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This study aims to investigate the potential effect of project-based learning (PBL) in alleviating the negative psychological factors that hinder language learning in an intensive-English course at a private Lebanese university through its meaningful, student-centered, collaborative, and creative pedagogical approach and supporting students in constructing a positive self-identity as an English language learner and user.

The L2 Motivation Self System theory describes the roles of the Ideal L2 Self, the Ought to L2 Self, and the L2 Learning Experience as the three dimensions that trigger L2 motivation, which is an important factor in achieving L2 learning outcomes. This pre- and post-test questionnaire study aims to investigate the impact of designing and implementing project-based learning as a creative pedagogical method on the L2 Learning Experience of tertiary EFL students undertaking an intensive English language course.

The paper found that such a pedagogical approach decreased students’ foreign language anxiety and positively impacted their attitudes toward L2 learning as they actively engaged in their projects in a meaningful, connected, and creative manner. This paper concludes that the adopted innovative pedagogical approach created an L2 language learning experience for EFL students to move closer from their actual self to their potential or imagined Ideal L2 Self as they embraced their creative self, social self, and risk-taking self within the frame of identity negotiation and construction. Findings from this study map to the wider literature on L2 language acquisition and foreign language learning.

This study has theoretical and practical implications. Theoretically, this research contributed to the existing body of literature on L2 education from a nuanced lens that maps students’ motivation, engagement, characteristics, and psychology to their identity as L2 learners to make their learning journeys more rewarding, productive, and connected.

Practically, this study showcases how the implementation of the PBL approach in a creative and aligned manner can positively impact students’ attitudes toward English teaching and learning, making novel reading a more engaging task that prompts students’ creativity, critical thinking, and risk-taking while facilitating the negotiation and construction of their identity as L2 learners and users. Additionally, the implementation of such creative pedagogical approaches prompts on an educational policy level the shift from the traditional ways of English teaching and learning to a more student-centered, engaging and connected state, creating a set of exemplars for EFL and ESL instructors to use to ensure that L2 learners connect to their own experiences and develop a range of transferrable skills while acquiring language capabilities.

This paper concludes that the adopted innovative pedagogical approach served as a channel for EFL students to move closer from their actual self to their potential or imagined Ideal L2 Self as they embraced their creative self, social self, and risk-taking self within the frame of identity negotiation and construction. Findings from this study map to the wider literature on L2 language acquisition and foreign language learning.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

In order to analyze the text complexity of Chinese and foreign academic English writings, the artificial neural network (ANN) under deep learning (DL) is applied to the study of text complexity. Firstly, the research status and existing problems of text complexity are introduced based on DL. Secondly, based on Back Propagation Neural Network (BPNN) algorithm, analyzation is made on the text complexity of Chinese and foreign academic English writings. And the research establishes a BPNN syntactic complexity evaluation system. Thirdly, MATLAB2013b is used for simulation analysis of the model. The proposed model algorithm BPANN is compared with other classical algorithms, and the weight value of each index and the model training effect are further analyzed by statistical methods. Finally, L2 Syntactic Complexity Analyzer (L2SCA) is used to calculate the syntactic complexity of the two libraries, and Mann–Whitney U test is used to compare the syntactic complexity of Chinese English learners and native English speakers. The experimental results show that compared with the shallow neural network, the deep neural network algorithm has more hidden layers and richer features, and better performance of feature extraction. BPNN algorithm shows excellent performance in the training process, and the actual output value is very close to the expected value. Meantime, the error of sample test is analyzed, and it is found that the evaluation error of BPNN algorithm is less than 1.8%, of high accuracy. However, there are significant differences in grammatical complexity among students with different English writing proficiency. Some measurement methods cannot effectively reflect the types and characteristics of written language, or may have a negative relationship with writing quality. In addition, the research also finds that the measurement of syntactic complexity is more sensitive to the language ability of writing. Therefore, BPNN algorithm can effectively analyze the text complexity of academic English writing. The results of the research provide reference for improving the evaluation system of text complexity of academic paper writing.

The use of three-dimensional virtual worlds (3DVWs) is increasingly becoming a common practice in language education to provide digital learning environments for second-language (L2) communicative classes. This study aimed to identify the key factors underlying communication in 3DVWs that can improve the communication skills of L2 learners.

To achieve this, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were conducted to validate the identified factors affecting communication in 3DVWs. A self-reported questionnaire with 47 items on a five-point Likert scale was administered to 513 pre-service teachers, teachers and lecturers in the field of language education.

The results of the EFA revealed four factors that contribute to communication in 3DVWs, namely learner motivation, interaction pattern, language development and learner autonomy. CFA results provided support for the updated model, with statistically significant Chi-square results (χ² (df = 83) = 181.049, p < 0.001) indicating a good fit between the model and the data.

The findings suggest that the four EFA-derived parameters are valid and can assist instructional designers and L2 instructors in creating 3DVWs that enhance L2 learners' communication abilities. This study provides valuable insights for educators, instructional designers and researchers in the field of language education and technology-enhanced learning.

