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Showing posts with label 81 Rusch. Show all posts
Showing posts with label 81 Rusch. Show all posts

Journal of Linguistics and Language Teaching

Volume 14 (2023) Issue 2, pp 187-202


Integrating Artificial Intelligence in Language Curricula: Empowering Students for Future Competencies


Silvia Adamcová (Bratislava, Slovakia) & Michaela Rusch (Zwickau, Germany)


Abstract   

In today's professional communication, a constant expansion of vocabulary is necessary to keep up with developments in technology and science. This paper looks at the current topic of artificial intelligence in relation to applications such as ChatGPT and chatbots. The investigation will also explore the potential of artificial intelligence in promoting and supporting linguistic skills. Additionally, the discussion will cover the implementation of these AI tools into foreign language curricula and classroom practices. Specific requirements for teachers and students are addressed under the aspect of future competencies, which represent a particular challenge given the high speed of diverse developments. This study contributes to the ongoing discussion regarding the role of artificial intelligence in higher education. Overall, this evaluation offers insights into a highly topical issue of AI application that will significantly influence linguistic and pedagogical practice in the future.

KeywordsArtificial Intelligence, future competencies, ChatGPT and Large Language Models, digital language learning, curricula design




1 Introduction

Increasing digitalisation has been leading to changes in almost all areas of our society - in business, politics, the media, and the working environment. Digital media and Artificial Intelligence (AI) tools have become an integral part of our everyday lives and therefore also need to be integrated into educational institutions. As a result, digital transformation is currently dominating the modern education policy discourse. The focus of public debate is usually on subject-specific, conceptual, curricular, or methodological issues that have partly been resolved in the past (Hrdličková 2017, 2018). Interest is primarily directed towards the material equipment of schools and universities with digital media. The high potential for innovation and the speed of technological developments and applications are associated with technical and methodological challenges that comprehensively affect academic disciplines, research, and the content of degree courses and bring with them new questions and opportunities. The use of digital media is increasingly prevalent in both teaching practices and beyond, leading to significant changes through digitalisation (Bär 2019).

One of the forms and types of modern digitalisation is AI, which is currently the subject of continuing debate in scientific and non-scientific circles. AI is one of the most important digital topics of the future and attracting increasing interest in science, business, and society. Developments are progressing rapidly. AI is associated with great potential for the future, but also with dangers such as threats to cybersecurity or job replacement. The development of AI has accelerated with Large Language Models (LLM). ChatGPT has suddenly enabled diverse, very concrete, and productive applications in almost all sectors, including foreign language teaching. The exploration and use of digital media in the classroom raises several key questions that will be addressed in this article: 

  • Digitalisation affects education, learning environments, and the processes of teaching and learning foreign languages. Which of these areas are associated with the greatest technical and methodological challenges?
  • Where is the greatest potential for innovation in new media?
  • What is the distinct impact of AI on the qualification requirements and future skills of graduates?
  • What changes are necessary in foreign language methodology to ensure the success of our graduates in the future?
  • How can an AI model such as ChatGPT improve and support foreign language teaching?

The answers to these questions help us imagine innovative future scenarios in the field of education that influence the institutional promotion of foreign language learning and teacher training. Overall, this topic has already had a significant impact on the field of language research, foreign language methodology, teacher training, and practice and will continue to do so (Bär 2019). 

The technologies of digitalisation, automation, and AI are not just futuristic concepts; they are an integral part of today's world. Therefore, it is necessary to respond to these changes in the short term. In the field of education, one of the most topical issues is the use of artificial intelligence to make schools and teaching practices more efficient.

As generative AI finds its way into more of the applications we use every day, from search engines to office software, design packages, and communication tools, people will come to understand its potential. (Marr 2023) 

However, these AI tools have been observed and used for several years now – not only in science but also in education. New technologies bring with them a wealth of data and the possibility of processing it in a more meaningful way (Blossfeld 2018). Data that are systematically collected and analysed by computers and subsequently by humans can help to plan and continuously renew learner curricula. They are also useful tools for planning the efficient use of classroom space in schools and can provide assistance for creating timetables faster and allocating suitable and available classrooms more efficiently. For teachers, in turn, these advances can mean that their work becomes more interesting. The rather repetitive parts — such as learning the beginner basics (for example, basic vocabulary, grammar, pronunciation), correcting tests, or answering repetitive questions — are now taken over by AI-assisted computer programs. Teachers can then take more time to discuss a particular topic or area with their learners. The use of new technologies in education should therefore be part of any forthcoming changes in public policy. Recent developments in the global education system show a new trend. In more and more countries, the focus of education is shifting from imparting encyclopaedic knowledge to skills, such as applying acquired knowledge more meaningfully, communicating effectively, collaborating on tasks, teamwork, or awareness in time management. These skills are needed not only in the labour market but also in the education sector. Moreover, they are also becoming increasingly important in our private lives (Salam 2022).

