ABSTRACT
Industry 4.0 and 5.0 topics are emerging fields and have seen rising demand recently. There is a critical need, on the other hand, for improved methods of instructing programming languages since a growing lack of student motivation during the pandemic has had a deleterious influence on the education of programmers. In this context, online/hybrid computer programming courses must be addressed with innovative solutions to support the field with well-educated professionals. In this paper, we present a case study to propose an innovative tailored instructional design for the online/hybrid learning environments for programming courses in engineering faculties. To develop the instructional design, the Kemp Instructional Design Model was followed. The instructional design is a result of the main outputs of the RECOM "Redesigning Introductory Computer Programming Using Innovative Online Modules” project, which aims to bridge the gap between the existing course design in programming courses and the needs of "Covid” and "post-Covid” generation students. © The Authors.
ABSTRACT
The first contact of freshmen students with computer thinking and programming languages is not an easy task. There are several strategies that can be used before, during and after face-to-face classes. Flipped classes are a way to save time in activities that can be better done in the form of previous work - guided by the teacher. A n d the time gained in person can be used in tasks that are much more productive than traditional lectures. This study is based on an introductory programming semester of post lockdown COVID-19, initially with 101 students, with the strategy of providing study materials for students to work on before class (as in flipped classes). We use attendance in classes, acce ss-work MOODLE, the two grades obtained during the semester, as well as some information about the student (age, course, gender, previous knowledge of programming languages), and the level that the students think it was their presence in classes and on MOODLE in the middle and at the end of the semester to measure the success of the experiment. It seems that this type of strategy can be excellent for students who attend classes weekly and do their homework, but it can be a cause of dropout if taken to the extreme. © 2022 IEEE.
ABSTRACT
This article presents a multi-stage guided technical project coding Python scripts for utilizing Amazon Web Services (AWS) to work with a document-store database called DynamoDB. Students doing this project should have taken an introductory programming class (ideally in Python) and a database class to have experience with Python coding and database manipulation/querying in a relational environment. Students learn new data formats (Python dictionaries, JSON text data, keyvalue storage structures) and learn how to transform data from one format to another. They also gain experience with data visualization. The project was first carried out in a business intelligence (BI) course during Spring 2020 semester in the midst of COVID and included video tutorials. Since then, it has been refined and used each semester the BI course is taught.
ABSTRACT
In China, healthcare specialists discovered a new and unknown virus around the end of December 2019. Later, it was recognized as Coronavirus;the virus rapidly spread over the globe. Lockdowns, and social isolation were the primary measures taken by every nation's government to control of the virus. In February 2022, the World Health Organization (WHO) announced that fast immunization reduces Coronavirus infection rates by 21 percent. After the COVID-19 epidemic, the researchers anticipated that another pandemic, mental health, would spread over the world. In fact, the psychological influence on the general population during and after the COVID-19 outbreak has grown vulnerable. The purpose of this work was to do a sentiment analysis on Twitter data using the Python programming language in order to determine the psychological influence of Twitter users in the post-COVID era.
ABSTRACT
Chemistry simulations using interactive graphic user interfaces (GUIs) represent uniquely effective and safe tools to support multidimensional learning. Computer literacy and coding skills have become increasingly important in the chemical sciences. In response to both of these facts, a series of Jupyter notebooks hosted on Google Colaboratory were developed for undergraduate students enrolled in physical chemistry. These modules were developed for use during the COVID-19 pandemic when Millsaps College courses were virtual and only virtual or online laboratories could be used. These interactive exercises employ the Python programming language to explore a variety of chemical problems related to kinetics, the Maxwell–Boltzmann distribution, numerical versus analytical solutions, and real-world application of concepts. All of the modules are available for download from GitHub (https://github.com/Abravene/Python-Notebooks-for-Physical-Chemistry). Accessibility was prioritized, and students were assumed to have no prior programming experience;the notebooks are cost-free and browser-based. Students were guided to use widgets to build interactive GUIs that provide dynamic representations, immediate access to multiple investigations, and interaction with key variables. To evaluate the perceived effectiveness of this introduction to Python programming, participants were surveyed at the beginning and end of the course to gauge their interest in pursuing programming and data analysis skills and how they viewed the importance of programming and data analysis for their future careers. Student reactions were generally positive and showed increased interest in programming and its importance in their futures, so these notebooks will be incorporated into the in-person laboratory in the future.
