Hasil untuk "Education"

H. Rheingold

R. Mickelson

Jeffrey A. Raffel, Christopher Jencks, Marshall S. Smith et al.

H. Schmidt, J. Rotgans, Elaine H. J. Yew

Z. Almahasees, K. Mohsen, M. Amin

COVID-19 pandemic has disrupted teaching in a vriety of institutions. It has tested the readiness of academic institutions to deal with such abrupt crisis. Online learning has become the main method of instruction during the pandemic in Jordan. After 4 months of online education, two online surveys were distributed to investigate faculty’s and Students’ perception of the learning process that took place over that period of time with no face to face education. In this regard, the study aimed to identify both faculty’s and students’ perceptions of online learning, utilizing two surveys one distributed to 50 faculty members and another 280 students were selected randomly to explore the effectiveness, challenges, and advantages of online education in Jordan. The analysis showed that the common online platforms in Jordan were Zoom, Microsoft Teams offering online interactive classes, and WhatsApp in communication with students outside the class. The study found that both faculty and students agreed that online education is useful during the current pandemic. At the same time, its efficacy is less effective than face-to-face learning and teaching. Faculty and students indicated that online learning challenges lie in adapting to online education, especially for deaf and hard of hearing students, lack of interaction and motivation, technical and Internet issues, data privacy, and security. They also agreed on the advantages of online learning. The benefits were mainly self-learning, low costs, convenience, and flexibility. Even though online learning works as a temporary alternative due to COVID-19, it could not substitute face-to-face learning. The study recommends that blended learning would help in providing a rigorous learning environment.

Christine R Schwartz, R. Mare

M. Adarkwah

Globally, Information and Communication Technology (ICT) is regarded as a dependable vehicle for facilitating educational reform and development, a platform for communication, and as a means to achieve the Sustainable Development Goal Four (SDG 4). Since the enactment of the No Child Left Behind Act (NCLB) and declaration of the SDG 4, many countries have opted to embrace the lifelong education for all by integrating ICT in teaching and learning at all school levels. The Ghanaian Government’s initiative to ensure “education anytime anywhere for everyone” by revolutionizing teaching and learning through ICT has faced a lot of challenges and criticisms. The main mission of the Ghana ICT for Accelerated Development (ICT4AD) in 2003 was to transform Ghana into an information and technology-driven high-income economy through education, but this goal is yet to be realized. In the wake of the COVID-19 which has forced many countries and educational sectors to adopt online learning, there is a need to discuss the effectiveness of online learning and barriers to online learning in the developing contexts, and how to successfully integrate ICT in schools for online learning, especially rural schools where students’ educational careers are in jeopardy because they benefit less from online learning. The paper identifies critical factors that affect online learning, recommends post COVID-19 strategies to promote e-learning for policymakers in education and the government, and concludes with a conceptual model for emergency transition to e-learning.

N.K. Gupta, Ayesha Ahmad, Uma Gupta

Education is derived 'Educatum' a Latin word, combination of 'e' and 'duco'. 'e' means 'out of' or 'from inside' and 'duco' means 'to lead out' - means to lead out of what is there inside the mind and soul of learner. Medical education has undergone significant changes in the last few decades due to the technological explosion, and medical students need to be exposed in appropriate and calculated manner at that stage of education

Hicham Bourhil, Yacine El Younoussi

The recent advancements in Artificial Intelligence (AI) in general, and in Natural Language Processing (NLP) in particular, and some of its applications such as chatbots, have led to their implementation in different domains like education, healthcare, tourism, and customer service. Since the COVID-19 pandemic, there has been an increasing interest in these digital technologies to allow and enhance remote access. In education, e-learning systems have been massively adopted worldwide. The emergence of Large Language Models (LLM) such as BERT (Bidirectional Encoder Representations from Transformers) and GPT (Generative Pre-trained Transformers) made chatbots even more popular. In this study, we present a survey on existing Arabic chatbots in education and their different characteristics such as the adopted approaches, language variety, and metrics used to measure their performance. We were able to identified some research gaps when we discovered that, despite the success of chatbots in other languages such as English, only a few educational Arabic chatbots used modern techniques. Finally, we discuss future directions of research in this field.

