The millennial generation is facing challenges in their career path and they believe that tertiary education can help them to equip better to tackle against. However, some students find it difficult to rush back to classroom due to work commitment. Fortunately, flexible education developed these years allows students to capture knowledge anytime and anywhere easier. In order to deliver courses in line with students’ need, many universities have considered offering alternative studying modes, such as flexible method, to enrich the course delivery. Using a case study, this paper investigates the delivery approach adopted by a school of a well-known university in Australia. This School offers architecture and construction management courses and has successfully adopted the flexible approach, with the aid of various online teaching and learning tools: the Cloud, Elluminate Live!, EchoSystem, Mediawiki and ePortfolio, in delivering subjects. It is welcomed by various cohorts of students. Not only the student numbers have been increased, but the School is also the first preference when students opting architecture and construction management studies. Statistics also indicate students’ satisfaction and course experience are improved. The success of this School proves itself to be an exemplar for other educators planning for flexible delivery.

The physical factors, which were studied less often than the other factors affecting students' learning, were considered in this study. The present study investigated the effect of the flexibility and non-flexibity of the physical classroom setting on undergraduate students' learning. The study adopted a mixed-method research design. The quantitative phase of the study employed the quasi-experimental method of research utilizing the pretest-posttest non-equivalent groups design. T Test and the Repeated Measures ANOVA test was used to compare the group means. In the qualitative phase of the study, the students received a questionnaire with open-ended questions to gather their opinions, and the data were analysed in NVIVO 11. There was no significant difference between the experimental and control groups in terms of learning; however, the achievement scores of both groups were found to be high. Furthermore, the views received from both groups indicated that the physical environment influenced learning in terms of motivation and enthusiasm.

Online learning during the Coronavirus disease (COVID-19) pandemic has awakened and affirmed the necessity of learning based on digital technology. The article was aimed to analyze the effectiveness of online learning at bachelor’s, master’s, and doctoral degrees of Islamic Religious Education as a reference to develop a learning pattern post-COVID-19 pandemic. The research employed a mixed-method design with a concurrent triangulation model. The samples were taken using stratified random and purposive sampling. Meanwhile, the data were collected through questionnaires, in-depth interviews, and forum group discussion. A descriptive analysis and one-way analysis of variance were used to analyze the quantitative data, while interpretative descriptive for the qualitative data. The research showed that online learning during the COVID-19 pandemic at the bachelor’s, master’s, and doctoral degrees of Islamic Religious Education have been effective. In detail, online learning at the doctoral degree was the most effective among all. On the other hand, face-to-face learning is still necessary. Therefore, the learning pattern developed post-COVID-19 pandemic combines face-to-face and online learning (hybrid learning). The formulation is adjusted to the characteristics, educational purpose and orientation, level of ability, readiness, and learning autonomy of the students at each educational level.

Technological tools are means by which online teaching could encourage the engagement of students, especially elementary students. The present research studies how elementary teachers develop their use of technological tools in their asynchronous and synchronous online teaching, specifically when this online teaching occurs during emergency education. The research was conducted in the academic year 2019/2020. We interviewed two elementary teachers, where one of them taught asynchronous lessons more than synchronous, while the second taught synchronous lessons more than asynchronous. We analyzed the data using two frameworks: one for interaction type and one for engagement type. The research results indicated that different interaction types influenced teachers’ decisions to use technological tools. In addition, what concerned the teachers’ use of tools at the beginning was the cognitive engagement, but they advanced towards focusing on behavioral and the affective engagement.

Biology laboratory courses (BLC) are designed to enhance and concretize students’ understanding of biology concepts. However, due to threats posed by the COVID-19 pandemic, education institutions were compelled to devise methods for teaching outside of laboratory structures and in a distant learning format. This phenomenological research explored the teachers’ articulation in the delivery of online distance learning (ODL) in BLC. Specifically, this study identified various methods and alternatives employed by biology teachers in conducting laboratory activities. Purposive sampling was used to select participants in survey, interview, and focus group discussion. The data were analyzed using thematic analysis. The study revealed that teachers articulate the delivery of online biology laboratory courses by employing different instructional practices in the three areas of learning experience: planning, implementing, and assessing stages. The results provide practical implications for the improvement of biology instruction and recommendations to support the delivery of flexible learning modalities during educational disruptions.

