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Given the persistent receptive skills challenges faced by language learners and the numerous merits of using technologically-enhanced learning in the form of mobile-assisted language learning in language teaching, this study decides to incorporate a context-analysis-practice-exploration lesson-planning framework with mobile learning to improve the receptive skills of learners. This step is necessary on the recommendation by scholarly research that while implementing technology, teacher training, digital literacy and expertise, incorporating good teaching practices and lesson planning frameworks may assist in yielding positive results.

This study decides to utilize a mixed-method research design through an experimental approach to elicit information from 90 EFL students concerning the effectiveness of incorporating the context-analysis-practice-exploration framework in a mobile-leaning mode instructional delivery to improve their reading and listening skills.

After collecting and analyzing data, the study found that while the participants perceived enhanced-mobile learning to make lessons enjoyable, integrating this framework and m-learning improved their reading skills. This study used notable findings to make pedagogical conclusions on the objective of this study.

This study contributes through empirical evidence on the effectiveness of incorporating mobile learning and a responsive lesson planning framework towards improving English as a foreign language learners' learning outcome. Besides, this study is the first to probe and unpack the effectiveness of a responsive lesson-planning framework in language education.

The purpose of the paper is to propose and demonstrate a novel approach for addressing the challenges of path planning and obstacle avoidance in the context of mobile robots (MR). The specific objectives and purposes outlined in the paper include: introducing a new methodology that combines Q-learning with dynamic reward to improve the efficiency of path planning and obstacle avoidance. Enhancing the navigation of MR through unfamiliar environments by reducing blind exploration and accelerating the convergence to optimal solutions and demonstrating through simulation results that the proposed method, dynamic reward-enhanced Q-learning (DRQL), outperforms existing approaches in terms of achieving convergence to an optimal action strategy more efficiently, requiring less time and improving path exploration with fewer steps and higher average rewards.

The design adopted in this paper to achieve its purposes involves the following key components: (1) Combination of Q-learning and dynamic reward: the paper’s design integrates Q-learning, a popular reinforcement learning technique, with dynamic reward mechanisms. This combination forms the foundation of the approach. Q-learning is used to learn and update the robot’s action-value function, while dynamic rewards are introduced to guide the robot’s actions effectively. (2) Data accumulation during navigation: when a MR navigates through an unfamiliar environment, it accumulates experience data. This data collection is a crucial part of the design, as it enables the robot to learn from its interactions with the environment. (3) Dynamic reward integration: dynamic reward mechanisms are integrated into the Q-learning process. These mechanisms provide feedback to the robot based on its actions, guiding it to make decisions that lead to better outcomes. Dynamic rewards help reduce blind exploration, which can be time-consuming and inefficient and promote faster convergence to optimal solutions. (4) Simulation-based evaluation: to assess the effectiveness of the proposed approach, the design includes a simulation-based evaluation. This evaluation uses simulated environments and scenarios to test the performance of the DRQL method. (5) Performance metrics: the design incorporates performance metrics to measure the success of the approach. These metrics likely include measures of convergence speed, exploration efficiency, the number of steps taken and the average rewards obtained during the robot’s navigation.

The findings of the paper can be summarized as follows: (1) Efficient path planning and obstacle avoidance: the paper’s proposed approach, DRQL, leads to more efficient path planning and obstacle avoidance for MR. This is achieved through the combination of Q-learning and dynamic reward mechanisms, which guide the robot’s actions effectively. (2) Faster convergence to optimal solutions: DRQL accelerates the convergence of the MR to optimal action strategies. Dynamic rewards help reduce the need for blind exploration, which typically consumes time and this results in a quicker attainment of optimal solutions. (3) Reduced exploration time: the integration of dynamic reward mechanisms significantly reduces the time required for exploration during navigation. This reduction in exploration time contributes to more efficient and quicker path planning. (4) Improved path exploration: the results from the simulations indicate that the DRQL method leads to improved path exploration in unknown environments. The robot takes fewer steps to reach its destination, which is a crucial indicator of efficiency. (5) Higher average rewards: the paper’s findings reveal that MR using DRQL receive higher average rewards during their navigation. This suggests that the proposed approach results in better decision-making and more successful navigation.