Marcelino Garcia, Renato Garcia, Arthur Parizotto et al.

Educational chatbots have gained prominence as support tools for teaching programming, particularly in introductory learning contexts. This paper presents a Systematic Mapping Study (SMS) that investigated how such agents have been developed and applied in programming education. From an initial set of 3,216 publications, 54 studies were selected and analyzed based on five research subquestions, addressing chatbot types, programming languages used, educational content covered, interaction models, and application contexts. The results reveal a predominance of chatbots designed for Python instruction, focusing on fundamental programming concepts, and employing a wide variety of pedagogical approaches and technological architectures. In addition to identifying trends and gaps in the literature, this study provides insights to inform the development of new educational tools for programming instruction.

Jingyuan Chen, Tao Wu, Wei Ji et al.

Large language models (LLMs) have emerged as powerful tools in natural language processing (NLP), showing a promising future of artificial generated intelligence (AGI). Despite their notable performance in the general domain, LLMs have remained suboptimal in the field of education, owing to the unique challenges presented by this domain, such as the need for more specialized knowledge, the requirement for personalized learning experiences, and the necessity for concise explanations of complex concepts. To address these issues, this paper presents a novel LLM for education named WisdomBot, which combines the power of LLMs with educational theories, enabling their seamless integration into educational contexts. To be specific, we harness self-instructed knowledge concepts and instructions under the guidance of Bloom's Taxonomy as training data. To further enhance the accuracy and professionalism of model's response on factual questions, we introduce two key enhancements during inference, i.e., local knowledge base retrieval augmentation and search engine retrieval augmentation during inference. We substantiate the effectiveness of our approach by applying it to several Chinese LLMs, thereby showcasing that the fine-tuned models can generate more reliable and professional responses.

Griffin Pitts, Viktoria Marcus, Sanaz Motamedi

The use of chatbots equipped with artificial intelligence (AI) in educational settings has increased in recent years, showing potential to support teaching and learning. However, the adoption of these technologies has raised concerns about their impact on academic integrity, students' ability to problem-solve independently, and potential underlying biases. To better understand students' perspectives and experiences with these tools, a survey was conducted at a large public university in the United States. Through thematic analysis, 262 undergraduate students' responses regarding their perceived benefits and risks of AI chatbots in education were identified and categorized into themes. The results discuss several benefits identified by the students, with feedback and study support, instruction capabilities, and access to information being the most cited. Their primary concerns included risks to academic integrity, accuracy of information, loss of critical thinking skills, the potential development of overreliance, and ethical considerations such as data privacy, system bias, environmental impact, and preservation of human elements in education. While student perceptions align with previously discussed benefits and risks of AI in education, they show heightened concerns about distinguishing between human and AI generated work - particularly in cases where authentic work is flagged as AI-generated. To address students' concerns, institutions can establish clear policies regarding AI use and develop curriculum around AI literacy. With these in place, practitioners can effectively develop and implement educational systems that leverage AI's potential in areas such as immediate feedback and personalized learning support. This approach can enhance the quality of students' educational experiences while preserving the integrity of the learning process with AI.

