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Siraprapa Kotmungkun; Wichuta Chompurach; Piriya Thaksanan – English Language Teaching Educational Journal, 2024
This study explores the writing quality of two AI chatbots, OpenAI ChatGPT and Google Gemini. The research assesses the quality of the generated texts based on five essay models using the T.E.R.A. software, focusing on ease of understanding, readability, and reading levels using the Flesch-Kincaid formula. Thirty essays were generated, 15 from…
Descriptors: Plagiarism, Artificial Intelligence, Computer Software, Essays

Arun-Balajiee Lekshmi-Narayanan; Priti Oli; Jeevan Chapagain; Mohammad Hassany; Rabin Banjade; Vasile Rus – Grantee Submission, 2024
Worked examples, which present an explained code for solving typical programming problems are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the example code. However, instructors rarely have time to provide…
Descriptors: Coding, Computer Science Education, Computational Linguistics, Artificial Intelligence
Guido Lang; Tamilla Triantoro; Jason H. Sharp – Journal of Information Systems Education, 2024
This study explores the potential of large language models (LLMs), specifically GPT-4 and Gemini, in generating teaching cases for information systems courses. A unique prompt for writing three different types of teaching cases such as a descriptive case, a normative case, and a project-based case on the same IS topic (i.e., the introduction of…
Descriptors: Computational Linguistics, Computer Software, Artificial Intelligence, Readability Formulas
Kole A. Norberg; Husni Almoubayyed; Logan De Ley; April Murphy; Kyle Weldon; Steve Ritter – Grantee Submission, 2024
Large language models (LLMs) offer an opportunity to make large-scale changes to educational content that would otherwise be too costly to implement. The work here highlights how LLMs (in particular GPT-4) can be prompted to revise educational math content ready for large scale deployment in real-world learning environments. We tested the ability…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Educational Change
Crossley, Scott A.; Skalicky, Stephen; Dascalu, Mihai; McNamara, Danielle S.; Kyle, Kristopher – Discourse Processes: A multidisciplinary journal, 2017
Research has identified a number of linguistic features that influence the reading comprehension of young readers; yet, less is known about whether and how these findings extend to adult readers. This study examines text comprehension, processing, and familiarity judgment provided by adult readers using a number of different approaches (i.e.,…
Descriptors: Reading Processes, Reading Comprehension, Readability, Adults
Solnyshkina, Marina I.; Harkova, Elena V.; Kiselnikov, Aleksander S. – English Language Teaching, 2014
The article summarizes the results of the comparative study of Reading comprehension texts used in B2 level tests: Unified (Russia) State Exam in English (EGE) and Cambridge First Certificate in English (FCE). The research conducted was mainly focused on six parameters measured with the Coh-Metrix, a computational tool producing indices of the…
Descriptors: Foreign Countries, Reading Comprehension, English (Second Language), Second Language Instruction
Aziz, Anealka; Fook, Chan Yuen; Alsree, Zubaida – Advances in Language and Literary Studies, 2010
Reading materials are considered having high readability if readers are interested to read the materials, understand the content of the materials and able to read the materials fluently. In contrast, reading materials with low readability discourage readers from reading the materials, create difficulties for readers to understand the content of…
Descriptors: Readability, Computational Linguistics, Reading Materials, Second Language Learning
Burke, Victoria; Greenberg, Daphne – Adult Basic Education and Literacy Journal, 2010
There are many readability tools that instructors can use to help adult learners select reading materials. We describe and compare different types of readability tools: formulas calculated by hand, tools found on the Web, tools embedded in a word processing program, and readability tools found in a commercial software program. Practitioners do not…
Descriptors: Reading Materials, Readability, Reading Material Selection, Comparative Analysis
Kouame, Julien B. – Journal of MultiDisciplinary Evaluation, 2010
Background: Readability tests are indicators that measure how easy a document can be read and understood. Simple, but very often ignored, readability statistics cannot only provide information about the level of difficulty of the readability of particular documents but also can increase an evaluator's credibility. Purpose: The purpose of this…
Descriptors: Readability, Readability Formulas, Evaluation Methods, Literacy