Applied Linguistics Research Articles

Structuralism’s Other Saussure

This article attempts to place the psychoanalyst Raymond de Saussure (son of Ferdinand de Saussure and an analysand of Freud) within the history of structuralism, by emphasizing the linguistic dimensions of his early psychoanalytic thought. With reference to numerous unpublished letters, and other archival material, it reconstructs in detail three pivotal moments in the young de Saussure’s early career. First, it locates a preliminary attempt to combine Freudian psychoanalysis with the linguistic theories of Ferdinand de Saussure in Raymond de Saussure’s correspondence with the linguist Charles Bally and his review of Antoine Meillet. An attempt is then made to situate Saussure within the context of an early Swiss interest in the relationship between linguistics and psychoanalysis through a study of the papers presented by his colleagues Jean Piaget and Sabina Spielrein, at the 1922 International Psychoanalytic Congress in Berlin. The article then shifts its focus to 1940s New York, to explore how Saussure assisted his close friends and collaborators Roman Jakobson and, to a lesser extent, Claude Lévi-Strauss in establishing the fundamental coordinates of the structuralist movement. The article aims to call attention to an earlier Freudo-Saussurean synthesis that has been overshadowed by Jacques Lacan’s later, more elaborate, application of Saussurean linguistics to psychoanalysis.

Malay phoneme-based subword news headline generator for low-resource language

The booming of technology has significantly increased the amount of news articles for readers. The headline of news plays an essential role in attracting readers. Traditionally, crafting the news headline is a manual task at the news desk. The motivation of this paper is to address the issues faced in low resource languages, such as the Malay language. The main contribution of this paper is a new hybrid model based on extractive- and abstractive-based text summarization with the integration of a geographical linguistics model; a Malay phoneme-based subword embedding has been developed to solve the complex morphological issue in the Malay language-based computational linguistic applications. The experiment involves various sequence-to sequence (seq2seq) models to generate the Malay news headlines. Besides that, the out-of-vocabulary (OOV) is assessed in the models. From the experiment, the proposed hybrid text summarization model shows significant improvement over the baseline models above 11.00 in ROUGE-1, 4.00 ROUGE-2, and 11.00 in ROUGE-L. The proposed model can reduce the OOV rate to below 15%.

From theory to practice: A case study and ethnographic exploration of translanguaging strategies in second language academic writing

This paper examines the intersection of case study and ethnographic research methodologies within the field of Applied Linguistics, focusing specifically on the investigation of translanguaging practices in academic writing. The paper explores the theoretical underpinnings and practical applications of these qualitative research methods, highlighting their key characteristics, benefits, and challenges. By reviewing exemplary studies, the paper aims to demonstrate the strengths and complexities of these methodologies in understanding the diverse language practices of multilingual learners in educational settings. It concludes by reflecting on the potential of these research approaches to inform the development of inclusive and effective teaching practices for diverse student populations in a globalized world.

An Analysis of Current Situation and Prospect of Natural Language Processing Application in Discourse Analysis

Abstract. Natural Language Processing is a subfield of Artificial Intelligence and an interdisciplinary field of Linguistics and Computer Science. Previous research mainly focuses on the comparison and practical application of natural language processing technology, but the amount of research on its applications in Linguistics is limited. To fill this gap, this article focuses on the current application of technologies in discourse analysis, which is one of the most popular fields in Linguistics. The researcher will initially summarize the existing techniques and tools of Natural Language Processing used for pre-processing, such as Tokenization, Stemming, and Named Entity Recognition. Open-source tools such as NLTK and Spacy for pre-processing are also mentioned in the article. Subsequently, the researcher will introduce commonly used technologies like sentiment analysis and semantic analysis. This research concludes that discourse analysis can benefit many industries such as Medicine, Economics, Agriculture and Politics. However, this paper also analyzes the drawbacks and challenges that NLP technologies for discourse analysis face. Barriers such as Word Sense Disambiguation (WSD) and the context dependency of human language made it difficult for NLP technologies to be applied in Pragmatic analysis.

