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The current state of the labor market requires modern engineers to acquire programming skills at different levels of advancement and to apply them in multidisciplinary environments. Not all modern engineers will become fully fledged programmers, but sometimes the possibility to use low-code programming environments like LabView or MIT App Inventor will be sufficient. In order to give good foundations for adulthood, schools use elements of visual programming, e.g., Scratch or StarLogo, to enhance the critical and algorithmic thinking of future engineers. This article attempts to answer the question of whether anyone cares about following general accessibility and usability guidelines in the case of solutions like Scratch, App Inventor, and StarLogo. Another goal is to show a set of tools that is successful in such an assessment. The authors used Nielsen's heuristics, followed by analyzing WAVE output and Web Content Accessibility Guidelines compliance. Especially, the last one provides insights usually omitted when evaluating low-code environments. It was found that Scratch and App Inventor are leading solutions in terms of look and feel, functionality, documentation, interface navigation, and memorization. The StarLogo interface, on the other hand, is less friendly in terms of aesthetics and functionality. [ABSTRACT FROM AUTHOR]

Programming is a digital competence necessary for life in the 21st century. In recent decades, education systems around the world have redefined curricula to include programming as a standalone subject or integrated into other subjects, from an early age. In addition to formal education, programming is also taught in non-formal educational contexts (NEC) and the use of educational robots is becoming more common. The aim of this paper is to familiarize with the advantages and challenges of using Sphero robots (BB-8 and SPRK+) in teaching visual programming in the NEC and to formulate practical implications. The research was conducted as a part of the Learning for the 21st Century project in 17 cities in Serbia. The quantitative research included 677 students (Mage = 12.16; SD = 1.10), and the qualitative 42 students and 5 workshop leaders. Descriptive quantitative and qualitative, thematic analysis was applied. The results show that using robots has additional educational and motivational value in the process of teaching visual programming and algorithmic thinking. From the point of view of the students and workshop leaders, the NEC has a number of advantages compared to traditional teaching of programming: learning through play, experiential learning, creativity and initiative of participants, insight that programming can be interesting, even though it is “hard”. Challenges are formulated in the paper, as well as practical recommendations for teaching practice.

Secondary school students (N = 269) participated in a daylong visual programming course held in a stimulating environment for start‐up enterprises. The tasks were application‐oriented and partly creative. For example, a wearable device with light‐emitting diodes, (ie, LEDs) could be applied to a T‐shirt and used for optical messages. Our research questions related to the control‐value model of achievement emotions. We measured experienced enjoyment four times and examined the dependence of enjoyment on the individual tasks. Experience of enjoyment was also tested for the prediction of students' self‐efficacy for programming. The results showed that momentary enjoyment was not significantly dependent on the task situation, but it was dependent on the general enjoyment of programming. However, students with lower enjoyment scores showed higher increases in enjoyment during the final tasks than those with higher initial scores. The emotion score of the girls increased more than those of the boys but the girls' overall enjoyment scores were lower than those of the boys. Students' self‐efficacy beliefs of both genders increased over the course, and some of the differences in beliefs can be explained by the enjoyment of the course. In conclusion, our teaching approach seemed beneficial for the motivation to learn programming, particularly among girls. Practitioner notes What is already known about this topic Lower secondary students often report a lack of self‐efficacy beliefs for visual programming, especially girls whose confidence in their abilities seems to be missing. Activities that show how programming can be used in everyday life or at work promote interest and enjoyment, especially among girls. What this paper adds Experiencing enjoyment did not depend on individual task types (more structured vs. more open), but proved to be stable across all tasks. The experience of positive emotions in our computer science course had an impact on the secondary school students' self‐efficacy beliefs. Implications for practice and/or policy The combination of smart textiles and programming was viewed as a motivating learning experience with the potential to foster secondary school students' confidence and problem‐solving skills in computer science. A guided sequence of learning to debug can provide a self‐enhancing foundation for the students' own activities with following tasks that are more open and creative approaches. What is already known about this topic Lower secondary students often report a lack of self‐efficacy beliefs for visual programming, especially girls whose confidence in their abilities seems to be missing. Activities that show how programming can be used in everyday life or at work promote interest and enjoyment, especially among girls. What this paper adds Experiencing enjoyment did not depend on individual task types (more structured vs. more open), but proved to be stable across all tasks. The experience of positive emotions in our computer science course had an impact on the secondary school students' self‐efficacy beliefs. Implications for practice and/or policy The combination of smart textiles and programming was viewed as a motivating learning experience with the potential to foster secondary school students' confidence and problem‐solving skills in computer science. A guided sequence of learning to debug can provide a self‐enhancing foundation for the students' own activities with following tasks that are more open and creative approaches. [ABSTRACT FROM AUTHOR]

