate our proposed framework; which informs the development of our Epistemological STEAM Model. This framework would serve as an effective guide for underserved secondary schools to implement sustainable hands-on programs with limited resources. It would also help policy makers enforce inclusion in the selection of students who participate annually in sponsored STEM programs and competitions; as well as drive optimal utilization of public STEM infrastructures.
Speaker
Speaker biography is not available.
Best State Estimate for the Phase Angles of Busbars in Power Systems via Circuit Modeled with DC Load Flow
Ronak Ali (University of Kentucky USA, USA); Shujaat Ali (Tianjin University, China); Tariq Pirzada (Nazeer Hussain University, Pakistan); Syed Hadi Hussain Shah (Muhammad Ali Jinnah University Karachi, Pakistan); Madad Shah (IBA Sukkur, Pakistan); Saeed Ahmed Khan (Sukkur IBA University, Pakistan)
1
State estimate is a digital processing method that gives many of the central control and dispatch operations in a power system a real-time data basis. It is essential to do state estimates to get rid of probable errors and boost system reliability. State variables, which are utilized to further calculate other power system characteristics, are necessary to determine the state of a system. Based on measurements, or input, such as active power, reactive power, voltage, and current magnitude collected from the system, these state variables are given a value. Voltage and phase angle are often utilized as state variables. The method used for state estimation will, however, affect the choice of state variables. In addition to input parameters, network data such as topology and impedances are also necessary. The measurements are made with a meter that has a predetermined full-scale reading that can be used as a starting point for calculations. When estimating the state, there may be errors that cause the reading from a meter to differ from the genuine value. Error in measurement is taken good care of here. Where measurement error, measurement and estimated value for the meter reading is considered. The best approximation of the voltage angles and power flow is obtained using it. The Weighted Least Squares Method is a widely used method for estimating system state.
Speaker
Speaker biography is not available.
Discussion on the Mathematics Behind Extinctions: A Detailed Statistical Assay on the Population Density of Northern White Rhinoceros
Manan Roy Choudhury (Maulana Abul Kalam Azad University of Technology, West Bengal & Government College of Engineering and Textile Technology, Serampore, India); Ishan Banerjee (Chennai Mathematical Institute, India)
1
Species extinctions have been a significant part in disturbing the biodiversity. This creates an importance in trying to simulate the populations of the species of interest to get an idea when its population looks threateningly low. We will try to get an idea regarding the mathematics working behind the prediction of the extinction time of a creature. We will briefly overview the associated ideas and how the predictions work mathematically. We will also take a real - life example to understand the idea better. A detailed statistical assay is being carried out using deterministic and non-deterministic approaches to study the Northern White Rhinoceros population curve. Probability heuristics is used along with its terminologies to analyze the extinction of Northern White Rhinoceros. Several fitting tests have been performed on the population dataset of the Northern White Rhinoceros to determine which statistical distribution fits well for the dataset. After testing it is observed that Weibull distribution fits well and it is to represent the demography of Northern White Rhinoceros year-wise from 1960 to 2022. Finally, a TreeMap has been used to represent the hierarchical population demography of Northern White Rhinoceros.
Speaker
Speaker biography is not available.
The trends of Research in STEM education in high scholarly journals
Hisham Barakat Hussein (King Saud University, Saudi Arabia)
1
This talk does not have an abstract.
Speaker
Speaker biography is not available.
Integrating Real-Life Examples into Software Engineering Instruction: A Case Study of Software Product Families
Swapna S. Gokhale (University of Connecticut, USA)
0
Many instructors indicate that integrating practical activities that can balance between teaching theoretical concepts
and their application to real-life systems is a significant
impediment in teaching software engineering courses. This
paper presents an active learning approach that can mitigate this problem. In this approach, students are challenged
to search from their experiences, examples of software
systems that exemplify a particular concept discussed in
the classroom. This approach was applied to elucidate the
idea of software product lines or product families. Students
crafted examples from many computing systems including
smartphones, operating systems, productivity suites, gaming,
music, media and communications software. Members from
these families were compared along the obvious, what-meetsthe-eye type of features to unobvious, niche functions. The
breadth and depth of product families and their comparative
analysis highlighted the willingness of the students to reorient their daily engagement with software systems within
the context of software engineering principles. A subsequent
assignment demonstrated that students indeed inculcated the
key concept underlying product families, which is the reuse
of abstract functions across systems in diverse, sometimes
even unrelated domains. This suggests that our approach
could be promising to build an appreciation for concepts
such as software product families, which may otherwise be
difficult to relate to, especially for inexperienced students.
and their application to real-life systems is a significant
impediment in teaching software engineering courses. This
paper presents an active learning approach that can mitigate this problem. In this approach, students are challenged
to search from their experiences, examples of software
systems that exemplify a particular concept discussed in
the classroom. This approach was applied to elucidate the
idea of software product lines or product families. Students
crafted examples from many computing systems including
smartphones, operating systems, productivity suites, gaming,
music, media and communications software. Members from
these families were compared along the obvious, what-meetsthe-eye type of features to unobvious, niche functions. The
breadth and depth of product families and their comparative
analysis highlighted the willingness of the students to reorient their daily engagement with software systems within
the context of software engineering principles. A subsequent
assignment demonstrated that students indeed inculcated the
key concept underlying product families, which is the reuse
of abstract functions across systems in diverse, sometimes
even unrelated domains. This suggests that our approach
could be promising to build an appreciation for concepts
such as software product families, which may otherwise be
difficult to relate to, especially for inexperienced students.
