İkinci dil öğretiminde Chatbot teknolojisinin kullanımına yönelik çalışmalardaki genel eğilimler

Year 2024, , 273 - 288, 31.05.2024

Sedat Maden , Okan Yetişensoy

https://doi.org/10.33400/kuje.1407998

Abstract

Bu araştırmanın amacı, ikinci dil öğretiminde “Chatbot” teknolojisinin kullanımına yönelik araştırma makalesi türündeki çalışmaların incelenerek bu konuda var olan eğilimlerin ortaya koyulmasıdır. Nitel araştırma yaklaşımına uygun olarak yürütülen bu çalışma, doküman incelemesi yöntemi ile yürütülmüştür. İkinci dil öğretiminde Chatbot kullanımını ele alan araştırma makalesi türündeki 40 çalışma ise bu araştırmanın temel veri kaynağını oluşturmuştur. Analizler sonucunda ikinci dil eğitiminde Chatbot kullanımına yönelik çalışmaların önemli bir kısmının önce deneysel bir sürecin yürütüldüğü, ardından katılımcılardan görüş alınan karma yöntem araştırmaları şeklinde kurgulandığı belirlenmiştir. Karma yöntem araştırmalarından sonra en sık olarak kullanılan yaklaşımların ise sırasıyla nicel ve nitel yaklaşımlar olduğu görülmüştür. Ayrıca araştırmaların büyük oranda İngilizcenin öğretimine odaklandığı görülmüş, Çince ve Almanca dillerine yönelik birer çalışma dışında farklı bir hedef dillere yönelik çalışmalara rastlanılmamıştır. Çalışmalardaki genel eğilimin hâlihazırda var olan chatbotları kullanma yönünde olduğu belirlenmiş, bu anlamda Replika, Andy, Alexa, Elbot, Mitsiku ve Google Asistan’ın yaygın olarak kullanıldığı görülmüştür. Araştırmacıların kendi Chatbot’unu geliştirdiği çalışma örneklerine de rastlanmıştır. Araştırmalardaki katılımcı gruplarını büyük oranda üniversite öğrencilerinin oluşturduğu görülmüş, lise, ortaokul ve ilkokul öğrencileri ile öğretmenlerin çalışma grubu olduğu çalışmaların nadir olduğu belirlenmiştir. Çalışmaların sıklıkla konuşma ve gramer becerileri etrafındaki akademik başarı faktörüne odaklandığı görülmüştür. Ayrıca katılımcıların görüş ve algılarını belirlemeye yönelik çalışmaların da bulunduğu, bu noktada en az çalışmanın motivasyon, ilgi, tutum gibi duyuşsal özellikler etrafında gerçekleştirildiği belirlenmiştir.

Keywords

Chatbot, Eğilim, İkinci dil öğretimi

General trends in studies on the use of Chatbot technology in second language teaching

Abstract

The purpose of this research is to reveal existing trends by examining research article-type studies on the use of "Chatbot" technology in second language teaching. This study, carried out in accordance with the qualitative research approach, utilized the document review method. Forty studies in the form of research articles addressing the use of Chatbots in second language teaching constituted the main data source of this research. As a result of the analysis, it was determined that a significant part of the relevant studies was designed as mixed methods research, in which an experimental process was first carried out, and then opinions were obtained from the participants. The most frequently used approaches after mixed methods research are quantitative and qualitative approaches, respectively. Additionally, it was observed that the research largely focuses on teaching English, and apart from one study on Chinese and German, no studies on different target languages were found. The general trend in the studies is to use existing chatbots, and in this sense, Replika, Andy, Alexa, Elbot, Mitsiku, and Google Assistant have been widely used. There are also examples of studies where researchers developed their own Chatbot. It was observed that the participant groups in the studies were largely composed of university students, and it was determined that studies in which high school, secondary school, and primary school students and teachers were the study groups were rare. Studies often focus on the academic success factor around speaking and grammar skills. It was also determined that there are studies aimed at determining the opinions and perceptions of the participants, but there are few studies conducted around affective characteristics such as motivation, interest, and attitude.

Keywords

Chatbot, Second language teaching, Trends

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