This study explores the transformative potential of integrating Building Information Modeling (BIM) and Generative Design methodologies in heritage conservation and building management. By utilizing BIM, detailed architectural, structural, and MEP models were created, facilitating precise design and effective stakeholder collaboration. Generative Design enabled the exploration of multiple design solutions, optimizing spatial layouts and structural integrity. The project also integrated automated management systems and IoT sensors to enhance real-time monitoring, energy efficiency, and user comfort through the development of a digital twin. Despite encountering challenges such as technical complexities and budget constraints, the project successfully preserved the cinema's historical essence while incorporating modern functionalities. The findings highlight the contributions of BIM and Generative Design to the AEC industry, emphasizing their role in improving design accuracy, operational efficiency, and sustainability. This research provides valuable insights for future projects in heritage conservation, offering a blueprint for balancing historical preservation with contemporary needs. The revitalization of the "Ex Cinema Santa Barbara" in Paternò exemplifies these advancements, demonstrating how these technologies can restore and modernize culturally significant historical buildings effectively. [ABSTRACT FROM AUTHOR]

Pocket Code is a visual programming-based mobile application for creating games, animations, music, videos, and other types of applications. This paper presents the integration of face recognition capabilities into Pocket Code through a visual programming interface based on the FaceNet architecture. The FaceNet dataset is used to train and deploy a face recognition model in Pocket Code visual programming. Integration of the FaceNet algorithm into Pocket Code aims to enhance the accessibility and simplicity of facial recognition technology for students and developers. Building face recognition applications typically involves writing complex code, which can be challenging for both beginners and experienced developers. The Pocket Code visual programming blocks have simplified the process, enabling anyone to easily incorporate face detection into their projects, irrespective of their coding experience. The article discusses the implementation and performance assessment of the FaceNet algorithm in Pocket Code visual programming. [ABSTRACT FROM AUTHOR]

The transformative wave of generative AI is reshaping the creative thinking processes of learners, posing a significant challenge to education and industry in cultivating technological literacy and creativity. This study delves into the exploration of how learners can effectively tackle new challenges by deconstructing fragments from a macro perspective and generating innovative methods or concepts. In the Scratch visual programming environment, learners in the self-regulated learning mode observed entire functioning projects, facilitating easy disassembly and learning, namely by using Code Decomposed by Learner (CDBL). A total of 104 fifth-grade students were divided into two learning scaffoldings: (1) domain-general, learning from the top down (CDBL-TD), and (2) domain-specific, learning from the bottom up (CDBL-BU). Students in the CDBL-TD group exhibited a high degree of completion, strong exploration abilities, and the willingness to experiment with unlearned functions. Although there was no significant difference in originality between the two groups, students in the CDBL-TD group showcased greater uniqueness in designing characters or items within the game. This study introduces a novel programming learning scaffolding, offering instructors a tool to guide students' creativity and enhance their programming capabilities. [ABSTRACT FROM AUTHOR]

