Computer Assisted Language Learning Tool Research Articles

Analyzing the Impact of CALL Tools on English Learners' Writing Skills: A Comparative Study of Errors Correction

The study seeks to compare the effectiveness of Computer-Assisted Language Learning Tools (ChatGPT, Grammarly, and Google Translate) in correcting the occurrences of common errors in English as a second/foreign language (ESL/EFL) learners’ writing. An experimental design offered instructions for Class A with ChatGPT, Class B with Grammarly, Class C with Google Translate, and Class D was the control group with no exposure to any of these tools. Data were collected from texts created by the students based on pictures, both before and after the intervention. It was found that ESL/EFL learners frequently made eight distinct types of errors in their writing: spelling, punctuation, capitalization, possessive words, verb forms, subject-verb agreement, articles, and prepositions. The interventions across different classes showed that ChatGPT in Class A significantly corrected spelling, verb form, and subject-verb agreement-related errors, Grammarly in Class B excelled in correcting prepositional errors, and Google Translate in Class C effectively addressed errors in article use, capitalization, and possessives. In contrast, the control group in Class D surpassed the others in enhancing punctuation. In Class A, ChatGPT, and in Class B, Google Translate displayed enhanced effectiveness in rectifying common writing errors of ESL learners compared to Grammarly in Class B and the control group. The findings suggest that employing targeted digital tools for distinct grammatical challenges can substantially enhance learning outcomes in a language learning context.

Hey <i>Google</i>, Let’s Write

Writing involves more than attention to form (e.g., orthography, grammar), since it requires attention to text type, content, and genre. However, most students of English as a second language (L2) tend to prioritize linguistic accuracy in their writing, to the detriment of the content of their texts. Automatic speech recognition (ASR) has the potential to mitigate this, as it reduces the cognitive burden of writing by facilitating the text input process (using a skill most humans possess—speaking), offering assistance in spelling, and allowing a focus on other aspects of the task (e.g., cohesion, content). Automatic speech recognition is not only accessible and free, but it also fulfills Chapelle’s (2001) criteria of an effective computer-assisted language learning tool (e.g., authenticity, learner fit). Despite these affordances, there is a dearth of studies examining the possible affordances of ASR for writing. This mixed methods, one-shot study examines L2 writers’ perceptions of using ASR to write using the technology acceptance model (TAM). Seventeen (N = 17) undergraduate students at a Canadian university were provided with training on Google Voice Typing (Google Docs) and carried out a series of ASR-based writing tasks over a two-hour period. In order to measure their perceptions of the target criteria, participants filled in a TAM-informed survey consisting of statements about their experience with ASR scored on a 7-point Likert scale. To further explore the participants’ perceptions, semi-structured interviews followed. Findings indicate positive perceptions of ASR’s usefulness in terms of language learning and its ease of use due to the user-friendly voice commands. This suggests that ASR has pedagogical potential, thus requiring further examination to determine its optimal use for L2 writing.

Evaluating the efficacy of Kahoot as a computer-assisted language learning tool in higher education

This study aimed to analyse the effectiveness of using the computer tool Kahoot for foreign language learning in higher education, as well as to address the problem of students' lack of motivation in learning English. This study hypothesised that using the Kahoot app in foreign language classes would improve students' motivation through its engaging approach. To test this hypothesis, a survey was conducted among students who had studied English using this tool. The results showed that students who used the Kahoot app in the classroom were significantly more motivated to learn English. This was made possible by the app's ability to vary the learning tool depending on the needs of the students, which encouraged their active participation in the learning process. The effectiveness of Kahoot as a tool in higher education for learning foreign languages is promising. Its engaging and interactive format, instant feedback, and collaborative learning opportunities make it a valuable tool for enhancing language learning. However, it is important for teachers to be aware of its limitations and complement it with other activities to ensure comprehensive language development. Overall, Kahoot can be a valuable addition to the language learning toolkit in higher education.

