Paper ID: 300. Presented by Raj Thakur. AI Based Education System Enhanced the Learning of Students. 

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AI Based Education System Enhanced the Learning of Students

International Conference on Advances in Computing Research on Science  Engineering and Technology (ACROSET 2024)

AI Based Education System Enhanced the Learning of Students. 

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AI Based Education System  Enhanced the Learning of Students

Authors Details:   Raj Thakur  Dr. Snehalata Barde   Neelesh Singh  Aaryan Barde Shreyansh Patel

Overview. Result & Discussion. Literary Review. Research Methods. 

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Abstract. The education sector is poised for a significant shift propelled by Artificial Intelligence (AI) technologies. This paper explores the various uses of AI in education, such as data driven decision assistance for instructors, adaptive assessment tools, intelligent tutoring, and personalized learning systems. It looks at how chatbots and virtual assistants driven by AI can improve learning by giving students instant, tailored support and direction. This paper also emphasizes how AI may improve student engagement and gamification of course materials, changing the educational environment into one that is dynamic, engaging, and pleasant.. 

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The education sector is poised for a significant shift propelled by Artificial Intelligence (AI) technologies. This paper explores the various uses of AI in education, such as data driven decision assistance for instructors, adaptive assessment tools, intelligent tutoring, and personalized learning systems. It looks at how chatbots and virtual assistants driven by AI can improve learning by giving students instant, tailored support and direction. This paper also emphasizes how AI may improve student engagement and gamification of course materials, changing the educational environment into one that is dynamic, engaging, and pleasant.

Introduction. 01. Personalized Learning at Scale. 

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Literary Review. Numerous studies highlight AI’s role in tailoring educational experiences to individual learning styles, improving student engagement and academic performance (VanLehn, K. (2018)).. 

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Numerous studies highlight AI’s role in tailoring educational experiences to individual learning styles, improving student engagement and academic performance (VanLehn, K. (2018)).

As AI becomes more integrated into education, addressing ethical considerations, including data privacy and algorithmic biases, is essential to ensure responsible implementation (Lynch, M. F., & Kuula-Luumi, A. (2018)).

AI tools offer immediate, detailed feedback, crucial for formative assessment. Studies show that intelligent tutoring systems enhance learning by providing personalized feedback tailored to student needs (Boyle & Nicol, 2016; Ma et al., 2019).

Research Methodology. strategies and approaches OF Traditional Education. 

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strategies and approaches OF Traditional Education

[image] Electonic
Gadgets
Social Media
Platforms
Chatbots
• Mobile Phones, Laptops and Pc etc
• Youtube , Applications and softwares.
• Brad , ChatGPT , Siri etc

In-Person Learning: Primarily classroom-based education with face-to-face instruction. Fixed Curriculum: Predefined course structures with little room for flexibility. Lectures and Textbooks: Dependence on teacher-led lectures and standardized materials. Standardized Testing: Uniform assessments for all students. Teacher-Centered Approach: Emphasis on teacher as the primary source of knowledge. Geographical and Resource Limitations: Physical classrooms and access to resources are geographically restricted.

05. AI Over Traditional Methods. Figure 2 Shows the retention rates of all methods. 

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Figure 2 Shows the retention rates of all methods

[image] Lecture
Reading
Demonstration
Discussion Group
Practice By Doing
Teach Others or Immediate Use of Learning
Average Retention Rates
5%
20%
75%
90%

Personalized Learning: Adapts to individual learning styles and needs. Immediate Feedback: Provides real-time assessments to enhance   understanding. Adaptive Learning: Adjusts difficulty based on student performance. 24/7 Availability: Learning accessible anytime, anywhere. Efficiency: Reduces administrative burdens for educators. Data-Driven Insights: Informs teaching strategies with analytics. Accessibility: Supports diverse learning needs and backgrounds. Interactive Learning: Engages students through gamification and interactive tools. Innovative Assessment: Offers varied assessment methods beyond standardized tests. Teacher Support: Assists educators in identifying and addressing student needs. Lifelong Learning: Facilitates ongoing education and skill development

Result & Discussion. 06. Impact of AI Education Before and After Pandemic. 