The optimal structural design is imperative in order to minimize material consumption and reduce the environmental impacts of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as the genetic algorithm (GA). However, the integration of AI-based optimization, together with visual programming (VP), in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps, including the following: (i) generation of parametric trusses in Dynamo VP; (ii) performing finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. This methodology provides a new interoperable framework with minimal interference with existing supply-chain processes, and it will be flexible to technology literacy and allow architectural, engineering and construction (AEC) professionals to employ VP, global optimization, and FEM in BIM-based projects by leveraging open-sourced software and tools, together with commonly used design software. The feasibility of the proposed workflow was tested on benchmark problems and compared with the open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction. Despite the success of this study in developing a workable, user-friendly, and interoperable framework for the utilization of VP, GA, FEM, and BIM for structural optimization, the results obtained could be improved by (i) increasing the callback function speed between Dynamo and RSA through specialized application programming interface (API); and (ii) fine-tuning the GA parameters or utilizing other advanced global optimization and supervised learning techniques for the optimization. [ABSTRACT FROM AUTHOR]

The emergence of foundation models, such as large language models (LLMs) GPT-4 and text-to-image models DALL-E, has opened up numerous possibilities across various domains. People can now use natural language (i.e., prompts) to communicate with AI to perform tasks. While people can use foundation models through chatbots (e.g., ChatGPT), chat, regardless of the capabilities of the underlying models, is not a production tool for building reusable AI services. APIs like LangChain allow for LLM-based application development but require substantial programming knowledge, thus posing a barrier. To mitigate this, we systematically review, summarise, refine and extend the concept of AI chain by incorporating the best principles and practices that have been accumulated in software engineering for decades into AI chain engineering, to systematize AI chain engineering methodology. We also develop a no-code integrated development environment, Prompt Sapper , which embodies these AI chain engineering principles and patterns naturally in the process of building AI chains, thereby improving the performance and quality of AI chains. With Prompt Sapper, AI chain engineers can compose prompt-based AI services on top of foundation models through chat-based requirement analysis and visual programming. Our user study evaluated and demonstrated the efficiency and correctness of Prompt Sapper. [ABSTRACT FROM AUTHOR]

Today computing is intricate in all aspects of our lives, beginning with communications and education to banking, information security, health, shopping, and social media. Development of the computing is proportional to the development of software which is becoming a serious part of all daily lives. This paper, therefore, assessed the impact of teaching Computer Programming Language in Tanzanian primary schools. To achieve this, a new tool for teaching and learning a computer programming language was developed. Furthermore, a two-tier approach was adopted where the training started on an algorithm first, then if, loops and case conditionals as the third concept inside the first tier. On the other hand, variables, lists, and functions are hooked on the second tier. Results indicate that students acquired together reasoning learning in a conceptual argument of view and skill performance. Students were able to accomplish the expertise to practice or apply the theories of programming knowledge in programming-connected tasks. [ABSTRACT FROM AUTHOR]

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Design for Manufacturing (DfM) is becoming increasingly important in computer-aided design (CAD) due to the growing complexity of products. Automatically evaluating design rules for manufacturability from CAD dimensions and geometry is one effective approach for DfM. However, implementing automated design-rule-checks requires coding complex programs on CAD systems and the expertise to implement them, which make it difficult to adopt the approach, or implement product-specific design-rules. In this study, to mitigate this barrier, we developed a visual programming environment for the design-rule programs and a graph neural network (GNN) based recommender system that assists users to create the visual program. The proposed visual programming environment allows users to make design rules by placing and connecting shape recognition and measurement function nodes. This simplifies and improves the programming interface. Furthermore, the proposed recommender system predicts the subsequent function node that users will append, which reduces the user’s cognitive load of choosing the right function nodes. By employing proposed GNN architecture in the visual program recommender system, the input-output relationships between the function nodes and their input arguments are naturally taken into account to produce accurate recommendations. We evaluated the performance of the proposed recommender in the off-line experiment and the experiment in real-world use. The results in both experiments demonstrate that the proposed GNN based visual program recommender system can suggest the function nodes in sufficient accuracy, which contributes to improved productivity of implementing automatic CAD design-rule-checks.

