Artificial Intelligence in Foreign Language Education

Artificial Intelligence (AI) has increasingly integrated into the education sector, revolutionizing teaching and learning methods. This article examines the beneficial effects of AI on education, emphasizing its ability to tailor learning experiences and enhance teaching practices, while also addressing the associated challenges. AI is undeniably paving the way for a more effective, customized, and sophisticated educational framework. Additionally, it explores the use of artificial intelligence in different aspects of everyday life, including ChatGPT applications, with a special focus on its role in foreign language education. An illustrative educational scenario is presented for teaching German in the 11th grade.

Introduction

The swift advancement and integration of artificial intelligence (AI) are reshaping the way students are educated and are expected to have an even greater impact in the future. AI is regarded as a key driver of progress and innovation in education. This discussion delves into how AI boosts learning, improves teaching methods, and the challenges that need to be overcome to fully leverage its positive effects in the educational sector. It also provides insights into the application of AI in Greece and other nations, highlighting the indispensable role of teachers, who must remain central to the educational process.

Artificial Intelligence

The term Artificial Intelligence (AI) describes a set of technologies related to various scientific fields. The key characteristic of AI is the development of computational systems that mimic human intelligence and cleverness. It is a rapidly evolving field that plays a crucial role in the transition from the third to the fourth industrial revolution.

Concept and Categories of Artificial Intelligence

Artificial intelligence has been defined in various ways. As stated by the European Commission [1], “Artificial intelligence pertains to systems that exhibit intelligent behavior by analyzing their surroundings and acting–with a certain level of autonomy–to achieve defined objectives. AI systems can either be entirely software-based, operating in virtual environments (such as voice assistants, image analysis tools, search engines, and systems for speech and facial recognition), or they can be integrated into physical devices (like advanced robots, self-driving cars, drones, or applications within the Internet of Things).”

AI systems collect data through sensors, databases, and other sources, then model, analyze, and process this information to make decisions and take actions aimed at resolving a problem or achieving a complex objective. Many AI systems have the ability to learn and adapt after making a decision and taking action, they review their environment by gathering new data and assess how effective their decision/action was. This evaluation helps them to learn, adjust, and refine their decision-making processes.

Artificial Intelligence is applied across many domains, including expert systems, natural language processing, video games, image recognition, machine learning, neural networks, and robotics [2]. In the first phase of AI development, expert systems were predominant, while machine learning became more prominent in the next phase [3]. Machine learning, a particularly widespread subfield of AI today, involves software applications that use learning algorithms. These systems have the ability to automatically learn, make decisions, predict, adapt, respond to changes, and improve from experience without needing explicit programming [4]. They process large amounts of data to identify recurring patterns. The more data they handle, the more precise the predictions, with learning occurring through a process of trial and error.

We can categorize AI systems into:

• General AI, which demonstrates intelligent behavior across a wide range of scenarios and problem areas. These systems have not yet been developed but are expected to be created in the future.

• Narrow AI, which shows intelligent behavior within specific functions. Currently, many narrow AI applications, particularly those involving machine learning, are present in everyday life and various sectors such as healthcare, transportation, agriculture, and industry, with frequent use of robotics [3].

The rapid development of AI raises concerns regarding its effects on employment, safety, and ethical issues [5], including:

• Biases in data (related to gender, ethnicity, age, etc.) being embedded into machine learning algorithms, which can result in biased decisions in areas such as hiring, firing, and loan approvals.

• Privacy and personal data protection: issues concerning technologies like facial recognition and the analysis of individuals’ online profiles.

• Realistic but altered multimedia content, such as images that have been convincingly edited.

• Non-transparent use of online behavior data, such as customizing product advertisements and political campaigns based on an individual’s digital activities.

To tackle these issues, the European Union has implemented regulations for AI [4].

What is ChatGPT?

ChatGPT, which stands for “Chat Generative Pre-Trained Transformer,” was developed by the AI research firm OpenAI. It is an artificial intelligence chatbot capable of understanding and processing natural human language to generate responses to user inquiries.

The term “bot” generally refers to an “internet robot” (sometimes also called an “agent”), which is a software application designed to perform automated tasks online. It is also known as a web bot or web robot. Essentially, it functions as an automated system programmed to execute specific tasks, and although we might visualize robots with physical forms, a bot is intangible, existing solely as a software application.

Function of ChatGPT

ChatGPT is a large language model that predicts which words are likely to follow in a sequence, without understanding the content of the words. It is based on deep learning algorithms and uses a neural network to learn language context. This means that the model does not understand the words but knows which symbols (words) are most likely to follow each other based on the data it has been trained on.