ABSTRACT
As shopping patterns have gradually shifted from offline to online mode, and with recent lockdowns during the coronavirus disease 2019 (COVID-19) pandemic restricting foreign trade and accelerating the growth of the domestic economy, digital transformation has become a major strategy for many retailers to support and expand their businesses. With the pandemic becoming a turning point, the business of major e-commerce companies in Taiwan in the retail of dry goods has grown significantly, and it has driven the online sales of fresh products as well. In this era of fierce competition, it is especially important to find a way that enables consumers to quickly find ideal fresh products on multiple platforms, shortens the time for price comparison, and improves the efficiency of online shopping. This study uses the Python programming language to write a web crawler program that captures product information from fresh food e-commerce platforms, including product introduction, price, origin, and sales volume, and then defines the relevant status of the product, such as product popularity. Accordingly, through Chinese text segmentation and term-frequency calculation, it aims to classify the product names and introductions into frequently occurring words and use them as product-related labels. Finally, the program combines the product information processing results and product-related labels to construct an online fresh food recommendation system. The results of the proposed system show that it reduces the time and energy spent comparing prices. It can also guide consumers to browse products that may be of interest using relevant tags and increase consumption efficiency by helping them find the ideal item when shopping.
ABSTRACT
This study reports the findings of a program that aims to develop pre-service science teachers' computational problem-solving skills and views on using information and communications technology in science education. To this end, pre-service science teachers were trained on computational thinking, computational problem solving, designing an algorithm, and Python coding, and then they were asked to solve problem situations determined within the science education program using the computational problem-solving process. The study was conducted in a faculty of education in Turkey and carried out conducted in an elective course in the spring semester of the 2019-2020 academic year (in an online platform due to the COVID-19 Pandemic). 38 pre-service science teachers were included in the study. In this process, pre-service science teachers' conceptual development levels regarding computational thinking and their views regarding the use of ICT in schools were collected quantitatively. The development of computational problem-solving skills of pre-service science teachers was scored by a rubric developed in this study. According to the analyzes, pre-service science teachers increased knowledge of computational thinking (t = -5,969, p = 0.000), enhanced views regarding the use of ICT in schools (t = -2,436, p = 0.020), and developed computational problem-solving skills (X[superscript 2][subscript (2)] = 9.000, p = 0,011). These findings have the potential to provide evidence on how computational problem-solving skills can be integrated into science teacher education programs.
ABSTRACT
In this work we perform an analysis of distance learning format influence, caused by COVID-19 pandemic on school students' academic performance. This study is based on a large dataset consisting of school students grades for 2020 academic year taken from "Electronic education in Tatarstan Republic" system. The analysis is based on the use of machine learning methods and feature importance technique realized by using Python programming language. One of the priorities of this work is to identify the academic factors causing the most sensitive impact on school students' performance. In this work we used the Shapley values method for solving this task. This method is widely used for the feature importance estimation task and can evaluate impact of every studied feature on the output of machine learning models. The study-related conditional factors include characteristics of teachers, types and kinds of educational organization, area of their location and subjects for which marks were obtained.
ABSTRACT
This innovative practice full paper presents a case of teaching modeling, simulation, and performance evaluation course online during the COVID-19 pandemic for graduate students. The course includes theoretical and practical sessions with varying complexity. Students should have a good background in math, statistics, and probability. Students must also have good experience in one of the computer programming languages to solve the homework and work on the term project. The challenge is how to teach these topics online and engage the students in the course as they learn in face-to-face classes. Delivering the course using PowerPoint slides and a whiteboard is not suitable for teaching the class online. Therefore, there must be an alternative way to deliver the course online. We noticed a growing interest in using Jupyter Notebook in teaching, which motivated us to apply it to the mentioned course with some innovations. Jupyter Notebook is an open-source web application that allows us to create and share documents that contain live code, equations, visualizations, and narrative text. We want to share our experience teaching this course online using Jupyter Notebook in this innovative practice. We will share the course development plan, delivery mode, lessons learned, and student feedback. I will also highlight maximizing the benefits of the Jupyter Notebook using add-ins and tools useful for teaching, such as converting the Jupyter Notebook to a slide show. Developing courses in Jupyter Notebook could be time-consuming and frustrating, especially if there are a lot of math equations, tables, and drawings. This effort pays off in terms of the quality of the instruction and learning, and it gives students a tool to help them practice and engage with the course material. © 2022 IEEE.
