Oral language accuracy, corrective feedback and learner uptake in an online EFL course

Les eines tecnològiques han ampliat el ventall de possibilitats en l'ensenyament i l'aprenentatge de llengües i han generat moltes preguntes en professors i investigadors: quina és la millor manera d'integrar la tecnologia? Quins efectes té la tecnologia en l'aprenentatge? Quin és el paper de la correcció d'errors en ambients totalment virtuals? Aquesta investigació busca identificar els errors més comuns, les estratègies de correcció més freqüents i les reaccions dels alumnes a les correccions dels professors en ambients sincrònics. Aquest és un estudi de cas qualitatiu que fa servir mètodes mixtos i l'anàlisi del discurs mitjançat per ordinador per analitzar la informació. Els resultats de la investigació mostren que els estudiants produeixen errors a velocitats similars, el professor tendeix a proveir la correcció explícita dels errors i els estudiants tendeixen a repetir les correccions del professor.Las herramientas tecnológicas han ampliado el abanico de posibilidades en la enseñanza y el aprendizaje de lenguas y han generado muchas preguntas en profesores e investigadores: ¿cuál es la mejor manera de integrar la tecnología?, ¿qué efectos tiene la tecnología en el aprendizaje?, ¿cuál es el rol de la corrección de errores en ambientes totalmente virtuales? Esta investigación busca identificar los errores más comunes, las estrategias de corrección más frecuentes y las reacciones de los aprendices a las correcciones de los profesores en ambientes sincrónicos. Este es un estudio de caso cualitativo que usa métodos mixtos y el análisis del discurso mediado por computador para analizar la información. Los resultados de la investigación muestran que los estudiantes producen errores a velocidades similares, el profesor tiende a proveer la corrección explícita de los errores y los estudiantes tienden a repetir la corrección del profesor.The use of computer-mediated communication (CMC) technologies has broadened the scope of possibilities for language teaching and learning, while also leading teachers and researchers alike to pose a number of relevant questions. What is the best way to blend such technologies into teaching? What impact will CMC technologies have on learners' target language development? What role does teacher feedback play in exclusively online language learning settings? To answer these questions, a qualitative case study was carried out to identify the most common errors made by language learners, the correction strategies employed by teachers and, finally, learners' reactions to these corrections in synchronous interactions. The study's main findings, based on a mixed-methods and computer-mediated discourse analysis approach, are as follows: most learners make mistakes at a similar rate, the number of mistakes drops towards the end of the course, the teacher tends to provide explicit corrective feedback and students' main strategy for amending their mistakes is to repeat the teacher's correction

Oral language accuracy, corrective feedback and learner uptake in an online EFL course

Les eines tecnològiques han ampliat el ventall de possibilitats en l'ensenyament i l'aprenentatge de llengües i han generat moltes preguntes en professors i investigadors: quina és la millor manera d'integrar la tecnologia? Quins efectes té la tecnologia en l'aprenentatge? Quin és el paper de la correcció d'errors en ambients totalment virtuals? Aquesta investigació busca identificar els errors més comuns, les estratègies de correcció més freqüents i les reaccions dels alumnes a les correccions dels professors en ambients sincrònics. Aquest és un estudi de cas qualitatiu que fa servir mètodes mixtos i l'anàlisi del discurs mitjançat per ordinador per analitzar la informació. Els resultats de la investigació mostren que els estudiants produeixen errors a velocitats similars, el professor tendeix a proveir la correcció explícita dels errors i els estudiants tendeixen a repetir les correccions del professor.Las herramientas tecnológicas han ampliado el abanico de posibilidades en la enseñanza y el aprendizaje de lenguas y han generado muchas preguntas en profesores e investigadores: ¿cuál es la mejor manera de integrar la tecnología?, ¿qué efectos tiene la tecnología en el aprendizaje?, ¿cuál es el rol de la corrección de errores en ambientes totalmente virtuales? Esta investigación busca identificar los errores más comunes, las estrategias de corrección más frecuentes y las reacciones de los aprendices a las correcciones de los profesores en ambientes sincrónicos. Este es un estudio de caso cualitativo que usa métodos mixtos y el análisis del discurso mediado por computador para analizar la información. Los resultados de la investigación muestran que los estudiantes producen errores a velocidades similares, el profesor tiende a proveer la corrección explícita de los errores y los estudiantes tienden a repetir la corrección del profesor.The use of computer-mediated communication (CMC) technologies has broadened the scope of possibilities for language teaching and learning, while also leading teachers and researchers alike to pose a number of relevant questions. What is the best way to blend such technologies into teaching? What impact will CMC technologies have on learners' target language development? What role does teacher feedback play in exclusively online language learning settings? To answer these questions, a qualitative case study was carried out to identify the most common errors made by language learners, the correction strategies employed by teachers and, finally, learners' reactions to these corrections in synchronous interactions. The study's main findings, based on a mixed-methods and computer-mediated discourse analysis approach, are as follows: most learners make mistakes at a similar rate, the number of mistakes drops towards the end of the course, the teacher tends to provide explicit corrective feedback and students' main strategy for amending their mistakes is to repeat the teacher's correction

