Generative AI Soaring in the Skies: New Horizons in Aviation English

Generative AI Soaring in the Skies: New Horizons in Aviation English

DOI: 10.4018/979-8-3693-1351-0.ch019
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Abstract

Several regulations in the aviation industry have been made by authorities to minimize the incidents due to language barriers; however, a more reasonable solution lies in equipping prospective pilots with necessary language skills in target settings. This requires a transformation in aviation English (AE) classrooms through the medium of emerging technologies. Accordingly, this chapter presents a novel strategy for rethinking AE instruction by using approaches from generative artificial intelligence. It investigates the ways in which prompt engineering and synthetic content production might be used to improve the efficacy of AE teaching. Learners may benefit from better language comprehension, communication skills, and situational awareness by seamlessly incorporating AI-driven language creation into the curriculum. Instructors could find examples of generative AI-driven classroom applications for improved learning outcomes. Considering these potential contributions to the field, this chapter may, in turn, innovate and uplift the AE courses and safety in the aviation industry.
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Introduction

In the context of a more connected global landscape, the significance of effective communication becomes vital, particularly within businesses that prioritize non-negotiable elements such as safety and accuracy. The aviation sector, which plays a significant role in facilitating worldwide connectivity and trade, exemplifies the essential need for effective and precise communication. In this context, the need for precise and unambiguous communication extends beyond mere convenience, including matters of utmost significance and potential fatality (FAA, 2016). The distinction lies in the contrast between a secure departure and a possible calamity, as well as between a seamless arrival and a potential catastrophe.

In the field of aviation operations, which span over international airspace and transcend linguistic and geographical boundaries, the establishment of a shared language emerges as a crucial facilitator for fostering effective and cooperative interactions. Aviation English, being a “codified, abbreviated, jargon-filled register” (Trippe & Baese-Berk, 2019, p. 1), effectively fulfills this duty. The domain-specific language serves as a means of communication for pilots, ATCOs, ground crew, and other professionals in the aviation industry. It not only facilitates the exchange of crucial information but also represents a collective dedication to upholding the utmost levels of safety and operational proficiency. This particular kind of communication functions as the dominant language used in aviation, enabling smooth and efficient contact among pilots, ATCOs, and aviation workers worldwide (ICAO, 2010). However, the interlocutors in the context of aviation may not necessarily possess shared first languages and cultural backgrounds, which constructs a significant hazard for mutual intelligibility and thus, safer skies (Ishihara & Prado, 2021). The importance lies in clarity, accuracy, and situational awareness since any instance of miscommunication or misunderstanding might potentially result in significant ramifications. The mastery of AE is, therefore, not only a question of adherence but rather an essential prerequisite for ensuring the safety and effectiveness of aircraft operations.

The use of language in aviation communication distinguishes it from other forms of linguistic expression. The concept covers a diverse range of situations, spanning from the exchange of standard phraseology to the handling of demanding and urgent crises (ICAO, 2003). Pilots are required to effectively communicate crucial information with accuracy and coherence while operating in complex operational environments. The task at hand involves adequately equipping learners to navigate many forms of communication seen in diverse settings, enabling them to effortlessly move between everyday interactions, specialized terminology, and time-sensitive instructions.

The field of AE is intricately connected with operating processes, safety regulations, and regulatory mandates. Merely possessing fluency in a language is inadequate; those working in the aviation industry must effectively combine their language proficiency with an in-depth awareness of aviation-specific procedures and norms (Alderson, 2009). The biggest challenge lies in developing comprehensive training programs that successfully address this gap.

Formerly, the delivery of AE education has mostly relied on traditional approaches, including in-person classroom teaching and the use of language textbooks. While these methods have shown some efficacy, they often fall short in addressing the dynamic and quickly changing nature of aircraft operations (Dincer, 2023). Moreover, the constraints imposed by static educational resources and the lack of real-world context might impede the acquisition of practical communication skills and situational awareness necessary in professional settings.

Key Terms in this Chapter

ChatBot: A digital assistant designed for interactive conversations, often automating tasks or providing information.

Large Language Models: Massive digital libraries trained on vast text data to predict and produce language.

Artificial Intelligence in Education: Infusing smart algorithms into learning environments to enhance teaching and student performance.

Aviation English: The specific language of the skies ensuring clear communication among aviation professionals.

ChatGPT: A virtual conversationalist designed to mimic human-like text interaction

Artificial Intelligence: A digital realm where machines mimic human cognition to solve tasks.

ICAO: The global agency that governs aviation standards, ensuring skies are navigated safely and seamlessly worldwide.

Air Traffic Controller: Those who orchestrate flight paths to ensure safety and efficiency.

Standard Phraseology: Preset language conventions to ensure clarity in specific contexts.

Generative Artificial Intelligence: The branch of AI that crafts new content based on patterns from data.

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