Balancing AI and authenticity: EFL students’ experiences with ChatGPT in academic writing DOI Creative Commons
Indah Werdiningsih,

Marzuki Marzuki,

Diyenti Rusdin

et al.

Cogent Arts and Humanities, Journal Year: 2024, Volume and Issue: 11(1)

Published: Aug. 19, 2024

This research explores the experiences of EFL students and their strategies when incorporating ChatGPT into academic writing process. A qualitative case study method was employed, involving three with different proficiency levels. Data were collected through semi-structured interviews. Key findings indicate that is valued for overcoming uncertainties, clarifying vocabulary, offering content suggestions, enhancing essay quality by allowing to focus on creative aspects. However, balancing AI tools human judgment crucial authenticity. raises concerns about authenticity work, highlighting need ethical guidelines fostering critical thinking. Its limitations, such as providing overly complex suggestions lacking cultural sensitivity, necessitate oversight. Students recognize importance using seeking feedback ensure work quality. Educators should develop use in writing, emphasizing thinking originality. Training programs teachers responsible integration are essential. Despite comprehensive approach, small sample size limits generalizability, reliance self-reported data introduces potential bias. Future involve larger, diverse samples incorporate objective measures mitigate

Language: Английский

Development of anatomically accurate digital organ models for surgical simulation and training DOI Creative Commons
Takashi Kimura,

Kazuaki Takiguchi,

Shöichiro Tsukita

et al.

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(4), P. e0320816 - e0320816

Published: April 9, 2025

Advancements in robotics and other technological innovations have accelerated the development of surgical procedures, increasing demand for training environments that accurately replicate human anatomy. This study developed a system utilizes AutoSegmentator extension 3D Slicer, based on nnU-Net, state-of-the-art deep learning framework automatic organ extraction, to import automatically extracted surface data into CAD software along with original DICOM-derived images. allows medical experts manually refine data, making it more accurate closer ideal dataset. First, Python programming is used generate save JPEG-format image from DICOM display Blender. Next, imported Slicer processed by extract 104 organs bulk, which then exported STL format. In Blender, custom-developed script aligns within same space, ensuring spatial coordinates. By using Blender’s functionality this boundaries can be adjusted resulting precise data. Additionally, blood vessels cannot newly created added referencing Through process, comprehensive anatomical dataset encompassing all required constructed. The easily customizable applied various simulations, including 3D-printed simulators, hybrid simulators incorporate animal organs, utilizing augmented reality (AR). Furthermore, built entirely open-source, free software, providing high reproducibility, flexibility, accessibility. system, professionals actively participate design processing simulation systems, leading shorter times reduced costs.

Language: Английский

Citations

0

The Impact of Generative AI Coding Assistants on Developers Who Are Visually Impaired DOI
Claudia Flores-Saviaga, Benjamin V. Hanrahan,

Kashif Imteyaz

et al.

Published: April 24, 2025

Language: Английский

Citations

0

Integrating AI and Machine Learning in Software Development DOI

Taye Iyinoluwa Adeyinka,

Kehinde Iyioluwa Adeyinka

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 40

Published: March 28, 2025

Software development techniques have changed due to the incorporation of artificial intelligence (AI) and machine learning (ML), which provide previously unheard-of levels automation, optimisation, creativity. T. developers can reduce human error, increase productivity, improve decision-making by utilising predictive models sophisticated algorithms. Advanced applications, including AI-driven debugging, generative AI for code synthesis, analytics risk assessment, are also covered in this chapter. Issues algorithmic biases, ethical concerns, integration difficulties discussed alongside workable solutions. The chapter ends with predictions future, highlighting how ML be used build more intelligent, safe, flexible software systems. Real-world case studies incorporated illustrate observable advantages useful applications AI-ML contemporary development.

Language: Английский

Citations

0

Developer and LLM Pair Programming: An Empirical Study of Role Dynamics and Prompt-Based Collaboration DOI Open Access

Sri Rama Chandra Charan Teja Tadi

International Journal of Advanced Research in Science Communication and Technology, Journal Year: 2025, Volume and Issue: unknown, P. 436 - 444

Published: May 12, 2025

With the introduction of large language models (LLMs) as coding partners, classic pair programming dynamics are being rewritten. This research empirically examines collaboration between software developers and LLMs on tasks, uncovering a dynamic role toggling informed by prompt accuracy contextual cues. Instead deterministic driver-navigator dichotomies, we find an emergent interdependence where programmers function orchestrators intent oscillate executor, interpreter, creative collaborator. Prompt design has emerged critical skill for orchestrating collaboration, shifting focus from code authorship to dialogical problem-solving. perspective introduces new vision human-AI co-creation in coding, highlighting its potential within future intelligent development environments.

Language: Английский

Citations

0

Balancing AI and authenticity: EFL students’ experiences with ChatGPT in academic writing DOI Creative Commons
Indah Werdiningsih,

Marzuki Marzuki,

Diyenti Rusdin

et al.

Cogent Arts and Humanities, Journal Year: 2024, Volume and Issue: 11(1)

Published: Aug. 19, 2024

This research explores the experiences of EFL students and their strategies when incorporating ChatGPT into academic writing process. A qualitative case study method was employed, involving three with different proficiency levels. Data were collected through semi-structured interviews. Key findings indicate that is valued for overcoming uncertainties, clarifying vocabulary, offering content suggestions, enhancing essay quality by allowing to focus on creative aspects. However, balancing AI tools human judgment crucial authenticity. raises concerns about authenticity work, highlighting need ethical guidelines fostering critical thinking. Its limitations, such as providing overly complex suggestions lacking cultural sensitivity, necessitate oversight. Students recognize importance using seeking feedback ensure work quality. Educators should develop use in writing, emphasizing thinking originality. Training programs teachers responsible integration are essential. Despite comprehensive approach, small sample size limits generalizability, reliance self-reported data introduces potential bias. Future involve larger, diverse samples incorporate objective measures mitigate

Language: Английский

Citations

3