How definite are we about the English article system? Chinese learners, L1 interference and the teaching of articles in English for academic purposes programmes.

Omission and overspecification of the/a/an/Ø are among the most frequently occurring grammatical errors made in English academic writing by Chinese first language (L1) university students (Chuang & Nesi, 2006; Lee & Chen, 2009). However, in the context of competing demands in the English for academic purposes (EAP) syllabus and conflicting evidence about the effectiveness of error correction, EAP tutors are often unsure about whether article use should or could be a focus and whether such errors should be corrected or ignored. With the aim of informing pedagogy, this study investigates: whether explicit teaching or correction improves accuracy; which article uses present the most challenges for Chinese students; the causes of error and whether a focus on article form can be integrated within a modern genre based/student centred approach in EAP. First, a questionnaire survey investigates how EAP teachers in higher education explicitly teach or correct English article use. Second, the effect of explicit teaching and correction on English article accuracy is investigated in a longitudinal experiment with a control group. Analysis of this study’s post-study measures raise questions about the sustained benefits of written correction or decontextualised rule-based approaches. Third, findings are presented from a corpus-based study which includes an inductive and deductive analysis of the errors made by Chinese students. Finally, in a fourth study hypotheses are tested using a multiple-choice test (n=455) and the main findings are presented: 1) that general referential article accuracy is significantly affected by proficiency level, genre and students’ familiarity with the topic; 2) Chinese students are most challenged by generic and non-referential contexts of use which may be partly attributable to the lack of positive L1 transfer effects; 3) overspecification of definite articles is a frequent problem that sometimes gives Chinese B2 level students’ writing an ‘informal tone’; and 4) higher nominal density of pre-qualified noun phrases in academic writing is significantly associated with higher error rates. Several practical recommendations are presented which integrate an occasional focus on article form with whole text teaching, autonomous proofreading skills, register awareness, and genre-based approaches to EAP pedagogy

The written production of ecuadorian efl high school students: grammatical transfer errors and teacher's and learner's perception of feedback

346 p.El objetivo de esta tesis doctoral es investigar los errores gramaticales de transferencia en la escritura en inglés como lengua extranjera de alumnos de secundaria ecuatorianos (n=180) y su grado de prevalencia en comparación a los errores léxicos de transferencia. Así mismo, se intenta comparar la variación de los errores gramaticales de transferencia obtenidos en tres grupos de alumnos clasificados de acuerdo a su nivel de dominio de inglés según el Marco Común Europeo (A1, A2, B1) y la variación de dichos errores entre dos tipos de ensayo: narrativo y argumentativo. Finalmente, se desea conocer las percepciones de los estudiantes y profesores con respecto a la retroalimentación en la escritura de inglés como lengua extranjera proporcionada en las clases. Todo esto se realiza con el propósito de contribuir a tratar de cumplir una parte de las metas del Ministerio de Educación del Ecuador relacionadas a la búsqueda de una mejora en el nivel de dominio de inglés como lengua extranjera en estudiantes de educación secundaria

