WHAT ARE THE EXPECTED IMPACTS OF AI ON EDUCATION, AND HOW SHOULD IT FORM THE FUTURE OF EDUCATIONAL PROGRAMS AND LEARNING TECHNIQUES?
Журнал: Научный журнал «Студенческий форум» выпуск №21(288)
Рубрика: Педагогика
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Научный журнал «Студенческий форум» выпуск №21(288)
WHAT ARE THE EXPECTED IMPACTS OF AI ON EDUCATION, AND HOW SHOULD IT FORM THE FUTURE OF EDUCATIONAL PROGRAMS AND LEARNING TECHNIQUES?
Abstract. This study explores how AI might affect education, with a particular emphasis on program and technique improvement. Based on a review of the literature and a survey carried out at NIS Aktobe, it looks at how AI may improve individualized learning, speed administrative procedures, and offer innovative teaching strategies. The study also takes algorithmic bias and data privacy into account. By combining findings, it suggests strategies to maximize AI benefits while mitigating risks, offering insights for creating an inclusive and equitable learning environment for all.
Keywords: individualized learning, education, artificial intelligence, and ethical concerns.
Introduction. The application of AI in education is growing quickly, with the potential to revolutionize programs and ways of teaching. While highlighting AI's potential to improve teacher development, equity, and educational outcomes, organizations such as UNESCO also raise concerns over privacy, equity, and academic integrity.
Research, like that of Kizilcec et al. (2017), demonstrates how real-time material adaptation by tailored AI systems can increase student performance and engagement. AI can help accelerate administrative work, freeing up teachers to concentrate more on instruction. However unequal access to AI resources might exacerbate educational disparities, and the integration of AI into education may change the function of instructors thereby decreasing the necessity for human educators (Zhang and Aslan, 2021). This study employs a mixed-method approach to shed light on the educational uses of AI, utilizing NIS Aktobe surveys and interviews. Itaims to inform policymakers and practitioners on integrating AI effectively and ethically in education.
Aims
- Develop practical AI applications to enhance personalized learning.
- Investigate AI's role in promoting academic integrity.
- Explore how AI can improve teaching effectiveness and student engagement.
Literature review
Artificial intelligence is transforming education by streamlining administrative tasks, enhancing teaching methods, and personalizing learning experiences. This review synthesizes recent findings on AI's impact on education.
AI's most significant contribution is its ability to personalize learning. Algorithms assess individual student strengths and weaknesses, creating tailored materials that improve engagement and performance (Kizilcec et al., 2017). Automated grading systems like Turnitin and Gradescope save time for teachers, allowing them to focus on creative teaching and mentoring (Kulkarni et al., 2015).
AI analytics provide educational institutions with data to make informed decisions, customize teaching strategies, and identify at-risk students, thus improving outcomes (Arnold & Pistilli, 2012). Intelligent Tutoring Systems (ITS) mimic human tutoring, offering feedback and adjusting lessons to improve learning outcomes (VanLehn, 2011).
In conclusion, AI has the potential to revolutionize education by making it more personalized, efficient, and accessible. Embracing AI's capabilities can lead to a future where education empowers students worldwide and fosters lifelong learning.
Methods
This study uses a quantitative methodology to examine AI's expected impacts on education and its role in shaping future educational programs and techniques, working primarily with numerical data. A literature review was conducted to understand the current perspectives on AI in education. Data was collected via a survey, targeting students and teachers at NIS Aktobe (grades 7 to 12) to gauge their reactions and opinions on AI implementation.
The survey was designed with input from a coordinating professor to ensure relevance and clarity, using a 5-point Likert scale, multiple-choice, and one open-ended question, totaling seven questions. The quantitative approach allowed for broad generalizations and predictions about the population's preferences, but also had limitations such as generalized responses, slow response rates, and a short time frame, which affected the accuracy and validity of the results.
To address these limitations, the study acknowledges the need for detailed feedback and justifies the methodology choices, suggesting that future research could benefit from combining surveys with interviews for more comprehensive insights.
Results
The survey at NIS Aktobe targeted students (grades 7-12) and teachers to gauge their views on AI in education. Out of 54 participants, the majority were 11th graders (55.6%), with others spread across 10th and 12th grades, and teachers.
Key Findings:
- Familiarity with AI: Most participants (70.3%) rated their familiarity with AI as high (4 or 5 out of 5).
- AI Usage: 88.9% had used AI for learning.
- Preferred AI Tools: 64.8% favored Chatbots like ChatGPT, while 35.2% preferred adaptive learning platforms and intelligent systems.
- AI in Lessons: 55.6% found AI useful for teaching, 16.7% did not, and 27.7% were neutral.
- Impact on Grading: Responses were mixed—35% positive, 35% negative, and 30% unclear.
Insights:
Most participants are familiar with AI and see value in tools like ChatGPT for learning. There's general support for using AI in teaching, but mixed feelings about its impact on grading. These findings underscore the need to integrate AI thoughtfully in education, balancing its benefits and challenges.
Conclusion
This study explored the transformative potential of AI in education, focusing on its impacts on students and teachers. While AI promises to revolutionize education, issues like equitable access and algorithmic bias pose significant challenges.
Findings from NIS Aktobe revealed AI's potential for personalized learning, but also highlighted challenges in access and integrity.
- Personalized Learning: AI can tailor education to individual student needs using adaptive learning systems.
- Academic Honesty: AI can help detect and prevent plagiarism, promoting ethical behavior.
- Teacher Support: AI can automate administrative tasks, providing data-driven insights for personalized student support and allowing teachers to focus on higher-order skills.
In summary, AI could significantly enhance education by improving student experiences, maintaining academic integrity, and supporting teachers. However, to fully realize this potential, challenges around bias, access, and integrity must be addressed to create an inclusive and effective educational system.
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