Amr Alshatnawi, Remi Sampaleanu, David Liebovitz

Artificial Intelligence (AI) has been advancing rapidly and with the advent of large language models (LLMs) in late 2022, numerous opportunities have emerged for adopting this technology across various domains, including medicine. These innovations hold immense potential to revolutionize and modernize medical education. Our research project leverages large language models to enhance medical education and address workflow challenges through the development of MediTools - AI Medical Education. This prototype application focuses on developing interactive tools that simulate real-life clinical scenarios, provide access to medical literature, and keep users updated with the latest medical news. Our first tool is a dermatology case simulation tool that uses real patient images depicting various dermatological conditions and enables interaction with LLMs acting as virtual patients. This platform allows users to practice their diagnostic skills and enhance their clinical decision-making abilities. The application also features two additional tools: an AI-enhanced PubMed tool for engaging with LLMs to gain deeper insights into research papers, and a Google News tool that offers LLM generated summaries of articles for various medical specialties. A comprehensive survey has been conducted among medical professionals and students to gather initial feedback on the effectiveness and user satisfaction of MediTools, providing insights for further development and refinement of the application. This research demonstrates the potential of AI-driven tools in transforming and revolutionizing medical education, offering a scalable and interactive platform for continuous learning and skill development.

Kayode David KOLAWOLE

The purpose of this paper is to identify the driving elements of the South African financial sector. While South Africa’s financial sector appears robust, there exists a dearth of empirical research investigating the determinants of its development. Thus, this work assesses how two critical factors: Infrastructure development, and government funding levels affect financial development (FD) in South Africa using annual data from 1990 to 2024. Preliminary findings show that the series are integrated, and they are cointegrated. Results from regression analysis suggest that the government funding exerts a positive and statistically significant influence on financial development across most indicators. Conversely, advanced infrastructure development, government funding and openness to trade are associated with a more developed financial sector. The implications of these findings are essential for policymakers and stakeholders in understanding the factors that drive financial development in South Africa. The study recommends that, among others, policymakers should prioritize investments in both physical and digital infrastructure, particularly in telecommunications.

Victor R. Kebande

Virtual Laboratories (V Labs) have in the recent past become part and parcel of remote teaching in practical hands-on approaches, particularly in Cybersecurity distance courses. Their potential is meant to assist learners with hands-on practical laboratory exercises irrespective of geographical location. Nevertheless, adopting V Labs in didactic approaches in higher education has seen both merits and demerits. Based on this premise, this study investigates the impact of V Labs on Active Learning (AL) and engagement in cybersecurity distance education. A survey with a limited number of learners and educators who have had an experience with cybersecurity distance courses that leveraged V Labs in their practical Lab assignment, was conducted at Blekinge Tekniska Högskola, Sweden, to assess the impact of V Labs on AL and engagement in Cybersecurity Distance Education. 29% and 73% of the learners and educators, respectively responded to the survey administered remotely and with good internal consistency of questionnaires based on the Cronbalch Alpha; the results showed that learners and educators had a positive perception of using V Labs to enhance AL in cybersecurity distance education. The key concentration of the study was on AL and engagement and problem-solving abilities when V Labs are used. Both the learners and educators found the V Labs to be engaging, interactive, and effective in improving their understanding of cybersecurity concepts.

Jinsook Lee, Yann Hicke, Renzhe Yu et al.

Large Language Models (LLMs) are increasingly adopted in educational contexts to provide personalized support to students and teachers. The unprecedented capacity of LLM-based applications to understand and generate natural language can potentially improve instructional effectiveness and learning outcomes, but the integration of LLMs in education technology has renewed concerns over algorithmic bias which may exacerbate educational inequities. In this review, building on prior work on mapping the traditional machine learning life cycle, we provide a holistic map of the LLM life cycle from the initial development of LLMs to customizing pre-trained models for various applications in educational settings. We explain each step in the LLM life cycle and identify potential sources of bias that may arise in the context of education. We discuss why current measures of bias from traditional machine learning fail to transfer to LLM-generated content in education, such as tutoring conversations because the text is high-dimensional, there can be multiple correct responses, and tailoring responses may be pedagogically desirable rather than unfair. This review aims to clarify the complex nature of bias in LLM applications and provide practical guidance for their evaluation to promote educational equity.

Abu Saleh Musa Miah, Md Mahbubur Rahman Tusher, Md. Moazzem Hossain et al.