The Role of Automated Corrective Feedback in Improving EFL Learners' Mastery of the Writing Aspects

Purpose. Automated Corrective Feedback (ACF) is one of the techniques used in EFL writing instruction and assessment. This technique has been widely employed to improve students’ writing skills over the last few decades. Adopting a mixed-method design with data triangulation, this study was conducted to investigate the effect of utilizing WRITER, one of the ACF software, on critical writing aspects including use and mechanics, vocabulary, structural organization, and content.
 Methods and procedure. A pre-post quasi-experimental research design was arranged to collect data from 44 Arab EFL learners assigned to four groups: two peer and self-editing control groups and two automated peer and self-editing experimental groups. While the two control groups were required to perform conventional self- or peer-editing tasks, the two experimental groups used WRITER, an ACF software, to edit both their own essays and those written by peers. Statistical analysis was run to examine differences in the writing aspects across the groups.
 Findings. The analysisиindicated significant differences among these four groups. Students involved in the peer-editing experimental group outperformed all groups on mechanics and structural organization. In addition, the self-editing experimental group did better than other groups in improving their vocabulary. Nonetheless, students in the self-editing control group, who did not utilize any type of ACF to improve their writing, performed better than all other groups in terms of the content aspect. Overall results revealed that ACF could increase the productivity of class time; provide valuable feedback on grammar, word choice, structural organization, use and mechanics and enhance students’ self-confidence in their compositions. These results suggest that ACF has a significant effect on EFL writing and can be an effective tool for improving writing skills. 
 Conclusions. This study examined the impact of ACF of WRITER, a type of computer-assisted language learning tool, on enhancing EFL learners’ knowledge of the writing aspects. The findings of the study have some practical implications in the EFL writing classroom, as they inspire educators to incorporate ACF in self- and peer-editing activities and help their students improve language competency.

Developing an intelligent tool for computer-assisted formulaic language learning from YouTube videos

AbstractThis paper presents IdiomsTube (https://www.idiomstube.com), the first-ever computer-assisted language learning tool for facilitating the learning of English idiomatic expressions from YouTube videos. The web-based tool is designed to automatically (1) assess the speech rate and lexical difficulty level of any learner-chosen English-captioned YouTube video; (2) generate a range of vocabulary-building and revision tasks (e.g. fill-in-the-blanks, the classic spelling game hangman, pronunciation, flashcards); and (3) recommend YouTube videos based on learners’ individual learning progress, class teachers’ instructions, and current trends. This paper describes the app’s current features in conjunction with the challenges endemic in the development of applications that automatically generate English language learning content out of internet video content. At the time of writing, the IdiomsTube app had over 8,000 registered users worldwide.

L2 interactional competence in asynchronous multiparty text-based communication: study of online collaborative writing

Web-based writing tools, which allow multiple writers to share and edit the same document, have attracted significant attention as computer-assisted language learning tools in the past decade. However, how L2 writers contribute to the shared document as a social action for interacting with other cowriters remains underexplored in L2 research. Inspired by conversation analysis, in this study, I conducted a moment-by-moment analysis of online, text-based (nonspeaking) asynchronous multiparty interactions consisting of two interactional modes: chat-based discussions and writing records displayed on the screen, with the aim of determining the methods employed by L2 learners to contribute writing changes over time. The data were taken from the online interactions of a group of nine or ten English as a foreign language university learners, who were asked to collaboratively write an essay in English, with the focus being on three learners to elucidate the changes in the methods used. The data analysis indicated that, over the course of the task, the participants used a greater number of methods to make their writing contribution to the entire essay more recognizable; these efforts included announcing the theme of the writing contribution, requesting corrections, and displaying alignment with an essay-in-progress by using a cohesive device in their writing, along with a variety of linguistic and semiotic repertoires. I also discuss the effects of the interlocutors on the online interactional competence of the individual learners.

