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The objective of this study is to investigate the key determinants affecting the acceptance and utilization of Blackboard as a Computer-Assisted Language Learning (CALL) platform among Saudi university students pursuing English as a foreign language (EFL) courses.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

The study's findings indicate that performance expectancy, social influence, effort expectancy and price value significantly affect the attitudes of EFL students toward using CALL. The habit factor was the most robust predictor of behavioral intention and technology use, indicating that CALL usage can become automatic for students and improve their engagement in EFL learning. The study highlights the importance of providing better technical and organizational support to EFL students who want to use CALL more effectively. The theoretical and practical implications of the study's findings are thoroughly discussed.

Understanding how to engage EFL students in their learning requires identifying the factors that influence their acceptance and use of CALL tools, particularly on Blackboard's LMS platform. This study proposes and validates a research framework that predicts students' behavioral intentions and usage of CALL by utilizing the UTAUT2 by Venkatesh et al. (2012). This research model provides insight into the various drivers that impact CALL acceptance via Blackboard LMS. The study's findings demonstrate UTAUT2's superior ability to address the fear of technology adoption and provide valuable insights into the factors that influence technology intention and usage.

Web-based language learning (WBLL) materials have long been favored by English language instructors because they are plentiful, easily accessible, user-friendly and, most importantly, free. This research looks into the effects of learning the simple perfect tense translation in three different English translation classes that used three different teaching methods: traditional face-to-face, integrative and web-based learning. It also aims to investigate the impact of gender on every mode of instruction and to identify the most effective method for learning translation.

The study is quantitative, with a pretest/posttest quasi-experimental research design. A total of 93 third-year undergraduate students (51 female and 42 male students) participated in the pretest/posttest design. Each group was exposed to one mode of instruction for nine weeks. All groups sat for a pretest in the first week of the treatment. After the treatment, the participants were provided with a posttest, and the data obtained were analyzed using the SPSS computer software program.

The findings revealed a significant difference in both tests for all modes used. All three groups improved in their gain score, but the highest gain among these groups was the integrative method, followed by web-based learning. The result of the independent sample t-tests and ANOVA exhibited that there was no significant difference in the level of students between the two groups, both were sig. two-tailed (p = 0.342). Furthermore, it was discovered that gender did not affect students' performance in the posttest (Z = −1.564, p > 0.05) when each mode of instruction was applied. Finally, the integrative method was observed to be the most effective.

The findings can inspire translation course designers to plan necessary policies or syllabi regarding English translation courses and may serve as a platform for improving the curriculum for training and motivating the next generation of English as a Foreign Language (EFL) learners.

The findings of this study could be used to improve English instruction in countries where English is a second or foreign language. The actual gap in knowledge is that no other studies have compared all three groups in the past few years.

This study aims to investigate the integration of heritage language and culture in technology-enhanced bilingual education and examine the dominance of the English language and culture in computer-assisted language learning settings.

This research used a narrative inquiry methodology. The data came from semi-structured interviews with 25 bilingual teachers in the Kurdistan region of Iraq and Texas.

The study found a significant bias in the use of technology toward the target language, often at the expense of heritage language and culture. The curricula analyzed were predominantly focused on superficial cultural elements of the target language, leading to a neglect of deeper cultural engagement.

This research highlights the phenomenon of cultural cringe within bilingual education and the skewed use of technology toward the target language.

The purpose of this study is to examine the impact of computer-assisted language learning on cultural adaptation and language learning in non-traditional classroom settings.

The data of this study came from extended periods of observation, multiple rounds of semi-structured interviews and home visits. Using narrative inquiry, it analyzes an immigrant's journey of language learning and cultural adaptation within a virtual knowledge community.

The findings of this study reveal the profound impact of virtual knowledge communities on enhancing second language learning and facilitating cultural adaptation.

This study offers original insights by demonstrating the transformative power of virtual knowledge communities for the purpose of second language acquisition and cultural adaptation.

