In the ever-evolving era of technological advancements, generative artificial intelligence (GAI) emerges as a transformative force, revolutionizing education. This review paper, guided by the PRISMA framework, presents a comprehensive analysis of GAI in education, synthesizing key insights from a selection of 207 research papers to identify research gaps and future directions in the field. This study begins with a content analysis that explores GAI’s transformative impact in specific educational domains, including medical education and engineering education. The versatile applications of GAI encompass assessment, personalized learning support, and intelligent tutoring systems. Ethical considerations, interdisciplinary collaboration, and responsible technology use are highlighted, emphasizing the need for transparent GAI models and addressing biases. Subsequently, a bibliometric analysis of GAI in education is conducted, examining prominent AI tools, research focus, geographic distribution, and interdisciplinary collaboration. ChatGPT emerges as a dominant GAI tool, and the analysis reveals significant and exponential growth in GAI research in 2023. Moreover, this paper identifies promising future research directions, such as GAI-enhanced curriculum design and longitudinal studies tracking its long-term impact on learning outcomes. These findings provide a comprehensive understanding of GAI’s potential in reshaping education and offer valuable insights to researchers, educators, and policymakers interested in the intersection of GAI and education. 

Transforming Education: A Comprehensive Review of Generative Artificial Intelligence in Educational Settings through Bibliometric and Content Analysis

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Intelligent Manufacturing through Generative Artificial Intelligence, Such as ChatGPT or Bard

Application of question answering systems for intelligent agriculture production and sustainable management: A review

In the era of rapid advancements in Artificial Intelligence (AI), ChatGPT (Chat Generative Pre-Trained Transformer) emerges as a pivotal tool reshaping educational landscapes. This research, based on self-determination theory, investigates how ChatGPT influences the motivation and academic performance of 35 seventh-semester English education students. Utilizing mixed methods, it contrasts the experiences of 25 ChatGPT users with those of 10 non-users. The quantitative analysis demonstrates notably higher levels of motivation and GPAs among ChatGPT users (with a mean motivation score of 44.88 and a mean GPA of 3.63) compared to non-users (with a mean motivation score of 17.60 and a mean GPA of 3.06). Qualitative insights highlight themes such as 'Improved Comprehension and Independent Learning' and 'Increased Academic Efficiency and Productivity,' illustrating how ChatGPT supports effective and thorough learning experiences. In keeping with the tenets of self-determination theory, these results demonstrate that ChatGPT has a beneficial effect on students' motivation. The study also recommends more experimental studies to investigate how students' motivation and performance can be improved by using ChatGPT.

Investigating the Implementation of ChatGPT in English Language Education

AI chatbots, e.g. ChatGPT, are becoming increasingly popular in education as a means to enhance student learning experiences and improve teaching efficiency. This study utilizes NVivo 12 Plus to examine the role of AI chatbots in education, ethical considerations, and sentimental analysis regarding the utilization of ChatGPT in education. ChatGPT has revolutionized education, but their use raises ethical concerns. They can enhance language learning, but may lead to plagiarism and information overload. Students may not develop discrimination skills and may rely on ChatGPT, leading to concerns about academic dishonesty and a failure to develop cognitive and analytical skills. The use of ChatGPT in clinical education also raises accountability and liability concerns regarding the use of patient information for educational purposes. Guidelines should be established to ensure privacy rights are upheld. Finally, the positive sentiment category was populated by predominantly positive sentiments, followed by neutral and negative sentiments. Future research on ChatGPT in education should focus on its application effectiveness in various educational settings and ethical considerations.

ChatGPT in Education

ChatGPT adds to the list of artificial intelligence-based systems designed to perform specific tasks and answer questions by interacting with users (Apple's Siri, Amazon's Alexa, Google's Assistant and Bard, Microsoft's Cortana, IBM's Watson, Bixby from Samsung, among others). ChatGPT works using OpenAI's GPT (Generative Pretrained Transformer) language model and is capable of learning from users' preferences and behavior patterns to customize its response. ChatGPT has the potential to be applied in different fields, including education, journalism, scientific writing, communication, cell biology, and biotechnology, where there is already evidence. The aim of this work was to analyze the possible applications of ChatGPT in the agricultural and livestock industry. First, a scientometric analysis was performed with VosViewer and Bibliometrix (Bliblioshiny). 3 clusters were identified: (a) Main characteristics; (b) learning systems you use; and (c) applications. To the question: What are the main applications in which ChatGTP will revolutionize agriculture (or livestock) in the world? ChatGPT responded: (a) in the agricultural field: improvement of agricultural decision-making, optimization of agricultural production, detection and prevention of plant diseases, climate management, and supply chain management; and (b) in the livestock field: improvement of animal health and welfare, optimization of animal production, supply chain management, detection and prevention of zoonotic diseases, and climate management for animal production. ChatGPT does not scientifically support its answer, but from the analysis carried out, we find that there is enough scientific evidence to conclude, in this case, that its answers were correct. While ChatGPT does not necessarily scientifically substantiate its answers, users should. There is a lack of studies on the use of Artificial Intelligence and its relationship with ethics.

/pdf/the-language-model-based-on-sensitive-artificial-9abdr3zs.pdf

The language model based on sensitive artificial intelligence -ChatGPT: Bibliometric analysis and possible uses in agriculture and livestock

This study aimed at measuring beef marbling scores in an objective and simple manner through spectral imaging and multiple linear regression (MLR). Beef marbling prediction by hyperspectral imaging and partial least squares regression (PLSR) was analyzed to calibrate and evaluate an MLR model with a few selected wavelengths. Data came from 44 beef samples and consisted of their spectral signatures (75 wavelengths) from hyperspectral reflectance images (400-1000 nm) and their marbling scores assigned by evaluators. The wavelengths that presented regression coefficients with the highest absolute values in the PLSR model, were used to calibrate the MLR model by a backward stepwise approach (p < 0.05). The coefficient of determination for prediction (R2p) and the standard error of prediction (SEP) were evaluated. The MLR model was suitable for practical use because it required only 12 wavelengths for reliable predictions (R2p = 0.824 > 0.8; SEP = 11.4% < 15%). A model is proposed for the objective and simple measurement of beef marbling score using multispectral imaging technology.

Beef marbling measurement using spectral imaging: A multiple linear regression approach

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The language model based on sensitive artificial intelligence -ChatGPT: Bibliometric analysis and possible uses in agriculture and livestock

Beef marbling measurement using spectral imaging: A multiple linear regression approach