Tools

LEADER 05502cam 2200589 i 4500

001 on1518003619;

003 OCoLC;

005 20260519120647.0;

008 250304s2025 flua 000 0 eng d;

015 a| GBC5289772| bnb;

016 7 a| 3005314452| Uk;

020 a| 9781032746685q| hardback;

020 a| 1032746688;

020 a| 9781032746654q| paperback;

020 a| 1032746653;

020 z| 9781040358993q| ePub ebook;

020 z| 9781040358948q| PDF ebook;

024 8 a| CIPO000208500;

029 0 a| UKMGBb| 300531445;

035 a| (OCoLC)1518003619;

050 4 a| LB1028.43b| .A36 2025;

082 04 a| 378.1734632| 23;

049 a| EREE;

245 00 a| Adopting artificial intelligence tools in higher education :b| student assessment /c| edited by Thangavel Murugan, Karthikeyan Periasamy, A.M. Abirami.;

246 30 a| Adopting AI tools in higher education;

264 1 a| Boca Raton :b| CRC Press,c| [2025].;

300 a| xix, 220 pages :b| illustrations (black and white) ;c| 24 cm;

336 a| textb| txt2| rdacontent;

336 a| still imageb| sti2| rdacontent;

337 a| unmediatedb| n2| rdamedia;

338 a| volumeb| nc2| rdacarrier;

504 a| Includes bibliographical references and index.;

505 0 a| AI-Driven Evaluation Techniques: Revolutionizing Student Practices / S. K. Sajida Sultana, R. Renugadevi, Maridu Bhargavi, and Shaik Abdul Afzal Biyabani -- Inclusive Learning and Assessment in the Era of AI / Minal Patil, R. H. Goudar, Anand Nayyar, G. M. Dhananjaya, and Vijayalaxmi N. Rathod -- Automated Grading Systems: Enhancing Efficiency and Consistency in Student Assessments / S. C. Vetrivel, V. P. Arun, Ramya Ambikapathi, and T. P. Saravanan -- The Potential and Drawbacks of Machine Learning for Student Assessment / K. Kartheeban, V. Aanandaram, D. Lakshminarasimman, and D. Kabalishwaran -- NLP-Driven Approaches to Automated Essay Grading and Feedback / V. Nikhil, R. Annamalai, and Senthil Jayapal -- Enhancing Learning Outcomes for the Dyslexic Students Using AI-Powered Assistants / Anjali Mathur -- Transforming Education through AI-Powered Personalized Assessment Models / S. Kanthimathi, Prayasha Nanda, Shravan Venkatraman, Varsana Renganayagan, and Sivaraman Eswaran -- Enhancing Student Engagement and Success in Post-COVID-19 through AI Technologies / A. Peter Soosai Anandaraj, V. Murugananthan, A. Judith Arockiya Gladies, S. Sridevi, V. Vijayalakshmi, and B. Senthilkumaran -- AI Tools for Plagiarism Detection and Academic Integrity / S. Baghavathi Priya, B. Kavya Sai, and Tamil Selvi Madeswaran -- Unlocking Potential: Personalizing Learning and Assessment with Cutting-Edge Technologies / R. Renugadevi, Maridu Bhargavi, G. Kalaiarasi, P. Ranjith Kumar, A. Arul Edwin Raj, and B. Saritha;

520 a| This edited volume explores the adoption of artificial intelligence (AI) tools in higher education, specifically focusing on student assessment. It examines the integration of various AI tools within higher education, discussing the challenges and opportunities they present and the innovative solutions they offer.The chapters explore various issues surrounding the use of AI in higher education and propose potential solutions. The book begins with a systematic exploration of AI's potential, presenting innovative ways to ensure fair and accurate assessments that enhance the overall quality of education. It highlights the benefits of AI-powered grading systems that streamline assessment processes, provide timely feedback, and promote fair evaluations. The text discusses how machine learning algorithms can revolutionize assessment methods, allowing individualized, adaptive testing tailored to each student's unique needs. Furthermore, it examines natural language processing (NLP) techniques for evaluating student essays by analyzing linguistic features such as grammar and semantic coherence. Moreover, it highlights AI-powered virtual assistants offering personalized feedback and learning recommendations. Case studies illustrate successful AI assessment implementations and methods for improving AI-based evaluations. The book also addresses engagement and success in the post-COVID-19 context. It raises concerns about plagiarism and academic integrity, comparing AI solutions to traditional methods while exploring the challenges associated with adopting AI in education. Educators, administrators, academics, and technology experts working in institutes of higher learning will find this volume compelling. It is also suitable for students taking courses in educational technology, e-learning, and digital learning.;

650 0 a| Artificial intelligencex| Educational applications.;

650 0 a| Education, Higherx| Data processing.;

650 0 a| Education, Higherx| Technological innovations.;

650 0 a| Student-centered learning.;

650 0 a| Gamification.;

700 1 a| Murugan, Thangavel,d| 1989-e| editor.;

