Background: Generative AI coding tools are increasingly used in university computing education, including emerging practices commonly described as vibe coding. However, evidence on their educational effects is scattered across studies that differ in...
In the context of artificial intelligence in chemistry, the first applications that come to mind are widely discussed ones, such as building surrogate models to replace costly numerical simulations or designing new compounds. However, one area where...
This review article provides an in-depth analysis of the growing field of AI-assisted programming tasks, specifically focusing on the use of code embeddings and transformers. With the increasing complexity and scale of software development, tradition...
The advent of Large Language Models (LLMs) has revolutionised natural language processing, providing unprecedented capabilities in text generation and analysis. This paper examines the utility of Artificial-Intelligence-assisted (AI-assisted) content...
Prior research suggests that programming is a fundamental competency for all students. Due to its importance, programming education is integrated across many disciplines beyond computer science (e.g., humanities, social sciences, and engineering). Al...
Automated assessment of programming assignments remains a major challenge in higher education, particularly in large-scale courses where timely, consistent, and pedagogically meaningful feedback is difficult to provide, while Large Language Models (L...
The rapid integration of artificial intelligence (AI) into higher education is reshaping teaching, learning, and assessment, particularly in programming education. While AI coding assistants can enhance feedback, scaffolding, and student engagement,...
The rapid integration of AI-powered coding assistants into developer workflows has raised significant privacy and trust concerns. As developers entrust proprietary code to services like OpenAI’s GPT, Google’s Gemini, and GitHub Copilot, the unclear d...
This paper provides a comprehensive review of the literature concerning the utilization of Natural Language Processing (NLP) techniques, with a particular focus on transformer-based large language models (LLMs) trained using Big Code, within the doma...
This paper presents a hybrid methodology for the creation of educational mobile robots, combining the efforts of developers in design, construction, and instrumentation with the use of “Vibe Coding” as an alternative programming approach....
Technical job interviews have become a vulnerable environment for social engineering attacks, particularly when they involve direct interaction with malicious code. In this context, the present manuscript investigates an exploratory case study, aimin...
The application of artificial intelligence (AI) in programming assistance has garnered researchers’ attention for its potential to reduce learning costs for users, increase work efficiency, and decrease repetitive coding tasks. However, given t...
Recent AI-assisted coding tools, such as GitHub Copilot and Cursor, have enhanced developer productivity through real-time snippet suggestions. However, these tools primarily assist with isolated coding tasks and lack a structured approach to automat...
Machine learning (ML) project outcomes emerge from the interplay of organizational and technical subsystems. A recent study of 65 experienced data scientists reported that more than 80% of AI projects failed, roughly twice the failure rate of traditi...
The rapid adoption of artificial intelligence (AI) programming assistants has raised questions about the actual benefits they provide in professional software development. This exploratory longitudinal case study compares configurations of three AI p...
Complex knowledge work depends on individual output and on public exchanges that document problems, evaluate contributions, route expertise, and preserve reusable knowledge. Software work makes this infrastructure unusually visible through GitHub iss...
Post-quantum migration is becoming binding for regulated systems, and delegating it to AI coding assistants is a plausible response. We measured what two open-weight coding models produced when asked to migrate a repository from RSA-based JSON Web To...
The integration of large language models (LLMs) such as GitHub Copilot, ChatGPT, and DeepSeek into programming education has introduced a new form of human–AI collaboration. These tools provide real-time code suggestions, debugging assistance,...
To support novice learners, the Java programming learning assistant system (JPLAS) has been developed with various features. Among them, code writing problem (CWP) assigns writing an answer code that passes a given test code. The correctness of an an...
Nowadays, Python is very popular as the first programming language for novices, including high school students, to learn due to its short code features with rich libraries. Thus, it is important to provide a learning environment supporting studies st...
AI code generators are increasingly used in creative contexts, offering operational efficiencies on the one hand and prompting concerns about psychological and neurophysiological strain on the other. This study employed a multimodal approach to exami...
Background: Digital twins (DTs) are a key technology of Industry 4.0 and play a crucial role in the digital transformation of industry. The education of experts for the needs of Industry 4.0 and the emerging 5.0 must align with the requirements of pr...
In this study, we compare the performance of five chatbots using large language models (LLMs) in handling web development tasks. Three human testers asked each chatbot nine predefined questions related to creating a simple website with a dynamic form...
An increased risk of cardiovascular events was identified in patients with peripheral artery disease (PAD). Clopidogrel is one of the most widely used antiplatelet medications. However, there are heterogeneous outcomes when clopidogrel is used to pre...
Heart failure (HF) is a global pandemic public health burden affecting one in five of the general population in their lifetime. For high-risk individuals, early detection and prediction of HF progression reduces hospitalizations, reduces mortality, i...
