University students may encounter situations where they perform poorly in a course and contemplate dropping out. This intention to drop out of a course manifests not only in thoughts or ideas but also in a cognitive self-evaluation of their performance and skills, enabling them to reflect on the possibility of dropping out. In this sense, there is a shortage of instruments that evaluate the intention to drop out of a course, so the aim was to develop and validate the Course Dropout Intention Scale (CDIS). Data from two samples (N1 = 198; N2 = 675) were used; the first was for the EFA, and the second was for the CFA, GRM, and SEM. The one-factor model was derived from the EFA and confirmed in the second sample, exhibiting appropriate goodness-of-fit indices. Similarly, the GRM obtained adequate fit indices; all items discriminated adequately, and the difficulty parameter had a monotonic increase. The SEM model of the effect of satisfaction with studies on the CDIS showed a negative and statistically significant effect. Thus, it was demonstrated that the CDIS is a robust instrument in its psychometric properties and empirical evidence with other variables.

Online learning has become increasingly popular, making the learning process more attractive. One of the most popular learning media is artificial intelligence (AI). However, students do not accept this technology at all. Therefore, this study examined the factors influencing accounting students' acceptance of AI in learning. The survey was conducted with 147 higher-education students who use AI as a learning medium. The data were analyzed using SmartPLS 4.0 with the partial least square approach. The results showed that perceived usefulness influenced behavioral intention to use and satisfaction. However, perceived ease of use was only significant for satisfaction. Similarly, perceived confidence must be consistent with intention. Although it may influence perceived usefulness, other constructs, such as AI quality and personal innovativeness, can increase students' perceptions of the benefits and convenience of adopting AI in learning. Thus, this study contributes to the development of the technology acceptance model (TAM) and the information systems success model and is helpful to scholars, especially in applying AI in learning. They need to pay attention to the quality of AI, such as the accuracy of the information produced. Thus, the need to control the information from the AI only serves as a reference without requiring you to trust it completely.

Flipped learning (FL) is one of the recent pedagogical models that seeks to promote student agency and hone 21st century skills for lifelong learning through its emphasis on collaboration, creativity, critical thinking, and autonomy. However, only some physical education (PE) classes globally have adopted this method and researched its effectiveness. Thus, this qualitative study discovered how the SPRING online FL model helped enhance the 21st century skills of college PE students. From the students’ responses in the questionnaire and the teacher-researchers observation notes, it was revealed that FL aids in the students’ 21st century skills as it allows the students to collaborate and improve their social skills; analyze people, tasks, and situations to create an output that is not only ingenuous and entertaining but beneficial to all; and study and master the skills independently at their own pace. Future studies can explore testing the SPRING model's effectiveness in younger students and other learning contexts.

Teacher well-being has gained significant prominence in academic publications indexed by Scopus in recent years. This study employs rigorous bibliometric analysis to trace the evolution of teacher well-being literature, examining 326 relevant publications from 1995 to 2022. Our findings reveal two crucial inflexion points in 2013, driven by the global economic downturn, and 2020, propelled by the widespread repercussions of the COVID-19 pandemic, including teacher unemployment. These inflexion points underscore the real-world events' profound impact on academic discourse in teacher well-being. Traditionally, authors from the United States, Australia, and the United Kingdom have shaped this discourse. Dutch scholars have also gained recognition, accumulating substantial citations. This paradigm shift is paramount as emerging nations like Iran, Ireland, China, and Austria increasingly contribute, challenging the dominance of Western authors. This shift underscores the evolving dynamics of scholarly contributions in teacher well-being research, emphasizing the need for a more diverse and inclusive academic dialogue. This study provides a panoramic view of the trajectory of teacher well-being research, shedding light on the interplay between global events and scholarly responses. It highlights nations' evolving roles in shaping this discourse, acknowledging established influences while recognizing the contributions emerging from voices in the field. These findings enrich the global dialogue surrounding teacher well-being and offer insights into the dynamic forces shaping this vital field of study, compelling the academic community to adapt, diversify, and foster a more inclusive conversation on teacher well-being.

