Artificial Intelligence and Machine Learning in enhancing Science Learning Experiences - Exploring Possibilities and Concerns

Aug 4, 2026

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Artificial Intelligence and Machine Learning are reshaping education by enabling individualized learning, adaptive feedback, innovative pedagogy, and data-driven insights that improve science learning experiences for students and teachers. AI tools such as virtual tutors and intelligent simulations analyze learning patterns and provide context-specific support to strengthen conceptual understanding and problem-solving skills. The paper reviews how AI can support inquiry-based learning and immersive virtual laboratories, helping reduce constraints caused by limited laboratory equipment. It also examines concerns including privacy risks, over-dependence on technology, potential bias from data, unequal access, and limits in fostering critical thinking and creativity.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages14

Reading Time35 min

AccessFree to download

Introduction

Technology’s impact on education

Challenges and considerations in educational technology

AI and ML in science education

Abstract

Benefits of AI/ML for science learning

Concerns and ethical issues

Proposed balance in integration

NIU Journal of Educational Research Copyright©2024 Nexus International University ISSN: 3007-1844; 10(2): 59-72 Artificial Intelligence and Machine Learning in enhancing Science Learning Experiences: Exploring Possibilities and Concerns CLARA DUMEBI MOEMEKE University of Delta, Agbor, Nigeria Abstract. The advent of Artificial Intelligence and Machine Learning has made remarkable impart in all sectors of human activities. In the field of science education, integrating AI and ML have opened new dimensions for improving learning experiences by offering individualized learning, adaptive feedback, innovative pedagogues and data-driven insights that enable science students and teachers to engage with science content and materials in interactive and personalized ways. AI-tools such as virtual tutors, intelligent simulations, and algorithms analyze students' learning patterns, generate context-specific assistance that deepens conceptual understanding of science concepts and problem-solving skills of students. This paper reviews the benefits AI and ML in fostering inquiry-based learning, creating immersive virtual labs where students can conduct experiments in simulated environments, thus helping to mitigate the challenges often posed by poor equipment in physical science laboratories especially in low economies. It highlights how AI tools can improve accessibility to otherwise complex topics, facilitate effective continuous assessment of students’learning outcome and improve students’ motivation to learn science through instant feedback. However, the integration of AI and ML in science education raises some concerns. The issue of privacy, over-dependence on technology, perpetrating educational inequalities due to differentials in access are critical challenges requiring mitigation. Ethical implications of using biased data and inability of AI to enhance critical thinking and creativity compared to human teachers are instructive. A balance in human and technology integration in science education is suggested. Keywords: Artificial intelligence; Machine learning; SCIENCE education; science learning; learning experiences; Educational technology 1. Introduction The rapid advancement of technology has profoundly influenced all landscapes especially education. From traditional classrooms to digital learning environments, technology has emerged as a transformative force, reshaping how humans perceive, impart, acquire, and apply knowledge in virtually all domains (Liando & Tatipang, 2024; Haidir, 2023; Nykyporets et al., 2023; Cheung et al.,2021; Groff, 2013) . This evolution has ushered in a new era in education characterized by enhanced accessibility, engagement, and customization (Malik, 2023; Bondac & Hrestic 2023; Crawford, 2017) . The growing role of technology in education and technology of education can be observed across various dimensions. Digital tools, ranging from interactive learning platforms to virtual simulations, have become integral components of modern pedagogical approaches (Kiong, 2023; Li, 2023; Haleem et al., 2022; Guaña-Moya et al., 2022; Asad et al., 2021; Makarova & Makarova, 2018) . These tools facilitate dynamic and immersive learning experiences that cater to diverse learning styles, engaging students in ways that textbooks and lectures alone cannot achieve. The availability of online resources and open educational materials have democratized education, breaking down geographical barriers and expanding learning opportunities beyond traditional classroom settings. This accessibility is particularly important in bridging educational gapsand promoting lifelong learning, as learners of all ages can access a wealth of information at their own pace and convenience (Luo, 2022; Inegbedion, 2022; Condruzbacescu, 2020; Nobre, 2020; Faridi & Ebad, 2018; Ritella, 2017) . Of note is the impact of collaborative technologies which have transformed the way students interact with peers and educators. Virtual cla

FAQs

How can AI and ML improve science learning experiences?

They enable individualized learning, adaptive feedback, immersive tools, and data-driven insights that help students and teachers interact with science content in personalized ways.

What learning activities does the paper associate with AI-supported science education?

It highlights inquiry-based learning and immersive virtual labs where learners can conduct experiments in simulated environments to overcome limited physical resources.

What concerns arise from integrating AI and ML into science education?

Key concerns include privacy, over-dependence on technology, educational inequality due to unequal access, and ethical implications such as bias and weaker support for critical thinking and creativity compared to human teachers.

Aug 4, 2026

Upload by Sage