This comprehensive systematic review delves into the increasing prevalence of integrating chatbots into language education. The general objective is to assess the current landscape of knowledge regarding chatbot utilisation and its influence on three crucial elements: students' skills, attitudes, and emotions. Additionally, the review seeks to scrutinise the advantages linked to incorporating chatbots in foreign language teaching, exploring their potential benefits while considering limitations and potential negative impacts on specific skills or user experiences. Consequently, this research offers valuable insights into the application of chatbots in foreign language education, shedding light on their potential advantages and areas that warrant further exploration and enhancement. The integration of chatbots in language learning, despite certain limitations, generally yields positive outcomes and enhances educational results in students' skills. Its characteristics can also influence a language learner's attitude, impacting factors such as motivation, interest, autonomy in learning, and engagement or even their sense of fun. Additionally, chatbots prove to be helpful in creating emotionally positive learning environments and can contribute to boosting students' self-esteem and self-confidence.

With the current rate of technological advancements, higher education institutions around the world are increasingly adopting a wide variety of technology-related approaches to instruction. One of the teaching strategies used on digital platforms that has been successfully and widely adopted in higher education institutions is blended learning (BL). The objective of this investigation is to provide a comprehensive examination of the research efforts on BL in the context of higher education (HE) over the past 20 years, including the rise in publications, the most cited scientific journals and sources, and the upcoming research topics. This paper uses bibliometric analysis with a dataset of 651 documents from Scopus data, including 638 authors from 95 countries published in 271 journal sources. The results of the study show that the top three countries for BL research in higher education are the United Kingdom, the United States, and Australia; the authors with the highest citation indexes are D. R. Garrison and B. Means, and the top two publishing sources are Education and Information Technologies and Internet and Higher Education. Based on the analysis, the main trends detected are (a) student participation and environment, (b) educational technology instructional innovation, (c) effective instructional strategies within the parameters of the COVID-19 pandemic, (d) effectiveness of evaluation in BL environments and (e) BL with Massive Open Online Courses (MOOCs) and Learning Management System (LMS) in HE. These findings offer meaningful insights to early career researchers who consult the publications and research lists above, as well as to policy makers who develop suitable BL in HE policies.

This study aims to design, produce, and validate an information collection instrument to evaluate the opinions of teachers at non-university educational levels on the quality of training in artificial intelligence (AI) applied to education. The questionnaire was structured around five key dimensions: (a) knowledge and previous experience in AI, (b) perception of the benefits and applications of AI in education, (c) AI training, and (d) expectations of the courses and (e) impact on teaching practice. Validation was performed through expert judgment, which ensured the internal validity and reliability of the instrument. Statistical analyses, which included measures of central tendency, dispersion, and internal consistency, yielded a Cronbach's alpha of .953, indicating excellent reliability. The findings reveal a generally positive attitude towards AI in education, emphasizing its potential to personalize learning and improve academic outcomes. However, significant variability in teachers' training experiences underscores the need for more standardized training programs. The validated questionnaire emerges as a reliable tool for future research on teachers' perceptions of AI in educational contexts. From a practical perspective, the validated questionnaire provides a structured framework for assessing teacher training programs in AI, offering valuable insights for improving educational policies and program design. It enables a deeper exploration of educational AI, a field still in its early stages of research and implementation. This tool supports the development of targeted training initiatives, fostering more effective integration of AI into educational practices.

Integrating generative artificial intelligence (GenAI) in education has gained significant attention, particularly in flexible learning environments (FLE). This study investigates how students’ voluntary adoption of GenAI influences their perceived usefulness (PU), perceived ease of use (PEU), learning engagement (LE), and student-teacher interaction (STI). This study employed a structural equation modeling (SEM) approach, using data from 480 students across multiple academic levels. The findings confirm that voluntary GenAI adoption significantly enhances PU and PEU, reinforcing established technology acceptance models (TAM). However, PU did not directly impact LE at the latent level—an unexpected finding that underscores students’ engagement’s complex and multidimensional nature in AI-enriched settings. Conversely, PEU positively influenced LE, which in turn significantly predicted STI. These findings suggest that usability, rather than perceived utility alone, drives deeper engagement and interaction in autonomous learning contexts. This research advances existing knowledge of GenAI adoption by proposing a structural model that integrates voluntary use, learner engagement, and teacher presence. Future research should incorporate variables such as digital literacy, self-regulation, and trust and apply longitudinal approaches to better understand the evolving role of GenAI inequitable, human-centered education.