The role of feedback in the processes and outcomes of academic writing in english as a foreign language at intermediate and advanced levels

Providing feedback on students’ texts is one of the essential components of teaching second language writing. However, whether and to what extent students benefit from feedback has been an issue of considerable debate in the literature. While many researchers have stressed its importance, others expressed doubts about its effectiveness. Regardless of these continuing and well-established debates, instructors consider feedback as a worthwhile pedagogical practice for second language learning. Based on this premise, I conducted three experimental studies to investigate the role of written feedback in Myanmar and Hungarian tertiary EFL classrooms. Additionally, I studied syntactic features and language-related error patterns in Hungarian and Myanmar students’ writing. This attempt was made to understand how students with different writing proficiency acted upon teacher and automated feedback. The first study examined the efficacy of feedback on Myanmar students’ writing over a 13-week semester and how automated feedback provided by Grammarly could be integrated into writing instruction as an assistance tool for writing teachers. Results from pre-and post-tests demonstrated that students’ writing performance improved along the lines of four assessment criteria: task achievement, coherence and cohesion, grammatical range and accuracy, and lexical range and accuracy. Further results from a written feedback analysis revealed that the free version of Grammarly provided feedback on lower-level writing issues such as articles and prepositions, whereas teacher feedback covered both lower-and higher-level writing concerns. These findings suggested a potential for integrating automated feedback into writing instruction. As limited attention was given to how feedback influences other aspects of writing development beyond accuracy, the second study examined how feedback influences the syntactic complexity of Myanmar students’ essays. Results from paired sample t-tests revealed no significant differences in the syntactic complexity of students’ writing when the comparison was made between initial and revised texts and between pre-and post-tests. These findings suggested that feedback on students’ writing does not lead them to write less structurally complex texts despite not resulting in syntactic complexity gains. The syntactic complexity of students’ revised texts varied among high-, mid-, and low-achieving students. These variations could be attributed to proficiency levels, writing prompts, genre differences, and feedback sources. The rationale for conducting the third study was based on the theoretical orientation that differential success in learners’ gaining from feedback largely depended on their engagement with the feedback rather than the feedback itself. Along these lines of research, I examined Hungarian students’ behavioural engagement (i.e., students’ uptake or revisions prompted by written feedback) with teacher and automated feedback in an EFL writing course. In addition to the engagement with form-focused feedback examined in the first study, I considered meaning-focused feedback, as feedback in a writing course typically covers both linguistic and rhetorical aspects of writing. The results showed differences in feedback focus (the teacher provided form-and meaning-focused feedback) with unexpected outcomes: students’ uptake of feedback resulted in moderate to low levels of engagement with feedback. Participants incorporated more form-focused feedback than meaning-focused feedback into their revisions. These findings contribute to our understanding of students’ engagement with writing tasks, levels of trust, and the possible impact of students’ language proficiency on their engagement with feedback. Following the results that Myanmar and Hungarian students responded to feedback on their writing differently, I designed a follow-up study to compare syntactic features of their writing as indices of their English writing proficiency. In addition, I examined language-related errors in their texts to capture the differences in the error patterns in the two groups. Results from paired sample t-tests showed that most syntactic complexity indices distinguished the essays produced by the two groups: length of production units, sentence complexity, and subordination indices. Similarly, statistically significant differences were found in language-related error patterns in their texts: errors were more prevalent in Myanmar students’ essays. The implications for research and pedagogical practices in EFL writing classes are discussed with reference to the rationale for each study

