Journal of Linguistics, Literature, and Language Teaching (JLLLT)

Demographic Factors Influencing Learner Autonomy among Indonesian EFL Students: A Quantitative Study

2025-06-10T06:44:04+07:00

This study explores how selected demographic factors, gender, language proficiency level, region of origin, faculty affiliation, and field of study relate to learner autonomy among English as a Foreign Language (EFL) students at Universitas Pamulang. Grounded in the constructivist view of learning and self-regulated learning theory, the research employed a quantitative survey using Biçer's (2017) Learner Autonomy Scale, with 80 students participating. Due to non-normal data distribution, non-parametric tests were used in the analysis. This study uniquely shows that only gender has a statistically significant effect on learner autonomy, with female students demonstrating higher autonomy in both planning and learning process dimensions. In contrast, no significant differences were found for the other demographic variables. These findings suggest that while some background characteristics like gender may influence learner autonomy, broader factors such as classroom practices, instructional design, and learner agency play a more central role. The study contributes to the EFL field by highlighting the limited role of static demographic factors and reaffirming the importance of pedagogical strategies that foster autonomy in diverse learner populations.

Semantic Urgency and Illusion of Authority in Phishing Emails: A Corpus-Based Analysis

2025-07-04T08:20:18+07:00

This study examines how urgency and authority are semantically framed in phishing emails to manipulate recipients’ behavior. Although linguistic features of deception have been widely studied, the semantic framing of phishing remains underexplored within the Frame Semantics framework. Using qualitative frame-semantic discourse analysis, ten phishing emails were purposively selected from the open-access corpus by Miltchev et al. (2024), focusing on scams related to account access and payment issues. The data were analyzed through Fillmore’s Frame Semantics to identify lexical units and frame elements (e.g., Agent, Goal, Instrument) that trigger urgency and authority. Results show that phishing messages use time-sensitive cues (e.g., immediately, within 24 hours) and institutional references (e.g., your account, verify your identity) to create a sense of crisis and compel compliance. These frames often co-occur, increasing cognitive pressure and reducing critical evaluation. By mapping manipulative strategies onto semantic frames such as Request, Threat scenario, and Commerce transfer, this study provides a structured approach to phishing analysis. It contributes to cyber linguistics and supports the development of frame-aware digital literacy, email security systems, and spam detection models based on semantic cues.

Grammatical and Lexical Errors in the Written English of Teacher Trainees: A Case Study of E.P. College of Education, Amedzofe

2025-06-16T16:18:03+07:00

This qualitative case study investigates the grammatical and lexical errors in the writing of fifty final-year students at the E.P. College of Education, Amedzofe. Drawing on Corder's Error Analysis framework, student essays were analyzed to identify error types, frequencies, and their potential causes. Data were collected by simple random sampling from scripts anonymized and supplemented with self-reports on reading habits and mother tongue usage. The most frequent errors involved vocabulary misuse, tense, and structural flaws. These findings highlight the implications for English instruction and teacher training curricula. We recommend enhanced writing practice, improved entry standards, and promotion of reading and spoken English to improve students' written proficiency. The study contributes to the field of second language acquisition and offers pedagogical implications that can improve English language teaching in the Colleges of Education.

The Interference of Banjarese Dialect on English Pronunciation

2025-10-07T07:56:23+07:00

This study investigates the influence of the Banjarese dialect on the English vowel pronunciation of two Banjarese speakers. The research is grounded in the understanding that English and Banjarese differ substantially in their vowel inventories and rhythmic structures, which may lead to systematic phonological transfer. Using a qualitative case study approach combining Praat-based acoustic phonetic analysis and narrative inquiry, this study recorded two male Banjarese speakers aged 20 pronouncing selected English words containing problematic vowels (/æ/, /?/, /?/, /u?/, /??/). The recordings were analyzed to identify deviations in vowel quality and centralization, while semi-structured interviews explored speakers' awareness of and challenges with these qualities. The findings revealed consistent substitution patterns such as /æ/?/e/, /?/?/e/ or /i/, and /?/?/i/, accompanied by fronting and the absence of vowel reduction in unstressed syllables. These patterns reflect the influence of the Banjarese vowel system, which lacks central vowels, tense-lax contrasts, and vowel length distinction. Acoustic evidence confirmed the persistence of full vowel quality, indicating syllable-timed rhythm interference. The study supports Flege's Speech Learning Model and Best and Tyler's Perceptual Assimilation Model by demonstrating dialect-specific phonemic transfer. Pedagogically, the results suggest that explicit instruction on vowel reduction, centralization, and rhythm awareness may help mitigate Banjarese interference in English pronunciation.

A Systematic Literature Review on the Application of Artificial Intelligence in Translation: Challenges, Innovations, and Impact Across Diverse Fields

2025-09-13T15:44:16+07:00

With the ongoing expansion of digital technology and global communication, the need for rapid and accurate language translation has become increasingly important. Artificial intelligence has led to significant progress in translation, especially through innovations such as Neural Machine Translation (NMT) and Large Language Models (LLMs). Despite ongoing advancements, these translation systems often fall short in areas such as gender fairness, maintaining accuracy from the source language, and recognizing cultural subtleties. This paper systematically analyzes 29 selected research works to highlight the challenges, novel contributions, and potential implications of AI-assisted translation. The approach used was a systematic review. Results show that Artificial intelligence has improved translation efficiency and identified new opportunities in global trade, research, healthcare, and cross-cultural communication. Yet it needs to tackle several issues, such as algorithmic bias, challenges and nuances in cultural retention, and ethical challenges in the human translation industry. The results of this analysis underscore the need for more comprehensive, precise, and ethical AI models, as well as the importance of AI-human collaboration to achieve the highest-quality translations. This study helps to understand the development of AI-based translation and develop methods for its long-term usage.