Academic literature on the topic 'AI for Quiz Conduction'

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Journal articles on the topic "AI for Quiz Conduction"

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Hirulkar, Sagar Ravindra, and Prof. Samata V. Athawale. "Quiz Master AI: An Interactive Machine Learning-Based Quiz Generator." International Journal of Ingenious Research, Invention and Development (IJIRID) 3, no. 5 (2024): 474–82. https://doi.org/10.5281/zenodo.14208814.

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Quiz Master AI is an innovative machine learning-based application designed to create an interactive and engaging platform for quiz-based learning. The primary goal of the project is to develop a system that generates multiple-choice questions (MCQs) from user-provided content and allows users to participate in quizzes, enhancing their learning experience. Participants can level up based on their performance, fostering a competitive and collaborative environment for knowledge acquisition. In Quiz Master AI, users can form groups with a designated group author who provides a paragraph or passage as input. This input is processed by a machine learning model trained to extract key information, identify important concepts, and generate contextually accurate and diverse multiple-choice questions. The goal is to test the comprehension and retention of the paragraph's content, making the learning process more interactive and effective. Once the questions are generated, the group members take the quiz, answering the MCQs based on their understanding of the input passage. After the quiz is completed, participants are scored, and each individual's performance determines their progression through different levels. This "level-up" system is designed to motivate users by rewarding them for their learning achievements and providing a sense of accomplishment as they improve. Quiz Master AI leverages natural language processing (NLP) techniques to ensure the questions are relevant, unambiguous, and educational. The model can handle a wide range of content topics, making it suitable for various educational purposes, from school subjects to professional training. Additionally, the platform's gamified approach encourages healthy competition and collaboration among users, making learning both fun and productive.
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Dr.Jayasree, Venkitachalam. "A Study Evaluating Usage of Artificial Intelligence in Higher Education among Faculty Members of Colleges in South Mumbai Region." International Journal of Advance and Applied Research 4, no. 32 (2023): 21–28. https://doi.org/10.5281/zenodo.8433849.

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<strong>Abstract:</strong> Higher education is entering a revolutionary period with impacts on teaching, learning, and institutional operations due to the growth of artificial intelligence (AI) technology. The purpose of conducting this research is to evaluate the awareness of artificial intelligence in higher education among faculty members of South Mumbai Region and also evaluate the demographic profile and usage of AI. The technique used in this study is a Wilcoxon one-sample signed rank test, ANOVA and independent t-test. The outcomes of the research showed that various artificial intelligence&nbsp;had different levels of awareness. High awareness was discovered in Canva, ChatGPT, GradeScope, Beautiful AI, Turnitin (plagiarism checker), Copilot Education, Google Board, Gamma, Quill Bot, and Grammarly. The amount of awareness was low in Sendsteps.ai, Yippity (Quiz), MagicSchool.ai, Red Cube Paper (Articles), and Squirrel AI, in contrast. The study also discovered that usage of AI in higher education is independent of gender but dependent on age groups.
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Lan, Shanxi. "Intelligent Teaching Assistants Combining Computer Vision and Natural Language Processing: Enhancing Personalized Tutoring in Online Education." Applied and Computational Engineering 138, no. 1 (2025): 133–38. https://doi.org/10.54254/2755-2721/2025.21383.

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This study explores the potential of Intelligent Teaching Assistants (ITAs) that utilize computer vision (CV) and natural language processing (NLP) technologies to improve personalized educational experiences in online learning environments. The ITA system uses computer vision to track students' facial expressions and physical stance together with eye movement while employing natural language processing to interpret spoken and written student questions for customized responses. The research details the ITA system's structural design which encompasses data gathering and real-time adaptability functions while assessing its effects on student engagement levels and academic performance and satisfaction measures. The two-week study with 50 students showed better learning results and higher engagement than standard online teaching techniques. The ITA system reached 85% student engagement by the end of the experiment and quiz scores increased by 20%. After conducting surveys post-experiment students exhibited high satisfaction levels because personalized feedback and adaptive responses enhanced their learning experience. The research reveals how AI-based ITAs could transform online education with their ability to provide scalable learning solutions that are customized for each student.
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Susanto, Dias Andris, Andi Priyolistiyanto, Fitra Pinandhita, A. B. Prabowo K.A, and Djoko Sri Bimo. "Utilizing ChatGPT on Designing English Language Teaching (ELT) Materials in Indonesia: Opportunities and Challenges." Celt: A Journal of Culture, English Language Teaching & Literature 24, no. 1 (2024): 157–71. http://dx.doi.org/10.24167/celt.v24i1.11633.