Introduction. Energy is one of the most important issues that attract the attention of the whole world, and this in turn is reflected in the increase in energy consumption in residential and industrial buildings Therefore, the process of assessing the efficiency and quality of interior spaces is an important step from which the process of developing and upgrading these spaces begins to reach a sustainable model from an environmental, economic and social point of view.Materials and methods. The research aims to study the distribution patterns of residential divisions and their reflection on the energy of a residential suburb consisting of twenty residential buildings in Tartous Governorate, through the development of a software tool using Dynamo, which is one of the visual programming methods used in (BIM) using a programming language (Python) with the addition of studying heating and air conditioning loads for current orientation with comparison with loads after directing the building at different angles in order to reduce consumption and benefit from solar radiation sources through Revit. An analytical approach was used, through the analysis and extrapolation of the literature and references related to the study, in addition to the deductive approach by deducing problems in the current situation and providing suggestions for solutions that can be followed in the management and analysis of energy.Results. The BIM approach contributed to the study of the building orientation and its reflection on thermal loads, taking into account all the factors causing this load, which can be adjusted according to any requirements or code.Conclusions. Studying the building orientation during the design stage contributes to reducing the total annual heat load by more than 20 %, and this percentage varies according to the way buildings are assembled.

Today, with increasing access to the internet and portable computing tools, the possibility of utilizing these tools in education has significantly expanded. Consequently, various tools have been introduced for creating and developing content and designing mobile-based educational courses. One of the essential and widely used tools for content creation and mobile-based course development is the MIT App Inventor tool, developed by a group of researchers at the Massachusetts Institute of Technology (MIT). It requires guidance on using this technology tool for content production in designing and implementing practical educational courses in health-related domains. This article aims to introduce the App Inventor software and its utilization in Technological Pedagogical Content Knowledge (TPACK). The tool is particularly beneficial for individuals outside the tech industry who seek to incorporate educational applications into teaching and learning processes.

The current state of the labor market requires modern engineers to acquire programming skills at different levels of advancement and to apply them in multidisciplinary environments. Not all modern engineers will become fully fledged programmers, but sometimes the possibility to use low-code programming environments like LabView or MIT App Inventor will be sufficient. In order to give good foundations for adulthood, schools use elements of visual programming, e.g., Scratch or StarLogo, to enhance the critical and algorithmic thinking of future engineers. This article attempts to answer the question of whether anyone cares about following general accessibility and usability guidelines in the case of solutions like Scratch, App Inventor, and StarLogo. Another goal is to show a set of tools that is successful in such an assessment. The authors used Nielsen’s heuristics, followed by analyzing WAVE output and Web Content Accessibility Guidelines compliance. Especially, the last one provides insights usually omitted when evaluating low-code environments. It was found that Scratch and App Inventor are leading solutions in terms of look and feel, functionality, documentation, interface navigation, and memorization. The StarLogo interface, on the other hand, is less friendly in terms of aesthetics and functionality.

Fascinating 3D shapes arise when a thin planar sheet is folded without stretching, tearing or cutting. The elegance amplifies when the fold/crease is changed from a straight line to a curve, due to the association of plastic deformation via folding and elastic deformation via bending. This results in the curved crease working as a hinge support providing deployability to the surface which is of significant interest in industrial engineering and architectural design. Consequently, finding a stable form of curved crease becomes pivotal in the development of deployable structures. This work proposes a novel way to evaluate such curves by taking inspiration from biomimicry. For this purpose, growth mechanism in plants was observed and an analogous model was developed to create a discrete curve of fold. A parametric model was developed for digital construction of the folded models. Test cases were formulated to compare the behavior of different folded models under various loading conditions. A simplified way to visualize the obtained results is proposed using visual programming tools. The models were further translated into physical prototypes with the aid of 3D printing, hybrid and cured-composite systems, where different mechanisms were adopted to achieve the folds. The prototypes were further tested under constrained boundary and compressive loading conditions, with results validating the analytical model. [ABSTRACT FROM AUTHOR]