Artificial intelligence and language learning merge almost seamlessly in online education. Textbooks, videos, and audio recordings may contain useful content, but they often lack personalisation. An example can be observed in students’ books of English for Specific Purposes. Many of the topics dealt with in the different chapters are typically related to a specific or scientific field (like medicine, chemistry, biology, or engineering). Nevertheless, not all the content is needed by all of the students enrolled in different degree programs (such as linguistics or international relations). Therefore, some chapters are frequently skipped in the classroom. Occasionally, this situation can lead to students progressing to the next level before they have truly understood the material dealt with in the previous unit. Language learners are often afraid when speaking a new language and expressing themselves in front of their classmates, which can hinder their learning process. An example of this is observed by some instructors when teaching English and German as foreign languages. In English language lessons, students in Germany and Slovakia typically have no difficulty expressing their opinions on a given topic or answering complex questions using basic vocabulary. However, when teaching German language lessons, students are often hesitant and do not participate in discussions as much. They frequently claim that German grammar is more complicated than English. In such a situation, the use of AI can create adaptive and safe learning environments. It can offer a range of exercises to challenge students in foreign language classes, allowing them to practise and improve their language skills independently. The objective is to produce learners who are self-motivated, self-directed, digitally proficient, and well-equipped for the future job market.


2   The Influence of AI on Future Skills and the Labour Market

2.1 The Development of Future Skills: Opportunities and Challenges

Theory-practice links are a topic of debate in methodological literature. This debate is about the development of students' professional skills which is based on a long-term process of personal experience. Developing students' professional skills during their studies has become a necessity in recent years, expanding the range of learning opportunities available to students. Competent management of professional and everyday situations requires scientific-theoretical knowledge and practical experience. Abstract knowledge is developed through a combination of tasks, reflection, and situational skills. At Slovakian universities, for example, students experience a severe lack of skills in the digital field – despite a constantly growing demand. This qualification profile is still underrepresented in many degree programs and courses at universities. In countries where German is highly valued economically, many German graduates seek employment in other sectors, which leads to a certain de-professionalisation. In various industries, there is an almost unmanageable variety of job-related language situations that require job-specific linguistic and communicative skills (Middeke 2021: 170). These can be achieved through the application and use of digital skills in the classroom, but also with the help of AI.

A general trend among university graduates appears to often search for employment in the industry or business, even when their degree is in the social sciences or humanities. Traditionally strong industries (such as the automotive industry) are in a phase of upheaval due to the radical innovations of new technologies (e.g. e-mobility and autonomous driving). Numerous branches of industry are transforming into so-called 'smart industries' through the use of artificial intelligence (Brühl 2020). "Smart industries" are defined as sectors whose products and services can have intelligent properties, such as traffic control systems, smart factories or web-based technologies, robotics, and consumer electronics. In addition, new future fields that focus on advancing digitalisation are emerging. These advances and innovations, including artificial intelligence, are not only changing the future world of labour, but also the requirements for university graduates in almost all courses of study. Artificial intelligence signals that we are facing a fundamental change and a turning point in the world of work. AI enables a high degree of autonomy, flexibility, and automation in production and can also facilitate the individualisation of products. In the coming years, it will be crucial for the economy to increase its competitiveness, especially in promising sectors, and to use AI and smart systems to improve productivity, quality, and sustainability and so as to reduce costs. According to Marr (2023), 2024 is the year when people will realise how powerful AI is. The increasing use of AI will change various work processes and the world of labour as a whole. Many routine tasks are expected to be performed by AI, not only in industry but also in the service sector. New activities and professions will emerge due to these developments, such as training algorithms, interpreting and evaluating AI suggestions, controlling or reprogramming AI systems:

Now, generative AI puts the power to create and intelligently automate the customer experience - as well as internal operations - in the hands of nearly every organization [...]. Machine intelligence, the blurring of the boundaries and the real and the virtual, and shaping ongoing evolution of the internet will all radically impact our lives. (Marr 2023)

The automation of cyber defence through AI and machine learning will be essential to make sure that not only individuals but also businesses are aware of sophisticated cyber-attacks and to ensure cyber resilience. AI is expected to be used for fraud detection, risk management, and high-frequency trading in the tech industry in 2024 (Marr 2023). Artificial intelligence and the associated automation and robotisation (e.g. Amazon, Microsoft, McDonald’s, medical robots, hairdressers or toilet cleaners) will also have a significant impact on the labour market. The robotisation of individual sectors of the economy will require a systematic retraining of employees. According to the OECD, the jobs most at risk will be those requiring a lower level of education, especially those involving routine work and repetitive tasks, such as work on assembly lines or in the service sector. On the other hand, occupations that require intermediate to higher education, good social and organisational skills, and creativity will be at lower risk. These occupations include managers, technicians, teachers, psychologists, and social service workers. Although these trends show that education is one of the areas which will be least at risk of job losses, education and retraining are crucial factors in maintaining a functioning labour market both at home and abroad. An OECD (Lassébie & Quintini 2022) study has warned that teachers will need to acquire new skills to complement computers. In light of the rise of artificial intelligence, the focus of their work shifts from imparting knowledge to guiding learning and developing social and communication skills. 