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This study aims to examine the impact of artificial intelligence (AI) on pragmatic English language teaching in universities. The scope of the study is limited to the opportunities and challenges of English language teaching. This study was carried out using a mixed method of conducting surveys and in-depth interviews. A questionnaire link using Google Forms from Spreadsheet was sent to 6 English lecturers via WhatsApp group and personal contact. The study sample consisted of 6 English lecturers from state and private universities in Central Java. Observation, questionnaire analysis, and interview transcripts show that the emergence of artificial intelligence (AI) technology has created opportunities and challenges to teaching and learning English. AI has transformed English language teaching in higher education. The findings and discussion elaborate some novelties of this study; 1) the profile of utilizing ChatGPT in pragmatics ELT teaching, portrays that ChatGPT roles in teaching scenarios play 3 major sessions, like; designing creative and innovative pragmatics teaching materials, setting up the midterm test of pragmatics project, and lastly, assessing and evaluating the pragmatics final test project. 2) The opportunities of using ChatGPT for lecturers, ChatGPT is one of the most sophisticated AI tools available today, and it can write nearly anything that an instructor wants it to. ChatGPT can help lecturers with a variety of tasks, such as creating course outlines, student progress reports, test and quiz questions, and grading rubrics; developing more inclusive and accessible learning activities; interacting with students and their families; and contributing text for websites or bulletin boards to maintain a connection between students and their families. 3) The challenges of applying ChatGPT for lecturers; ChatGPT can provide immediate responses to student questions, ChatGPT can adapt to individual student needs, ChatGPT can increase accessibility and inclusivity by providing language support for students with diverse learning needs, ChatGPT can serve as a valuable tool for language practice and strengthening, ChatGPT can encourage active learning by encouraging students to ask questions, engage in discussions, and seek clarification on challenging concepts, Integrating ChatGPT into language teaching can inspire innovative teaching approaches, such as blended learning models, flipped classrooms, and gamified learning experiences, that leverage technology to improve student learning outcomes
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Suzuki, Jun, Koji Matshuda, Masatoshi Suzuki, Takuma Kato, Shumpei Miyawaki, and Kyosuke Nishida. "Live Competition: AI King—Quiz AI Japan Championship—." Journal of Natural Language Processing 28, no. 3 (2021): 888–94. http://dx.doi.org/10.5715/jnlp.28.888.

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Deepthi, J. "MCE Website with AI ChаtBot". INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, № 05 (2025): 1–9. https://doi.org/10.55041/ijsrem48166.

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ABSTRACT In the digital era, integrating intelligent systems within academic environments has become essential for enhancing student experiences and providing efficient educational services. This project presents a comprehensive web-based student support portal tailored for Malnad College of Engineering (MCE). Built using React.js, the application delivers multiple interactive features aimed at guiding students in their academic and career journeys. Key functionalities include an AI-powered chatbot, a future course recommendation quiz, detailed guidance on higher studies options, and a role-based admin panel for managing quiz content and analyzing results. The chatbot assists with general queries, while the quiz intelligently analyzes user input to suggest domains such as Artificial Intelligence, Cybersecurity, Cloud Technologies, and Data Science. The higher education module visually maps out progression paths from school to professional degrees, offering insight into programs like M.Tech, MBA, and international study options. The admin module is protected using JWT authentication, allowing secure access to content management features. Overall, this system bridges the gap between traditional educational advising and modern digital tools, offering a personalized and responsive platform for student development.
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Bhargavi, J., R. Naveena, G. Gowtham Raju, and D. Ganesh. "AI Virtual Classroom Assistance Using Zoom." International Scientific Journal of Engineering and Management 04, no. 01 (2025): 1–6. https://doi.org/10.55041/isjem02232.

