Rahioui, et al

Exploring Complex Biological Processes Through Artificial Intelligence

Fatima Rahioui, Sidi Mohamed Ben Abdellah University
Mohammed Ali Tahri Jouti, Sidi Mohamed Ben Abdellah University
Mohammed El Ghzaoui, Sidi Mohamed Ben Abdellah University

https://doi.org/10.9743/JEO.2024.21.2.9

Abstract

Artificial intelligence (AI) is now affecting all aspects of our social lives. Without always knowing it, we interact daily with intelligent systems. They serve us invisibly. At least that’s the goal we assign to them: to make our lives better, task by task. Artificial intelligence has the potential to make biology education more engaging, personalized, and effective by providing students with interactive simulations, personalized learning experiences, and other tools that help them understand complex biological concepts. In this paper, we discuss the integration of AI into the virtual classroom, which significantly enhances student learning experiences in various ways. The study shows that an effective integration of technology into the virtual classroom requires a thoughtful approach that aligns with educational goals and the specific needs of students. In fact, interactive simulations can help make biology more engaging and memorable for students. Besides, personalized learning AI algorithms can help biology students receive a more tailored and effective learning experience, helping them to better understand the course material and develop a deeper appreciation for the natural world. In this work, we will discuss the use of AI to enhance interactive simulation-based cellular processes, with additional application in anatomy, physiology, and ecology teaching. Moreover, this paper discusses how AI could be used to analyze student data and propose personalized learning using adaptive assessments, content recommendations, and data sciences. This paper illustrates examples of AI algorithms that could be useful for teaching biology.

Keywords: artificial intelligence, machine learning, biological processes, personalized learning, biological concepts, cellular processes, interactive simulations, adaptive assessment, content recommendation


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