With the advent of Large Language Models (LLMs) such as ChatGPT, the development of AI has accelerated. The use of these technologies has the potential for greater productivity and progress. AI is expected to bring about a new era in human history, both technologically and culturally, and give rise to new business models, transform entire industries, trigger an enormous surge in productivity, and revolutionise the world of work. Especially in companies where processes are automated already or will be automated in the future such as production, logistics or advertising, AI can lead to efficiency gains and cost savings. AI can optimise core activities as well as repetitive manual activities and tasks, such as procurement, production, marketing, customer service or sales. Machine learning or data analysis will provide insights into market trends by recognising customer preferences. In addition, AI can support employees in many routine activities - which, in turn, can alleviate the shortage of skilled workers. According to Kugoth (2023), AI functions most frequently used by companies worldwide include robotic process automation, computer vision, natural language text interpretation, and virtual agents. For example, at a large German car manufacturer, AI systems can detect whether two transmission parts fit together perfectly or rub against each other by analysing (nearly) inaudible sounds. 

In summary, AI can influence students' future skills in these respects:

  • The new generation of graduates will need to adapt to constant digital and technological change.
  • ChatGPT is an impressive example of the rapid acceleration of the development and adoption of AI, which is also called the '4th Industrial Revolution' or 'AI Gold Rush').
  • Students must get accustomed to daily human-machine interaction when using AI. This will be an elementary skill for future graduates.
  • Media (meta)competence and digital sovereignty will be required of nearly all students. This includes competencies related to machine interaction, deep-fake tracing, text analysis, and AI literacy.
  • For human-machine interaction (with ChatGPT), a new idiolect / new language variety must be acquired, which is closely linked to the acquisition of the specialist vocabulary of AI.
In companies working in the fields of tourism, medicine, electrical engineering, mechanical engineering, vehicle construction, services, transport, trade, finance, and logistics, such as Amazon, CNET / BuzzFeed, McDonald's, Microsoft, Coca-Cola, AI is taking over more and more cognitive and manual activities 


2.2 Digital Language Learning

Foreign language learning is currently undergoing a rapid and complex process of change influenced by new technologies and applications, which has unfolded in society, i.e. outside of school, for example in business, politics, trade, industry, and finance. Digitalisation can create more individualisation, authenticity, communicative reality, and new future skills. These skills cannot be learned at universities, because they are not always part of the curriculum. Therefore, new opportunities should be offered and the often inadequate technical equipment in schools be modernised. To successfully shape the digital transformation in schools and classes, several basic requirements need to be met: 

  • Well-trained teachers who are competent in the use of media and supported by the institutions;
  • Empirically tested and well-constructed learning media that are geared towards the skills to be taught;
  • Intelligent media systems that combine digitally supported learning with practical teaching methods (Schmidt & Strasser 2016).

It is assumed that a competent teacher, well-trained in teaching, education, assessment, and innovation, who uses digital media professionally and methodologically in their lessons, will be at the core of every effective digitally-supported foreign language class in the future. Our aim will also be to work out how competent foreign language teachers can be supported by intelligent technologies. This poses new challenges for today's schools and offers opportunities to improve school education. 


3   Education 4.0 

This section highlights and prioritises key challenges in designing educational systems for AI. It addresses two fundamental issues: What is the specific impact of AI on skills needs and how can education be better designed and implemented to meet these needs? The results can be outlined as follows:

  • Due to the development and introduction of AI, some skills may be increasingly in demand and trained through technology. This applies to both manual and cognitive skills such as planning, deliberation, comprehension, and expression. ChatGPT is a good example of how rapidly AI will evolve. 
  • The skills required to develop AI, as well as to use it, will become more important. In some areas, specialised AI skills will be required, and there will be a growing demand for digital and data processing skills. These skills will go hand in hand with cognitive ones. It is becoming increasingly important for workers in various occupations to possess the ability to effectively develop and use AI.
  • Training for specific AI skills will require a redesign of curricula in education and further job qualification.
  • After having introduced AI in the workforce, companies will want to provide AI training. A major barrier to the adoption of AI is the lack of suitable skills for current employees. One of the challenges is that the use of AI in education is likely to lead to significant changes in the qualification requirements of teachers. 
  • Many companies are still not investing enough in AI training due to a lack of information on how to implement AI effectively.
  • National policies need to be developed to encourage greater training provision by employers and the development of AI skills at all stages of the lifecycle.
  • Many politicians acknowledge the significance of particular skills for AI but do not adequately support their development.
  • There are already several examples of the use of AI in education, although risks should be carefully addressed and evaluated, in particular when using ChatGPT, which is an impressive example of an AI model that can work just as well as a human, and much faster and more accurately, being able to write essays, formulate medical diagnoses, develop games, process images, explain scientific concepts to a wide audience. Yet, it can also hallucinate, i.e. provide false information.


