Revolutionizing Technology Education with Artificial Intelligence and Machine Learning: A Comprehensive Systematic Literature Review

Musawer Hakimi, Mohammad Shuaib Zarinkhail, Hamayoon Ghafory, Shir Ahmad Hamidi — Tue, 26 Nov 2024 00:00:00 +0000

Machine learning and artificial intelligence in education will help to personalize the student learning process, reduce the time wastage in imploding administration systems, and innovate teaching methods. The article reports the findings of a study on the effects of these technologies on the educational systems of application, benefits, and challenges and looks forward to the implications. This has been realized through a systematic review of peer-reviewed journal articles, government reports, and policy documents published between 2021 and 2024. Results show great benefits, including enhanced personalized learning experiences and administrative efficiencies, but also highlight several challenges, such as equitable access, data privacy, and the need for professional development of educators. Rather, this research outlines the imperatives that there is a need to address challenges for the realization of the potential of AI and ML in education. The paper makes recommendations for key stakeholders and points out areas for possible future research to guide sustainable and ethical integration into educational systems. Further research should be done to understand whether these technologies affect student outcomes in the long term and are applicable with the same efficacy in other cultural and socioeconomic contexts.

Design of an IoT-Based Automatic Weighing System for Catfish Farming to Support Smart Aquaculture

Sutra Wardatul Jannah, Ahmad Muhtadi — Tue, 26 Nov 2024 00:00:00 +0000

Enhancing the accuracy and efficiency of the catfish weighing process is essential for farmers to optimize distribution to retailers and wholesalers while improving productivity and operational performance. This study focuses on developing an IoT-based automatic weighing system to provide a real-time and automated solution to these challenges. The proposed system incorporates a load cell sensor for weight measurement, an ESP32 microcontroller with a WiFi module for seamless data transmission, and an intuitive web-based interface for monitoring and control. Powered by solar energy, the system emphasizes the integration of renewable energy in aquaculture. The research involves designing the system's mechanical, electrical, and software components to create a practical and accessible tool for farmers. Field trials on catfish farms assess the system’s performance in terms of accuracy and efficiency, comparing it to conventional manual weighing methods. This innovation aims to boost operational efficiency in aquaculture while contributing to the adoption of sustainable and intelligent farming technologies.

TIERS Information Technology Journal

Revolutionizing Technology Education with Artificial Intelligence and Machine Learning: A Comprehensive Systematic Literature Review

Design of an IoT-Based Automatic Weighing System for Catfish Farming to Support Smart Aquaculture