Speaker
Speaker biography is not available.
A Pragmatic Approach To Training The Next Generation Cyber-Physical Workforce
Jeffrey S Chavis, Daniel P Syed, Prathista Annapareddi and Ian Chu (Johns Hopkins University Applied Physics Laboratory, USA)
0
Training the next generation Cyber-Physical workforce takes a novel and pragmatic approach to offer the necessary skills and experiences needed for up incoming candidates to be successful in the workplace. During the summer of 2022, the Cyber-Physical Systems Development and Cyber Capabilities Development groups at the Johns Hopkins University Applied Physics Laboratory (APL) implemented a pilot project combining educational opportunities for university students and mentoring opportunities for early career staff to develop necessary Cyber-Physical skill sets. The pilot centered on a cohort of ten college interns from a sponsoring organization on a short term rotation at APL; they were supported by a number of additional college-level interns from within the CIRCUIT. The internship experience centered around building relevant IoT and Cyber-Physical capability. Its goals were to provide the cohort with hands-on experience and guidance working with cyber-physical systems and to introduce them to working with an unstructured problem as a team. This paper describes the pilot program and its outcomes.
Speaker
Speaker biography is not available.
E-learning Utilization Based on Language
Emad Abu-Shanab and Alaa Abuhuzaima (Qatar University, Qatar)
0
The use of technology and e-learning systems grown significantly during and after Covid-19 era. Language is an important factor in the efficient utilization of technology in education. This study tested the influence of survey language on an integrated research model. The research model incorporated three educational factors that present the operational view of learning: Assessment methods, course design, and interaction of students. Results showed that language differences influenced only course design factor, but failed to show significant results regarding assessment and interactions. In addition, the study supported the role of gender in differentiating the research relationships, with substantially greater influence than language. Finally, the research model yielded better prediction power that classical theories, but failed to show full support for TAM or the extensions proposed.
This study showed that students interactions were the most influential factor in the model, which shows that technology (based on a social theory perspective) is a crucial factor in this domain.
This study showed that students interactions were the most influential factor in the model, which shows that technology (based on a social theory perspective) is a crucial factor in this domain.
Speaker
Speaker biography is not available.
Representation of Distribution Network for Teaching Power Flow Analysis- A Case Study of an Academic Campus
Suresh H Jangamshetti (Basaveshwar Engineering College (Autonomous), India); Sangamesh Goudappanavar (Basaveshwar Engineering College, Bagalkot India, India)
2
This paper presents representation and analysis of 11 kV, 15-bus electrical distribution network of an academic campus for effective teaching of network topology and power flow analysis. Distribution network of Basaveshwar Engineering College, Bagalkote, Karnataka India is considered for the case study. It has dual path radial distribution network which is spread over 92 acres with overhead transmission length of 0.89 km. Seven 11 kV/440 V distribution transformers are connected using ACSR rabbit type overhead lines. The transformers are located close to load centres, viz different departments. The real-time data of campus distribution network helped students to draw single line diagram, obtain line data, bus data and formation of admittance matrix. The resultant data of topology is employed to perform load flow analysis using MiPower simulation software. The proposed scheme is included in undergraduate curriculum of academic years 2017-18 and 2018-19. The outcome clearly showed improvement in understanding the practical concepts of power flow analysis. The proposed topology is further used for short circuit and stability studies. The study can be extended for campus energy management, distribution network analysis and integration of renewable energy sources.
Speaker
Speaker biography is not available.
Local Energy Marketplace Agents-based Analysis
Ameni Boumaiza (ALRAYYAN & QEERI, Qatar)
0
A new role known as an energy prosumer is created when distributed energy generation is established through home and commercial PV applications. This eliminates the conventional distinction between energy producers and consumers. Blockchain technology automates direct energy transactions within a distributed database architecture based on cryptographic hashing and consensus-based verification, consumers, prosumers, offering energy, and utilities with a unique, affordable, and safe energy-trading solution. The goal of this study is to deploy a general ABM simulation framework for electricity exchange and illustrate the predicted households' power profiles as well as the functionality of any blockchain process (see Figure. 1). For a Transactive Energy (TE) type Distributed Energy Resources (DER) within the ECCH microgrid that is dependent on blockchain engineering, an original version of a robust multi-agent structure was built and simulated. Recent blockchain-based LEM proposals use auction systems to balance supply and demand in the future. As a result, these blockchain-based LEMs depend on precise short-term projections of the energy output and consumption of specific households. Such precise estimates are frequently just taken for granted. This assumption was put to the test in the current study by first assessing the forecast accuracy that can be achieved for specific households using cutting-edge energy forecasting techniques, and then by analyzing the impact of prediction errors on market outcomes in three different supply scenarios. Although an LSTM model can produce reasonably low forecasting errors, the evaluation revealed. The prediction procedure will be adjusted to the configuration of an LEM built on a blockchain. Therefore, the current research stands out significantly from earlier experiments that make a complete attempt to estimate the time sequence of smart meters in general .
Speaker
Speaker biography is not available.
Session Chair
Steve Bonk (IEEE), Amber Mills (JHU/APL)
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