한국인 고등학생의 영어 형용사 타동결과구문 학습에서의 인공지능 챗봇 기반 교수의 효과

학위논문(박사) -- 서울대학교대학원 : 사범대학 외국어교육과(영어전공), 2022.2. 김기택.English adjectival transitive resultative constructions (VtR) are notoriously challenging for Korean L2 English learners due to their syntactic and semantic differences from their L1 counterparts. To deal with such a complex structure, like English adjectival VtR, Korean L2 English learners need instructional interventions, including explicit instructions and corrective feedback on the target structure. Human instructors are virtually incapable of offering adequate corrective feedback, as providing corrective feedback from a human teacher to hundreds of students requires excessive time and effort. To deal with the practicality problems faced by human instructors in providing corrective feedback, numerous artificial intelligence (AI) chatbots have been developed to provide foreign language learners with corrective feedback on par with human teachers. Regrettably, many currently available AI chatbots remain underdeveloped. In addition, no prior research has been conducted to assess the effectiveness of corrective feedback offered by an AI chatbot, a human instructor, or additional explicit instruction via video material. The current study examined the instructional effects of corrective feedback from an AI chatbot on Korean high school students’ comprehension and production of adjectival VtR. Also, the current study investigated whether the corrective feedback generated by the AI chatbot enables Korean L2 English learners to expand their constructional repertoire beyond instructed adjectival VtR to uninstructed prepositional VtR. To investigate these issues, text-based Facebook Messenger AI chatbots were developed by the researcher. The effectiveness of the AI chatbots’ corrective feedback was compared with that of a human instructor and with additional video material. Students were divided into four groups: three instructional groups and one control group. The instructional groups included a chatbot group, a human group, and a video group. All learners in the three instructional groups watched a 5-minute explicit instruction video on the form and meaning pairings of the adjectival VtR in English. After that, learners were divided into three groups based on their preferences for instructional types. The learners volunteered to participate in the instructional procedures with corrective feedback from a text-based AI chatbot, a human instructor, or additional explicit instruction using a 15-minute video. Moreover, they took part in three testing sessions, which included a pretest, an immediate posttest, and a delayed posttest. The control group students were not instructed, and only participated in the three testing sessions. Two tasks were used for each test session: an acceptability judgment task (AJT) and an elicited writing task (EWT). The AJT tested participants’ comprehension of instructed adjectival VtR and uninstructed prepositional VtR. The EWT examined the correct production of instructed adjectival VtR and uninstructed