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Exploring Complex Biological Processes through Artificial Intelligence

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Title: Exploring Complex Biological Processes through Artificial Intelligence
Language: English
Authors: Fatima Rahioui, Mohammed Ali Tahri Jouti, Mohammed El Ghzaoui
Source: Journal of Educators Online. 2024 21(2).
Availability: Journal of Educators Online. Grand Canyon University, 23300 West Camelback Road, Phoenix, AZ 85017. e-mail: CIRT@gcu.edu. Web site: https://www.thejeo.com
Peer Reviewed: Y
Page Count: 15
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Descriptors: Artificial Intelligence, Biological Sciences, Scientific Concepts, Technology Integration, Science Instruction, Virtual Classrooms, Learning Experience, Computer Simulation, Learner Engagement, Data Analysis, Individualized Instruction, Interactive Video
ISSN: 1547-500X
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 is 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.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1427744
Database: ERIC
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  Data: 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 is 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.
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      – SubjectFull: Biological Sciences
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      – SubjectFull: Scientific Concepts
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      – SubjectFull: Technology Integration
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      – SubjectFull: Science Instruction
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      – SubjectFull: Virtual Classrooms
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      – SubjectFull: Learning Experience
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      – SubjectFull: Computer Simulation
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      – SubjectFull: Individualized Instruction
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      – SubjectFull: Interactive Video
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