AUTOMATED SARCASM RECOGNITION USING APPLIED LINGUISTICS DRIVEN DEEP LEARNING WITH LARGE LANGUAGE MODEL

Posting sarcastic comments on social media has become popular in the modern era. Sarcasm is a linguistic expression that typically conveys the contrary meaning of what has already been said, making it challenging for machines to find the literal meaning. It depends mainly on context, making it a tedious process for computational analysis. It is well known for its modulation with spoken words and an irony undertone. In addition, sarcasm conveys negative sentiment using positive words, which easily confuses sentiment analysis (SA) models. Sarcasm detection is a natural language processing (NLP) process and is prevalent in SA, human–machine dialogue, and other NLP applications due to sarcasm’s ambiguities and complex nature. Concurrently, the advancement of machine learning (ML) techniques makes it easier to develop robust sarcasm detection methods. This paper presents an automated sarcasm recognition using applied linguistics-driven deep learning with a large language model (ASR-ALDL3M) technique. The purpose of the ASR-ALDL3M technique is to focus on recognizing the sarcastic data using the DL model. In the ASR-ALDL3M technique, the initial data preprocessing phase is utilized, and glove word embedding is applied. Next, the sarcasm recognition procedure is applied using the long short-term memory (LSTM) model. Moreover, the hyperparameter selection of the LSTM model is performed using the fractals monarch butterfly optimization (MBO) technique. At last, a large language model (LLM) is utilized to enhance the sarcastic recognition process. A comprehensive result analysis is made to validate the outcomes of the ASR-ALDL3M technique. The performance evaluation outcomes stated that the ASR-ALDL3M method gains better performance over other models.

Preservation of the Author’s Tonality as a Tool for Evaluating Translation Quality

Introduction. This paper examines the methodology of text analysis using phono-semantic assessment based on the “VAAL-mini” program. The study includes an analysis of the original text and its translation to identify the author's tonality and its [non]preservation in the translation. The relevance of the chosen topic is determined by the application of psycholinguistic methods in the interpretation of V.P. Belyanin and the use of quantitative text analysis methods. The novelty of the research lies in employing the domestic linguistic computer program “VAAL-mini” as a tool capable of categorizing emotional elements of the text. Methodology and sources. The methodological foundation of the research is a psycholinguistic approach to assessing the quality of translation, which justifies the significance of the author category in the interpretation and translation of fiction texts. It also allows for an examination of how translation affects the perception and emotional response of the reader, as well as how accurately the translator conveys the cognitive and emotional aspects of the original text. The primary research method proposed is a quantitative method using the computer program “VAAL-mini”, which is capable of categorizing the emotional elements of the text. The material for the study is the novel by P. Suskind “Perfume: The Story of a Murderer” and its translation into Russian by E.V. Vengerova. Results and discussion. The literature review conducted allows for tracing the current state of psycholinguistics as per Belyanin and its developmental dynamics. In accordance with the identified concept, we performed a comprehensive analysis of P. Suskind's work “Perfume: The Story of a Murderer” and its Russian translation. The results of this analysis help to gain a deeper understanding of the emotional and lexical components of the text, as well as to assess the quality of the translation. The integration of a psycholinguistic approach with modern quantitative analysis methods-using corresponding computer programs enables a more comprehensive understanding of the studied work. Conclusion. As a result of the analysis based on determining the type of text using the linguistic application VAAL-mini, findings were obtained that refuted the external (qualitative) impression of stylistic and emotional equivalence between Süskind's original text and E.V. Vengerova's translation of the novel. This result demonstrates the viability of the proposed methodology for assessing translation quality.

Phrasal frequency and literacy as predictors of individual differences in on-line processing and comprehension of English complex NP subject-verb agreement

