Multilingualism and verbal senses in learning Persian for Medical Purposes comprehension through Artificial Intelligence social robots

This study investigates the potential of Artificial Intelligence social robots to stimulate students’ verbal senses in understanding Persian for Medical Purposes. To this end, using an embedded design, the performance and approach of 400 non-Iranian monolingual and bilingual students studying at Isfahan University of Medical Sciences in the 2024 academic year were examined in their interactions with Artificial Intelligence robots and assistants. While the data related to the participants’ performance were analyzed quantitatively using Generalized Estimating Equations, Interview content analysis was employed to extract themes and subthemes from the data obtained from the participants’ responses to interview questions. The findings indicated that Artificial Intelligence robots have great potential to stimulate bilingual students’ verbal senses and promote Persian for Medical Purposes comprehension. Natural Language Processing algorithms, by calling content from Artificial Intelligence Libraries, made it possible to implement realistic interactive contexts for practicing Persian for Medical Purposes listening and reading. Meanwhile, bilingual students with better performance found learning Persian for Medical Purposes through Artificial Intelligence robots enjoyable. The design and implementation of an Artificial Intelligence robot-assisted language learning for academic purposes is discussed based on applied language learning.
Extended Abstract:
Introduction
Artificial Intelligence (AI) social robots help establish interpersonal interaction and focus on developing language skills through enhancing students’ senses. Multilingualism stimulates the audio-visual senses of students as they specifically learn a new language to deal with their needs in authentic environments. Developers of robot-assisted language learning exploit different senses in their current works in university language learning. Chatbots are AI assistants in language learning in which students pose their questions to join a conversation.
While a broad array of studies has investigated the potential of social robots and AI assistants in language learning at universities, only a few studies have been conducted in Persian for Medical Purposes learning concerning stimulating students’ senses and multilingualism. Research has indicated that AI social robots serve as real-like conversation partners, which subsequently help students learn receptive and productive skills through enhanced torso. Nevertheless, mediation of students’ proficiency in first and/or second language has not been taken into account. In addition, several studies have tackled the effect of robot’s senses on language learning. Their findings revealed that enhancing the senses of robots facilitates language leaning; however, they did not address the probable effect of multilingualism on heightening the audio-visual senses in learning language for specific purposes.
To fill the research gaps, the researchers mediate the monolingual and bilingual in learning Persian for Medical Purposes listening and reading through audio-visual senses of AI robots and chatbots. Artificial Intelligence assistants allow users to predict reading and listening to address their language needs. Therefore, using tools of touch monitors in robots’ torsos or students’ mobile devices, the researchers in this study mediates students’ Persian for Medical Purposes to help them understand language needs in both universities and fields. Artificial Intelligence-based language education is affiliated with social psychology, which, in turn, is concerned with the study of how a learning process is influenced by the presence of others.
Methodology
In the 2024 academic year, 480 non-Iranian male and female students were selected through the design of experiments. First, to identify monolingual and bilingual students, a TOEFL-like test was administered. Three hundred and twelve students were bilingual and 88 students were monolingual. Eighty students, whose English proficiency scores were one standard deviation higher than the mean, were excluded from the study. Then, the Persian proficiency of 400 students was determined by a general Persian test. According to the Common European Framework of Reference for Languages, the participants were placed in three levels and were randomly assigned to control and experimental groups. In an introductory session, the participants were taught how to read and listen with chatbots or AI robots. Besides, the structure of interviews was explained. In weeks 2-16, the participants were first co-taught with the teachers; then, they joined conversation with chatbots or AI robots to practice Persian for Medical Purposes listening and reading. Finally, the participants’ listening and reading were assessed in university- and field-like situations. Parallel with the treatment, focus-group interviews were conducted.
Results and Discussion
The study explored the effectiveness of AI robots in learning Persian for Medical Purposes, focusing on listening and reading skills across two control and experimental groups. The control group practiced with chatbots, while the experimental group engaged with AI robots. The results indicated a significant difference in performance between the two groups. Students in the chatbot group exhibited lower learning outcomes compared to their fellows in the AI robot group. This finding suggests that while both technologies aim to enhance language learning, AI robots may be more effective in facilitating comprehension of medical concepts in universities and fields. Moreover, proficiency in Persian emerged as an important factor influencing student success. Those with higher proficiency levels performed better, emphasizing the importance of foundational language skills in achieving effective learning outcomes. In terms of interaction effects, the study revealed that the impact of time on learning varied significantly between the two groups. As students progressed through the sessions, the effectiveness of the chatbot group fluctuated, suggesting that the learning experience may not have been as consistent as that of the AI robot group. Additionally, the interaction between language background and time indicated that bilingual students experienced different learning trajectories, potentially influenced by their prior exposure to the language. While the benefits of bilingualism were not statistically significant in this setting, the complexity of language learning in medical settings cannot be overlooked. Overall, these findings highlight the nuanced relationship between technology, language proficiency, and learning outcomes in specialized fields. The results advocate for a more tailored approach in language instruction, suggesting that leveraging the strengths of AI robots could enhance educational experiences in medical language education. Future research should further explore these dynamics to refine pedagogical strategies and optimize learning environments for students in medical fields.
Conclusion
In conclusion, this study highlights the significant advantages of bilingualism in the context of learning Persian for Medical Purposes. The findings indicate that bilingual students easily engaged in conversation with AI robots compared to their monolingual counterparts, suggesting that their verbal senses were more effectively stimulated. Additionally, the superior outcomes observed in the AI-robot group, as opposed to the chatbot group, underscore the potential of interactive and immersive learning environments in enhancing Persian for Medical Purposes listening and reading. Although bilingual students did not excel in developing their listening and reading skills in Persian, they reported a higher level of enjoyment in the learning process. These results emphasize the importance of considering linguistic backgrounds in language education and suggest that incorporating AI technologies, such as social robots, can significantly enhance the learning experience for medical students. Future research could further explore the implications of these findings and the potential for broader applications in medical language education.