3.1 The Complex Role of AI – Perspectives and Concepts for Teaching and Education

The question of how digital media can contribute to adapting learning in heterogeneous foreign languages to the individual needs of learners is currently occupying the minds of many teachers and researchers. In recent years, digital technologies have become a scientific, practical, and methodological focus in the foreign language classroom. Recently, there has been talk of media-supported and learner-oriented teaching; today it has become Technology-Enhanced Language Learning" (TELL). TELL is part of an extensive global discussion that presents both favourable and unfavourable positions and opinions. Research studies have shown that technology can influence the processes and outcomes of education, and many countries are investing in technological support for foreign language teaching (Paiva & Bittencourt 2020). AI is one of the latest technological developments related to these issues. This new technology has been developed for educational purposes, including language learning (for example in Apps like Duolingo). The potential of these innovative programmes focuses on new methods of optimising learning and teaching processes. This brings a new era of personalised and student-centred teaching to the fore. This technology encourages learners to approach digitally enhanced subjects and courses in a new way. Although foreign language programmes have been widely available and used on the Internet for several decades, only some products employed in education provide intelligent systems implemented through AI. The result of the modernisation of such programmes is the intensification of interdisciplinary cooperation between linguists, psychologists, computer scientists, and education professionals. As a result, more and more companies and educational stakeholders are investing in AI-supported technologies. Before discussing the applications of AI and its methodology, an overview of the key AI concepts concerning language learning is specified (according to Schmidt & Strasser 2022: 167): 

1. Natural language processing (NLP) is a field of AI and linguistics that deals with the automated processing and analysis of written and spoken language. It covers lexical, morphological, and syntactic aspects of language and their presence in discourse. 

2. Machine learning is a subfield of artificial intelligence that deals with information and experience to provide solutions to various problems in natural language processing. 

3. Deep learning is a branch of AI that uses artificial neural networks to learn from big data. Deep learning mainly focuses on visuality. It can also be used for NLP purposes. 

Below some AI programs that contribute to language learning and have already been used in practice, are discussed: 

  • Machine translation: This is the automatic translation of a spoken or written text from one language into another, which extensive linguistic corpora are used for. One of the most popular AI-supported translation websites is currently DeepL (https://www.deepl.com/translator). There are several ways in which this technology can be used in the classroom. It is helpful when it comes to understanding the essentials, acquiring specialist terminology, and expanding the learner's lexicon. The disadvantage of this program is that it cannot adequately recognise intercultural situations or differentiate between linguistic varieties (e.g., slang, dialects, regional idioms, etc.).
  • AI Writing Assistants: Spelling rules in word processing have improved dramatically in recent years. They help users to recognise and correct spelling mistakes more easily. As we communicate more and more digitally, our texts are spread across different channels and networks, and it is crucial to ensure reliable checking of our written discourse. Several AI-powered writing tools such as Grammarly (https://app.grammarly.com/) or LanguageTool (https://languagetool.org/) have entered the market and offer spelling and grammar checks as well as functions that can check the written text for coherence better than ever before. This writing tool can help learners improve their (academic) writing skills and offers opportunities to improve the style and grammar in their texts.
  • Chatbots: In general, chatbots aim to mimic the discursive behaviour of humans. As chatbots have access to huge linguistic corpora, they are becoming increasingly 'intelligent'. As a result, companies have started developing their virtual bots. In particular, they offer tips for better communication with customers and often display clear, formulaic structures without significant semantic, syntactic, or lexical peculiarities. In general, a chatbot should be user-friendly so that learners can practise the target language using audio, videos, and images while writing or speaking to the chatbot. The most popular chatbots for foreign language learning are Memrise, Babbel, and Duolingo. (Schmidt & Strasser 2022: 168-172).