We present experimental evidence suggesting that frequency and literacy predict online processing and comprehension of subject-verb agreement constructions by adult native speakers of English. We measured participants’ eye fixations, reaction times, and response accuracy in a forced-choice task using audio-visual eye-tracking paradigm. Participants completed a battery of tasks, inc. the Literacy Rating Scale (Tarone et al., Literacy and Second Language Oracy-Oxford Applied Linguistics, Oxford University Press, 2013), Agreement Judgement Task (e.g., Veenstra et al., Frontiers in Psychology 5:783, 2014). The AJT involved matching an auditorily presented subject phrase to one of two images of easily distinguishable colours presented on a computer screen (e.g., stars, circles). Participants heard 42 test sentences, counterbalanced across the three types: Type 1 (e.g., ‘The stars with the circles are blue’), Type 2 (e.g., ‘The star with the circles is blue’) and Type 3 (e.g., ‘The star with the circles are blue’*. Type 1 and Type 2 constructions are considerably more frequent in writing than in speech (Miller et al., Spontaneous spoken language: Syntax and discourse, Oxford University Press on Demand, 1998) with Type 2 producing more attraction errors (Bock et al., Cognitive Psychology 43:83–128, 2001; Becker, L., & Dąbrowska, E. (2020). Does experience with written language influence grammaticality intuitions? UK Cognitive Linguistics Conference: University of Birmingham [conference presentation].). Data were analysed with linear mixed effects models and generalised additive models. Results show lower literacy participants took longer to process sentential cues and made more attraction errors. These findings support usage-based research showing frequency and experience effects on online comprehension of canonical and non-canonical constructions (Farmer, T. A., Misyak, J. B., & Christiansen, M. H. (2012). Individual differences in sentence processing. In Cambridge handbook of psycholinguistics (pp. 353-364)., Street, Language Sciences 59:192–203, 2017), detection and production of agreement attraction errors (Becker, L., & Dąbrowska, E. (2020). Does experience with written language influence grammaticality intuitions? UK Cognitive Linguistics Conference: University of Birmingham [conference presentation].) and demonstrate how linguistic and attentional processes interact (Tomlin and Myachykov, Attention and salience, Handbook of Cognitive Linguistics, 2015). They also complement corpus-based studies by providing evidence that native speakers are sensitive to observed distributions (Miller et al., Spontaneous spoken language: Syntax and discourse, Oxford University Press on Demand, 1998).

Teacher Feedback Across Thesis Writing Stages: The What and How

This paper explores the significance and impact of teacher feedback in the thesis writing process for master’s students at Tribhuvan University in Nepal, particularly in the fields of English Language Teaching (ELT) and Applied Linguistics. The main objective of the study is to understand how feedback supports students across key stages of thesis writing, including topic selection, research design, drafting, and revisions. The research adopts a qualitative descriptive design, using in-depth interviews with recent graduates to gather detailed insights into their experiences with teacher feedback. The method focuses on exploring how feedback influences the development of research questions, the refinement of methodology, and the improvement of writing clarity and coherence. The study revealed that teacher feedback plays a significant developmental role, not only helping students refine their research and writing but also fostering critical thinking, self-assessment, and academic independence. Moreover, the paper claims that effective feedback significantly enhances the overall quality of theses, ensuring that they are well-structured, methodologically sound, and academically rigorous which prepares students for future academic and professional success.

Teaming in Translation: training interpreting, medical, and midwifery students in simulated birth settings

This paper reports on the TeamTra – Teaming in Translation project, conceived in response to calls for improved training of both professional interpreters and healthcare providers. TeamTra is a cooperation among the Medical Faculty, the University Hospital, the Institute for Applied Linguistics and Translation Studies (IALT), and the Oriental Institute (OIL) at Leipzig University. The program is aimed at medical, midwifery, and interpreting students and draws upon interprofessional and simulation education models to provide students with a hands-on experience for different professions using simulated patient-physician/midwife encounters in maternal health. Special attention is devoted to cultural differences, varying degrees of health literacy and challenges of triadic communication. The course was carried out for approximately 80 students in the 2022/2023 winter semester and in the 2023 summer semester. This paper reports on the first year of the project, which included a pre-kick-off survey, a satisfaction survey, and feedback sessions.

Examining teacher-written conference abstracts: Rhetorical functions and syntactic complexity features

This study explored the characteristics of accepted conference abstracts (CAs) written by language teachers for a large-scale national conference on English Language Teaching (Best Practices in Language Education Conference; BEST) compared to those produced by researchers or teacher-researchers for the teaching-oriented strands of a large-scale international conference on Applied Linguistics (American Association of Applied Linguistics Conference; AAAL). The comparative analysis focused on three rhetorical features of the abstracts (move-step realization, embeddedness, and sequence) and move-specific syntactic complexity features. Adopting the CA move/step framework of Yoon and Casal (2020a), we examined rhetorical functions and syntactic features in 60 abstracts from each conference: all BEST abstracts and the abstracts accepted to the two pedagogy-oriented strands of the AAAL conference. Our findings generally indicate prominent differences between BEST and AAAL writers in their use of moves, steps, and embedded steps. They also show differences between the two groups in terms of the use of some syntactic measures, such as the length of sentences and the use of complex nominals. These findings contribute to a better understanding of the characteristics of the CA genre and provide insight into language teachers’ research literacy with a focus on CA writing, which may be useful for the development of evidence-based CA writing guidelines for teachers.