prepositional VtR. The results of the AJT revealed that the instructional treatment (e.g., corrective feedback from the AI chatbot or a human instructor, or additional explicit instruction from the video material) was marginally more effective at improving the comprehension of adjectival VtR than was the case with the control group. On the other hand, the instructional treatment on the adjectival VtR failed in the generalization to prepositional VtR which was not overtly instructed. In the EWT, the participants in the corrective feedback groups (e.g., the chatbot and human groups) showed a more significant increase in the correct production of the instructed adjectival VtR more so than those in the video and control groups. Furthermore, the chatbot group learners showed significantly higher production of uninstructed prepositional VtR compared to any other group participants. These findings suggest that chatbot-based instruction can help Korean high school L2 English learners comprehend and produce complex linguistic structures—namely, adjectival and prepositional VtR. Moreover, the current study has major pedagogical implications for principled frameworks for implementing AI chatbot-based instruction in the context of foreign language learning.영어 형용사 타동결과구문(English Adjectival Transitive Resultative Construction)은 한국인 영어 학습자들에게 모국어의 대응 구문이 갖는 의미 통사론적 차이로 인해 학습하기 매우 어려운 것으로 알려져 있다. 따라서 영어 형용사 타동결과구문과 같은 복잡한 구문을 학습하기 위해서, 한국인 영어 학습자들에게는 목표 구조에 대한 명시적 교수와 교정적 피드백을 포함한 교수 처치가 요구된다. 수백 명의 학습자들에게 교정적 피드백을 제공하기 위해서는 과도한 시간과 노력이 요구되기 때문에, 인간 교사가 적절한 양의 교정적 피드백을 제공한다는 것은 사실상 불가능하다. 교정적 피드백을 제공할 때 직면하는 이러한 실용성 문제를 해결하기 위하여, 외국어 학습자들에게 인간 교사와 유사한 교정 피드백을 제공할 수 있는 수많은 인공 지능(AI) 챗봇이 개발되었다. 유감스럽게도, 현재 사용 가능한 많은 외국어 학습용 인공지능 챗봇은 아직 충분히 개발되지 않은 상태에 남아있으며, 인공지능 챗봇의 교정적 피드백이 갖는 교수효과를 비교 분석한 연구는 현재 이루어지지 않은 상태다. 이러한 선행연구의 한계에 초점을 두어, 본 연구에서는 인공지능 챗봇의 교정적 피드백이 한국 고등학생의 영어 형용사 타동결과구문의 이해와 생성에 미치는 교수 효과를 살펴보았다. 또한 본 연구에서는 이러한 교수 효과가 언어적으로 관련된 다른 영어 구문의 학습에도 영향을 끼치는지를 알아보기 위해 교실에서 직접 가르치지 않았던 구문인 영어 전치사 타동결과구문(English Prepositional Transitive Resultative Construction)의 학습 양상을 알아보았다. 이를 위해, 본 연구에서는 텍스트 메시지 기반의 페이스북 메신저에서 구동되는 인공지능 챗봇을 개발하였다. 인공지능 챗봇의 교수효과 검증을 위해 본 연구에 참여한 학생들은 네 개의 집단으로 구분되었다: 세 개의 교수 집단에는 교수처치가 적용되었고, 한 개의 통제 집단에서는 교수처치가 적용되지 않았다. 교수처치가 적용된 세 개의 집단은 챗봇그룹, 인간그룹, 영상그룹으로 분류되었으며, 이들은 모두 영어로 된 형용사 타동결과구문의 형태와 의미 쌍에 대한 5분 길이의 학습 비디오를 시청함으로써 명시적 교수 처치를 받았다. 또한 비디오를 시청한 후 세 그룹의 학습자들은 교재를 통해 제공되는 언어연습자료를 해결하는 과업에 참여하였다. 다음으로 세 집단(챗봇그룹, 인간그룹, 영상그룹)은 다음과 같은 추가적 교수처치를 받았다: 챗봇그룹 학습자들은 교재 활동과 관련된 텍스트 기반 인공지능 챗봇과의 대화에 참여함으로써 오류에 대한 교정적 피드백을 받았다. 인간그룹 학습자들은 교재활동을 완수한 내용을 인간 교사에게 전송하고, 이에 대한 교정적 피드백을 받았다. 영상그룹 학습자들은 교재활동을 완수한 후 이에 대한 15분의 추가적인 명시적 교수자료를 영상으로 시청하였다. 학습자의 교수효과는 사전시험, 사후시험 및 지연 사후시험으로 검증되었다. 한편 통제 집단 학생들은 교수처치 없이 세 번의 시험에만 참여하였다. 세 차례의 시험에서는 수용성판단과제(AJT)와 유도작문과제(EWT)의 두 가지 과제가 사용되었다. 수용성판단과제를 통하여, 교수된 영어 형용사 타동결과구문과 지시되지 않은 영어 전치사 타동결과구문 대한 참가자의 이해도를 측정하였다. 유도작문과제를 통하여 교수된 영어 형용사 타동결과구문과 지시되지 않은 영어 전치사 타동결과구문을 참여자가 정확하게 산출할 수 있는지를 측정하였다. 시험의 결과는 다음과 같았다. 수용성판단과제의 경우, 교수처치가 적용된 세 집단이 통제 집단보다 형용사 타동결과구문의 이해도 향상에 약간 더 효과적인 것으로 나타났다. 