Exploring the impact of generative artificial intelligence on students’ learning outcomes: a meta-analysis

Education and Information Technologies, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 26, 2025

Language: Английский

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Implementing AI-Assisted Assessment in Educational Institutions

Digital education and learning, Journal Year: 2025, Volume and Issue: unknown, P. 193 - 243

Published: Jan. 1, 2025

Language: Английский

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AI in Assessment Analysis and Improvement

Digital education and learning, Journal Year: 2025, Volume and Issue: unknown, P. 159 - 192

Published: Jan. 1, 2025

Language: Английский

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AI-driven educational transformation in ICT: Improving adaptability, sentiment, and academic performance with advanced machine learning

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(5), P. e0317519 - e0317519

Published: May 19, 2025

This study significantly contributes to the sphere of educational technology by deploying state-of-the-art machine learning and deep strategies for meaningful changes in education. The hybrid stacking approach did an excellent implementation using Decision Trees, Random Forest, XGBoost as base learners with Gradient Boosting a meta-learner, which managed record accuracy 90%. That indeed puts into great perspective huge potential it possesses measures while predicting setups. CNN model, predicted 89%, showed quite impressive capability sentiment analysis acquire further insight emotional status students. RCNN, Forests, Trees contribute possibility data complexity valuable complex interrelationships within ML models contexts. application bagging algorithm, attained high 88%, stamps its utility toward enhancement academic performance through strong robust techniques model aggregation. dataset that was used this sourced from Kaggle, 1205 entries 14 attributes concerning adaptability, sentiment, performance; reliability richness analytical basis are high. allows rigorous modeling validation be done ensure findings considered robust. has several implications education develops on key dimensions: teacher effectiveness, leadership, well-being From obtained information about student adaptability developed system helps educators make modifications instructional strategy more efficiently particular enhance effectiveness teaching. All these aspects could provide critical insights leadership devise data-driven would overall school-wide performance, well create caring atmosphere. integration structure brings inclusive, responsive attitude ensuring students’ and, thus, environment. is closely aligned sustainable ICT objectives offers transformative integrating AI-driven practice field. By notorious DL methodologies challenges, research future innovations area. Ultimately, improvement system.

Language: Английский

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Exploring the impact of artificial intelligence on the transparency and rationality of Peruvian public works: perceptions, expectations, challenges and opportunities

Transforming Government People Process and Policy, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Purpose This study aims to examine the perception of public works experts on application artificial intelligence (AI) as a tool potentially increase rationality and transparency works. Design/methodology/approach paper is based an exploratory quantitative design. It uses original survey use AI in works, targeting from Peru. Data was analyzed using structural equation modeling. Findings reveal experts’ interest AI, highlighting its potential improve efficiency, although labor changes are anticipated. monitoring could impact economic quality control areas, vital fight against corruption. Infrastructure, government policies financial resources emerge fundamental enablers. Originality/value The advent advanced systems has raised promises help corruption through new capabilities that enhance rationality. However, few studies have assessed contributes this gap by testing framework explores how perceive considering their perceptions, expectations, perceived challenges opportunities over works’ transparency.

Language: Английский

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Opinion mining of professors' sentiments towards the adoption of technology, the latest teaching trends, and their effectiveness

Social Sciences & Humanities Open, Journal Year: 2024, Volume and Issue: 11, P. 101249 - 101249

Published: Dec. 24, 2024

Language: Английский

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