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This work investigates developing an AI-powered virtual classroom assistant integrated with Zoom. The system enables users to input a topic for a class and select from four AI voice lecturers: Indian male, Indian female, UK male, and UK female. Users can schedule the class once the voice is selected, which generates a link directing them to the official Zoom website. During the 15-minute session, the AI lecturer presents the topic. Post-class, the system automatically generates a PowerPoint presentation on the chosen topic and conducts a quiz to evaluate students. Students scoring low are provided with simpler quizzes. It will generate the results also. The quiz is conducted under proctoring to ensure integrity. A chatbot feature allows students to ask questions and resolve doubts. The implementation leverages Python with Flask, Selenium, and libraries like PyAutoGUI, Pyperclip, and threading for seamless functionality and interaction. . Keywords: AI virtual classroom, Zoom integration, voice assistants, automated PowerPoint generation, AI lecturer, proctored quiz, chatbot, Python Flask, Selenium, interactive learning.
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Dr., Anitha S., G. Balasurya, Vishruth N. V. Dinu, C. Jenish, and A. Kathiresh. "AI Based Automated MCQ Generator." Journal of Advancement in Software Engineering and Testing 8, no. 3 (2025): 44–50. https://doi.org/10.5281/zenodo.15575106.

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<em>This project aims to develop an AI-based Automated MCQ Generator that can dynamically generate multiple-choice questions from user-provided input such as text topics or uploaded study materials. The development of an AI-powered Automated MCQ Generator capable of dynamically creating multiple-choice questions based on user inputs, including uploaded study materials (PDF, DOCX, TXT files) or manually entered topics. Unlike traditional systems that depend on a pre-existing question database, our solution leverages the Gemini API to generate fresh, contextually relevant questions in real time. The system is built with a lightweight and interactive frontend (HTML, CSS, JavaScript) and a Flask-based backend that handles file processing, topic input, and API integration. All MCQs are generated on demand, eliminating the need for static storage. In-memory session management ensures efficient handling of quiz sessions, without reliance on external databases.By automating the MCQ creation process, the project significantly reduces the manual effort required by educators and offers a scalable solution for personalized and adaptive assessments. This tool is especially suited for online education platforms, teachers, and learners seeking quick, intelligent quiz generation tailored to specific learning materials or topics.</em>
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Raghuvanshi, Deepansh. "Edu AI Summarizer." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 1373–76. https://doi.org/10.22214/ijraset.2025.68205.

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Edu AI Summarizer serves as an innovative platform which enhance the educational video experience for students and teachers while helping researchers make the most of their study materials. The platform uses advanced speech-to-text technology along with natural language processing (NLP) to detect video topics after which it forms tidy summaries. Users receive downloadable PDFs containing straightforward well-prepared study materials derived from original video summaries. The system enhances student revision efficiency by providing clear content direction to educators and enables researchers to quickly derive academic findings from discussions. Edu AI Summarizer provides an efficient learning solution through its development using React.js together with Spring Boot and MySQL and its integration of tools such as OpenAI and Whisper. The platform will develop additional exciting features such as multilingual support and handwriting recognition and automatic quiz creation to offer greater value to the e-learning community in future iterations.
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Fernández-Martínez, Carmen, Isidoro Hernán-Losada, and Alberto Fernández. "Early Introduction of AI in Spanish Middle Schools. A Motivational Study." KI - Künstliche Intelligenz 35, no. 2 (2021): 163–70. http://dx.doi.org/10.1007/s13218-021-00735-5.

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AbstractThis paper describes the practical initiative to include Artificial Intelligence (AI) in the Spanish educational system’s curriculum at an early age. This proposal is in line with the current trend of introducing AI in school curricula all over the world. To this end, we propose an Artificial Intelligence workshop for middle schools within the existing subject, Technology, Programming and Robotics. In order to test the suitability of introducing AI at an early age, we conducted the activities at a bilingual middle school in Madrid. As evaluation tools, a quiz and motivational study of the students concerning AI was carried out using Situational Motivational Scale (SIMS) before and after introducing the activities. Responses of 84 students were analysed and the conclusion was reached that it is slightly better to introduce AI at an early age.
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Books on the topic "AI for Quiz Conduction"

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Delbecchi, Nanni. La coscienza di Mike: Storia confidenziale della critica televisiva dalle imprese del re del quiz ai blog, ovvero, come Lascia o raddoppia? ha trasformato l'elettrodomestico più amato nella nutrice degl'italiani, ha reso il piccolo schermo materia letteraria e ha spinto un gruppo di scrittori e cronisti a inventarsi un nuovo mestiere. Mursia, 2009.

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Patente Nautica Entro le 12 Miglia - Testo Tecnico-Didattico: Per la Preparazione Ai Quiz D'esame 2019. Independently Published, 2021.