Coherence Relations and Niche Establishment in Applied Linguistics PhD Thesis Introductions

This study explores how PhD students of applied linguistics relate sentences to be coherent in the process of realizing a communicative move of the PhD thesis introduction genre called Move 2 or “establishing a niche” (Swales, 1990). The analyzed data includes 300 excerpts extracted from 300 thesis introductions, each consisting of sentences used by the thesis writer to establish their research niche. The “Create A Research Space” model (Swales, 1990) was used to identify sentences used to establish a niche, and rhetorical structure theory (Mann & Thompson, 1988) was used to analyze how these sentences are related to each other in this process. The study sought to identify the types of coherence relations utilized to realize Move 2 and the frequency with which they occur. The findings revealed that the use of coherence relations varied across the different rhetorical steps. In Step 1B (Indicating a gap), Elaboration was the most common, followed by Contrast and Concession. For Step 1C (Question-raising), Elaboration was again the most common, followed by the List relation. In Step 1D (Continuing a tradition), Contrast, Elaboration and Motivation were frequently used. These findings may have implications for teaching academic writing to PhD students and for the ways novice researchers use to situate their work within the existing literature.

Assessing the Grammatical Rules Proficiency among Polytechnic and Colleges of Education Students in Anambra State Using Evidence Centered Design Assessment

Language assessment is a broad concern in Applied Linguistics because it focuses on the measurement and judgment of learners’ proficiency, and the efficiency of the learning practice used by the learners as well as the teaching method employed by language teachers. This research paper adopted Evidence Centered Design (ECD) as its theoretical framework to form the bedrock of this study. The ECD methodology is an assessment approach or design which underscores the central sole of evidentiary reasoning in assessment. ECD assessment deisgn is used in this study to explore the efficiency of Evidence Centered Design in the assessment of English language proficiency level of the Igbo speakers of 200 undergraduates from three polytechnics and one college of education in Anambra State, Nigeria. The study adopted qualitative and quantitative research design, primary and secondary source of data to help the researcher make predictions and judge the communicative competence of these learners by using diagnostic model of test to determine their interactive knowledge in the use of parts of speech. The study used simple percentage which is the statistical analysis acceptable in Language studies, to analyze the data collected from the questionnaire and the test. The findings from this study proved the validity of ECD assessment in determining language proficiency.

APPLIED LINGUISTICS WITH DEEP LEARNING-BASED DATA-DRIVEN TEXT-TO-SPEECH SYNTHESIZER FOR ARABIC CORPUS

The field of Applied Linguistics, which deals with language and its practical uses, connects with technology in interesting methods, especially in the advancement of text-to-speech (TTS) synthesizers. TTS synthesizers change written text into spoken words, deploying ethics from phonology, phonetics, and syntax to create natural-sounding speech. Within linguistics use, these methods are invaluable purposes such as increasing communication in fractal human–computer interactions (HCIs), language-learning tools, and providing accessibility solutions for visually impaired individuals. TTS purposes at synthesizing understandable and natural speech from text, and it has advanced quickly in recent times because of the progress of artificial intelligence (AI). During past years, deep learning (DL)-based TTS techniques have been established quickly, enabling the generation of natural speech with a high-quality narrator that matches human levels. Creating TTS methods at the quality of the human level has always been the aspiration of speech synthesis practitioners. Although current TTS techniques achieve impressive voice quality, there remains an evident gap in quality compared to human recordings. In this paper, we present an Applied Linguistics with Deep Learning-based Data-Driven Text-to-Speech Synthesizer (ALDL-DDTTS) technique for Arabic corpus. The ALDL-DDTTS technique mainly aims to detect the text and convert it into speech signals on Arabic corpora. In the ALDL-DDTTS technique, a multi-head attention bi-directional long short-term memory (MHA-BiLSTM) approach can be employed with fractal optimization methods to predict the diacritic and gemination signs. Additionally, the Buckwalter code has been deployed for capturing, storing, and displaying the Arabic texts. To boost the efficiency of the ALDL-DDTTS technique, the hyperparameter selection process uses the fractal ant lion optimization (ALO) algorithm. For examining the boost performance of the ALDL-DDTTS methodology, a wide range of simulations is involved. The experimental outcomes illustrated that the ALDL-DDTTS technique reaches better performance than other models.