The study investigated the feedback seeking abilities of learners in L2 writing classrooms using ChatGPT as an automated written corrective feedback (AWCF) provider. Specifically, the research embarked on the exploration of L2 writers’ feedback seeking abilities in interacting with ChatGPT for feedback and their perceptions thereof in the new learning environment.

Three EFL learners of distinct language proficiencies and technological competences were recruited to participate in the mixed method multiple case study. The researcher used observation and in-depth interview to collect the ChatGPT prompts written by the participants and their reflections of feedback seeking in the project.

The study revealed that: (1) students with different academic profiles display varied abilities to utilize the feedback seeking strategies; (2) the significance of feedback seeking agency was agreed upon and (3) the promoting factors for the development of students’ feedback seeking abilities are the proactivity of involvement and the command of metacognitive regulatory skills.

Additionally, a conceptual model of feedback seeking in an AI-mediated learning environment was postulated. The research has its conceptual and practical implications for researchers and educators expecting to incorporate ChatGPT in teaching and learning. The research unveiled the significance and potential of using state-of-the-art technologies in education. However, since we are still in an early phase applying such tools in authentic pedagogical environments, many instructional redevelopment and rearrangement should be considered and implemented.

The work is a pioneering effort to explore learners' feedback seeking abilities in a ChatGPT-enhanced learning environment. It pointed out new directions for process-, and student-oriented research in the era of changes.

This research explores the potential incorporation of Indonesian folklore, particularly the folklore of the origin of Bandung, into Arabic language teaching materials. Integrating local cultural elements into language instruction can enhance students' language learning experience and promote a deeper understanding of Indonesian culture.

The origin city of Bandung is one of the famous folklore stories in Indonesia that originates from West Java. Through ethnographic studies, various aspects of the folklore of the origin of the city of Bandung will be examined, which can be utilized in Arabic language teaching. This includes analyzing the linguistic structure, vocabulary and cultural references embedded in the story. Additionally, we will explore how teachers can effectively incorporate this folklore into their teaching materials to create engaging and culturally relevant Arabic language lessons.

This research aims to contribute to developing innovative and culturally responsive language learning by investigating the use of Indonesian folklore in Arabic language instruction. It aims to empower teachers and students by fostering a deeper appreciation of Indonesian culture while improving Arabic language proficiency. This approach enhances language learning outcomes, promotes cultural awareness and cultivates a deeper connection between students and the local culture. By embracing folklore, teachers can create dynamic and meaningful language learning experiences that empower students to become proficient Arabic speakers with a strong appreciation for Indonesian wisdom and culture.

Overall, using folklore as a foreign language teaching material provides significant advantages for students in developing a deeper understanding of language, cultural skills and interest in the language and culture being studied. This approach improves language learning outcomes, promotes cultural awareness and fosters deeper relationships between students and local culture so that foreign language (Arabic) learning is effective. By embracing folklore, teachers can create dynamic and meaningful language learning experiences that empower students to become proficient Arabic speakers with a strong appreciation for local Indonesian wisdom and culture.

Practically, this involves understanding the social, political, economic or cultural context in which the folklore arose, as well as new interpretations that provide a broader understanding of the stories' values, messages or conflicts. In contributing to knowledge, this research has implications for insight into linguistic knowledge and learning a second language in the norms of the first language without shifting the culture of the first language.

Empirically, this study combines an interdisciplinary approach to folklore research that can bring a new understanding of the relationship between folklore and other fields such as linguistics, literature, anthropology or psychology. This approach can produce a more comprehensive insight into folklore and its influence on various aspects of life. Contributing to social impact, introducing culture in learning materials is an educational tourism attraction for students. This also has an impact on public policy that tourism education about folklore is introduced as teaching and used as further field study for students.

This research conceptualizes the diversity of Indonesian culture integrated into the instructional materials of Arabic language learning in Indonesia through folklore. To integrate folktales into the learning process, families, traditions and rituals need to play a role in preserving and educating. Researchers can develop new insights, broaden our understanding of culture and traditions and enrich our knowledge and cultural heritage. These new approaches have the potential to yield discoveries and a deeper understanding of folklore as an important cultural heritage. This research explores the potential incorporation of Indonesian folklore, particularly the folklore of the origin of Bandung, into Arabic language teaching materials. Integrating local cultural elements into Arabic language teaching for Indonesian speakers can enhance students' language learning experience and promote a deeper understanding of Indonesian culture through Arabic language teaching as a foreign language.

