Prior Programming Knowledge Research Articles

PREPs: An Open-Source Software for High-Throughput Field Plant Phenotyping.

An open-source software for field-based plant phenotyping, Precision Plots Analyzer (PREPs), was developed using Window.NET. The software runs on 64-bit Windows computers. This software allows the extraction of phenotypic traits on a per-microplot basis from orthomosaic and digital surface model (DSM) images generated by Structure-from-Motion/Multi-View-Stereo (SfM-MVS) tools. Moreover, there is no need to acquire skills in geographical information system (GIS) or programming languages for image analysis. Three use cases illustrated the software's functionality. The first involved monitoring the growth of sugar beet varieties in an experimental field using an unmanned aerial vehicle (UAV), where differences among varieties were detected through estimates of crop height, coverage, and volume index. Second, mixed varieties of potato crops were estimated using a UAV and varietal differences were observed from the estimated phenotypic traits. A strong correlation was observed between the manually measured crop height and UAV-estimated crop height. Finally, using a multicamera array attached to a tractor, the height, coverage, and volume index of the 3 potato varieties were precisely estimated. PREPs software is poised to be a useful tool that allows anyone without prior knowledge of programming to extract crop traits for phenotyping.

Investigating the influence of temperature on salt solubility in water: a STEM approach with pre-university chemistry students

Abstract In a society heavily influenced by technological advancements, developing scientific and technological literacy among young people is essential. Along these lines, this research describes a STEM activity developed to promote the teaching of chemistry content related to the solubility of potassium nitrate in water. It also facilitated the mastery of technological skills such as programming Arduino microcontrollers and using Microsoft Excel as tools for automatic data acquisition and analysis. Eighty pre-university Chemistry students participated in this research. This pedagogical approach was divided into three main stages: (1) preliminary research on components used in the experimental apparatus; (2) introduction to the assembly of electrical circuits and Arduino programming; (3) experimental investigation of the dependence of potassium nitrate solubility on temperature. The activity allowed the students to successfully achieve the proposed chemistry learning objectives while mobilizing other scientific and technological knowledge and skills. Despite the students’ limited prior knowledge of programming and electronics, as well as their limited proficiency in data analysis software, the integration of programming in the Chemistry class proved to be a differentiating factor with a highly positive impact, particularly in terms of motivation and interest among most students.

Automation of the <i>Ad Hoc</i> Approach for Derandomization of Proteins: A Tutorial for Undergraduates in Molecular Sciences

Data analysis and manipulation software are vulnerable to user error during data processing and computations take considerable time when handling huge data and multiple repetitive tasks. These problems are usually mitigated by creating an app to repeat any given task reproducibly any number of times. This paper discusses the development of app that systematically automates the <i>ad hoc</i> approach for derandomization of proteins and, or peptides. Thirty second-year undergraduates with little-to-no prior knowledge of computer programming are (were) asked to create this app with modules that sequentially convert spectra from original units to molar extinction and subtract baseline spectrum from the resultant spectra, derandomize the spectra by removing suspected significant unfolded domains from them, concatenate the generated files to a single file in an acceptable format for structural analysis, process our group structural algorithm output files into a user-friendly format to ease data analysis. In addition, they are (were) asked to prepare protein solution, determine its concentration spectroscopically, collect circular dichroism measurements of the protein, derandomize the protein spectra, and determine the secondary structure of the resultant protein spectra with our structure algorithm. The assessment results demonstrated that the students could prepare samples for CD analysis, collect spectra of proteins, and create an app to automate the <i>ad hoc</i> approach. The hands-on activities enable students to acquire knowledge in basic programming and circular dichroism, CD spectroscopy.

PROpwr: a Shiny R application to analyze patient-reported outcomes data and estimate power

ABSTRACT Patient Reported Outcomes (PROs) are widely used in quality of life (QOL) studies, health outcomes research, and clinical trials. The importance of PRO has been advocated by health authorities. We propose this R shiny web application, PROpwr, that estimates power for two-arm clinical trials with PRO measures as endpoints using Item Response Theory (GRM: Graded Response Model) and simulations. PROpwr also supports the analysis of PRO data for convenience of estimating the effect size. There are seven function tabs in PROpwr: Frequentist Analysis, Bayesian Analysis, GRM power, T-test Power Given Sample Size, T-test Sample Size Given Power, Download, and References. PROpwr is user-friendly with point-and-click functions. PROpwr can assist researchers to analyze and calculate power and sample size for PRO endpoints in clinical trials without prior programming knowledge.