In recent years, advanced artificial intelligence technologies, such as ChatGPT, have significantly impacted various fields, including education and research. Developed by OpenAI, ChatGPT is a powerful language model that presents numerous opportunities for students and educators. It offers personalized feedback, enhances accessibility, enables interactive conversations, assists with lesson preparation and evaluation, and introduces new methods for teaching complex subjects. However, ChatGPT also poses challenges to traditional education and research systems. These challenges include the risk of cheating on online exams, the generation of human-like text that may compromise academic integrity, a potential decline in critical thinking skills, and difficulties in assessing the reliability of information generated by AI. This study examines both the opportunities and challenges ChatGPT brings to education from the perspectives of students and educators. Specifically, it explores the role of ChatGPT in helping students develop their subjective skills. To demonstrate its effectiveness, we conducted several subjective experiments using ChatGPT, such as generating solutions from subjective problem descriptions. Additionally, surveys were conducted with students and teachers to gather insights into how ChatGPT supports subjective learning and teaching. The results and analysis of these surveys are presented to highlight the impact of ChatGPT in this context.

О. P. Korzhova, D. S. Makashin, P. E. Popov et al.

The article focuses on the potential integration of the SFM digital control system into production. To achieve a more accurate implementation of the dSFM system, the article identifies its strengths and weaknesses. It evaluates and outlines the factors contributing to the successful implementation of the dSFM system in production. The article also analyses the traditional Lean manufacturing system, the analogue SFM system and its digital version. The study scrutinised the manner in which workers interact with the «System of Operations Management» with the purpose of refining its assimilation into manufacturing processes and enhancing employee output.

Randi Hovden Borge, Håkon A Johannessen, Knut Inge Fostervold et al.

OBJECTIVES: Several studies have found higher sickness absence in shared and open workspaces than in private offices, but little is known about why these differences occur. We propose and test job control as a potential mechanism underlying observed differences in the risk of physician-certified sickness absence between private offices and shared and open workspaces. METHODS: We conducted a counterfactual mediation analysis using observational survey data from a nationally representative sample of Norwegian employees merged with prospective data from national registries (N=5512). The registry data included information about whether participants had any physician-certified sickness absence the year following the survey. Models were adjusted for age, sex, education level, occupation group, executive/leadership responsibility, and time spent on office work. RESULTS: We found significantly higher sickness absence risk in conventional [risk ratio (RR) 1.12, 95% confidence interval (CI) 1.01‒1.25] and non-territorial (RR 1.20, 95% 1.04‒1.37) open-plan and non-territorial shared-room offices (RR 1.29, 95% CI 1.13‒1.48) compared to private offices. Natural indirect effects due to job control were statistically significant in all contrasts and accounted for 19–34% of total effects depending on contrast. CONCLUSIONS: Findings were in line with hypothesized relationships and suggest that job control may be a mechanism underlying observed differences in sickness absence across office concepts. Future studies should continue to explore potential mechanisms linking shared and open workspaces to higher sickness absence and other unfavorable outcomes in the workplace, particularly with study designs that provide stronger basis for causal inference.

Lingyao Li, Zihui Ma, Lizhou Fan et al.

The rapid advancements in generative AI models present new opportunities in the education sector. However, it is imperative to acknowledge and address the potential risks and concerns that may arise with their use. We analyzed Twitter data to identify key concerns related to the use of ChatGPT in education. We employed BERT-based topic modeling to conduct a discourse analysis and social network analysis to identify influential users in the conversation. While Twitter users generally ex-pressed a positive attitude towards the use of ChatGPT, their concerns converged to five specific categories: academic integrity, impact on learning outcomes and skill development, limitation of capabilities, policy and social concerns, and workforce challenges. We also found that users from the tech, education, and media fields were often implicated in the conversation, while education and tech individual users led the discussion of concerns. Based on these findings, the study provides several implications for policymakers, tech companies and individuals, educators, and media agencies. In summary, our study underscores the importance of responsible and ethical use of AI in education and highlights the need for collaboration among stakeholders to regulate AI policy.