This research paper aimed to investigate the affordances of using virtual reality (VR) in teaching culture among in-service teachers of teaching Persian to speakers of other languages (TPSOL) in Iran.

This qualitative case study, conducted at two Iranian universities, used purposeful sampling to select 34 eligible in-service Persian teachers from a pool of 73. Data collection used an open-ended questionnaire and interviews.

Before the TPSOL in-service training workshop, teachers expressed their reservations regarding the use of VR to teach culture in TPSOL courses. The emerged themes were “skepticism toward effectiveness,” “practicality concerns,” “limited awareness of VR applications,” “technological apprehension” and “prevalence of traditional teaching paradigms.” During the post-workshop interview, it was discovered that the teachers’ perceptions of VR in teaching culture had undergone a positive shift. The workshop generated emergent themes that reflected positive perceptions and affordances for using VR to teach culture in TPSOL, including “enhanced cultural immersion,” “increased student engagement,” “simulation of authentic cultural experiences,” and “facilitation of interactive learning environments.”

One primary limitation is the lack of prior experience with VR for teaching practices in real-world classrooms among the participants. While the study aimed to explore the potential of VR in enhancing pedagogical approaches, the absence of participants with prior exposure to VR in educational contexts may impact the generalizability of the findings to a broader population. Additionally, the study faced practical constraints, such as the unavailability of sufficient facilities in the workshop. As a result, the instructor had to project the VR cont7ent on a monitor, potentially diverging from the immersive nature of true VR experiences. These limitations offer opportunities for future research to refine methodologies and gain a more comprehensive understanding of the implications of integrating VR into teaching practices.

Extensive research has been conducted on the effectiveness of VR in language education. However, there is a significant gap in research on TPSOL, which is considered a less commonly taught language. This study aims to address this gap by exploring the use of VR in the TPSOL through the lenses of in-service teachers. As part of a larger investigation, this qualitative inquiry focuses on the perceptions of in-service teachers about VR, with a particular emphasis on the cultural understanding of the Persian language.

Computer-assisted language learning (CALL) can create participatory cultures by removing barriers to access materials, encouraging student modes of expression, differentiating student interactions through digital environments and increasing learner autonomy. Participatory cultures require competencies or new media literacy (NML) skills to be successful in a digital world. However, professional development (PD) often lacks training on CALL and its implementation to develop such skills. The purpose of this study is to describe teachers use of digital tools for multilingual learners through a relevant theoretical perspective.

This design-based research study examines 30 in-service teachers in South Carolina, a destination state for Latinx immigrants, focusing data over three semesters of PD: interviews and instructional logs. The researchers address the question: How are teachers using digital tools to advance NML for multilingual learners (MLs)?

The authors analyzed current elementary teachers’ use of digital tools for language learning and NML purposes. Three themes are discussed: NMLs and digital literacy boundaries, digital tools for MLs and literacy teaching for MLs and NML skills.

Teacher PD often needs more specificity regarding the intersection of MLs and digital literacy. The authors contribute to the literature on needed elementary teaching practices for MLs, the integration of NML and how these practices may be addressed through PD.

The proliferation of ChatGPT, as in many other digital technologies and social media, has increasingly impacted many aspects of modern life, including second and foreign language education. This study, building on a common theoretical position of all these advances in Artificial intelligence (AI), seeks to establish a model for ChatGPT research on English language learning. It specifically explores the dimensions in which ChatGPT aids students in their English language learning.

The study adopts grounded theory in collecting and analyzing data from 20 ResearchGater (RG) through a two-week RG discussion about ChatGPT uses in their language learning contexts. Data collected via the discussion was analyzed thematically.

Preliminary findings show that ChatGPT can be used in developing learners' language skills; scaffolding the learning process by providing feedback to students on their language use and acting as partners in practicing language with recommended activities for more language practice.