Research suggests that girls' initial interest in computer science tends to decline during their teenage years, a trend that is not observed among boys. This paper addresses this gender gap and proposes integrating programming into handicraft lessons to provide a creative activity for all students. The project was conducted in three Austrian schools over one year (2019-2020), involving 229 middle school students. The evaluation included questionnaires and the assessment of programmed and stitched designs to structure gender-sensitive workshops. While boys consistently reported higher scores than girls in interest, sense of belonging, and enjoyment, girls' scores remained more stable. However, girls were significantly more likely to express pride in their final designs than boys, and overall, more girls completed individual designs as final products. These findings can be applied to interdisciplinary handicraft lessons in line with the Maker-Education movement to foster interest in programming. [ABSTRACT FROM AUTHOR]

Today, with increasing access to the internet and portable computing tools, the possibility of utilizing these tools in education has significantly expanded. Consequently, various tools have been introduced for creating and developing content and designing mobile-based educational courses. One of the essential and widely used tools for content creation and mobile-based course development is the MIT App Inventor tool, developed by a group of researchers at the Massachusetts Institute of Technology (MIT). It requires guidance on using this technology tool for content production in designing and implementing practical educational courses in health-related domains. This article aims to introduce the App Inventor software and its utilization in Technological Pedagogical Content Knowledge (TPACK). The tool is particularly beneficial for individuals outside the tech industry who seek to incorporate educational applications into teaching and learning processes. [ABSTRACT FROM AUTHOR]

Learning basic concepts of programming resulting in a development on computational thinking (CT) can be reached by means of digital programming environments. As a counterpart, the application of unplugged programming activities seems also to have promising potential regarding the impact on CT. The main characteristic of unplugged programming is that it comprises activities without the use of information and communication technologies (ICT). Since previous research has shown that the application of sense-reason-act (SRA) programming with different types of output demonstrated a better understanding of underlying complex programming concepts with an impact on CT, our research investigates whether the application of unplugged programming, offered via SmartGames, can also generate such a distinctive impact on developing CT. To capture the effects of the different interventions applied, a mixed-methods study was conducted among primary school students aged ten to twelve. Research data were obtained by means of a pretest–posttest questionnaire survey using the validated Computational Thinking Test (CTt), and by conducting interviews to determine the effects of CT and to ascertain identifiable learning effects. Our research indicates that unplugged programming by applying SmartGames can be a consummate regarding the development of CT, similar to SRA-programming using either robotics with tangible output or robot simulations with on-screen output. The research findings identified support our claim that the application of unplugged SmartGames shows equivalent development on CT sub-characteristics in comparison with plugged-in SRA-programming with tangible or on-screen output. A better understanding of complex programming concepts and positive identified learning effects could only be partly demonstrated. [ABSTRACT FROM AUTHOR]

The design processes based on parametric design and generative design allows multiple alternatives to be generated, analysed and corrected. The aim of the developed program was to automate the urban design concept development process for selected land units with a local development plan. This document, ordinances and other sources were the guidelines for the program to be developed. The solution-generating program starts by taking in the data, and then geometrical objects are created that have the right relationships to each other. Finally, results are evaluated on the basis of calculated indices and further generations are created taking into account the best options. This process must be overseen by a human, but with the development of machine learning and artificial intelligence, automation will progress, reducing human effort. The results of the study were collated and compared with other experiments in an in-depth literature review. [ABSTRACT FROM AUTHOR]