3.3 Using LLMs and ChatGPT in the Foreign Language Classroom

One of the significant features of ChatGPT centres on generating content, as it can be requested to answer questions, translate texts, write essays, or give feedback. ChatGPT often appears in semi-realistic and natural conversations because it has been trained to use an extensive database of conversational texts (including forums, chats, and social media). One crucial skill when using this chatbot is the ability to ask fruitful questions, also called prompts. Providing appropriate prompts when working with applications like ChatGPT has become an essential skill because when an appropriate prompt is given, the answer will be of valuable content. Yet, critical thinking and problem-solving are still essential for learning and enhancing knowledge and competencies. One of the critical points in working with ChatGPT, though, is where the information comes from. When students start using this application, questions remain like how to cite the results obtained, whether citations should be used, and whether results can be considered plagiarism. To raise their awareness about such questions, students will need to be invited to discuss their approach. In this way, the accuracy of information provided by ChatGPT needs to be repeatedly checked and verified by additional sources. In our opinion, excluding ChatGPT from classroom settings permanently – as considered in other countries (McCallum 2023) – is not advisable, as training is required to develop competencies in working with it. Students must learn to manage the ambivalence of ChatGPT and its output, depending on the tasks they are required to perform.


3.4 The Importance of Intelligent AI Practice

Communicative learning tasks and language learning play a central role in modern foreign language teaching. These language skills can be enhanced with the support of digital tools. The targeted use of AI makes it possible for students to solve learning tasks better, facilitate communicative activities, focus on the content and meaning of texts, and achieve a high degree of authenticity in the foreign language classroom. This modern type of processing foreign language texts facilitates the cognitive mapping of form, meaning, and usage. According to Bär (2019) and Schmidt & Strasser (2016), intelligent practice (with the help of AI) should be used in the foreign language classroom instead of doing mechanical exercises using the audio-lingual method with the aim of:

  • focussing on the learner's needs to be able to communicate fluently and freely in the target language,
  • being authentic in terms of language and content,
  • providing feedback (linguistic correctness, communicative appropriateness, strategic approach),
  • adapting to the learner's cognitive needs,
  • developing metacognitive (linguistic) learning skills, and
  • assisting students in acquiring the necessary skills to excel in the future.

Thus, the role of practice in communicative foreign language instruction differs from earlier approaches that focused on memorising vocabulary, sentences, and certain structures without any communicative and pragmatic purpose being targeted at. The aim of today's task is to personalise the practice process to effectively assist learners in developing their language skills. The technology-enhanced activities are not solely focused on mastering the language system, but rather on emphasising the linguistic challenge through the target task. It is important to provide learners with support and high-quality feedback throughout this process. The question at hand is whether digital learning programs and systems can be utilised to achieve these goals effectively and intelligently. It is important to consider the extent to which they can be used and how they can be implemented.

AI-powered systems will ensure that learners from different backgrounds and language levels will have equal opportunities to acquire knowledge and access educational resources they never had before. Experts from the fields of pedagogy, methodology, psychology, computational linguistics, and multimedia will work closely together to create these digital systems. In the future, digitally assisted classrooms will aid in diagnosing needs and tracking progress, while also providing direct access to differentiated learning opportunities. Future language instruction will, therefore, be an AI-supported digital learning system, a tool for learners and teachers that will enrich learning processes. In the classroom of the future, the advantages of digital learning will be combined with computer-based methods, contents, and tasks: 

And even in 2040, we will still have and need teachers: well-trained, data-literate teachers who are competent, critical, and reflective in their use of media and technology support, and who use empirically established digital scenarios […]. (Schmidt & Strasser 2022: 180)

To start implementing these changes in language learning curricula, one of the first steps will be to understand and acquire the basic vocabulary of AI. This is essential not only for students but also for teachers and educational institutions.  


4 The Inclusion of AI in University Language Teaching and Learning

Having provided the (theoretical) framework, the following section of the article discusses the implementation of AI in foreign language curricula. Specific methodological and didactic suggestions will be made to help prospective students learn and acquire specialised vocabulary in foreign languages, as well as recommendations and considerations for teaching when using AI tools. At the University of Economics in Bratislava, the first steps and experiments are being made in this direction, as digitalisation processes are starting to become part of the curricula and teachers are being encouraged to incorporate these processes into their teaching. The Faculty of Applied Languages provides foreign language courses to students across various faculties and study programs, including Economics, Marketing, IT, International Relations, and Applied Languages. The courses are designed to require students to complete independent work with the help of instructions from the lecturers. Thus, the weekly double lesson is significantly extended by self-study. During self-study, AI can be useful as it provides programs that can act as a teacher at home. For instance, these programs can simplify and clarify complex foreign language vocabulary, as well as present theories, concepts, and definitions in a more accessible manner. A concrete example:  Slovak students learning English and German often encounter difficulties when dealing with synonyms in the field of business or economics. Another linguistic challenge is understanding, using, and translating idioms from students’ mother tongues into a foreign language. At the university, teachers can explain idiomatic phrases in foreign languages, but they may not be able to translate them into all the native languages of their students. This is due to the large and heterogeneous groups of students, including those with Hungarian, Ukrainian, Polish, and Czech mother tongues who are studying in Slovakia. To solve this difficulty more quickly during classes, AI translation programs such as DeepL, Google Translator, Translator Online or ChatGPT can be used. In Germany, a similar situation can be observed, where language courses and study programs with culturally diverse AI can help bridge potential gaps. The University of Applied Sciences in Zwickau has established study programs in Green Engineering and the Internet of Things, which demonstrate the current dimension of AI application. This is reflected in the curriculum of the programmes as well as in the accompanying language courses.