The paper’s originality stems from its unique combination of Q-learning and dynamic rewards, its focus on efficiency and speed in MR navigation and its ability to enhance path exploration and average rewards. These original contributions have the potential to advance the field of mobile robotics by addressing critical challenges in path planning and obstacle avoidance.

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.

The integration of digital technologies into education has brought about a profound transformation, fundamentally reshaping the learning landscape. The purpose of this study is to underscore the importance of investigating the factors influencing students’ engagement (SE) in this evolving digital era, particularly within formal digital learning environments. To address this need, the study is grounded in self-determination theory (SDT) and presents a comprehensive model comprising interconnected elements: digital competence (DC), smartphone use (SPU), perceived autonomy (PA), digital formal learning (DFL) and SE.

The research conducted an investigation within Saudi Arabian universities, collecting a robust data set of 392 cases. This data set underwent rigorous analysis to validate the proposed model. To untangle the intricate relationships within the framework, the study used partial least squares structural equation modelling. Given the distinct dimensions of the two constructs under study, the researcher used a disjoint two-stage approach to establish reflective-formative higher-order constructs (HOC).

The findings revealed that digital literacy and digital skills (DS) constitute the foundational constituents of DC. Simultaneously, the study identified facilitation, distraction and connectedness as integral components of SPU. Importantly, the study established that DC, SPU, PA and DFL significantly influence SE. Furthermore, the research illuminated the mediating roles played by SPU, PA and DFL in the complex relationship between DC and SE.

This study advances the literature by delineating the dynamic interplay between DC, SPU and SE in digital learning. It extends SDT within educational contexts, emphasizing the role of internal motivations and DS. Methodologically, it innovates through reflective-formative HOCs, deepening the analysis of complex educational constructs. Managerially, it guides institutions in enhancing DC and integrating smartphones effectively into learning, advocating for tailored strategies to foster engaging and autonomous digital learning environments, thereby enriching both theoretical understanding and practical application in education.

The flipped classroom model is an emerging teaching pedagogy in universities, colleges and secondary schools. This model will likely be successful if students prepare and acquire basic knowledge before class hours. Pre-class video lectures are common for students to access knowledge before class hours. However, students often do not watch the pre-class videos or do so only immediately before class hours due to poor engagement and supporting strategies, which can have detrimental effects on their learning achievement. To address this issue, embedding quiz questions into pre-class recorded videos may increase the completion of pre-class activities, students' engagement and learning success. This study examines the effect of a quiz-based flipped classroom (QFC) model to improve students' learning achievement and engagement in a computer science course.

The study involved 173 participants divided into experimental and control groups. The experimental group consisted of 78 students who used the QFC model, while the control group consisted of 73 students who used the conventional flipped classroom (CFC) model.

The 10-week experiment showed that the QFC model effectively improved students' learning achievement and engagement (both behavioral and agentic) compared to the CFC model.

Embedding quiz strategy into the pre-class video demonstrated the potential support to enhance the efficacy of the CFC model. Based on the results of this research, the authors recommended that flipped educators can use the quiz strategy to minimize pre-class issues (especially students' disengagement).

This research adds to the existing literature by evaluating the effect of the newly proposed model on students' learning outcomes and engagement. This study's results can guide colleges and universities intending to implement a blended learning or flipped learning model. The research also gives design, content and course implementation guidelines, which can help engage students to achieve their learning objectives.

The objective of this study is to propose a model for the implementation of a technological platform for participants to develop solutions to problems related to the Fourth Industrial Revolution (4IR) megatrends, and taking advantage of artificial intelligence (AI) to develop their complex thinking through co-creation work.

The development of the model is based on a combination of participatory action research and user-centered design (UCD) methodologies, seeking to ensure that the platform is user-oriented and based on the experiences of the authors. The model itself is structured around the active and transformational learning (ATL) framework.

This study highlights the importance of addressing 4IR megatrends in education to prepare students for a technology-driven world. The proposed model, based on ATL and supported by AI, integrates essential competencies for tackling challenges and generating innovative solutions. The integration of AI into the platform fosters personalized learning, collaboration and reflection and enhances creativity by offering new insights and tools, whereas UCD ensures alignment with user needs and expectations.