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Pollastri, Stefano. Patente Nautica Entro e Oltre 12 Miglia - Testo Tecnico-Didattico: Per la Preparazione Ai Quiz D'esame. Independently Published, 2022.

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Pollastri, Stefano. Patente Nautica Entro le 12 Miglia - Testo Tecnico-Didattico: Per la Preparazione Ai Quiz D'esame 2019. Independently Published, 2018.

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Marmo, Roberto. Quizmania: Scopri Come Aumentare le Tue Chance di Partecipare ai Quiz Televisivi e Vincere Premi da Favola. Bruno Editore, 2021.

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I3FDZ, Fiorino De Lazzari. AGGIORNAMENTO Ai Testi Quiz Di Elettronica e Normativa per Radioamatori: AGGIORNAMENTO Alla Prima Edizione Dei Testi Quiz Di Elettrotecnica per Paterne Di Radioamatore e Normativa per Radioamatori. Independently Published, 2021.

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Cosa Preferisci? : : Libro Di Domande per Bambini Dai 7 Ai 12 Anni, un Divertente Gioco per Famiglie e Grandi Gruppi. Divertiti con Questo Quiz Di Domande Assurde! Independently Published, 2022.

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Final Jeopardy: Man vs. machine and the quest to know everything. Houghton Mifflin Harcourt, 2011.

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La coscienza di Mike: Storia confidenziale della critica televisiva dalle imprese del re del quiz ai blog, ovvero, come Lascia o raddoppia? ha trasformato l'elettrodomestico più amato nella nutrice degl'italiani, ha reso il piccolo schermo materia letteraria e ha spinto un gruppo di scrittori e cronisti a inventarsi un nuovo mestiere. Mursia, 2009.

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Book chapters on the topic "AI for Quiz Conduction"

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Boateng, George, Jonathan Abrefah Mensah, Kevin Takyi Yeboah, et al. "Brilla AI: AI Contestant for the National Science and Maths Quiz." In Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64315-6_17.

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Chico, Víctor Jesús Sotelo, Júlia Ferreira Tessler, Rodrigo Bonacin, and Julio Cesar dos Reis. "BEQuizzer: AI-Based Quiz Automatic Generation in the Portuguese Language." In Lecture Notes in Computer Science. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-70242-6_23.

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Lang, Michael. "Using Data Analytics to Detect Possible Collusion in a Multiple Choice Quiz Test." In Responsible AI and Analytics for an Ethical and Inclusive Digitized Society. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-85447-8_63.

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Bleakley, Chris. "America’s Favourite Quiz Show." In Poems That Solve Puzzles. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198853732.003.0010.

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Chapter 11 tells the tale of the IBM Jeopardy! Challenge. Jeopardy! is America’s favourite television quiz show. Three players compete on the buzzer to respond to clues provided by the host. The twist is that the clues are “answers” and the player’s guesses are phrased as “questions”. In 2011, the two all-time greatest Jeopardy! players played IBM’s Watson computer for a US$1 million prize. IBM had been working on Watson for almost six years. The IBM team developed an array of new AI algorithms, each dealing with a different clue type. The computer’s memory was packed with libraries of books and even entire encyclopaedias. At the end of the first episode, Watson was neck-and-neck with Brad Rutter. The second episode was a landslide for Watson. The finale was an emphatic victory for the computer. Ken Jennings raised the white flag for humanity: “I, for one, welcome our new computer overlords”.
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Guven, Ceren, and Hakan Altinpulluk. "Unveiling the Untapped Potential." In Advances in Educational Technologies and Instructional Design. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-5518-3.ch008.

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In this study, the characteristics of artificial intelligence tools used in the field of education are analyzed by dividing them into certain categories. The web content analysis conducted between January 15 and February 12, 2024, examined the characteristics of these tools and their relationship with education in detail. According to the findings, AI tools such as chatbots (ChatGPT, Gemini, and Microsoft Copilot), presentation tools (SlidesGo, Presentation.AI, Gamma), quiz tools (QuizBot, Quizgecko, and Questen), and document analysis tools (Quillbot, ChatPDF, and Summarizer.org) offer various features. The results show that although there are differences for each category and tool, there are significant differences and limitations in terms of language supported and pricing policies in all the tools analyzed. These findings emphasize that AI tools offer solutions for various needs in education, but these solutions come with some limitations.
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Sanhong, Tong, Wei YaoYang, Li Wei, Pei Jun, and Uzma Sarwar. "Implementing Adaptive Learning Systems." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-1827-1.ch002.