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Impact of AI Education Before and After Pandemic

Parameter Before pandemic After pandemic During pandemic AI in education Access to education Not widely available Personalized the learning Lack of access of technology to many individuals AI has been used to develop chat bots that can answer students’ questions, provide feedback, and offer personalized learning experiences. Learning outcomes Not used much in educating Shift to smart learning and adapting AI technology Disturbance in traditional learning AI has been used to develop intelligent tutoring systems that can provide real-time feedback, adapt to students’ learning styles, and improve learning outcomes. Teaching methods Traditional methods are used Gamification, Simulations and interactive video technique are used for teaching Force teachers to adapt to Hybrid learning AI has been used to develop intelligent authoring tools that can help teachers create engaging content, assess student performance, and provide feedback. Student engagement AI is not used to engage students in their studies Development of new ways like virtual classroom, online group discussion, and forum etc. Students face difficulty in engaging with the teachers and many students face anxiety, depression and stress AI has been used to develop intelligent Chatbots that can engage with students in natural language conversations, answer their questions, and provide feedback. Mental health Not used AI is used to provide mental health services like counseling, mindfulness practice, and therapy. The pandemic has had a significant impact on students’ mental health, with many experiencing anxiety, depression, and stress. AI can detect the sign of depression and stress from the message to the Chatbots, and provide suitable services. Teacher training Traditional methods are used  AI is used to provide students automated grading and support scalable can help the teacher. The pandemic has highlighted the need for teachers to be trained in online teaching methods. AI has been used to develop intelligent training systems that can provide personalized training experiences for teachers based on their needs and preferences. Assessment methods Traditional methods such as exams was conducted The pandemic has forced educational institutions to rethink their assessment methods. The pandemic has led to the development of new assessment methods that are more flexible and adaptable. AI has been used to develop intelligent assessment systems that can provide real-time feedback on student performance, identify areas of weakness, and suggest personalized study plans. Curriculum  The curriculum is static, it is predefined and fix. The pandemic has highlighted the need for a more flexible and adaptable curriculum It is redesigned in accordance to hybrid learning AI has been used to develop intelligent curriculum design tools that can help educators create customized curricula based on student needs and interests. Cost of education The cost of education was generally stable before the pandemic. The cost of education is expected to increase due to the additional expenses associated with hybrid learning environments. The cost of education decrease as during pandemic all the learning was on virtual mode. AI has been used to develop intelligent financial aid systems that can help students find scholarships, grants, or other forms of financial assistance based on their needs and qualifications.

Result & Discussion. 07. Impact of AI Education Before and After Pandemic. 

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Improvement in the learning process from pandemic years

Infrastructure Improvement Enhance internet connectivity and technological resources in schools. Localized Content Develop AI tools and educational materials tailored to regional languages and cultures. Teacher-Student Ratio Improvement Utilize AI to support teachers and manage larger classrooms effectively. Community Engagement Involve local communities in the adoption and implementation of AI solutions. Pilot Programs and Scalability Test AI initiatives in select regions before wider implementation.

Conclusion. 08. Support for Educators. Localized and Relevant Content. 

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Reference. Ma, W., Adesope, O., Nesbit, J. C., & Liu, Q. (2019). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 111(5), 857-877.. 

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Ma, W., Adesope, O., Nesbit, J. C., & Liu, Q. (2019). Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of Educational Psychology, 111(5), 857-877.

Boyle, J. T., & Nicol, D. J. (2016). Feedback: A crucial element of formative assessment. Assessment & Evaluation in Higher Education, 41(2), 229-241.

Lynch, M. F., & Kuula-Luumi, A. (2018). Ethical considerations for educational uses of artificial intelligence. Educational Technology Research and Development, 66(5), 1163-1185.

Anderson, T. (2017). Towards a theory of online learning. In The Theory and Practice of Online Learning (pp. 45-74). Athabasca University Press.

S. Barde, V. Kaimal “Raga Identification using Praat: An Acoustic Signal Processing Tool”, International Journal of Management, Technology And Engineering, Volume IX, Issue III, MARCH 2019,970-974. ISSN NO: 2249-7455

Blue and White Simple Thesis Defense Presentation

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