Lexical Profile of AI-Generated Content in Higher Education

Inbunden, Engelska, 2025

869 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

This book investigates vocabulary use in texts generated by Artificial Intelligence. The growing use of AI tools such as ChatGPT and DeepSeek in University settings indicates the importance of evaluating the products of such technology as potential reading material. In the study reported, twelve AI-generated samples of writing covering arts, commerce, law and science are analysed for vocabulary use, and compared with four research articles published in journals on the same topics. The vocabulary profiling covers high-frequency words, academic and technical vocabulary, most frequently used content words and low-frequency words. Potential future developments in AI are explored.

Produktinformation

Utgivningsdatum2025-10-08
Mått152 x 229 x 15 mm
Vikt374 g
FormatInbunden
SpråkEngelska
SerieLinguistic Insights
Antal sidor188
Upplaga25001
FörlagPeter Lang AG, Internationaler Verlag der Wissenschaften
ISBN9783034361132

Tillhör följande kategorier

List of Tables - List of Figures - 1. Introduction - 1.1. The GenAI Era - 1.2. GenAI in Higher Education - 1.3. Vocabulary Profiling - 1.4. Vocabulary Lists - 1.5. Anticipations of the Future - 2. GenAI in Higher Education - 2.1. Artificial Intelligence - 2.2. Generative Artificial Intelligence - 2.2.1. Machine Learning - 2.2.2. Natural Language Processing - 2.2.3 Large Language Models - 2.2.4. Datasets - 2.2.5. Algorithms - 2.3. GenAI Tools in Higher Education - 3. Vocabulary Profiling - 3.1. Lexical Nature of Academic Writing - 3.1.1. High Frequency Words - 3.1.2. Academic Words - 3.1.3. Technical Words - 3.1.4. Proper Nouns - 3.1.5. Low Frequency Words - 3.2. K1, K2 and AWL Word Lists - 3.3. BNC-COCA Word Lists - 4. The Current Study - 4.1. Selection of GenAI Tools - 4.2. Selection of Prompts for GenAI Text Generation - 4.3. Analysis of Texts - 5. Analysis 1: K1, K2 and AWL Words - 5.1. Arts Texts - 5.1.1. Non-GenAI - 5.1.2. GenAI Scite - 5.1.3. GenAI Jenni - 5.1.4. GenAI Yomu - 5.1.5. Comparison of Arts Texts - 5.2. Commerce Texts - 5.2.1. Non-GenAI -5.2.2. GenAI Scite - 5.2.3. GenAI Jenni - 5.2.4. GenAI Yomu - 5.2.5. Comparison of Commerce Texts - 5.3. Law Texts - 5.3.1. Non-GenAI - 5.3.2. Non-GenAI Scite - 5.3.3. Non-GenAI Jenni - 5.3.4. Non-GenAI Yomu - 5.3.5. Comparison of Law Texts - 5.4. Science Texts - 5.4.1. Non-GenAI - 5.4.2. Non-GenAI Scite - 5.4.3. Non-GenAI Jenni - 5.4.4. Non-GenAI Yomu - 5.4.5. Comparison of Science Texts - 6. Analysis 2: K1 to K10 Words - 6.1. Arts Texts - 6.2. Commerce Texts - 6.3. Law Texts - 6.4. Science Texts - 7. Analysis 3: 20 Most Frequently Occurring Content Words - 7.1. Arts Texts - 7.2. Commerce Texts -7.3. Law Texts - 7.4. Science Texts - 8. Analysis 4: Low Frequency Word Use - 8.1. Arts Texts - 8.2. Commerce Texts - 8.3. Law Texts - 8.4. Science Texts - 9. Conclusion - 9.1. Use of GSL K1, GSL K2 and AWL Words - 9.2. Use of BNC-COCA K1 to K10 Words - 9.3. 20 Most Frequently Occurring Content Words - 9.4. Use of Low Frequency Words - 9.5. Final Comments - References - Appendices - Index

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Del 318 i serien Linguistic Insights

Lexical Profile of AI-Generated Content in Higher Education

Inbunden, Engelska, 2025

AvDavid Hirsh,Maurizio Gotti

869 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Produktinformation

Utgivningsdatum2025-10-08
Mått152 x 229 x 15 mm
Vikt374 g
FormatInbunden
SpråkEngelska
SerieLinguistic Insights
Antal sidor188
Upplaga25001
FörlagPeter Lang AG, Internationaler Verlag der Wissenschaften
ISBN9783034361132

Tillhör följande kategorier

List of Tables - List of Figures - 1. Introduction - 1.1. The GenAI Era - 1.2. GenAI in Higher Education - 1.3. Vocabulary Profiling - 1.4. Vocabulary Lists - 1.5. Anticipations of the Future - 2. GenAI in Higher Education - 2.1. Artificial Intelligence - 2.2. Generative Artificial Intelligence - 2.2.1. Machine Learning - 2.2.2. Natural Language Processing - 2.2.3 Large Language Models - 2.2.4. Datasets - 2.2.5. Algorithms - 2.3. GenAI Tools in Higher Education - 3. Vocabulary Profiling - 3.1. Lexical Nature of Academic Writing - 3.1.1. High Frequency Words - 3.1.2. Academic Words - 3.1.3. Technical Words - 3.1.4. Proper Nouns - 3.1.5. Low Frequency Words - 3.2. K1, K2 and AWL Word Lists - 3.3. BNC-COCA Word Lists - 4. The Current Study - 4.1. Selection of GenAI Tools - 4.2. Selection of Prompts for GenAI Text Generation - 4.3. Analysis of Texts - 5. Analysis 1: K1, K2 and AWL Words - 5.1. Arts Texts - 5.1.1. Non-GenAI - 5.1.2. GenAI Scite - 5.1.3. GenAI Jenni - 5.1.4. GenAI Yomu - 5.1.5. Comparison of Arts Texts - 5.2. Commerce Texts - 5.2.1. Non-GenAI -5.2.2. GenAI Scite - 5.2.3. GenAI Jenni - 5.2.4. GenAI Yomu - 5.2.5. Comparison of Commerce Texts - 5.3. Law Texts - 5.3.1. Non-GenAI - 5.3.2. Non-GenAI Scite - 5.3.3. Non-GenAI Jenni - 5.3.4. Non-GenAI Yomu - 5.3.5. Comparison of Law Texts - 5.4. Science Texts - 5.4.1. Non-GenAI - 5.4.2. Non-GenAI Scite - 5.4.3. Non-GenAI Jenni - 5.4.4. Non-GenAI Yomu - 5.4.5. Comparison of Science Texts - 6. Analysis 2: K1 to K10 Words - 6.1. Arts Texts - 6.2. Commerce Texts - 6.3. Law Texts - 6.4. Science Texts - 7. Analysis 3: 20 Most Frequently Occurring Content Words - 7.1. Arts Texts - 7.2. Commerce Texts -7.3. Law Texts - 7.4. Science Texts - 8. Analysis 4: Low Frequency Word Use - 8.1. Arts Texts - 8.2. Commerce Texts - 8.3. Law Texts - 8.4. Science Texts - 9. Conclusion - 9.1. Use of GSL K1, GSL K2 and AWL Words - 9.2. Use of BNC-COCA K1 to K10 Words - 9.3. 20 Most Frequently Occurring Content Words - 9.4. Use of Low Frequency Words - 9.5. Final Comments - References - Appendices - Index