As previously mentioned, the University of Economics in Bratislava offers various foreign language courses, including Business English and Academic English, across different faculties and degree programs. These courses typically use a prescribed textbook covering a range of topics such as banking, marketing, new technologies, the environment, tourism, and culture. This can be problematic because degree programs are designed and oriented differently, and not all university students are required to learn the same vocabulary or deal with the same topics. Teachers can use AI programs to adapt these chapters and the vocabulary to the specific study group. The benefits of these AI programs are evident not only in the acquisition of vocabulary but also in the improvement of grammar, style, pragmatics, and text production and comprehension by students (Pokrivčáková 2023). Their language skills are enhanced and automated, ensuring correct usage of the foreign language. As students do not currently receive independent courses on AI, the use of AI in lessons by interested and tech-savvy teachers can be advantageous for them. This method of enhancing language lessons with AI tools combines foreign language and digital skills, which are essential for future careers. By providing AI learning opportunities to all students, teachers can equip them with the knowledge and skills necessary to succeed in a world that is increasingly influenced by AI. (Southworth et al. 2023). Teachers can now customize language learning methods and instructions to fit the needs of each individual or group, instead of using the same approach for everyone. Using interactive AI programs and tools (such as Virtual Reality, Internet of Things, or AI games) can also complement traditional language education (Weng & Chiu 2023, Ericsson & Johansson 2023).

To start implementing this new technology and harness its full potential, it is crucial to address the lack of conception and efficient didactic models for these innovations (Mekacher 2019). We will now offer some recommendations and considerations for teachers to ensure the successful integration of AI tools into their foreign language courses. Some educators believe that implementing AI tools requires expertise or prior experience with the technology. Teachers may sometimes be hesitant to use AI due to its novelty and lack of specific training opportunities. It is clear, however, that the use of modern AI tools does not necessarily require in-depth skills and experience: for example, the use of chatbots, such as ChatGPT, is limited to relatively simple communication with the programme. When considering a specific language skill or topic, it is essential to have a clear objective for the teaching unit: teachers should be very specific about the skills that they would like to practise with their students. Appropriate programmes should be selected and used to achieve specific objectives: for example, if the aim is to practice translation skills, machine translation programmes such as DeepL or LanguageTool can be chosen; on the other hand, if the aim is to improve pronunciation, language learning apps such as Duolingo, Memrise, Phase 6 or Babel would be more useful. AI programmes may require registration, which could result in the collection and storage of personal data. Therefore, students may be advised to use third-party apps or websites to access such programmes. When planning a given teaching unit, short 10-minute exercises with AI should be used at the beginning to slowly and consistently prepare students for these tools and specific tasks; for example, the exercise can aim to help students practice and automate new vocabulary or memorise grammatical rules using a chatbot (ChatGPT, Microsoft Bing AI, Google Bard etc.).

At the beginning of the use of AI, it is essential to make clear to students the ethical use of these tools and the concept of plagiarism. There should also be a discussion about the potential biases that may be present in AI systems. After the exercise or lesson, it should be evaluated whether the learning objectives have been achieved, what the advantages and disadvantages of working with AI are, and whether the work can be continued in this way. The assessment of students' work, such as written texts, can indicate their progress in learning a foreign language. Learners obviously experience a sense of accomplishment when conversing with AI chatbots, which appears to simulate the feeling of authentic language use scenarios and encourages students' social presence through effective, open, and coherent communication (Suman et al. 2023, Huang, et al. 2021, Klimova et al. 2023).

AI can provide significant benefits for teachers. It can assist in creating syllabi and preparing lessons, generating test questions from uploaded textbooks (such as the AI tool Hello Vaia), and developing supplementary exercises. In addition, AI can generate personalised exercises for each student based on their knowledge and skills, or assist with gamified exercises that cover challenging topics or vocabulary, enhancing the learning experience. For example, when practising idiomatic expressions, ChatGPT recommends ten interactive vocabulary exercises for higher education learners. These exercises include charades, crossword puzzles, thematic word maps, and vocabulary bingo. Overall, the use of AI tools can be helpful for language teachers and students, supporting the language learning and teaching experience.