This research presents an innovative educational model that combines ATL with AI to foster complex thinking and co-creation of solutions to problems related to 4IR megatrends. Integrating ATL ensures engagement with real-world problems and critical thinking while AI provides personalized content, tutoring, data analysis and creative support. The collaborative platform encourages diverse perspectives and collective intelligence, benefiting other researchers to better conceive learner-centered platforms promoting 21st-century skills and co-creation.

The objective of the study was to explore which COVID-19 teaching and learning methods, that enhanced accounting students' learning experience, should be applied at a residential university after the pandemic.

A qualitative exploratory approach within an interpretive paradigm was applied. A total of 15 semi-structured interviews were conducted with accounting students and the data were analysed using thematic analysis.

This study shows how pre-COVID-19 accounting education can be adapted by learning from the teaching and learning experiences gained during the pandemic and that there are various teaching and learning methods that can be applied in the post-COVID-19 period to enhance students' learning experience. These blended active teaching and learning methods include: the flipped classroom, discussion forum, electronic platform (to ask questions during class), key-concept videos and summary videos. Introducing these teaching and learning methods comes with challenges and the study provides recommendations on how to overcome foreseen obstacles. The contribution of the research is that it informs accounting lecturers' decision-making regarding which teaching and learning methods to apply in the aftermath of COVID-19 to enhance students' learning experience.

It is uncertain which teaching and learning methods employed during the COVID-19 pandemic should be applied at a residential university to enhance the teaching and learning experience after the pandemic. Accounting lecturers might return to their pre-COVID-19 modus operandi, and the valuable experience gained during the pandemic will have served no purpose.

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.

Project-based learning is one of the most effective methods of transferring academic knowledge and skills to real-world situations in higher education. However, its effectiveness is not much investigated focusing on the students' narrative. This study aims at evaluating the students' experience and perspective on adopting project-based learning in master by research and doctoral programmes for proactive skills development.

This study evaluates the self-reflection of 10 postgraduate students and their supervisor who have participated in developing a software tool for solar photovoltaics (PV) integrated building envelope design, management and the related education.

Findings reveal that the students have effectively improved their knowledge on the subject via collaborating with the industry, self-learning/observation, peer learning, problem-solving and teamwork. Dividing the project into student-led tasks has improved the decision-making and leadership skills, risks identification, planning and time management skills. The overall experience has (1) built up confidence in students, (2) enhanced their creativity and critical thinking and (3) improved their proactive skills and context knowledge.

A clear research gap can be seen in exploring the effectiveness of project-based learning for master by research and doctoral programmes, which mainly focus on extensive research. These programmes do not necessarily focus on developing students' proactive skills, which is the main requirement if they intend to work in the construction industry. This paper addresses the above research gap by demonstrating the effectiveness of project-based learning for developing the proactive skills in a research-intensive learning environment.

The purpose of this study is to propose a research model based on the stimulus-organism-response (S-O-R) model to explore whether gamification and personalization as environmental stimuli to learners’ learning engagement (LE) can affect their learning persistence (LP) in massive open online courses (MOOCs) and, in turn, their learning outcomes in MOOCs.

Sample data for this study were collected from learners who had experience in taking gamified MOOCs provided by the MOOCs platform launched by a well-known university in Taiwan, and 331 usable questionnaires were analyzed using structural equation modeling.

This study demonstrated that learners’ perceived gamification and personalization in MOOCs positively influenced their cognitive LE and emotional LE elicited by MOOCs, which jointly explained their LP in MOOCs and, in turn, enhanced their learning outcomes. The results support all proposed hypotheses and the research model, respectively, explaining 82.3% and 65.1% of the variance in learners’ LP in MOOCs and learning outcomes.

This study uses the S-O-R model as a theoretical base to construct learners’ learning outcomes in MOOCs as a series of the psychological process, which is influenced by gamification and personalization. Noteworthily, while the S-O-R model has been extensively used in prior studies, there is a dearth of evidence on the antecedents of learners’ learning outcomes in the context of MOOCs, which is very scarce in the S-O-R view. Hence, this study enriches the research for MOOCs adoption and learning outcomes into an invaluable context.