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Enhancing Biology and Chemistry Learning in Nigerian Secondary Schools Through AI Technologies.

Domaine:

education

Type de record:

paper
Créateur:
BraBadOguFas
Éditeur:
Zenodo
Hôte:avatar

The composites of AI for practical Biology and Chemistry (BAC) involved causal, 
predictive, and generative types of AI, which have cutting edge capabilities for problem solving in BAC. Integrating AI into the BAC for Senior Secondary Schools was necessitated out of the needs for addressing more intricate issues in BAC practical. The use of virtual labs, AI-powered simulations, intelligent tutoring systems (ITS) and virtual dissection tools, had revolutionized how BAC students were engaged with practical without physical apparatus, equipment, specimens or chemicals. The purpose of this study was to investigate how AI-based technologies, would enhance SSS students’ BAC practical skills and learning experiences. The population for this study involved all senior secondary school (SSS) students offering biology and chemistry (BAC) in Lagos State, Nigeria. A total of 184 students were purposively selected for the study from six senior secondary schools (SSS) in Education District V of Lagos State. Two research instruments were used for collecting data in this study. The content and face validity of the instruments were established with pilot studies and further validated with the opinions and suggestions of experts of AI, chemistry education and biology education. Cronbach’s Alpha reliability test for AIBACPQ gave 0.89 reliability index. Results revealed that AI technologies have promising solutions to the challenges in BAC practical and empower students with innovative skills, which transforms the barriers in their learning experiences. By implications, AI supports BAC teachers’ competencies and enhanced students’ practical works’ engagements, interests, motivation, achievements and learning experiences in BAC. 

Visit

doi.org

Tags

Enhanced Practical Skills, AI, Learning Experiences, Virtual Laboratories, Innovative Skills, Simulation Learning.

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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