Research into the Effects of an ICALL Program on Teaching Word Classes to Learners of English

This study investigated the effectiveness of an intelligent computer-assisted language learning (ICALL) program on learning word classes to Turkish learners of English. Learning word classes is a common problem for Turkish students, so the main aim of this research is to help students to overcome this problem. Within the scope of this research, an ICALL application with a word class analyzer was developed and used on Foundation English School Students to measure its effects on students’ achievement in the mastery of word classes and also their attitudes toward such an ICALL environment. The study employed a pre-test—post-test control group design. The sample consisted of 38 B1 level students who were divided into experimental and control groups. The t test was used to investigate the differences between the experimental and control groups. Learners’ achievements in the knowledge of word classes were measured. The results showed that the reading activities with this system had positive effects on students’ word classes learning and their attitudes toward the intelligent computer-assisted language learning tool. According to the statistical results obtained from the study, there is a significant difference between the groups in favor of the experimental group.

ASSESSING LIVEMOCHA AND DUOLINGO EVALUATION TASKS: ADAPTING CHAPELLE CALL ASSESSMENT CRITERIA IN AUTONOMOUS LEANING EXPERIENCE

Computer assisted language learning has been the major issue in the recent decades. Several free networking sites focusing on language learning are offered abundantly. Nonetheless, most of the extant studies seem to compare the traditional way of learning language and modern one per se. This paper, on the other hand, will focus on task evaluation of CALL system as proposed by Chapelle (2001). Six criteria of CALL assessments; language learning potential, learner fit, authenticity, meaning focus, positive impact, and practicality, will be employed to delve Livemocha and Duolingo’s language learning task on Dutch course for basic level. The researcher here plays role as the key instrument in which the data were gained through the experience of using Livemocha and Duolinggo. The Dutch, as foreign language, is chosen as the subject to be studied. As the results, it is intriguing that Livemocha’ task for Dutch course is not adequately fit to beginner leaners. Meanwhile, its counterpart questionably complies authenticity point. The beginner learners may efficiently make use of computer assisted language learning tool to foster their study on foreign language. Nonetheless, they have to be aware of which tool can accelerate their purpose better.

Identification and Disambiguation of Cognates, False Friends, and Partial Cognates Using Machine Learning Techniques

Cognates are words in different languages that have similar spelling and meaning. They can help a second-language learner on the tasks of vocabulary expansion and reading comprehension. The learner needs to pay attention to pairs of words that appear similar but are in fact false friends, have different meanings. Partial cognates are pairs of words in two languages that have the same meaning in some but not all contexts. Detecting the actual meaning of a partial cognate in context can be useful for Machine Translation tools and for Computer-Assisted Language Learning tools. In this article we present a method to automatically classify a pair of words as cognates or false friends. We use several measures of orthographic similarity as features for classification. We study the impact of selecting different features, averaging them, and combining them through machine learning techniques. We also present a supervised and a semi-supervised method to disambiguate partial cognates between two languages. The methods applied for the partial cognate disambiguation task use only automatically-labeled data therefore they can be applied to other pairs of languages as well. We also show that our methods perform well when using corpora from different domains. We applied all our methods to French and English.

Disambiguation of partial cognates

Partial cognates are pairs of words in two languages that have the same meaning in some, but not all contexts. Detecting the actual meaning of a partial cognate in context can be useful for Machine Translation tools and for Computer-Assisted Language Learning tools. We propose a supervised and a semi-supervised method to disambiguate partial cognates between two languages: French and English. The methods use only automatically-labeled data; therefore they can be applied to other pairs of languages as well. The aim of our work is to automatically detect the meaning of a French partial cognate word in a specific context.

A Method of Computer-Assisted Language Learning: The Elaboration of a Tool Designed for an ‘Un-Schoolable’ Public

Thanks to a Leonardo da Vinci project, nine countries are working together on a brand new computer assisted language learning tool. This method is aimed at training people who work far away from the teaching place and who usually have had a negative schooling experience. It will be based on a multicultural needs analysis. The CD-Rom constitutes the stable part of the training. It includes two types of teaching device. The first is the professional situation of linguistic learning and remains identical for all countries involved in the partnership. This device allows the student to be able to communicate in a very short period time. The second part will be different for each country as it gives relevant information about the culture of each country partner. The main focus of the paper will be the methodological aspects of the tool: the goals, the steps of the construction and the theoretical foundations.