700 1 a| Periasamy, Karthikeyan,e| editor.;

700 1 a| Abirami, A.M.,e| editor.;

776 08 i| ebook version :z| 9781040358993;

938 a| YBP Library Servicesb| YANKn| 21361220;

938 a| YBP Library Servicesb| YANKn| 21361219;

938 a| Brodartb| BRODn| 138118809;

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999 a| LB1028.43 .A36 2025w| LCc| 1i| 30372017784395k| AVAIL_SOONl| JGESm| JOYNERr| Ys| Yt| JGESBKu| 5/19/2026x| BOOKz| JSTACKSo| .STAFF. jssb;

Adopting artificial intelligence tools in higher education : student assessment / edited by Thangavel Murugan, Karthikeyan Periasamy, A.M. Abirami.

Other author	Murugan, Thangavel, 1989- editor.
Other author	Periasamy, Karthikeyan, editor.
Other author	Abirami, A.M., editor.
Format	Book
Publication	Boca Raton : CRC Press, [2025].
Description	xix, 220 pages : illustrations (black and white) ; 24 cm
Subjects	Artificial intelligence--Educational applications. Education, Higher--Data processing. Education, Higher--Technological innovations. Student-centered learning. Gamification.

Portion of title	Adopting AI tools in higher education
Contents	AI-Driven Evaluation Techniques: Revolutionizing Student Practices / S. K. Sajida Sultana, R. Renugadevi, Maridu Bhargavi, and Shaik Abdul Afzal Biyabani -- Inclusive Learning and Assessment in the Era of AI / Minal Patil, R. H. Goudar, Anand Nayyar, G. M. Dhananjaya, and Vijayalaxmi N. Rathod -- Automated Grading Systems: Enhancing Efficiency and Consistency in Student Assessments / S. C. Vetrivel, V. P. Arun, Ramya Ambikapathi, and T. P. Saravanan -- The Potential and Drawbacks of Machine Learning for Student Assessment / K. Kartheeban, V. Aanandaram, D. Lakshminarasimman, and D. Kabalishwaran -- NLP-Driven Approaches to Automated Essay Grading and Feedback / V. Nikhil, R. Annamalai, and Senthil Jayapal -- Enhancing Learning Outcomes for the Dyslexic Students Using AI-Powered Assistants / Anjali Mathur -- Transforming Education through AI-Powered Personalized Assessment Models / S. Kanthimathi, Prayasha Nanda, Shravan Venkatraman, Varsana Renganayagan, and Sivaraman Eswaran -- Enhancing Student Engagement and Success in Post-COVID-19 through AI Technologies / A. Peter Soosai Anandaraj, V. Murugananthan, A. Judith Arockiya Gladies, S. Sridevi, V. Vijayalakshmi, and B. Senthilkumaran -- AI Tools for Plagiarism Detection and Academic Integrity / S. Baghavathi Priya, B. Kavya Sai, and Tamil Selvi Madeswaran -- Unlocking Potential: Personalizing Learning and Assessment with Cutting-Edge Technologies / R. Renugadevi, Maridu Bhargavi, G. Kalaiarasi, P. Ranjith Kumar, A. Arul Edwin Raj, and B. Saritha
Abstract	This edited volume explores the adoption of artificial intelligence (AI) tools in higher education, specifically focusing on student assessment. It examines the integration of various AI tools within higher education, discussing the challenges and opportunities they present and the innovative solutions they offer.The chapters explore various issues surrounding the use of AI in higher education and propose potential solutions. The book begins with a systematic exploration of AI's potential, presenting innovative ways to ensure fair and accurate assessments that enhance the overall quality of education. It highlights the benefits of AI-powered grading systems that streamline assessment processes, provide timely feedback, and promote fair evaluations. The text discusses how machine learning algorithms can revolutionize assessment methods, allowing individualized, adaptive testing tailored to each student's unique needs. Furthermore, it examines natural language processing (NLP) techniques for evaluating student essays by analyzing linguistic features such as grammar and semantic coherence. Moreover, it highlights AI-powered virtual assistants offering personalized feedback and learning recommendations. Case studies illustrate successful AI assessment implementations and methods for improving AI-based evaluations. The book also addresses engagement and success in the post-COVID-19 context. It raises concerns about plagiarism and academic integrity, comparing AI solutions to traditional methods while exploring the challenges associated with adopting AI in education. Educators, administrators, academics, and technology experts working in institutes of higher learning will find this volume compelling. It is also suitable for students taking courses in educational technology, e-learning, and digital learning.
Bibliography note	Includes bibliographical references and index.
Issued in other form	ebook version : 9781040358993
ISBN	9781032746685 hardback
ISBN	1032746688
ISBN	9781032746654 paperback
ISBN	1032746653
ISBN	ePub ebook
ISBN	PDF ebook
Standard identifier#	CIPO000208500

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Adopting artificial intelligence tools in higher education : student assessment / edited by Thangavel Murugan, Karthikeyan Periasamy, A.M. Abirami.

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