Enterprise AI Analysis
AI-Enhanced Digital STEM Language Learning in Technical Education
This article introduces a framework for scientific and professional language training tailored for STEM (Science, Technology, Engineering and Mathematics) specialists, emphasising the integration of digital technologies and artificial intelligence (AI) in language education. The framework aims to develop students' research communication skills and digital competencies, which are essential for effective participation in both national and international scientific discourse. The article discusses contemporary trends in STEM education, emphasising the importance of interdisciplinary approaches, project-based learning, and the utilisation of digital tools to boost language skills and scientific literacy. The article outlines the development and deployment of a digital platform aimed at supporting personalised and adaptive learning experiences, integrating various educational technologies and approaches. Empirical research conducted through a pedagogical experiment demonstrates the effectiveness of the framework, showing significant improvements in students' academic and linguistic competencies across multiple modules. The findings highlight the importance of combining language training with STEM education to equip future engineers for the challenges of a globalised and digitalised professional world. This work reports on the "Enhancing Scientific and Professional Language Learning for Engineering Students in Kazakhstan through Digital Technologies" project conducted at Saginov Technical University (STU) in Kazakhstan and funded by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19678460). The research contributes to the ongoing discussion on improving language teaching in STEM fields, offering a framework that aligns with current educational demands and technological progress.
Executive Impact: Key Metrics
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Instructional Modules
Deep Analysis & Enterprise Applications
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Digital Approach
Design Thinking Approach
Interdisciplinary Approach
Communicative Approach
Sociocultural Approach
Digital Approach
Contemporary linguo-didactics actively employs digital technologies to improve learning and boost interactivity. The digital approach to scientific and linguistic literacy in STEM aims to develop students' skills in working with electronic information sources, scientific databases, machine translation systems, and text visualisation and analysis tools. The use of artificial intelligence (AI) opens new opportunities for personalised learning. AI-driven systems provide automatic checking of lexical and grammatical structures, style analysis, and feedback and suggestions to enhance written work. This approach is realised by creating a virtual educational environment that features gamification elements, interactive simulations, chats, and scientific interaction forums. This aims to boost student motivation and foster independent learning.
Design Thinking Approach
This approach perceives learning as a process of designing and finding solutions, grounded in empathy, analysis, ideation, and testing hypotheses. When applied to engineers' language training, design thinking supports the development of students' research skills, their ability to understand task contexts, set communication goals, and tailor language to professional situations. The use of design thinking encourages creativity, critical thinking, and teamwork. During classes, students progress through identifying problems, gathering data, generating ideas, and implementing solutions through oral and written projects from analytical reports to scientific posters. This fosters innovative scientific writing skills, using language as a means for constructing knowledge.
Interdisciplinary Approach
Interdisciplinarity is a fundamental principle of STEM education. The proposed model implements this by combining linguistic, technical, and research-based content. Education is centred on professional themes across engineering, physics, mathematics, environmental, and information sciences, with scientific language acting as a link between disciplines. An interdisciplinary approach enables students to develop a comprehensive understanding of scientific processes and the capacity to combine knowledge from different fields to solve complex engineering challenges. Language learning becomes an essential part of project and research activities, and linguistic training acts as a tool for professional socialisation.
Communicative Approach
The communicative approach remains important as a core principle of language teaching across any professional field. In engineering education, it specifically focuses on developing academic, research, and technical communication skills. Developing students' ability to use scientific language as a means of interpersonal and professional interaction is the main goal of this approach. The communicative component is carried out through role-playing activities, simulated scientific conferences, and the preparation of reports, presentations, and debates.
Sociocultural Approach
The sociocultural approach is based on the idea that language is both a product and a tool of culture. For engineers, proficiency in scientific language involves understanding the norms of scientific communication, academic ethics, publication structure, and citation rules. Within the framework of the scientific and linguistic literacy model in STEM, this approach aims to develop students' intercultural communicative competence essential for participating in international scientific projects and conferences.
9.94
Average Score Gain in Experimental Groups (55% performance increase)
Enterprise Process Flow
Analysis of the Current State
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Development of the Digital Program
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Teaching materials design
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Pilot Implementation
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Integration and Support
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AI-Driven Adaptive Feedback on Writing Skills
AI-driven systems provide automatic checking of lexical and grammatical structures, style analysis, and feedback and suggestions to enhance written work. This approach is realised by creating a virtual educational environment that features gamification elements, interactive simulations, chats, and scientific interaction forums, boosting student motivation and fostering independent learning. This ensures personalised learning pathways and effective progress tracking, which was validated by the significant improvements in students' academic and linguistic competencies across modules focused on academic writing skills and STEM terminology usage.
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Your AI Implementation Roadmap
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Phase 1: Analysis of the Current State
Diagnostics of proficiency levels and goal setting.
Phase 2: Development of the Digital Program
Platform structure, content creation, and program launch.
Phase 3: Teaching Materials Design
Teacher training, methodological recommendations, and evaluation criteria.
Phase 4: Pilot Implementation
Group selection, platform training, and feedback collection.
Phase 5: Integration and Support
Curriculum integration, program updates, and expansion.
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