Modern education demands innovative approaches to engage students effectively and enhance learning outcomes. This article explores the implementation of an innovative pedagogical approach, namely Project-Based Learning (PjBL), in the context of the Visual Programming course. The study aims to investigate the impact of this approach on students’ participation and learning achievements. Using a Classroom Action Research (CAR) design, the research was conducted in two cycles. The participants were 30 students enrolled in the Educational Technology Informatics program at Universitas Negeri Padang. The study used a descriptive comparative method to assess the outcomes, comparing pre-cycle to Cycle II results. The findings reveal remarkable improvements in student’s cognitive growth (53.33%), affective development (46.66%), and psychomotor skills (56.66%) following the application of the PjBL approach. Furthermore, there was a noticeable increase of 43.44% in the active participation of students during the learning process after incorporating the PjBL approach. In conclusion, this study underscores the effectiveness of PjBL in fostering active participation and elevating learning achievements in the Visual Programming course. The article contributes to the discourse on innovative pedagogical strategies. It highlights the potential of PjBL to revolutionize traditional educational methods, equipping students with skills engagingly and effectively. [ABSTRACT FROM AUTHOR]

Abstract. Simulation models are primary tools for synthesizing plant physiological knowledge, supporting farmers' decisions and predicting crop yields and functioning under climate change. The conventional approach within the scientific community consists of disseminating model outcomes through articles and technical reports, often impeding the share of knowledge among science, policy and society. This work presents the mandala (m odelled and a bstracted p la nt), a simulation model translating crop phenology and physiology as a function of environmental drivers into symbols and sounds, focussing on plant responses to cold, drought and heat stresses. The mandala has been realized with object-oriented (C#) and visual (vvvv) programming, and the source code is free for extension and improvement. We tested the mandala in six heterogeneous climates to show the potential to convey essential information on maize and wheat growth and responses to abiotic stresses. Despite lacking in artistic refinement, this work attempts to illustrate that visual and sound art can serve as unconventional means of disseminating crop model insights while showing their potential to enhance the breadth of information delivered to the public. [ABSTRACT FROM AUTHOR]

Reproducibility, replicability, and expandability (RRE) have emerged as fundamental concerns in the realm of scientific research and development. Wherein, devising effective solutions for RRE within geospatial analysis stands out as a particularly critical challenge that demands immediate attention. Although there has been an evolution from basic reproducibility of code and data to a more comprehensive cyberinfrastructure, this integrated solution is still grappling with issues of limited user accessibility, steep learning curves particularly in coding skills, and difficulties in achieving collaboration with other data science platforms This study proposes a framework that combines open-source GIS with visual programming platforms, grounded in principles of standardization and educationalization, to advance the RRE framework in geographic analysis. Using the Geospatial Analytics Extension for KNIME as an example, we demonstrate the platform’s adaptability and utility through case studies in a recent textbook with an in-depth illustration of spatial accessibility analysis, specifically via the Generalized Two-Step Floating Catchment Area (G2SFCA) method. Our findings shed light on the transformative potential of such an integrative strategy, offer fresh perspectives for enhancing the RRE in geospatial analysis and craft a well-structured, intuitive, and extensive GIS knowledge tree.

Introduction. The current practice of pile foundation selection is a time-consuming, incoherent and non-standardized process. The aim of the study is to develop a methodology for optimizing structural calculations on the example of a pile field, based on cone penetration test data. For this purpose it is necessary: to prepare an algorithm for processing data from engineering-geological surveys; to develop a strictly deterministic process of justification of the best option depending on the cost of the pile foundation; to obtain a visual representation of the data for the possibility of verification of the selected solution.Materials and methods. A genetic algorithm is used to optimize structural calculations of the pile field, which is implemented using the Galapagos plug-in based on the Grasshopper visual programming language. Python programming language is used to prepare initial data of geotechnical engineering surveys.Results. Linked algorithms for cone penetration test data processing and preliminary estimation of the optimal pile foundation configuration based on its total cost, on the bearing capacity of the pile foundation soil were developed.Conclusions. The developed algorithms can be used for preliminary calculation and rapid evaluation of pile foundation options. The required input data can be generated from calculation programmes. Alternatively, selection and optimization can be performed directly in Python code, using Grasshopper and Rhino only for force extraction and subsequent visualization of the results. Areas for further research and development include: consideration of layered geotechnical elements; estimation of the bearing capacity of each foundation footing independently and according to the underlying geotechnical elements; grouping of piles according to their position in the pile field and loads; consideration of the non-linear behaviour of the soil mass.

