Findings from this qualitative study reveal that AI-driven techniques used in foreign language learning can have a positive impact on the well-being of students, including the development of language skills, particularly productive skills: speaking, writing, and more. This has been confirmed by other research studies9,10,11. For example, Reiss11 It argues that AI-driven technology can enhance student learning and complement teacher work without distributing teachers. This was extended by Meunier et al.12states that human interaction, teacher scaffolding, or emotions are of paramount importance when applying AI-driven technology to foreign language education and should be observed with care as well as ethical concerns. It is also supported by this study, which has been noted by the subjectively perceived experiences of students. Furthermore, Wiboolyasarin et al.13 The authors warn that most studies still rely on small samples and short interventions, while the authors warn that the authors found consistent benefits by writing fluency, quality and learner motivation. Similarly, the law14 A scoping review of generative applications in language education concludes that Genai reduces barriers to spontaneous interactions and personalized feedback, but amplifies the need for important data literacy instructions so that learners can recognize hallucinations and biased output.
Therefore, despite the positive aspects of AI-driven technology to foreign language education, there are certain ethical issues that reduce these benefits. As the results of this qualitative study show, students were relatively positive about subjective safety when using AI-driven techniques in foreign language learning, but were quite concerned about the safety of their personal and private data.15. For example, Stöhretal.16 In a multicenter survey of 2,100 higher education students, we observed that willingness to share data was strongly correlated with perceived self-efficacy in controlling for AI settings rather than demographic variables. In contrast, pilot intervention between Polakova and Klimova17 In the EFL Chatbot class, it was shown that non-IT majors felt significantly less control and therefore demanded stricter institutional guidance.
Furthermore, the principles of physical safety play an important role in the use of AI-driven technologies in learning, as the findings reveal.6. As Mezgár and Vancza18 Say: “Users' acceptance of AI technology relies on trust in these systems that are highly affected by both the legal environment involved., Standards and technical background. People are hardly sure they will trust “black box” technology. therefore,, Safety and other features, safety, Transparency, Explanational possibilities are very important. In fact, this last sentence reflects the trust of students using AI-driven techniques in this study, as the majority are skeptical of this study.
Furthermore, students of this research and Virtual chatbot friends It will be provided. This is one of the students' AI-driven requests and is perhaps one of the most sophisticated chatbots used in L2 practices. The chatbot clearly sought inappropriate photos without obvious reasons or intentions from the student's part, which appears to be extremely inadequate and potentially dangerous (Figure 8). AI is trained on a huge amount of data (big data) from various people and sources, so that's a possible answer to the question of where this response came from. However, it is important to draw attention to these possible serious issues (and perhaps it will).
Replika print screen requesting sexy photos.
Therefore, it is not possible to create anything without forgetting an engineer, designer, programmer, businessman, and without in mind many different ethical issues that are inevitably related to the field. Also, ethical related issues seem to gain momentum when different types of virtual, augmented and mixed reality become everyday parts of our lives. For all these reasons, interdisciplinary interconnectivity appears to be important as it requires typification of technical aspects with ethical considerations.19.
The authors of this study recommend that students be aware of such cases and encourage them to carefully consider the personal information and personality data they share. Furthermore, there are no legal guidelines yet to protect individual rights of students when using AI technology for learning purposes (https://apuedge.com/artificial-in-education-where-are-the-laws/). As the results of this study show, computer science students may recognize the threats of using AI technology, while others may not. Overall, there should be an open global call for joint cooperation between all stakeholders, IE, AI developers, academics and end users.
limit
The limitations of this qualitative study involve most respondents being computer specialists and naturally more or less aware of some ethical issues, such as data misuse, and acted accordingly when using AI in foreign language learning. Therefore, this study should be replicated with users of AI in other fields who are less aware of these threats to confirm or refute these findings. The findings of this study should not be generalized as respondents are IT experts and further research is required for non-IT experts as well.
Additionally, a variety of other research will be needed (and will come in the near future as it appears to be a key area of education development supported by AI-driven tools, utilizing other methodologies such as quantitative research). Additional ethical challenges such as accuracy and bias of teaching materials, and how language is practiced and practiced by several names, requires undivided attention and requires further research.
Future research lines
Based on the recommendations of this research, further research should focus on the use of AI-driven technologies in other fields such as the social sciences. AI developers should be aware of the fact that there should be cooperation between them, educators and end users, and thus focus on using AI-driven technology to implement the use of AI-driven technology. Activities.
Practical Recommendations
There may be some practical recommendations related to our findings, such as: First, institutions should integrate short, practical modules on AI ethics into language and ICT courses, particularly for non-technical students, to raise awareness about data privacy, algorithm transparency, and the potential misuse of AI-driven tools. Second, developers of AI-driven language learning apps should include clear and user-friendly disclosures about how personal data is collected, stored and used before users can begin interacting with the app. They also need to train them in how to ethically develop AI tools. Third, universities should establish a review committee to review AI tools used in education, meet ethical standards and avoid exposing students to inappropriate content or data risks, as shown in the description of replica cases. Fourth, educational institutions must implement an anonymous reporting system for students to safely report unethical or unpleasant experiences with AI tools. This can be used to inform you of policy and tool selection. And finally, we encourage collaboration between AI developers, educators, psychologists and ethicists to co-design AI tools that are not only pedagogically effective, but also ethically sound and psychologically safe for students.20.