Foundations and Frameworks of ELT and Applied Linguistics Research: Principles, Processes and Practices

This article offers a comprehensive analysis of the core principles, processes, and practices that characterize research in English Language Teaching (ELT) and Applied Linguistics. The article highlights the key distinctions between scholarship, aimed at personal knowledge acquisition, and research, which generates socially useful knowledge. Research in applied linguistics is problem-oriented, focused on addressing practical language-related challenges such as language acquisition, teaching methodologies, and multilingual communication. The paper emphasizes the interdisciplinary nature of applied linguistics, integrating insights from fields like psychology, sociology, and computer science to provide comprehensive solutions. Methodological diversity is a hallmark of this research, encompassing both qualitative and quantitative approaches, including case studies, surveys, and experimental studies. The research cycle, from identifying a problem to collecting and analyzing data, is systematically outlined. Key areas of ELT research-such as second language acquisition, curriculum development, and language assessment-are discussed, underscoring the field's contributions to both theory and practice. The article concludes by emphasizing the importance of applying research findings to improve language education, develop policies, and enhance communication across diverse linguistic contexts Int. J. Soc. Sc. Manage. Vol. 11, Issue-4: 126-135.

ENHANCING NATURAL LANGUAGE PROCESSING USING WALRUS OPTIMIZER WITH SELF-ATTENTION DEEP LEARNING MODEL IN APPLIED LINGUISTICS

Sentiment analysis (SA) is the popular natural language processing (NLP) problem utilized for analyzing texts, including uploaded reviews and user posts on e-commerce portals, forums, and social media platforms, regarding their opinions about the event or person, product, and service. The SA task comprises analyzing text to determine whether the sentiment expressed is negative, positive, or neutral, aiming for precise subjective data analysis. The deep learning (DL) technique enables various architectures to model SA tasks and has surpassed other machine learning (ML) techniques as the first method to perform SA tasks. Recent advancements in the DL model depart from the growing dominance of transformer language algorithms and convolutional neural network (CNN) and recurrent neural network (RNN) models. Utilizing pre-trained transformer language models to transfer knowledge to downstream tasks has emerged as a cutting-edge model in NLP. Therefore, the study designs a fractal walrus optimizer with self-attention DL-based SA in applied linguistics (WOSADL-SAAL) method. The WOSADL-SAAL method aims to recognize and classify the presence of sentiments in social media content. In the WOSADL-SAAL technique, data preprocessing is initially performed to transform the input dataset into a meaningful format. In addition, the WOSADL-SAAL technique uses the bag of words (BoW) model for extracting features. The self-attention bidirectional long short-term memory (SA-BiLSTM) network is applied to classify sentiment. The walrus optimizer (WO) model performs the hyperparameter tuning model to boost the detection outcomes of the SA-BiLSTM network. The performance evaluation of the WOSADL-SAAL method takes place under the benchmark SA dataset. The experimental analysis of the WOSADL-SAAL method exhibited a superior accuracy value of 99.07% and 99.24% under TUSA and IMDB datasets over existing approaches.

The Effect of Using Error Analysis as a Remedial Teaching Strategy on English Major Students’ Productive Skills

The objective of this study was to examine the impact of employing Error Analysis as a remedial teaching method on the productive skills of English Major Students. The study included thirty-six students enrolled in the Department of English Language and Literature at Al-Isra University during the first semester of the academic year 2022/2023. The study participants were initially divided into two sections: section A, comprising thirty students who registered for the Syntax Course, which was assigned as the experimental group. The material was taught using Error Analysis as a remedial teaching method. Section B comprised sixteen students who enrolled in the Applied Linguistics Course. The control group was chosen and instructed using conventional teaching methods. A pre/post-test was administered to evaluate the impact of utilizing error analysis as a remedial teaching method on enhancing the productive skills of English as a Foreign Language (EFL) students. Both groups of students took a pre-test to determine their equivalence prior to commencing the experiment. Following a duration of eight weeks, the identical test was administered to both groups as a post-test in order to evaluate their progress in the Productive skills. The statistical analysis employed included measures, standard deviation, T-test, One-way ANOVA, and Scheffe. The study's findings demonstrated that implementing Error Analysis as a method of Remedial Teaching had a notable impact on enhancing students' Productive skills. The findings also demonstrated a clear advantage for the experimental group. This could be attributed to the impact of employing Error Analysis as a method of Remedial Teaching. Consequently, a set of recommendations was given at the conclusion of the study to promote the use of Error Analysis as a strategy for Remedial Teaching in order to enhance the development of productive skills in English Major students.