하지만 형용사 타동결과구문에 대한 교수적처치는 교수되지 않은 전치사 타동결과구문으로의 학습에 영향을 주지 못하였다. 유도작문과제의 경우, 인공지능 챗봇이나 인간 교사에 의해 제공되는 교정 피드백 그룹의 참가자가 영상그룹 및 통제집단의 참가자보다 형용사 타동결과구문의 올바른 생성에 더 유의미한 영향을 미치는 것으로 드러났다. 동일한 교수 효과가 전치사 타동결과구문의 학습에서도 관측되어, 형용사 타동결과구문의 학습이 전치사 타동결과구문의 학습에 일반화가 일어났다. 본 연구는 인간 교사가 직면해야 하는 실용성 문제를 극복하고, 인공지능 챗봇이 한국인 고등학교 L2 영어 학습자가 형용사 및 전치사 타동결과구문과 같은 복잡한 언어 구조를 이해하고 생성하는 데에 인간 교사와 비견될 정도로 교정적 피드백을 제공할 수 있을 것임을 시사한다. 또한, 본 연구는 인공지능 챗봇 기반 외국어 교육의 실제적 사례 및 효과를 선도적으로 보여주었다는 점에서 의미가 있다.ABSTRACT i TABLE OF CONTENTS iii LIST OF TABLES v LIST OF FIGURES vii CHAPTER 1. INTRODUCTION 1 1.1. Statement of Problems and Objectives 1 1.2. Scope of the Research 6 1.3. Research Questions 9 1.4. Organization of the Dissertation 10 CHAPTER 2. LITERATURE REVIEW 12 2.1. Syntactic and Semantic Analysis of Korean and English Transitive Resultative Constructions 13 2.1.1. Syntactic Analysis of English Transitive Resultative Construction 13 2.1.2. Syntactic Analysis of Korean Transitive Resultative Constructions 25 2.1.3. Semantic Differences in VtR between Korean and English 46 2.1.4. Previous acquisition study on English adjectival and prepositional VtR 54 2.2. Corrective Feedback 59 2.2.1. Definition of Corrective Feedback 59 2.2.2. Types of Corrective Feedback 61 2.2.3. Noticeability in Corrective Feedback 67 2.2.4. Corrective Recast as a Stepwise Corrective Feedback 69 2.3. The AI Chatbot in Foreign Language Learning 72 2.3.1. Non-communicative Intelligent Computer Assisted Language Learning (ICALL) 73 2.3.2. AI Chatbot without Corrective Feedback 79 2.3.3. AI Chatbot with Corrective Feedback 86 2.4. Summary of the Literature Review 92 CHAPTER 3. METHODOLOGY 98 3.1. Participants 98 3.2. Target Structure 102 3.3. Procedure of the Study 106 3.4. Instructional Material Shared by the Experimental Group 107 3.4.1. General Framework of the Instructional Session 108 3.4.2. Instructional Material Shared by Experimental Groups 111 3.5. Group-specific Instructional Treatments: Post-Written Instructional Material Activities on Corrective Feedback from Chatbot, Human, and Additional Explicit Instruction via Video 121 3.5.1. Corrective Feedback from the AI Chatbot 122 3.5.2. Corrective Feedback from a Human Instructor 136 3.5.3. Additional Instruction via Video Material 139 3.6. Test 142 3.6.1. Acceptability Judgment Task (AJT) 144 3.6.2. Elicited Writing Task (EWT) 150 3.7. Statistical Analysis 152 CHAPTER 4. RESULTS AND DISCUSSIONS 154 4.1. Results of Acceptability Judgment Task (AJT) 154 4.1.1. AJT Results of Instructed Adjectival VtR 155 4.1.2. AJT Results of Uninstructed Prepositional VtR 160 4.1.3. Discussion 164 4.2. Results of Elicited Writing Task (EWT) 175 4.2.1. EWT Results for Instructed Adjectival VtR 176 4.2.2. EWT Results of Uninstructed Prepositional VtR 181 4.2.3. Further Analysis 187 4.2.4. Discussion 199 CHAPTER 5. CONCLUSION 205 5.1. Summary of the Findings and Implications 205 5.2. Limitations and Suggestions for Future Research 213 REFERENCES 217 APPENDICES 246 ABSTRACT IN KOREAN 297박

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