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The artificial intelligence (AI) revolution has dramatically transformed education, with the possibility of personalizing learning through adaptive systems within reach. Despite these promises, classroom adoption of AI-based systems is still difficult and faces various barriers, including resistance from educators, issues of privacy, and low scalability. This study addresses said challenges by developing a new hybrid adaptive learning framework combining Collaborative Filtering (CF) and transformer-based BERT models. While CF makes recommendations based on the behavior of the students, BERT improves personalization with context-aware and semantic insights, capturing the emotional and cognitive nuances. The framework was validated with 300 students and 50 instructors, showing a 40.32% improvement in quiz scores, a 30.91% increase in resource engagement, and a 32.35% rise in recommendation accuracy. This proves hybrid system overcomes many of the obstacles to adoption, presenting a scalable, ethical solution in personalized education within and beyond traditional teaching practice
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Barakat, Hadeer Ehab, and Islam Tharwat Abdel Halim. "Implications of Artificial Intelligence for Medication Therapy Management and Its Efficacy in Clinical Pharmacy." In Advances in Wireless Technologies and Telecommunication. IGI Global, 2024. https://doi.org/10.4018/979-8-3373-1132-6.ch007.

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Medication therapy management (MTM) is of importance for the assistance of healthcare providers to create medication plans that fit with each patient's specific requirements. MTM includes services provided by pharmacists or other qualified healthcare professionals to improve the treatment regimen for each patient. These services can involve assessment of the patients' health status, conduction of pharmaceutical care plan, and decrease the hospital stays.Artificial intelligence (AI) allows MTM to be conducted with higher efficiency and effectiveness in the applications of clinical pharmacy. AI has been indispensable in the medical field by assisting providers in reducing expenditures, enhancing patient outcomes, and increasing the overall efficacy of patient treatment through enhancing medication safety, predicting health risks and outcomes across diverse populations, reducing time and costs of treatment, monitoring medication adherence, and scheduling follow-up healthcare services. As a result, healthcare providers are currently obligated to implement AI to assist with MTM services
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Sultan, Muhammad Faisal, Muhammad Nawaz Tunio, Muhammad Asim, and Erum Shaikh. "Artificial Intelligence and Its Implications for Cattle and Buffalo Farming." In Advances in Finance, Accounting, and Economics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-5723-1.ch011.

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The purpose of writing this chapter is to make readers understand the role of AI in cattle farming. Previously studies on this topic were scarce and did not contain all the possible benefits of smart-cattle farming. Therefore, this study is developed through consulting multiple studies to reflect vividly on benefits that AI may provide to cattle farmers. Hence, this study is highly significant for researchers, scholars, and academicians who as this study is not only beneficial for improvement of knowledge and conduction of further studies but may also aid better business practices and policy making associated with the use of AI in cattle farming. However, this is a generic form of study which is developed for better understanding and improvement of research activities rather than to reflect outcomes inferentially. Hence, further work that may add to one's understanding must be conducted through focusing on the gist of this study.
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Sharma, Manvi, Indra Kishor, Anju Dwivedi, and Abhishek Bhattacherjee. "Smart Devices for Augmenting Sensory Perception Empowering Differently-Abled Individuals Through Advanced Assistive Technologies." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-2307-7.ch020.

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.This study aims to design and validate a low-cost, AI-powered wearable system that provides real-time, adaptive, and personalized sensory augmentation for differently-abled individuals using edge-based intelligence and multi-modal feedback. The proposed system integrates vision, audio, and motion sensors with lightweight AI models deployed on edge devices. Feedback is delivered through bone conduction audio, haptic actuators, or OLED displays, depending on the impairment type and environmental conditions. Testing involved 20 users across three impairment categories in real-world environments. The system achieved 91.3% object detection accuracy, 93.2% speech recognition accuracy, and maintained sub-150ms response latency. Usability scores exceeded 85 on the SUS scale across all user groups. Average battery life was over 7.5 hours. Compared to existing commercial systems, the proposed solution demonstrated superior adaptability, offline functionality, and cost-effectiveness.
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Gonçalves, Rogério Sales, Guilherme Salomão Agostini, Reinaldo A. C. Bianchi, et al. "Inspection of Power Line Insulators." In Handbook of Research on New Investigations in Artificial Life, AI, and Machine Learning. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-8686-0.ch018.