5   Conclusion

Digitalisation is the basis for far-reaching changes in almost all aspects of our lives. It has already had an impact on school education, including on the teaching and learning of foreign languages. Digital change will require the acquisition of new skills to ensure individual success and participation in social life in the future. Consequently, there is an urgent need to modify educational curricula and degree programs. Aiming for digital competence in foreign language teaching means to develop learners’ and teachers’ skills and to create teaching conditions that ensure the successful use of digital media (Schramm 2019: 237). In the future, intelligent systems and tools will be developed that can simplify teaching processes and facilitate technical learning using data and corpora. As technology becomes more advanced every day, teachers and learners are facing challenges in using the new options offered by technology. The field of language and humanities learning is currently undergoing significant changes in societal learning. In addition, AI has numerous applications in fields such as medicine and industry, which have shown many positive aspects. However, there are also potential dangers associated with ChatGPT and similar programs. In 1997 Baacke (for a definition of media competence: 1999a: 31-35) pointed out that increased media competence is required. Prompts and prompt language require an understanding of appropriate requests. The methodology of foreign language teaching should make use of existing media skills but also be open to new technological possibilities (for experimental media competency: Wampfler 2020: 18-23, Lenzen 2023).

Nevertheless, with the full implementation of AI, the question of legal dimensions remains, especially with regard to copyright measures. As the authors advocate the inclusion of AI and its features in language learning, study and teaching, one suggestion may be to discuss the potential advantages and disadvantages of integrating AI language models such as ChatGPT into the curriculum. Authenticity also needs to be questioned. Regarding foreign language teaching, the use of digital media can provide improved opportunities to introduce learners to real foreign language communication in a receptive and productive manner and to allow them to participate in media discourses (Schmidt 2019: 228). Finally, new technologies offer new opportunities for settling into the target culture and language.




References

Alkaissi, Hussam & Sami I. McFarlane (2023). “Artificial Hallucinations in ChatGPT: Implications in Scientific Writing”. Cureus 15 (2), e35179. (https://doi.org/10.7759/cureus.35179; 12-12-2023).

Bär, Marcus (2019). Fremdsprachenlehren und -lernen in Zeiten des digitalen Wandels. Chancen und Herausforderungen aus fremdsprachendidaktischer Sicht. In: Burwitz-Melzer, Eva, Claudia Riemer & Lars Schmelter (Hrsg.) (2019): Das Lehren und Lernen von Fremd- und Zweitsprachen im digitalen Wandel. Arbeitspapiere der 39. Frühjahrskonferenz zur Erforschung des Fremdsprachenunterrichts. Tübingen: Narr. 12-24.

Baacke, Dieter (1997). Medienpädagogik. Tübingen: Niemeyer.

Baacke, Dieter (1999a). Medienkompetenz als zentrales Operationsfeld von Projekten. In: Baacke, D. u.a. (Hrsg.) (1999). Handbuch Medien: Medienkompetenz - Modelle und Projekte. Bonn: Bundeszentrale für politische Bildung, 31-35.

Beutel, Grenot, Eline Geerits & Jan T. Kielstein (2023). Artificial hallucination: GPT on LSD?”. In: Critical care (London, England) 27 (1), 148 (https://doi.org/10.1186/s13054-023-04425-6; 20-10-2023).

Blossfeld, Hans-Peter, et al. (2018). Digitale Souveränität und Bildung. Gutachten. Münster: Waxmann.

Brühl, Völker (2020). “Deutschland hat Nachholbedarf in einigen Zukunftsindustrien”. In: Wirtschaftsdienst 100, 138-143 (2020). https://doi.org/10.1007/s10273-020-2585-7 (20.10.2023)

Ericsson, Elin, Johansson, Stefan (2023). “English speaking practice with conversational AI: Lower secondary students' educational experiences over time”. In: Computers and Education: Artificial Intelligence Volume 5, 100164 (https://doi.org/10.1016/j.caeai.2023.100164; 27-12-2023). 

Hrdličková, Zuzana (2017). Constant Enrichment of the Mental Lexicon with New Lexis. In: CASALC Review 6 (3), 28-44.

Hrdličková, Zuzana (2018). Promoting media, information and reading literacy through a business communication e-course. In: DisCo 2018: Overcoming the Challenges and the Barriers in Open Education, 178-198.

Huang, Weijiao, et al. (2021). Chatbots for language learning – are they really useful? A systematic review of chatbot‐supported language learning. In: Journal of Computer Assisted Learning 38 (1), 237-257. (https://doi.org/10.1111/jcal.12610; 31-12-2023).

Klimova, Blanka, et al. (2023). The use of persona in foreign language learning facilitated by chatbots. Preprint. (https://doi.org/10.21203/rs.3.rs-3129096/v1; 30-12-2023).

Kugoth, Jana (2023). Vorständin Stars über Chancen neuer Technik: „KI wird künftig bei VW eine noch größere Rolle spielen” (https://www.tagesspiegel.de/wirtschaft/mobilitaet/vorstandin-hauke-stars-uber-ki-bei-volkswagen-klar-mehr-chancen-als-risiken-9611474.html: 20-10-2023).