The study contributes a five-dimension model for artificial intelligence assisted language learning (AIALL). The model involves flexible teacher's role to consolidate learner autonomy and provide enjoyable learning, urges future innovation, and celebrates various applications. Examining the AIALL model of ChatGPT for language learning, teachers should provide some directions for properly using this new application.

The purpose of this study was to gain a deeper understanding of the experiences and challenges of Middle Eastern refugee mothers in using technology for language learning in regional Australian context.

This study used a qualitative research design and used a narrative enquiry technique to understand participants’ experiences of language acquisition with limited access to technology in new resettlement setting.

The findings presented in this paper were derived from a qualitative investigation conducted on a sample of 21 refugee mothers from Middle Eastern countries. The research aimed to explore the role of a language education programme on their integration within the regional Australian context. Participants discussed a variety of aspects of their everyday lives within their new resettlement context while offering insights on the language education programme and its impacts on their educational progress. The theme “lack of access/use of technology in English language learning” emerged from the narratives. This paper draws on selected interview data from the participants.

This study fills the gap in the literature on Middle Eastern refugees in regional Australia by exploring how lack/limited technology access can impact language acquisition of women from under-represented contexts.

The smart contract provides an opportunity to improve existing contract management practices in the construction projects by replacing traditional contracts. However, translating the contracts into computer languages is considered a major challenge which has not been investigated. Thus, it is necessary to: (1) identify the obstructing clauses in real-world contracts; and (2) analyze the replacement's technical and economic feasibility. This paper aims to discuss the aforementioned objectives.

This study identified the flexibility clauses of traditional contracts and their corresponding functions through inductive content analysis with representative standard contracts as materials. Through a speculative analysis in accordance to design science paradigm and new institutional economics, the economic and technical feasibility of existing approaches, including enumeration method, fuzzy algorithm, rough sets theory, machine learning and artificial intelligence, to transform respective clauses (functions) into executable codes are analyzed.

The clauses of semantic flexibility and structural flexibility are identified from the contracts. The transformation of semantic flexibility is economically and/or technically infeasible with existing methods and materials. But with more data as materials and methods of rough sets or machine learning, the transformation can be feasible. The transformation of structural flexibility is technically possible however economically unacceptable.

Given smart contracts' inability to provide the required flexibility for construction projects, smart contracts will be more effective in less relational contracts. For construction contracts, the combination of smart contracts and traditional contracts is recommended. In the long run, with the sharing or trading of data in the industry level and the integration of machine learning or artificial intelligence reducing relevant costs, the automation of contract management can be achieved.

This study contributes to the understanding of the smart contract's limitations in industry scenarios and its role in construction project management.

This research aimed to visualize and analyze the co-word network and thematic clusters of the intellectual structure in the field of linked data during 1900–2021.

This applied research employed a descriptive and analytical method, scientometric indicators, co-word techniques, and social network analysis. VOSviewer, SPSS, Python programming, and UCINet software were used for data analysis and network structure visualization.

The top ranks of the Web of Science (WOS) subject categorization belonged to various fields of computer science. Besides, the USA was the most prolific country. The keyword ontology had the highest frequency of co-occurrence. Ontology and semantic were the most frequent co-word pairs. In terms of the network structure, nine major topic clusters were identified based on co-occurrence, and 29 thematic clusters were identified based on hierarchical clustering. Comparisons between the two clustering techniques indicated that three clusters, namely semantic bioinformatics, knowledge representation, and semantic tools were in common. The most mature and mainstream thematic clusters were natural language processing techniques to boost modeling and visualization, context-aware knowledge discovery, probabilistic latent semantic analysis (PLSA), semantic tools, latent semantic indexing, web ontology language (OWL) syntax, and ontology-based deep learning.

This study adopted various techniques such as co-word analysis, social network analysis network structure visualization, and hierarchical clustering to represent a suitable, visual, methodical, and comprehensive perspective into linked data.