This study uses a mixed methods approach to investigate the pedagogical approaches and teaching practices that the English Department at a private Lebanese university implemented to rectify the deteriorating speaking skills of their students during the first few months of the lockdown in Lebanon between March and June 2020. The data consisted of semi-structured interviews with English instructors, the speaking assessment scores, and the English peer support program (PSP) enrollment records. Qualitative analysis of the interviews identified the main challenges that the English instructors faced during their transition from face-to-face (FTF) to distance education. The analysis also identified the intervention strategies that were implemented to overcome these barriers to learning and adapt to and even benefit from computer-mediated communication (CMC) instruction and other technological resources to develop and improve the oral proficiency and fluency of tertiary English as a Foreign Language (EFL) students. The quantitative analysis referred to the average percentage variation of the pre-test and post-test scores of the speaking assessment to track the improvement (or lack thereof) of the students’ speaking skills across four semesters, prior to and after the intervention. A one-way ANOVA test was also conducted for the enrollment records of the English PSP and speaking assessment scores that showed that the program was an effective form of intervention that helped struggling students to at least prevent the further deterioration of their speaking capabilities in English. These findings show that for students to develop and enhance their speaking skills in English in a distance education context and during emergency times, efforts need to be made to reduce the hindering psychological factors and address all technology-related barriers that disrupt the online language learning environment and process.

Metacognitive strategies are learning strategies that involve planning, self-monitoring, and self-evaluation. Metacognition is characterised as a build that alludes to considering one’s reasoning or the human capacity to be aware of one’s mental processes. According to Flavell (1976) metacognitive learning is ‘one’s learning concerning one’s own particular intellectual procedures and items or anything identified with them, e.g., the learning-applicable properties of data or information’. The purpose of the study is to investigate to what extent the university English as a Foreign Language (EFL) learners employ metacognitive reading strategies in reading comprehension. Further, it aims to research the most used strategy of MARSI inventory subscale: reading performance in reading EFL. Statistical analysis has been calculated by using ANOVA, correlation, and metacognitive awareness reading strategy inventory (MARSI), which in fact is the self-report instrument. The study has identified that EFL students of Kosovo universities possess considerable amount of awareness over metacognitive strategies in reading comprehension.

High-stakes decision-makers, including human resource (HR) professionals, often exhibit accent biases against second language speakers in professional evaluations. We extend this work by investigating how HR students evaluate simulated job interview performances in English by first and second language speakers of English.

Eighty HR students from Calgary and Montreal evaluated the employability of first language (L1) Arabic, English, and Tagalog candidates applying for two positions (nurse, teacher) at four points in the interview (after reading the applicant’s resume, hearing their self-introduction, and listening to each of two responses to interview questions). Candidates’ responses additionally varied in the extent to which they meaningfully answered the interview questions.

Students from both cities provided similar evaluations, employability ratings were similar for both advertised positions, and high-quality responses elicited consistently high ratings while evaluations for low-quality responses declined over time. All speakers were evaluated similarly based on their resumes and self-introductions, regardless of their language background. However, evaluations diverged for interview responses, where L1 Arabic and Tagalog speakers were considered more employable than L1 English speakers. Importantly, students’ preference for L1 Arabic and Tagalog candidates over L1 English candidates was magnified when those candidates provided low-quality interview responses.

Results suggest that even in the absence of dedicated equity, diversity, and inclusion (EDI) training focusing on language and accent bias, HR students may be aware of second language speakers’ potential disadvantages in the workplace, rewarding them in the current evaluations. Findings also highlight the potential influence of contextual factors on HR students’ decision-making.

This study aims to discover how domain familiarity and language affect the cognitive load and the strategies applied for the evaluation of search engine results pages (SERP).

This study used an experimental research design. The pattern of the experiment was based upon repeated measures design. Each student was given four SERPs varying in two dimensions: language and content. The criteria of students to decide on the three best links within the SERP, the reasoning behind their selection, and their perceived cognitive load of the given task were the repeated measures collected from each participant.

The evaluation criteria changed according to the language and task type. The cognitive load was reported higher when the content was presented in English or when the content was academic. Regarding the search strategies, a majority of students trusted familiar sources or relied on keywords they found in the short description of the links. A qualitative analysis showed that students can be grouped into different types according to the reasons they stated for their choices. Source seeker, keyword seeker and specific information seeker were the most common types observed.

This study has an international scope with regard to data collection. Moreover, the tasks and findings contribute to the literature on information literacy.

The purpose of this study is to theorize that computer-assisted language learning (CALL) can be integrated in English language learning with a focus on cultural learning of both home and target language.

The present study used a systematic methodology to conceive the language and home-culture integrated online learning (LHIOL) curriculum design based on relevant conceptual frameworks and gather qualitative data from focused group interviews of 30 teachers and 3,000 students’ open-ended questionnaires, along with learning artifacts to identify major themes.

CALL, used as cultural and linguistic material, helps students embrace their cultural identities, especially ethnic minorities, capitalize on their distinctive values, and appreciate and empathize with other languages and cultures. The instructors advocate for localizing intercultural communicative competence (ICC) educational content into Vietnamese culture, using real multimedia resources. However, the LHIOL curriculum faced systemic constraints regarding competitions between linguistic and cultural instruction, teachers’ refusal to recognize ICC’s importance and recognition of an explicit link between virtual cultural learning and their lives.

LHIOL is a preliminary practical effort to suggest how a cultural education from one’s native tongue can be integrated into a culture-focused English/Western language environment. By incorporating fundamental concepts that underpin the integration of language and culture as well as CALL, improving ICC offers a framework that can be applied to elucidate cultural learning.