ABSTRACT
In early 2020, COVID-19 appeared and widely spread worldwide. It affected all vital sectors, including commercial activities and education. Most governments decided to temporarily close educational institutions, including schools and universities. Developed countries with adequate learning-management systems moved to the online teaching mode. Hence, the sudden transition from the traditional to online teaching mode has impacted learning outcomes. The ultimate goal of this paper is to develop a method for evaluating the experience of teaching online during epidemics. More precisely, it assesses the teaching of programming language courses in the computer science and engineering college at the University of Hail. It statistically measures the courses' learning outcomes in the online mode compared to the traditional mode. Perhaps surprisingly, the difference was not significant, which shed light on the positive side of the crisis. According to the obtained results, the experience of teaching online during an epidemic has led us to investigate the opportunities of using online teaching, especially for programming language courses. This highlighted opportunities for using online platforms as supportive teaching tools or even merging them with traditional teaching approaches at times when attending classes on campus is impossible. Finally, to ensure best practices, the author recommended some guidelines to follow. © 2022 IEEE.
ABSTRACT
Computer programming is a complex field that requires rigorous practice in programming code writing and learning skills, which can be one of the critical challenges in learning and teaching programming. The complicated nature of computer programming requires an instructor to manage its learning resources and diligently generate programming-related questions for students that need conceptual programming and procedural programming rules. In this regard, automatic question generation techniques help teachers carefully align their learning objectives with the question designs in terms of relevancy and complexity. This also helps in reducing the costs linked with the manual generation of questions and fulfills the need of supplying new questions through automatic question techniques. This paper presents a theoretical review of automatic question generation (AQG) techniques, particularly related to computer programming languages from the year 2017 till 2022. A total of 18 papers are included in this study. one of the goals is to analyze and compare the state of the field in question generation before COVID-19 and after the COVID-19 period, and to summarize the challenges and future directions in the field. In congruence to previous studies, there is little focus given in the existing literature on generating questions related to learning programming languages through different techniques. Our findings show that there is a need to further enhance experimental studies in implementing automatic question generation especially in the field of programming. Also, there is a need to implement an authoring tool that can demonstrate designing more practical evaluation metrics for students. © 2022, International Journal of Advanced Computer Science and Applications. All Rights Reserved.
ABSTRACT
With significance in improving and developing local design culture as well as in supplementing global design history, this essay describes a study on the past and a clear prediction of the future by exploring Taiwan’s design history from approximately the 1960s to 2020 based on the evolution of theme, diversity, and sustainability. In this research, the Python programming language is used to apply three algorithms of term frequency–inverse document frequency (TF-IDF), Simpson’s diversity index (SDI), and latent Dirichlet allocation (LDA) to conduct a text exploration of design journals. The results show the following: in the 1960s–1980s, the evolution of theme focused on evaluation strategies, technical practices, and foreign cultures, on digital design, multiculturalism, and design aesthetics in the 1990s, and on emotional human factors, intelligent technology, and local culture since the beginning of the 21st century. Local culture and intelligent technology are the main driving forces of the current design industry. Regarding diversity, after a period of rapid change and stable rising, it has shown a downward trend in recent years. This indicates that current design needs to be stimulated by external environmental variations. Sustainability was focused on technology, the market, and education during the 1960s–1980s;on consumers, design education, and eco-design during the 1990s;and on integration across fields during the 2000s–2020. In order to gain a wider perspective of the complete design context of Chinese culture, the results show the current and future trends of the academic community, in addition to a reference for the study of the design histories of other areas in the world.