Lassébie, Julie, Glenda Quintini (2022). What skills and abilities can automation technologies replicate and what does it mean for workers?: New evidence. In: OECD Social, Employment and Migration Working Papers 282. OECD Publishing. Paris, (https://doi.org/10.1787/646aad77-en; 20-10-2023).

Lenzen, Manuela (2023). Der elektronische Spiegel: Menschliches Denken und künstliche Intelligenz (Originalausgabe). München: C.H.Beck.

McCallum, Shiona (2023). ChatGPT accessible again in Italy. In: BBC News (https://www.bbc.com/news/technology-65431914; 12-11-2023).

Marr, Bernard (2023). The 10 Biggest Business Trends For 2024 Everyone Must Be Ready For Now. In: Forbes.com (https://www.forbes.com/sites/bernardmarr/2023/09/25/the-10-biggest-business-trends-for-2024-everyone-must-be-ready-for-now/; 20-10-2023).

Mekacher, Leila (2019): Augmented reality (ar) and virtual reality (vr): the future of interactive vocational education and training for people with handicap. In: PUPIL: International Journal of Teaching, Education and Learning 3 (1), 118-129 (https://doi.org/10.20319/pijtel.2019.31.118129; 27-12-2023).

Middeke, Annegret (2021). Service Learning – analog und digital. Zur Entwicklung von Lehrkompetenzen für das Vermittlungshandeln im berufsbezogenen DaF/DaZ-Unterricht. In: Busch-Lauer, Ines-Andrea & Julia Hartinger (Hrsg.): Fachlich-Digital-Regional: Perspektiven auf das Sprachenlernen und -lehren. Berlin: Frank und Timme, 169-185.

Paiva, Ranilson & Ig Ibert Bittencourt (2020). Helping Teachers Help Their Students: A Human-AI Hybrid Approach. In: Bittencourt, Ig Ibert et al. (Eds): Artificial Intelligence in Education. Cham: Springer Switzerland International Publishing, 448-459. (Doi: 10.1007/978- 3-030-52237-7_36.; 12-11-2023).

Pokrivčáková, Silvia (2019). Preparing teachers for the application of AI-powered technologies in foreign language education. In: Journal of Language and Cultural Education 7 (3), 135–153 (https://doi.org/10.2478/jolace-2019-0025; 31-12-2023).

Schmidt, Torben (2019). Digitally empowered teaching and learning - Kompetente Fremdsprachenlehrkräfte und intelligente Technologie. In: Burwitz-Melzer, Eva & Riemer, Claudia, Lars Schmelter (Hrsg.): Das Lehren und Lernen von Fremd- und Zweitsprachen im digitalen Wandel. Tübingen: Narr Francke Attempto, 228-236.

Schramm, Karen (2019): DaF-Unterricht in Zeiten digitalen Wandels. In: Burwitz-Melzer, Eva & Riemer, Claudia, Lars Schmelter (Hrsg.): Das Lehren und Lernen von Fremd- und Zweitsprachen im digitalen Wandel. Arbeitspapiere der 39. Frühjahreskonferenz zur Erforschung des Fremdsprachenunterrichts. Tübingen: Narr Verlag, 237 – 248.

Salam, Erum (2022). Touchscreens, conveyor belts: McDonald’s opens first largely automated location. In: The Guardian  https://www.theguardian.com/business/2022/dec/23/mcdonalds-automated-workers-fort-worth-texas; (20-10-2023).

Schmidt, Torben & Thomas Strasser (2016). Digital Classroom. In: Der fremdsprachliche Unterricht Englisch 50 (144), 2-7.

Schmidt, Torben & Thomas Strasser (2022). Artificial Intelligence in Foreign Language Learning and Teaching: A CALL for Intelligent Practice. In: Anglistik: International Journal of English Studies 2022 33 (1), 165-184.

Southworth, Jane et al. (2023). Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy. In: Computers and Education: Artificial Intelligence 4, 100127 (https://doi.org/10.1016/j.caeai.2023.100127; 27-12-2023).

Wampfler, Philippe (2020). Digitales Schreiben: Blogs & Co. im Unterricht. Ditzingen: Reclam.

Weng, Xiaoing & Thomas K.K. Chiu (2023): Instructional design and learning outcomes of intelligent computer assisted language learning: Systematic review in the field. In: Computers and Education: Artificial Intelligence 4, 100117 (https://doi.org/10.1016/j.caeai.2022.100117; 27-12-2023).




Authors:

Mgr. Silvia Adamcová, Ph.D.

Assistant Professor

Department of Linguistics and Translation

Faculty of Applied Languages

University of Economics in Bratislava

Slovakia

Email: silvia.adamcova@euba.sk


Dr Michaela Rusch

Lecturer/Researcher for LSP English and German

Department of Applied Languages

Faculty of Applied Languages and Intercultural Communication

University of Applied Sciences Zwickau

Germany

Email: Michaela.Rusch@fh-zwickau.de