Impact of working with Arduino on mathematics and science teacher students’ self-assessment of TPACK and self-efficacy

To prepare mathematics and science teacher students for the implementation of digitally transformed teaching, we are developing and researching a course using the design-based research paradigm at the University of Graz. Based on the findings of curriculum analyses and surveys, we selected two main content areas for the course: digital data acquisition with Arduino and dealing with misinformation. Learning arrangements were developed based on empirical findings and theoretical foundations. The initial implementation of the course took place in the summer semester of 2022 with 17 teacher students. We examined the teacher students’ learning processes and the effectiveness of the learning arrangements in terms of the teacher students’ learning using a mixed-methods design (pretest, posttest, reflection journal, and field observations of course instructors). This article presents the triangulation of the research findings related to the work with Arduino and the derived criteria for redesigning the learning arrangements. The results show that self-assessment of technological competencies and self-efficacy expectations related to working with Arduino differ between teacher students with and without prior programming knowledge. Our findings suggest that there is a need to implement scaffolds that support teacher students as they undertake practical work with Arduino.

SRT-Server: powering the analysis of spatial transcriptomic data

BackgroundSpatial resolved transcriptomics (SRT) encompasses a rapidly developing set of technologies that enable the measurement of gene expression in tissue while retaining spatial localization information. SRT technologies and the enabled SRT studies have provided unprecedent insights into the structural and functional underpinnings of complex tissues. As SRT technologies have advanced and an increasing number of SRT studies have emerged, numerous sophisticated statistical and computational methods have been developed to facilitate the analysis and interpretation of SRT data. However, despite the growing popularity of SRT studies and the widespread availability of SRT analysis methods, analysis of large-scale and complex SRT datasets remains challenging and not easily accessible to researchers with limited statistical and computational backgrounds.ResultsHere, we present SRT-Server, the first webserver designed to carry out comprehensive SRT analyses for a wide variety of SRT technologies while requiring minimal prior computational knowledge. Implemented with cutting-edge web development technologies, SRT-Server is user-friendly and features multiple analytic modules that can perform a range of SRT analyses. With a flowchart-style interface, these different analytic modules on the SRT-Server can be dragged into the main panel and connected to each other to create custom analytic pipelines. SRT-Server then automatically executes the desired analyses, generates corresponding figures, and outputs results—all without requiring prior programming knowledge. We demonstrate the advantages of SRT-Server through three case studies utilizing SRT data collected from two common platforms, highlighting its versatility and values to researchers with varying analytic expertise.ConclusionsOverall, SRT-Server presents a user-friendly, efficient, effective, secure, and expandable solution for SRT data analysis, opening new doors for researchers in the field. SRT-Server is freely available at https://spatialtranscriptomicsanalysis.com/.

Fully immersive learning with virtual reality for assessing students in art history

Immersive learning systems using consumer grade headsets for virtual reality (VR) software can now reach the classroom. VR represents an important step toward situated learning for bringing realistic experiences to show to students different types of content the way it appears in real life. With the three-dimensional effect, it adds an immersive dimension that can bring the student into a unique environment that is directly connected to the learning content. While VR experiences can be helpful in educational settings, they must satisfy the learning objectives of the course and the specific needs of the students. In this paper, we propose a customizable VR application for displaying paintings for their analysis, and their associated questions designed for instructors in art history. To improve the accessibility and adaptivity to instructors and specific learning materials, we propose the definition of the paintings’ characteristics and the questionnaires associated with the paintings in the JSON open-standard file format, facilitating application changes without any prior programming knowledge. We compare the proposed VR modality with a web-based application on a computer desktop with 35 undergraduate students with art history experience. In both modalities, we assess the workload and usability; the VR sickness symptoms and the motivation in the VR condition. The results indicate better usability and lower workload with the VR condition. While there are no differences in terms of students’ performance for answering the questions, 77% of students prefer the VR condition. The Reduced Instructional Materials Motivation Survey shows a high motivation in the student population. Finally, the system evaluation supports the conclusion that the proposed VR system can be deployed in the art history classroom as the system has a high usability and medium workload.