ABSTRACT
All first-year students at the J. B. Speed School of Engineering (SSoE) at the University of Louisville (UofL) are required to complete a two-course sequence. The purpose of the two-course sequence is to introduce incoming students to the fundamentals and profession of engineering. The first course in the sequence is titled Engineering Methods, Tools, & Practice I (ENGR 110) and primarily focuses on introduction to and practice with fundamental engineering skills. The second course Engineering Methods, Tools, & Practice II (ENGR 111) is a makerspace-based course primarily focused on application and integration of the fundamentals learned in ENGR 110. ENGR 111 includes a variety of fundamental skills in its instruction, one of which is programming. Therefore, all disciplines of SSoE engineering students are exposed to the basics and applications of programming through this course sequence. Programming instruction in ENGR 111 is designed to include relevant software development skills that students might encounter in the engineering profession. The students have learned initial programming skills in their ENGR 110 course through the Python programming language. In ENGR 111, students practice programming skills learned in ENGR 110 on two different platforms: Arduino Microcontrollers (Arduino) and Programmable Logic Controllers (PLCs). In normal face-to-face semesters, students are put into teams of 3 to 4 and given modules to develop and practice these skills (two for Arduino, two for PLCs). Due to the COVID-19 pandemic, ENGR 111 was augmented into a synchronous remote course to avoid close proximity and shared tools in the makerspace. Arduino programming instruction was performed using Tinkercad (tinkercad.com), a website that allows for Arduino programming and circuitry simulations. PLC instruction was performed utilizing a free online PLC simulator website, “PLCfiddle” [1]. At the end of each semester, students take a survey on their perceptions of the course. Included in this survey are questions pertaining to programming instruction. These questions assess student confidence in programming and platform preference. Results of these questions from Spring 2019 (a makerspace iteration) and Spring 2021 (a remote iteration) are compared in this paper. © American Society for Engineering Education, 2022.
ABSTRACT
This paper introduces a new set of infrastructures and online interactive tools that can be employed to motivate students to learn programming languages. The tools were used to experiment in one of the introductory first-year engineering courses. The final project of the course requires implementing an AI program for a game called “Reversi''. Reversi is a medium to hard level programming project that has been used in the course for several years requiring an immediate restructuring. Furthermore, due to COVID-19 and the restriction of in-person teaching, it has been a challenge for educators to excite, support, and encourage students. The new infrastructure provided an interactive platform for the students to familiarize themselves with the Reversi game project. It also provided a leaderboard, an interactive scoreboard, allowing students to compete with their classmates. The tools can instantaneously synchronize to students' code submission to help students check their latest ranking among their classmates in real-time. This increased students' level of engagement and learning. In addition, it allowed students to collaborate with their fellow classmates and discuss their algorithms. The tools and platform developed can also be employed in other courses as well other programming games. The result from students' surveys and the active trend of the class online discussion forum indicates that the new online interactive system created a positive atmosphere and increased students' motivation in learning programming languages. © American Society for Engineering Education, 2022.
ABSTRACT
In the spirit of innovation, the development of an intelligent robot system incorporating the basic principles of Industry 4.0 was one of the objectives of this study. With this aim, an experimental application of an industrial robot unit in its own isolated environment was carried out using neural networks. In this paper, we describe one possible application of deep learning in an Industry 4.0 environment for robotic units. The image datasets required for learning were generated using data synthesis. There are significant benefits to the incorporation of this technology, as old machines can be smartened and made more efficient without additional costs. As an area of application, we present the preparation of a robot unit which at the time it was originally produced and commissioned was not capable of using machine learning technology for object-detection purposes. The results for different scenarios are presented and an overview of similar research topics on neural networks is provided. A method for synthetizing datasets of any size is described in detail. Specifically, the working domain of a given robot unit, a possible solution to compatibility issues and the learning of neural networks from 3D CAD models with rendered images will be discussed.
