Cited by IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback

Enhancing Critical Thinking and Argumentation Skills in Colombian Undergraduate Diplomacy Students: ChatGPT-Assisted and Traditional Debate Methods DOI

Mario Alberto de la Puente Pacheco, José Marcelo Torres Ortega,

Ana Laura Blanco Troncoso

et al.

Journal of Political Science Education, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 11

Published: Jan. 10, 2025

This study tests the effectiveness of integrating ChatGPT into debate sessions to strengthen critical thinking and argumentation skills among undergraduate diplomacy students in Colombia. One hundred sixty-two participants were randomly assigned an experimental group using during debates a control engaging traditional debates. Pretest post-test assessments measured participants' adapted versions Watson-Glaser Critical Thinking Appraisal custom rubric. Multivariate analysis covariance (MANCOVA) found higher scores for combined learning outcomes. Univariate analyses (ANCOVAs) showed improvements understanding complex concepts, thinking, group. Structural equation modeling (SEM) noted direct indirect effects on these skills. The also analyzed perceptions through qualitative data from open-ended questions. These findings highlight ChatGPT's potential fostering essential resource-constrained educational settings, while noting implementation challenges developing nations. research adds growing literature AI-powered tools education, particularly economically emerging regions.

Language: Английский

Citations

Towards AI-Assisted Mapmaking: Assessing the Capabilities of GPT-4o in Cartographic Design DOI

Abdulkadir Memduhoğlu

ISPRS International Journal of Geo-Information, Journal Year: 2025, Volume and Issue: 14(1), P. 35 - 35

Published: Jan. 17, 2025

Cartographic design is fundamental to effective mapmaking, requiring adherence principles such as visual hierarchy, symbolization, and color theory convey spatial information accurately intuitively, while Artificial Intelligence (AI) Large Language Models (LLMs) have transformed various fields, their application in cartographic remains underexplored. This study assesses the capabilities of a multimodal advanced LLM, GPT-4o, understanding suggesting elements, focusing on established principles. Two assessments were conducted: text-to-text evaluation an image-to-text evaluation. In assessment, GPT-4o was presented with 15 queries derived from key concepts cartography, covering classification, theory, typography. Each query posed multiple times under different temperature settings evaluate consistency variability. evaluation, analyzed maps containing deliberate errors assess its ability identify issues suggest improvements. The results indicate that demonstrates general reliability text-based tasks, variability influenced by settings. model showed proficiency classification symbolization tasks but occasionally deviated theoretical expectations. hierarchy layout, performed consistently, appropriate choices. effectively identified critical flaws inappropriate schemes, poor contrast misuse shape size variables, offering actionable suggestions for improvement. However, limitations include dependency input quality challenges interpreting nuanced relationships. concludes LLMs like significant potential design, particularly involving creative exploration routine support. Their critique generate elements positions them valuable tools enhancing human expertise. Further research recommended enhance reasoning expand use variables beyond color, thereby improving applicability professional workflows.

Language: Английский

Citations

Unifying Bias and Unfairness in Information Retrieval: New Challenges in the LLM Era DOI

Sunhao Dai, Xu Chen, Shicheng Xu

et al.

Published: Feb. 26, 2025

Language: Английский

Citations

FAIR-QR: Enhancing Fairness-Aware Information Retrieval Through Query Refinement DOI

F.L. Chen, Hui Fang

Lecture notes in computer science, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 9

Published: Jan. 1, 2025

Language: Английский

Citations

Leveraging Large Language Models and Causal Inference to Build Trust in Environmental Decision-Making DOI

Süleyman Uslu,

Mehedi Mahmud Kaushik,

Praneeth Reddy Mukthapuram

et al.

Lecture notes on data engineering and communications technologies, Journal Year: 2025, Volume and Issue: unknown, P. 342 - 353

Published: Jan. 1, 2025

Language: Английский

Citations

RAG Combined with Instruction Tuning for Traditional Chinese Medicine Syndrome Differentiation Thinking DOI

Chun-Liang Chen, Ming Guan, Wenjing Yue

et al.

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 78 - 89

Published: Jan. 1, 2025

Language: Английский

Citations

Industrial applications of large language models DOI

Mubashar Raza,

Zarmina Jahangir,

Muhammad Bilal Riaz

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: April 21, 2025

Large language models (LLMs) are artificial intelligence (AI) based computational designed to understand and generate human like text. With billions of training parameters, LLMs excel in identifying intricate patterns, enabling remarkable performance across a variety natural processing (NLP) tasks. After the introduction transformer architectures, they impacting industry with their text generation capabilities. play an innovative role various industries by automating NLP In healthcare, assist diagnosing diseases, personalizing treatment plans, managing patient data. provide predictive maintenance automotive industry. recommendation systems, consumer behavior analyzers. facilitates researchers offer personalized learning experiences education. finance banking, used for fraud detection, customer service automation, risk management. driving significant advancements tasks, improving accuracy, providing deeper insights. Despite these advancements, face challenges such as ethical concerns, biases data, resource requirements, which must be addressed ensure impartial sustainable deployment. This study provides comprehensive analysis LLMs, evolution, diverse applications industries, offering valuable insights into transformative potential accompanying limitations.

Language: Английский

Citations

Align with Me, Not TO Me: How People Perceive Concept Alignment with LLM-Powered Conversational Agents DOI