Generating a Template for an Educational Software Development Methodology for Novice Computing Undergraduates: An Integrative Review

Aim/Purpose: The teaching of appropriate problem-solving techniques to novice learners in undergraduate software development education is often poorly defined when compared to the delivery of programming techniques. Given the global need for qualified designers of information technology, the purpose of this research is to produce a foundational template for an educational software development methodology grounded in the established literature. This template can be used by third-level educators and researchers to develop robust educational methodologies to cultivate structured problem solving and software development habits in their students while systematically teaching the intricacies of software creation. Background: While software development methodologies are a standard approach to structured and traceable problem solving in commercial software development, educational methodologies for inexperienced learners remain a neglected area of research due to their assumption of prior programming knowledge. This research aims to address this deficit by conducting an integrative review to produce a template for such a methodology. Methodology: An integrative review was conducted on the key components of Teaching Software Development Education, Problem Solving, Threshold Concepts, and Computational Thinking. Systematic reviews were conducted on Computational Thinking and Software Development Education by employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) process. Narrative reviews were conducted on Problem Solving and Threshold Concepts. Contribution: This research provides a comprehensive analysis of problem solving, software development education, computational thinking, and threshold concepts in computing in the context of undergraduate software development education. It also synthesizes review findings from these four areas and combines them to form a research-based foundational template methodology for use by educators and researchers interested in software development undergraduate education. Findings: This review identifies seven skills and four concepts required by novice learners. The skills include the ability to perform abstraction, data representation, decomposition, evaluation, mental modeling, pattern recognition, and writing algorithms. The concepts include state and sequential flow, non-sequential flow control, modularity, and object interaction. The teaching of these skills and concepts is combined into a spiral learning framework and is joined by four development stages to guide software problem solving: understanding the problem, breaking into tasks, designing, coding, testing, and integrating, and final evaluation and reflection. This produces the principal finding, which is a research-based foundational template for educational software development methodologies. Recommendations for Practitioners: Focusing introductory undergraduate computing courses on a programming syllabus without giving adequate support to problem solving may hinder students in their attainment of development skills. Therefore, providing a structured methodology is necessary as it equips students with essential problem-solving skills and ensures they develop good development practices from the start, which is crucial to ensuring undergraduate success in their studies and beyond. Recommendation for Researchers: The creation of educational software development methodologies with tool support is an under-researched area in undergraduate education. The template produced by this research can serve as a foundational conceptual model for researchers to create concrete tools to better support computing undergraduates. Impact on Society: Improving the educational value and experience of software development undergraduates is crucial for society once they graduate. They drive innovation and economic growth by creating new technologies, improving efficiency in various industries, and solving complex problems. Future Research: Future research should concentrate on using the template produced by this research to create a concrete educational methodology adapted to suit a specific programming paradigm, with an associated learning tool that can be used with first-year computing undergraduates.

Transitioning from Scratch to Java: A mixed method investigation into students' learning processes

This research examines the transition from Scratch to Java programming, highlighting high achievement among participants. The study includes 70 students and utilizes mixed methods, combining quantitative analysis and qualitative narratives. Findings demonstrate the effectiveness of Scratch Visual Teaching Aids (VTA) in developing educational games, understanding algorithm concepts, and improving programming projects. Students' attitudes towards Scratch VTA show increased interest, concentration, and enjoyment in learning. Quantitative analysis indicates positive tool capabilities (mean scores ranging from 3.25 to 3.46). Qualitative narratives reveal varying perceptions of the transition, with prior programming knowledge influencing the shift. Challenges include adapting to the learning session and mastering Java's syntax and concepts. This study enhances programming education practices, providing recommendations for educators during the Scratch-to-Java transition.

Enhancing elementary school students' computational thinking and programming learning with graphic organizers

Computational thinking is widely recognized as an essential skill for adapting to the current era, with programming learning being the most effective means to develop it. It is recommended that computational thinking and learning programming be introduced as early as elementary school. However, elementary school students often possess limited prior knowledge of programming, posing challenges in their learning process. The graphic organizers (GOs) may serve as a bridge between students’ existing knowledge and new learning, facilitating a deeper processing of the overall information and thereby enhancing the learning process. This can be particularly advantageous for early-stage learners when grappling with difficult subjects. Consequently, this study employed GOs to assist elementary school students in their computational thinking and programming learning, employing a quasi-experiment design to evaluate their effectiveness. The results showed that although all students demonstrated awareness of applying computational thinking to solve problems, those exposed to GO-based instruction exhibited higher levels of computational thinking, programming skills, and flow experiences.

Statistical evaluation of the achievements of professional students by combination of the random forest algorithm and the ANFIS method

This research is of great importance because it applies artificial intelligence methods, more specifically the Random Forest algorithm and the Anfis method to research the key factors that influence the success of students in vocational schools. Identifying these influencing factors is not only useful for improving curriculum and practice but also provides valuable guidance to help students master the material more effectively. The main goal of this research is to penetrate deeply into the core of the factors that influence the success of students in vocational schools, using two different methods. Each of the factors represented as input is mutually independent and does not affect each other, but each of them affects the output variable. The parameters considered as input variables are prior programming knowledge and pretest requirements. Then, by finding one factor that has the greatest influence, the factor of pre-exam obligation was investigated in more detail, using the Anfis method, which was broken down into several input parameters. These results emphasize the importance of the combination of the Random Forest algorithm and the ANFIS method in the statistical evaluation and assessment of student achievement in vocational schools. This study provides useful guidelines for improving education and practice in vocational schools to optimize educational outcomes.