ABSTRACT
In accordance with the new recovery plan, Next Generation EU (NGEU), and the need to speed up the transition of cities towards a new sustainable model, this paper provides an overview of the outcomes of the PEDRERA project, which is focused on the development of a novel tool able to calculate multiple key performance indicators that can support renovation actions at the district level, according to a Positive Energy District (PED) concept. The new tool is programmed in Python programming language and is useful to evaluate several strategies for the renovation of existing building stock. It moves from a quick list of input according to several Public Private Partnership (PPP) models, in addition to other potential business models. Furthermore, the design of the model is supported by a step-by-step methodology in order to deal with a “financial appraisal” that is interactive in each context, customizable for each stakeholder, and user-friendly. The paper describes this innovative tool and reports on the stronger potential that this model can offer when it runs in a QGIS software environment and interacts with a PostgreSQL database, as demonstrated in two case studies located in Spain.
ABSTRACT
Sentiment analysis is a classification technique that specializes in categorizing a body of texts into various emotions. This categorization had proven to be handy in classifying tweets into positive, negative, or neutral emotions. The focus of this paper is to determine the sentiment analysis of Indians and Americans. Using a lexicon-based analytic architecture and a dataset used for this research work was gotten from an online database Kaggle dataset called "All COVID-19 Vaccines Tweets". The dataset contains 125,906 entries with 16 columns with every country in the world from which tweets with location marked India and USA/United States were extracted. The analysis was done in Python Programming Software with the application of a python module TextBlob. The result shows that the Americans have larger positive sentiments over the Indians with 3.26%.
ABSTRACT
This article describes the development and assessment of RaspyLab which is a low-cost Remote Laboratory (RL) to learn and teach programming with Raspberry Pi and Python language. The RL is composed of 16 stations or nodes that contain hardware components such as display LCD, robotic arm, temperature sensor, among others, and two modes of programming (graphical and text-based) for the students to experiment with their designed algorithms. The concept of the RL was conceived as a pedagogical tool to support the students of Engineering and Computer Science (CS) in an online learning format, given the context of the COVID-19 pandemic. The laboratory has been used by ([Formula Omitted]) CS students during the second semester of 2020 in the subject of mathematical logic through the methodology of Problem-Based Learning (PBL). To evaluate preliminary the laboratory, it was used a survey with 3 open-ended questions and 12 closed-ended questions on a Likert scale according to the Technology Acceptance Model (TAM). The outcomes show a good reception of the laboratory, an enhancement of the students’ learning regarding the concepts addressed in the course, and an interest of the students for the laboratory to be included in other subjects of the curricula.
ABSTRACT
We might come across lots of paralyzed patients in our day-to-day life. The cause of the condition could be due to trauma because of accidents, stroke, polio etc., Depending on the nerve response to the brain and spinal cord, the specific parts of the body or even the whole body become paralyzed accordingly. To make distance communication between the patient and caretaker easier, we have implemented an IoT based system to send and receive an SMS by using LabVIEW Software. The patient can send the SMS easily by hand movements. The message will be sent according to the direction of the patient's hand movement. This Software is used to send, read the data to the cloud and message will be sent to the caretaker's mobile simultaneously. We have also used GSM in our project to send the message as SMS. The main motto of this project is to send the message to the caretaker as fast as possible. Besides paralysed individuals, visually impaired persons and Covid patients in hospitals who are unable to use a cell phone and need to make contactless communication with physicians, can utilize it. This gadget can be used for a multitude of long-distance communications. The prototype is relatively inexpensive and portable. © 2021 IEEE.
ABSTRACT
In this reporting period, the didactic coursework and training opportunities that were proposed for this project were completed. However, significant disruptions to research activities were encountered due to the ongoing COVID-19 pandemic response and ACURO approval delays. These factors led to the application and approval of a no cost extension to complete all proposed work. Nevertheless, all study approvals (IACUC, ACURO, HRPO) have been obtained and experiments using fibroblast growth factor receptor and androgen receptor inhibitors inpatient derived xenograft models are underway. The approved project objectives and scope will not change and the work to be completed in the extension period will include all experiments and analyses related to Specific Aim 1.