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Insulators are power transmission line components responsible for two key tasks: the first one is to support the mechanical stress originated by the weight of the cables and devices, and the second one is to avoid electrical dissipation from the cables to the tower structure. Even though the shape and material of the insulator is made in such a way as to avoid the conduction of electrical current on its surface, if some types of dirty accumulates excessively, the insulator can still conduct an electric arc to the tower, causing damage to the power grid. This chapter first presents the state-of-the-art power line insulator cleaning methods and the techniques used to identify insulators that require cleaning. Then, this chapter describes an algorithm that makes use of machine learning, deep learning, and computer vision technics, which can be used embedded in an unmanned aerial vehicle, to support the energy company in the assessment of the levels of dirt on the insulators. Finally, experimental results are presented showing the challenges and the open problems.
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Conference papers on the topic "AI for Quiz Conduction"

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Chang, Chia-Kai, and Lee-Chia-Tung Chien. "Enhancing Academic Performance with Generative AI-Based Quiz Platform." In 2024 IEEE International Conference on Advanced Learning Technologies (ICALT). IEEE, 2024. http://dx.doi.org/10.1109/icalt61570.2024.00062.

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Bhatia, Gaurav, and Raya Alhajri. "Accelerate Learning with AI Powered Quiz Master Using Llama LLM." In 2025 International Conference for Artificial Intelligence, Applications, Innovation and Ethics (AI2E). IEEE, 2025. https://doi.org/10.1109/ai2e64943.2025.10983252.

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Memeti, Agon, Ibrahim Neziri, Neshat Ajruli, Krenar Huseini, Asri Nuhi, and Aqim Iljazi. "Context-Aware AI for Real-Time Content and Quiz Recommendations in Student Learning Environments." In 2025 3rd Cognitive Models and Artificial Intelligence Conference (AICCONF). IEEE, 2025. https://doi.org/10.1109/aicconf64766.2025.11063980.

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Pant, Aastha, Rashina Hoda, and Paul McIntosh. "Raising AI Ethics Awareness: Insights from a Quiz-Based Workshop with Software Practitioners - An Experience Report." In 2025 IEEE/ACM International Workshop on Responsible AI Engineering (RAIE). IEEE, 2025. https://doi.org/10.1109/raie66699.2025.00014.

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Kobayashi, Hisaya, and Masanori Takagi. "Learning by Quiz Creation: A Novel Approach Using Interactive Generative AI and Its Experimental Application." In 2024 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE). IEEE, 2024. https://doi.org/10.1109/tale62452.2024.10834337.

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Wang, Xia, Silke Elisabeth Wrede, Lars van Rijn, and Joachim Wöhrle. "AI-BASED QUIZ SYSTEM FOR PERSONALISED LEARNING." In 16th annual International Conference of Education, Research and Innovation. IATED, 2023. http://dx.doi.org/10.21125/iceri.2023.1257.

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Teo, Wei, Ze Teoh, Dayang Abang Arabi, et al. "What Would You do? An Ethical AI Quiz." In 2023 IEEE/ACM 45th International Conference on Software Engineering: Companion Proceedings (ICSE-Companion). IEEE, 2023. http://dx.doi.org/10.1109/icse-companion58688.2023.00036.

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MacNeil, Stephen, James Prather, Rahad Arman Nabid, et al. "Fostering Responsible AI Use Through Negative Expertise: A Contextualized Autocompletion Quiz." In ITiCSE 2025: Innovation and Technology in Computer Science Education. ACM, 2025. https://doi.org/10.1145/3724363.3729067.

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Woldai, Betiel, Sophie Henne, Mascha-Lea Fersch, Sudarshan Kamath Barkur, and Sigurd Schacht. "A Qualitative Evaluation of an AI-Supported Quiz Application to Assess Learning Progress." In The Paris Conference on Education 2023. The International Academic Forum(IAFOR), 2023. http://dx.doi.org/10.22492/issn.2758-0962.2023.39.

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Sugumari, G., and Narsimhulu Dunna. "Numerical study on heat conduction model for multi-layered heat resistant thermal protection fabric." In AI POWERED TECHNOLOGY INTEGRATION FOR SUSTAINABILITY (AI-PTIS-2024). AIP Publishing, 2025. https://doi.org/10.1063/5.0279459.

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