Artificial intelligence (AI) and formal verification and validation (V&V) are two of the most consequential areas in safety-critical systems engineering, and they interact in a dual way: AI is increasingly used to support V&V, while V&V i...
This study introduces a new methodology for an Inference Index (InI) called the Inference Index In Testing Model Effectiveness methodology (INFINITE), aiming to evaluate the performance of Large Language Models (LLMs) in code generation tasks. The In...
Generative AI enables both software engineers and non-programmer domain experts to easily generate executable code. However, software engineers often lack domain-specific nuance to detect subtle AI logic errors, while domain experts typically lack th...
Recent advances in large language models (LLMs) have enabled new forms of software creation through natural-language interaction. However, many AI-assisted coding tools continue to assume familiarity with development environments, programming workflo...
Wellbore fluid flow and heat transfer are strongly coupled during drilling and well construction, where temperature, pressure, rheology, gas behavior, transient operations, and cementing displacement jointly affect pressure-window control and wellbor...
Artificial intelligence (AI) is entering audit workflows while sustainability reporting expands the evidence subject to professional evaluation. This exploratory study examines how the UK Big Four publicly describe safeguards that keep AI-assisted wo...
Extended reality (XR) technologies, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), offer new opportunities for immersive and experiential learning; however, their spatial and interactive characteristics are difficult...
Informal learning increasingly occurs in digital environments, where citizens access, evaluate and apply knowledge outside of formal education. In the context of disaster preparedness, such informal learning is crucial for promoting individual and co...
This dataset was developed to support research at the intersection of web accessibility and Artificial Intelligence, with a focus on evaluating how Large Language Models (LLMs) can detect and remediate accessibility issues in source code. It consists...
Generative artificial intelligence (genAI) enables educators to build custom learning tools, but the feasibility and impact of educator-driven, AI-assisted development (“vibe coding”) in medical education remain unclear. This study descri...
In the era of generative artificial intelligence, writing has evolved into a programmable practice capable of generating sustainable narratives and preserving cultural heritage through poetic prompts. This study proposes “Writing Is Coding &rdq...
Detecting tool wear in CNC milling is a central challenge for data analytics and sensor integration in Industry 4.0, as gradual degradation increases the risk of tool breakage and downtime and often leads manufacturers to replace tools early and inef...
Background: Legal capacity assessment requires multidisciplinary evaluation integrating cognitive, functional, neurological, psychiatric, and medico-legal information. Although large language models (LLMs) have shown promise in structured clinical re...
With the rapidly increasing reliance on advances in IoT, we persist towards pushing technology to new heights. From ordering food online to gene editing-based personalized healthcare, disruptive technologies like ML and AI continue to grow beyond our...
High-density school design has become an important challenge in rapidly urbanizing cities, where land scarcity, increasing educational demand, and evolving pedagogical models generate multiple and interrelated design constraints. Although a wealth of...
Objective: To develop and validate a ResNet-50-based deep learning model for automatic detection of osteomyelitis (DFO) in plain radiographs of patients with diabetic foot ulcers (DFUs). Research Design and Methods: This retrospective study included...
This article introduces the Olfactory Attribution Circle (OAC), a conceptual tool for integrating olfaction, color and semantic attributes in the design of sensory atmospheres. Developed through a multi-method strategy, the research combined a litera...
Engineering education research (EER) draws on a wide range of philosophical traditions, yet the ontological, epistemological, and axiological (OEA) commitments that shape how knowledge is produced are rarely made explicit in published work. This stud...
To correspond to the advancement of technology, programming has become an indispensable course in university curricula. However, students easily become confused by the rules governing program execution or by complex logical structures. Mastering prog...
This study investigates the educational potential of Large Language Models (LLMs) for automating rule-checking tasks in Building Information Modeling (BIM) instruction. A quasi-experimental classroom implementation was conducted over two consecutive...
While general network dynamics have been extensively modeled using stochastic methods, the emergence of dense Internet of Things (IoT) ecosystems demands a more specialized analytical framework. IoT environments are characterized by extreme non-linea...
Background: Accurate digital transfer of implant positions is critical for the long-term success of full-arch prosthetic rehabilitation. Photogrammetry remains the benchmark for accuracy, but its high cost and complexity limit clinical adoption. Arti...
The contemporary media landscape has sustained a substantial transformation with the rise of AI-driven algorithmic platforms that enable activist organizations to produce and disseminate their own forms of political communication and campaigns. This...
This work investigates the use of LLMs to enhance automation in software testing, with a particular focus on generating high-quality, context-aware test scripts from natural language descriptions, while addressing both text-to-code and text+code-to-c...
The volume of academic and scientific publications grows rapidly, increasing the need for efficient mechanisms for accessing, obtaining and managing large collections of Open Access (OA) journal articles. For the purposes of an ongoing project requir...
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