CC BY
0УДК 372.881.111.1 ГРНТИ 14.25.09
EXPLORING AN AI-SUPPORTED APPROACH TO CREATIVE WRITING IN SECONDARY SCHOOL ENGLISH CLASSES
ASSYLBEKOVA NAZIK
Student of the Faculty of foreign language teacher training «Astana International University»,
Astana, Kazakhstan
Scientific advisor: MADINA L. ANAFINOVA, Candidate of Philological Science, Ass.Prof. Astana, Kazakhstan
Abstract: This review article looks into how AI-assisted writing tools affect secondary school pupils' creative writing in Kazakhstan. This project uses the Text Generator tool—which was created using natural language processing algorithms—to provide AI-basedprompts, recommendations, and feedback to students in an effort to improve their creative writing abilities. The study measures changes in students' writing skills using a pre-test, while-test, and post-test methods. In addition, surveys, writing samples, feedback sessions, and classroom observations are used to collect qualitative data in order to evaluate the AI tool's perceived efficacy and user experience. The study assesses the impact of the tool on the creativity, coherence, and general quality of student writing by comparing pre-and post-test results. This allows for an evaluation of the tool's ability to assist and enhance creative writing in educational contexts.
Keywords: AI-assisted writing tools, natural language generation, creative writing, educational technology, writing pedagogy, student engagement, writing quality assessment.
Natural language generation (NLG) technologies have become cutting-edge writing tools as artificial intelligence (AI) finds its way into education. This study assesses how Kazakhstani secondary school students' creative writing abilities are affected by the AI tool Text Generator. The linguistic and cultural diversity of the nation offers this study a special setting
However, the extensive possibilities of writing are often limited or they are not given sufficient importance in the learning process. Ultimately, the article brings empirical evidence and theoretical reflections to the discussion about AI in education and informs educators, policymakers, and researchers about the potential benefits and challenges of integrating AI into the pedagogy of creative writing in the secondary education system.
The study measures changes in students' writing skills using the Text Generator application using pre-, while-, and post-tests. Through the examination of writing examples and feedback, the study seeks to ascertain how well the tool improves writing quality, coherence, and creativity. The results will further knowledge of how AI may enhance teaching methods and foster creative writing.
The purpose of this paper is to assess how Text Generator, an AI-enabled tool, has improved Kazakhstani secondary school pupils' creative writing abilities. The goal of the study is to evaluate how AI-based prompts, suggestions, and feedback affect students' writing ability using a pre-test, while-test, and post-test methodology.
It is important to mention the works of Daphne Ippolito, Anyuan, Andy Koenen, and Mehman Burnham, who have made a huge contribution to the study of creative writing using artificial intelligence. They plunged into the fascinating field of creative writing based on artificial intelligence instruments. Their work, "Creative Writing with an Artificial Intelligence-Based Writing Assistant: The Views of Professional Writers" explores the potential impact of natural language Generation (NLG) on creative writing. In this study, they collaborated with 13 professional, published authors from different creative circles. These experienced writers used Worldcraft, a text editor equipped with AI-based writing assistance tools. NLG technology has shown promise in various aspects of creative
writing, including brainstorming, creating story details, building peace, and helping with research [2,
p.3].
Rafael Perez y Perez, a leading researcher in the field of computational creativity and artificial intelligence has developed this idea and conducted extensive research in the field of creative writing systems and interactive storytelling, exploring how artificial intelligence can be used to create narratives and support human creativity in writing. Dr. Perez y Perez is a professor at Universidad Autónoma Metropolitana, Cuajimalpa, therefore he has investigated plenty of his scholarly research around Mexico. One of his academic works was titled "MEXICA: A Computer Model of a Cognitive Account of Creative Writing" [5, p.3].
Furthermore, Pablo Gervás, a professor at Universidad Complutense de Madrid is known for his work on computational creativity and natural language generation. He has exploded AI techniques for generating creative texts, including poetry and narrative. The title of his work is "Computational Approaches to Storytelling and Creativity". As a professor known for his expertise in computational creativity and natural language generation, Gervase's contributions may include discussions of various computational models and algorithms for generating narratives, analyzing narrative structures, or understanding the role of computational methods in stimulating creative storytelling [3, p.1].
Similarly, Tony Veale, a researcher in the field of computational linguistics and creative language generation has conducted research in the field of metaphor generation and computer humor, exploring how artificial intelligence can be used to create engaging and creative writing.