ComsystanJ: A collection of Fiji/ImageJ2 plugins for nonlinear and complexity analysis in 1D, 2D and 3D.

Complex systems such as the global climate, biological organisms, civilisation, technical or social networks exhibit diverse behaviours at various temporal and spatial scales, often characterized by nonlinearity, feedback loops, and emergence. These systems can be characterized by physical quantities such as entropy, information, chaoticity or fractality rather than classical quantities such as time, velocity, energy or temperature. The drawback of these complexity quantities is that their definitions are not always mathematically exact and computational algorithms provide estimates rather than exact values. Typically, evaluations can be cumbersome, necessitating specialized tools. We are therefore introducing ComsystanJ, a novel and user-friendly software suite, providing a comprehensive set of plugins for complex systems analysis, without the need for prior programming knowledge. It is platform independent, end-user friendly and extensible. ComsystanJ combines already known algorithms and newer methods for generalizable analysis of 1D signals, 2D images and 3D volume data including the generation of data sets such as signals and images for testing purposes. It is based on the framework of the open-source image processing software Fiji and ImageJ2. ComsystanJ plugins are macro recordable and are maintained as open-source software. ComsystanJ includes effective surrogate analysis in all dimensions to validate the features calculated by the different algorithms. Future enhancements of the project will include the implementation of parallel computing for image stacks and volumes and the integration of artificial intelligence methods to improve feature recognition and parameter calculation.

Creative Console: A Player-Driven Game Based on a Modular Fast-Evolving-and-Verifying Framework

We present Creative Console, a player-driven game in which a player, without prior knowledge of game programming, can design and realize a game within 15 minutes. Players design a game by selecting, adding, or changing a game component and then playtesting the game immediately. We refer to this central process as the Fast-Evolving-And-Verifying (FEAV) module. Players play successive FEAV modules, each taking around 3 minutes, and progressively complete a game design. We conducted an exploratory study of Creative Console. Within 48 hours, all 21 participants developed 527 game levels, covering 10 genres of games. The study demonstrates that Creative Console is enjoyable to play and effectively empowers creative and diversified game design. We furthermore conducted a grounded theory analysis of their design process. Our analysis concludes that modular FEAV, serendipity, and social communication are the three pillars of Creative Console, which casts light on future player-driven creative design systems.

COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2.

Implementing a specific cloud resource to analyze extensive genomic data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a challenge when resources are limited. To overcome this, we repurposed a cloud platform initially designed for use in research on cancer genomics (https://cgc.sbgenomics.com) to enable its use in research on SARS-CoV-2 to build Cloud Workflow for Viral and Variant Identification (COWID). COWID is a workflow based on the Common Workflow Language that realizes the full potential of sequencing technology for use in reliable SARS-CoV-2 identification and leverages cloud computing to achieve efficient parallelization. COWID outperformed other contemporary methods for identification by offering scalable identification and reliable variant findings with no false-positive results. COWID typically processed each sample of raw sequencing data within 5min at a cost of only US$0.01. The COWID source code is publicly available (https://github.com/hendrick0403/COWID) and can be accessed on any computer with Internet access. COWID is designed to be user-friendly; it can be implemented without prior programming knowledge. Therefore, COWID is a time-efficient tool that can be used during a pandemic.

SENTIMEN ANALISIS CHATGPT DENGAN ALGORITMA NAÏVE BAYES DAN OPTIMASI PSO

Abstract— ChatGPT which is an OpenAI technology that responds to conversations between humans and machines. enabling users of all ages and backgrounds to communicate naturally in multiple languages ​​without having prior knowledge or experience in programming or the computer world. However, a technology will always be at odds and has flaws on the human side, various assumptions about chatGPT are formed from many sides, such as in the world of education, chatGPT creates parallels for teachers and lecturers. When giving assignments, students/students can use chatGPT as material in answering assignments from teachers/lecturers. And that results in students/students not carefully reading the answers to these assignments, if that continues to happen, students/students will find it too easy to get something and then will lose interest in solving problems with their own efforts. This article aims to analyze sentiment analysis whose data is taken from Twitter using the keyword "CahtGPT OpenAI". With 2,000 data calculated using the naive Bayes algorithm and optimized using PSO, it is found that sentiment analysis for chatGPT itself has an accuracy of 69.23% with a positive class of 0.503 and a negative of 0.497 and obtains an AUC curve value of 0.68 +/- 0.55..