Current versions of chatbots, like ChatGPT and its competitor Google Bard, do not make truly “intelligent” decisions. Instead, they replicate words that are commonly found next to each other on the internet. This process relies on mathematics and probabilities. The companies that develop these models present them as productivity tools that can generate text much faster than a human could. ChatGPT utilizes data from the internet and receives feedback from users to improve the naturalness of its outputs.

A 2021 report by Barracuda shows that over two-thirds of internet traffic comes from bots. Specifically, 67% of malicious bot traffic comes from public data centres in North America. Bots are designed with algorithms for specific tasks, such as mimicking human conversations or gathering content from other websites. There are various types of bots: some rely on predefined rules, while others use machine learning to identify key words and create interactions.

OpenAI, founded in 2015 with the goal of advancing artificial intelligence for the benefit of humanity, released ChatGPT on November 30, 2022. The chatbot quickly became popular, attracting over a million users within five days. GPT-1, introduced in June 2018, set the foundation for future models with 117 million parameters. GPT-2, released in February 2019, featured 1.5 billion parameters and demonstrated significant improvements in text generation. A large language model trained on a diverse dataset can perform well across many domains. GPT-2 achieves state-of-the-art results on seven of eight language modeling tasks in zero-shot settings, showing that models trained on varied text can learn to handle many tasks without explicit supervision [6]. However, due to concerns about misuse, its release was delayed until November 2019.

GPT-3, launched in June 2020, represented a massive leap forward with 175 billion parameters, showcasing remarkable text generation capabilities and the ability to answer questions. For all tasks, GPT-3 is applied without any gradient updates or fine-tuning, with tasks and few-shot demonstrations specified purely via text interaction with the model. GPT-3 achieves strong performance on many NLP datasets, including translation, question-answering, and cloze tasks, as well as several tasks that require on-the-fly reasoning or domain adaptation, such as unscrambling words, using a novel word in a sentence, or performing 3-digit arithmetic. At the same time, we also identify some datasets where GPT-3’s few-shot learning still struggles, as well as some datasets where GPT-3 faces methodological issues related to training on large web corpora. Finally, we find that GPT-3 can generate samples of news articles which human evaluators have difficulty distinguishing from articles written by humans. We discuss broader societal impacts of this finding and of GPT-3 in general [7]. GPT-4, the latest version, continues this trend with features like better understanding of user intent, reduced likelihood of generating harmful content, increased accuracy, and real-time internet browsing capability.

ChatGPT includes self-monitoring mechanisms for sensitive or controversial topics. For example, it avoids answering questions about conflicts or political issues. However, these mechanisms may vary by region, and the reliability of responses may be questioned. The use of internet data by AI systems also has legal implications, as demonstrated by the New York Times’ lawsuit against Microsoft and OpenAI for copyright infringement.

ChatGPT has had significant effects across various domains, including:

• Customer Service: Companies use ChatGPT to automate responses to common queries.

• Education: It is utilized to create advanced teaching systems that provide personalized support to students.

• Content Creation: Journalists, copywriters, and content creators employ ChatGPT for generating creative ideas, drafting articles, and even writing poetry.

• Business: Professionals leverage the chatbot to automate tasks such as composing emails or writing code.

• Healthcare: It assists providers and staff with applications like clinical decision support, maintaining medical records, analyzing medical literature, and disease monitoring.

• Entertainment: ChatGPT contributes to the development of video game narratives, movie scripts, dialogue writing, and game enhancements.

• Integration into Other Applications and Platforms: Companies are exploring how to integrate large language models and chatbots into their products and services, such as search engines like Google and Microsoft’s Bing.

The cost of using ChatGPT services varies. Version 3.5 is available for free, as is the Microsoft Copilot chatbot, which is based on ChatGPT 4.0. Free access can be started via  http://chat.openai.com/ [8].

Artificial Intelligence and Education

Why is AI Crucial for Education?

There is a growing belief that to adequately prepare future generations, a certain level of proficiency in Artificial Intelligence is essential. AI is undergoing a major shift with models like BERT, DALL-E, and GPT-3, trained on large, diverse datasets and adaptable to many tasks. These are called foundation models, as they are essential but incomplete. While based on deep learning, their scale leads to new abilities and widespread use but also raises concerns about flaws being inherited by all downstream models. Understanding foundation models will require interdisciplinary research due to their complexity [9].

The Importance of AI in Education

AI is expected to have a profound impact on many areas of science and daily life in the coming decades, including education. Key areas of impact include [10]:

• Learning with AI: AI technologies are being integrated into the educational process to enhance learning and improve teaching. Learning analytics, leveraging data from students’ interactions in digital learning environments alongside machine learning, can offer continuous feedback and personalized, real-time learning experiences [11], [12].

• Learning about AI: This involves gaining skills in computational thinking, problem-solving, and related competencies, often taught in computer science courses or through interdisciplinary approaches in foreign language classes.