"Research in Creative Writing, Creativity and Language Learning: The Andreas Mueller-Hartmann Festschrift" is a collection of essays and research papers that celebrate Andreas Mueller-Hartmann's academic contributions in the field of creative writing, creativity and language learning. Although Tony Veale's specific contribution to this work may vary depending on the content of the book, his chapter or essay in the collection is likely devoted to computer approaches to creativity in language learning and creative writing [4, p.1].
It is crucial to note Simon Colton, Prof. Computational Creativity at Queen Mary University of London, UK & Monash University, Australia also has contributed to several publications that touch upon creative writing. It can be noticed from his work which is called "The Painting Fool: Stories from Building an Automated Painter" (2012). Although it mostly focuses on visual art, it highlights the principles and issues of computer creativity relevant to creative writing [1, p.4].
In addition, Geraint Wiggins, Professor of Computational Creativity at the VUB and Queen Mary University of London, UK, is famous for his work named "Computational Creativity: The Final Frontier?" (2006). In this paper, Wiggins discusses the concept of computational creativity and its implications for various creative domains, including creative writing. He explores the challenges and opportunities of using AI techniques to support and augment human creativity in literary endeavors [1, p.5].
Methodology. The participants of the study consist of secondary school students enrolled in English classes in Kazakhstan. Convenience sampling is employed to select participants, ensuring representation across different grade levels and proficiency levels in English writing. The AI-enabled tool, Text Generator, is developed in collaboration with experts in artificial intelligence and creative writing pedagogy. Text Generator utilizes natural language processing algorithms to generate prompts, suggestions, and feedback tailored to enhance students' creative writing skills.
Experimental Procedure:
Pre-Test: Before the intervention, students complete a pre-test to assess their baseline creative writing abilities. This involves writing a short story or essay on a given prompt without AI assistance.
While-test: Students are introduced to Text Generator and instructed on how to use it to support their creative writing process. They are encouraged to utilize the tool during in-class writing activities and assignments over a designated period.
Post-Test: Students complete a post-test similar to the pre-test, writing a short story or essay on a given prompt, this time with the option to use Text Generator.
Feedback Session: Students participate in a feedback session where they reflect on their experiences using Text Generator and provide insights into its perceived impact on their creative writing skills.
Writing Samples: Students' pre-test and post-test writing samples are collected and analyzed to assess changes in creativity, coherence, and quality of writing.
Students complete surveys or questionnaires to provide feedback on their experiences using Text Generator, including perceived usefulness, ease of use, and impact on writing confidence. Observations are conducted during in-class writing activities to document students' engagement with Text Generator and any observable changes in their writing process.
In conclusion, this study reveals the potential of an artificial intelligence-based approach to teaching creative writing in high school English lessons. Recognizing the difficulties faced by students in effectively expressing themselves in a foreign language, the study explores how artificial intelligence technology, using the example of the Text Generator tool, can support and improve the creative writing process. Through a methodology that includes pre-tests, during testing, post-testing, and feedback sessions, complemented by data collection methods such as surveys, questionnaires, and classroom observations, the study provides valuable information about the effectiveness of Text Generator in enhancing students' creative writing skills. In the result, the study highlights the importance of introducing innovative approaches to teaching and learning, Harnessing the power of artificial intelligence to empower students and promote their development as effective communicators and creative thinkers in the 21st century.
1. Colton, S., & Wiggins, G. A. (2012). Computational creativity: The final frontier? Proceedings of the 4th International Conference on Computational Creativity (pp. 1-8). Vrije Universiteit Brussel.
2. Daphne, I. A., & Mehman, B. (2022). Creative writing with an artificial intelligence-based writing assistant: The views of professional writers.
3. Gervás, P. (2009). Computational approaches to storytelling and creativity. AI Magazine, 30(3), 49-62.
4. Jones, R. H. (2019). Creativity in language learning and teaching: Translingual practices and transcultural identities. Applied Linguistics Review, 10(4), 627-637.
5. Pérez y Pérez, R., & Sharpies, M. (2014). MEXICA: A computer model of a cognitive account of creative writing. Journal of Experimental & Theoretical Artificial Intelligence, 26(3), 267-287.
6. Simon, C. (2012). The Painting Fool: Stories from building an automated painter. In Computers and Creativity (pp. 3-38).
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