Konfiks Derivasi Per-/-an dalam Debat Capres-Cawapres Tahun 2024: Metode Linguistik Korpus

This research aimed to discuss the “per-/-an” confix which has undergone derivation in Indonesian. This research used the presidential and vice presidential candidate debate script number 01 as the research object studied. This research used a qualitative corpus linguistics approach. The corpus linguistic approach used in this research utilized the KORTARA (Korpus Nusantara) corpus linguistic application. The KORTARA corpus linguistic application (Korpus Nusantara) is an application that can help to collect, process and analyze linguistic data digitally. Data collection in this research utilized the affix word search feature to find specific data containing affixes. The affix word search feature was lasted by accessing the corpus menu in the KORTARA (Korpus Nusantara) application, then selecting the 2024 presidential-cawapres debate script as the object for research. Based on the research that has been carried out, 56 data were obtained on the use of the derivation confix per-/-an in the corpus of the 01 Presidential-Cawapres debate texts in 2024. The results of this research can have implications in the scientific field of morphology related to the principles of derivational development in Indonesian.

Multilingualism rather than English-only: policy and practice in classical music higher education

ABSTRACT The rise of English-medium education in (European) higher education has attracted considerable attention, but most analyses of the topic to date have been conducted in traditional universities. Highly international fields such as that of classical music higher education (CMHE) remain under-researched. Dafouz, E., and U. Smit. 2016. “Towards a Dynamic Conceptual Framework for English Medium Education in Multilingual University Settings.” Applied Linguistics 37 (3): 397–415 and Dafouz, E., and U. Smit. 2020. ROAD-MAPPING English Medium Education in the Internationalised University. Palgrave Macmillan. The ROAD-MAPPING framework provides an analytical tool for examining such complex contexts and unpacking the various factors at play in these multilingual university settings. In this paper, we present a mixed-methods case study at one of Austria’s largest state-funded music universities, comprising a policy analysis, a survey and semi-structured interviews with students, teachers and management. Using the ROAD-MAPPING framework to guide our analysis, we found that university policy and reported practice were coherent among all groups, with German as the default medium of education. English is explicitly designated the second academic language, while multilingualism and multimodality are actively promoted as a means of achieving educational and professional goals. However, we also noted that many strategies for coping with these multilingual teaching and learning contexts seem to be rather ad hoc, suggesting that there is a need for more awareness of multilingual pedagogy, and confirming the value of the ROAD-MAPPING framework for examining such complex settings.

Implementation of an ePortfolio to promote professional pathways: A case study of international students in Australian higher education

Given the current status of ‘English as a global language’, master’s and postgraduate programs in Applied Linguistics and TESOL are becoming an increasingly popular choice for international students in Australia and elsewhere. However, international students enrolled in such programs often lack practical experience and a potential employment pathway. In this respect, an ePortfolio as an assessment tool has been found to assist students to become independent thinkers as they develop self-regulated, purpose-driven behaviours during construction of their ePortfolio. However, building an ePortfolio is a new concept for many of the international students in Australian higher education. The aim of this case study research was thus to identify the support international students require in completion of their ePortfolios. Research data in this mixed method study was collected through two survey questionnaires applied to international students within a course requiring an ePortfolio as a major assessment item. Results indicate the need for more focused training for these students not only in how to structure their ePortfolios, but also more broadly in the employability skills needed in the Australian workplace. This research will help to improve the design of similar courses, and consequently to improve the learning experience for future international students undertaking such courses.

Incorporating replication in higher education: Supervisors’ perspectives and institutional pressures

ABSTRACT Background: Even though replication research has gained traction within academia over the recent years, it is not often well-received as a stand-alone thesis topic by supervisors and university administrators. Methods: In this qualitative investigation, we delve into the perspectives of academic supervisors on the feasibility of replication as a thesis topic within the field of applied linguistics (AL). Drawing on Institutional Theory, administrative pressures facing supervisors on what to be considered permissible for a thesis were also explored. By conducting semi-structured e-mail interviews with a global cohort of AL supervisors and a thematic analysis of their responses, a nuanced landscape was brought to light. Results: Supervisors outlined numerous benefits associated with replication including fostering academic advancement as well as providing opportunities for reevaluating prior research. Nonetheless, they also pointed to several obstacles along the way, such as concerns over originality, constraints on time and resources, and the necessity for mentorship. Moreover, supervisors emphasized their pivotal role as decision-makers in accepting or rejecting replication for a thesis project, while acknowledging the partial influence of institutional pressures. Conclusions: Lastly, some implications and recommendations on allocating more resources to replication research are provided.