• AI Literacy: Today’s students are growing up in an era increasingly dominated by AI applications. Familiarity with these technologies helps students to use AI effectively, engage with it critically, and understand its applications. Students are expected to recognize AI uses, learn about its capabilities, create their own AI applications, and consider associated ethical and safety concerns.

Examples of AI Learning Applications Include:

• Smart Learning Systems: Examples are Robotutor [13], Carnegie Learning’s Mathia [14], and Autotutor [15].

• Digital Assistant Chatbots: ChatGPT, launched by OpenAI in November 2022, is an AI application that generates responses based on prompts.

• AI-Powered Chatbots: Other options include Europeana [16] and Character. AI [17].

• Language Learning Tools: Platforms such as Duolingo [18] and Grammarly [19] assist with language learning and writing. Additional resources include searching for foreign authors or books via Ocean of Books [20] and generating poetry in the style of specific poets with Verse by Verse [21].

• Academic Support: Services like Brainly [22] and Socratic [23] offer assistance with various academic subjects.

Educational Scenario with Mobile Learning and Artificial Intelligence: Teaching Intervention in German Language Class–“Famous Personalities”–An Example

This educational scenario explores the integration of mobile learning and artificial intelligence in a German language class. By focusing on the theme of “Famous Personalities,” students engage in interactive activities that enhance language acquisition through AI-powered tools. The lesson combines digital resources, real-time feedback, and personalized learning paths to foster deeper understanding and engagement.

In Fig. 1, you will find a concise overview of the educational scenario and activity description (Fig. 2). Students are divided into three groups, each creating one of the following characters in Character.AI: Einstein, Callas, or Hundertwasser. They engage in a dialogue, asking questions in the past tense about their chosen figure’s life and achievements. Afterward, they work with their textbook to organize biographical details in the correct order. If needed, they can revisit Character.AI for additional information. Finally, each group presents their findings to the class. This approach enhances engagement by combining AI interaction with traditional learning resources.

Fig. 1. Workflow of educational scenario.

Fig. 2. Description of the activity.

Challenges and Opportunities

The rapid advancement and application of artificial intelligence (AI) are set to significantly impact education and research, although the full extent of this influence is not yet completely understood. Consequently, it is essential to focus on and further explore the potential long-term effects on these fields [24].

AI will make tasks faster, cheaper, and more efficient, affecting both simple and complex tasks, including industries like consulting, finance, and law. It will also change how companies engage with customers and others [25].

While AI offers numerous benefits for education, it also presents several challenges. One major issue is ensuring the protection of students’ personal data. Addressing these ethical concerns is crucial to ensure that AI is used in a fair and responsible manner in educational settings [26].

Another challenge is addressing disparities in technology access. AI tools for education are primarily accessed through online platforms, necessitating reliable internet access and digital devices. In regions where socioeconomic conditions or infrastructure limitations restrict access to these resources, there is a risk that the advantages of AI in education could be lost.

Moreover, the rise of AI might threaten human interaction in education, potentially changing the nature of teaching as we know it [24].

Additionally, the development of these technologies could impede students’ independence and critical thinking by providing ready-made solutions, which may prevent them from developing their own reasoning and justifying their knowledge [24].

Successful integration of AI in education requires educators who are proficient with the technology and its capabilities. This need for familiarity necessitates ongoing training and professional development for teachers. Furthermore, creating advanced technologies demands substantial resources to achieve the desired outcomes.

Although AI technologies might assume teaching roles by offering personalized and adaptive learning experiences more effectively than human educators, or at least reduce teachers to more functional roles, it is unlikely that AI will completely replace educators. Instead, the future of teaching appears to be one where teachers’ roles evolve and adapt, allowing them to use their time more efficiently and leverage their expertise more effectively. Teaching involves more than just transferring knowledge; it is fundamentally a social process. Therefore, AI’s primary role should be to support teachers in their instructional activities and assist students [27].

Conclusions

The goal of technological innovation in education is to enhance the quality of the educational process. Recent advances in AI are contributing to the creation of educational tools designed to improve learning effectiveness and help students grasp concepts through new educational methods.

Countries such as Australia, China, Estonia, France, Singapore, South Korea, and the USA are at the forefront of developing, evolving, and integrating AI applications in education. AI systems are expected to significantly transform educational processes over the coming decades.

In Greece, AI applications have not yet been incorporated into the educational system. Introducing educational robotics into the curricula of kindergartens, primary schools, and secondary schools might represent an initial step toward integrating AI into education, but this process is still in its early stages. As technological innovations have the potential to transform the quality of education, it is expected that AI applications will eventually play a role in enhancing learning and education in Greece as well [28].

The successful integration of AI in teaching largely depends on the acceptance of these technologies by educators. While technological advancements can drastically improve the quality of education, it is crucial for teachers to remain central to the educational process.