The Geospatial Analytics Extension for KNIME (GAEK) is an innovative tool designed to integrate visual programming with geospatial analytics, streamlining GIS education and research in social sciences. GAEK simplifies access for users with an intuitive, visual interface for complex spatial analysis tasks and contributes to the organization of the GIS Knowledge Tree through its geospatial analytics nodes. This paper discusses GAEK's architecture, functionalities, and its transformative impact on GIS applications. While GAEK significantly enhances user experience and research reproducibility, future updates aim to expand its functionality and optimize its bundled environment.

The aim of this study is to investigate the effects of the integration of goal-based scenario (GBS) approach into a block-based coding instruction. Scratch platform was used to find out the effects of GBSs on programming skills of students, who did not have any programming experience. GBSs were used during practice and the development in students' weekly products was examined. This study was designed on the basis of mixed methodology. The quasi-experimental part includes experimental and control groups. The groups received the same lecture by the same lecturer, but in the laboratory sessions the practicing approach was designed separately. The experimental group received GBS integrated tasks. The scenario flow of each week occurred through an existing character. The students completed 10 products during one semester. The scores of students' weekly products, observation notes of the researchers, pre and post-test scores, and interview data were analyzed and used in a complimentary manner. The analyses showed that GBS integration significantly affected the knowledge and skill improvement in block-based programming. The knowncontributions of block-based tools were also observed, but the realistic nature of GBSs contributed the programming instruction in the affective dimension. They served as tools for motivation, scaffolding, and monitoring. [ABSTRACT FROM AUTHOR]

Smart design and construction have emerged as pivotal forces in the construction industry. Numerous studies have been conducted in the realm of design optimization, using artificial intelligence data-driven approaches and optimization theories. This increase in research has sparked interest in generative design, a process that automatically generates algorithm-based design alternatives, thereby reducing human effort and time by a significant margin. The objective of this study was to explore the potential of generative design to boost productivity within architectural practices and reduce redundant and unnecessary tasks for an aging construction workforce. Specifically, it illustrates the process of selecting superior alternatives by generating various three-dimensional layouts, using a generative design methodology. This occurs during the creation of a building layout concept with subsequent partial evaluations. The methodology of this study was mainly divided into four stages: objective setting, design algorithm development, the establishment of evaluation methodology, and the comparison of the results' values. The findings of this study confirmed that the design algorithm and evaluation methodology form a single loop, generating a multitude of design alternatives that satisfy the algorithm designer's evaluation criteria. [ABSTRACT FROM AUTHOR]

The primary objective of this research is to demonstrate the feasibility of a model-based construction safety assessment system using building information modeling (BIM) and diagnosing accident-prone BIM objects through prevention through design (PtD). Although extensive research has focused on early risk detection and accident predictions in safety, previous approaches have often missed opportunities to identify safety issues arising from design choices. Potential safety risks have been assessed retrospectively by reconstructing safety concerns based on completed design options. To address this gap, this research aims to provide foresight regarding construction safety hazards from the early design stage. First, risks embedded in design decisions are identified by analyzing safety incident reports using text-mining techniques. Then, the relationships among design elements, accident precursors, and risk events are established through if-then relationships. The potential hazards associated with design choices are evaluated by developing and running visual scripts and assessing design model parameters in BIM. This approach enables architects to track construction risks during their design stage, even without extensive onsite construction experience. In addition, owners can evaluate design decisions considering construction safety risks, and contractors can forecast and monitor risky elements, materials, and locations during construction execution. The research outcomes contribute to enhancing safety risk awareness in the early design phases and support efficient and predictive safety management during construction. [ABSTRACT FROM AUTHOR]