A Review on Web Content Management system (WCMS) Features and Software

Web Content Management System, a type of Content Management System, allows an organization to handle digital information on a website by creating and handling content without prior knowledge of programming or markup languages. The management of online material is beneficial for organizational business applications, producing statistics for decision-making and accomplishing results. The components, functions, software, applications, and benefits and drawbacks of online content management systems have been covered in this study.

Teaching Academic Staff to Implement Interactive Graphics for Their Courses

Many academic teachers present data as static graphics in their lectures and courses. However, data structures have become more complex in the last decades, especially in the biomedical disciplines, and interactive graphics can provide a better means to communicate the scientific contents to students. Besides, the technological qualifications of academic staff are diverse, and it has been little studied how these teachers can be trained to program and implement interactive graphics for their courses. It is also little known whether interactive graphics will be helpful for teaching and learning. We conducted a pilot online workshop to identify aspects that need to be addressed when teaching academic staff to program interactive graphics in form of Shiny-apps based on the programing language R. The n = 25 participants were academic staff from the fields of medicine or natural sciences. Pre- and post-workshop questionnaires were used to identify which aspects should be considered in future workshops, to query the usefulness of interactive graphics for teachers and students, and to identify the impact of the workshop on the teacher’s opinion towards digital teaching devices and their preparedness to program own interactive graphics. Most participants showed strong interest to use interactive graphics in their courses after the workshop, and interactive graphics were overall rated as very helpful for teachers and students. However, only those with prior programming knowledge intended to implement own graphics. We conclude that an extension of the workshop will be necessary to provide additional training for participants with no background in R programming.

Introduction to artificial intelligence and deep learning using interactive electronic programming notebooks.

Artificial intelligence (AI), or deep learning (DL), approaches have already found their way into our everyday lives. Furthermore, these methods are a central part of research in the life and natural sciences and have been applied in the form of machine learning for decades. In pharmaceutical and medicinal chemistry, and in computer-aided drug discovery, current developments are also changing the way drugs are developed. It is essential to familiarize students with AI methods already during their studies and prepare them for future tasks and challenges. We developed a set of interactive learning materials based on cheminformatics examples that can be used to establish such introductory AI courses in the life and natural sciences. These interactive notebooks are easily accessible without the need for installation, and no prior programming knowledge is required. Through these notebooks, students can easily study how AI/DL works and how these methods can be applied. This knowledge will foster a general competence when interacting with and evaluating future DL applications later in their career. The materials are freely available and publicly accessible through a GitHub repository in German and English.

A Generalized Estimating Equations Approach to Investigate Predictors of Teacher Candidates’ Views of Coding

This paper reports the analysis of data from five different studies to identify predictors of preservice, early childhood teachers’ views of (a) the nature of coding, (b) integration of coding into preschool classrooms, and (c) relation of coding to fields other than computer science (CS). Significant changes in views of coding were predicted by time, prior robot programming experience, and perceptions of the value of coding. Notably, prior programming knowledge and positive perceptions of mathematics predicted decreases in views of coding from pre- to post-survey.

Developing a weather prediction project-based machine learning course in facilitating AI learning among high school students

The rapid growth of artificial intelligence (AI) technology has changed lifestyles, work patterns, and educational approaches. However, courses that can guide students through the practical applications of AI technology are still scarce in K-12 education. This study aimed to develop a project-based machine learning (ML) course for the implementation of AI technology. The core idea of this course, which focused on the supervised learning of AI ML technology, was designed based on the project of weather prediction. Furthermore, data collection and status display were realized using various hardware devices such as Arduino and sensors, whereas ML algorithms were implemented in Python programming language. A total of 68 eleventh-grade senior high school students from a public school in Southern Taiwan participated in this study. The main variables included understanding AI concepts, computational thinking (CT), and learning attitude. Data were analyzed using quantitative statistics, including descriptive statistics, t-test, and analysis of covariance, supplemented with qualitative data. Based on the findings, the following conclusions were drawn: (1) the proposed course on the implementation of ML helps students understand the basic concepts of AI; (2) students demonstrate a significant improvement in CT skills after attending this course; (3) although the students’ attitude toward learning AI shows no significant change after attending this course, their overall view for it is positive; (4) contrary to their learning attitude, the CT skills among the students with different capabilities of learning AI are significantly dissimilar. Overall, the machine-learning implementation course developed in this study can serve as a reference for promoting AI education in the future. However, considering learners’ prior knowledge in programming, setting up appropriate learning scaffolding for them, and providing them with more examples of the applications of AI in real-life scenarios is still necessary when conducting the course for improving the students’ attitude toward AI.