The central focus of this study is exploring the potential of Artificial Intelligence (AI) Chatbots in enhancing digital dialogue for students. The study investigates the key attributes of Chatbots that can contribute to the feasibility of facilitating digital dialogue to improve students' communication skills through discussions and dialogues. The study employed a descriptive method using a questionnaire to gather the perspectives of 35 educational experts on the use of AI Chatbots in digital dialogue skills. This study revealed that using AI Chatbots plays a crucial role in enhancing digital dialogue skills and can be effectively integrated into instructional practices to facilitate meaningful dialogue among students. Finally, the study recommends that educational technology specialists leverage new technologies, such as Al Chatbots to help improve student performance and facilitate digital dialogue in education.

The purpose of this research is to develop a worksheet that can support a digital science practicum. Conducting a needs analysis comes first in the development of worksheets, then comes product creation. The product produced based on the needs test analysis is a worksheet with the help of science worksheet-augmented reality (SWAR). Two knowledgeable education professionals then evaluate the finished product and test it out on participants or students. The results of the study show that worksheets equipped with augmented reality media are necessary. Meanwhile, the resulting product is valid in an almost perfect category (Pe = 0.7219; Po = 0.9744; K = 0.9078). Student perceptions of the products produced are at an "excellent" level in each category (ME-Av, mean = 3.466; CO-Av, mean = 3.472; CT-Av, mean = 3.503; ST-Av, mean = 3,507; TA-Av, mean = 3.440; IN-Av, mean = 3.640; MO-Av, mean = 3.640). There is a significant inverse relationship between media features (ME-Av) and student interest (IN-Av) based on Pearson's correlation test with r = -.50 (p < .50). Further explanation is presented based on the data that has been collected.

Situational interest is an important factor that has a great influence on learning success in both in-school and out-of-school learning situations. Although there has been extensive research on interest in its diverse forms for decades, an evaluated measurement instrument for situational interest that covers the three theoretically defined components of interest (emotional, cognitive, value-related) is still missing. Therefore, in this study, based on person-object theory of interest, a short scale was developed that can be used in a variety of learning programs independent of content or methods. In study 1, eight suitable items were selected and their structure was examined using exploratory methods. In study 2, the results of study 1 were verified using confirmatory factor analyses. Study 3 shows an example of a practical application of the newly developed scale in two different learning settings. The findings provide evidence that the scale developed here is a practical instrument to measure situational interest taking into account all its components. On the one hand, the scale can help teachers evaluate their educational programs; on the other hand, it can be used by researchers to empirically investigate the construct of interest. Thus, the scale makes an important contribution to research and practice.

This research attempts to map the trend of research related to differentiated instruction (DI). The research was conducted in May 2023 by researching research articles in the Scopus database. The search data from Scopus used title, abstract, and keyword searches. Research articles were analyzed descriptively based on year of publication, journal name, affiliation, country, and researcher name. The article database from Scopus was analyzed through VOSviewer and RStudio software so that a bibliometric map could be depicted in research related to DI. Based on the Scopus analysis results, it showed that publications of articles related to DI had increased from 2011 to 2021, although it decreased in 2016. The journal with the largest contributor to the publication of research articles related to DI was the Teaching and Teacher Education Journal. Vrije Universitiet Brusel was the university with the most published articles on DI. The country that contributed the most to the research articles related to DI was the United States. Struyven was the most productive scholar related to DI. Through network visualization, it was revealed that the evolution map of research related to DI was divided into five clusters.

Faculty members’ beliefs in their ability to conduct research and publish research outputs are expected to impact research productivity directly. Thus, the study described the research self-efficacy and productivity among faculty members, their research self-efficacy influence on productivity, and their challenges in research writing and publication. The study utilized a mixed-method sequential explanatory research design, with 36 and nine faculty member-participants for the quantitative and qualitative study. For the quantitative study, the faculty members’ research self-efficacy was ascertained using a validated questionnaire, and their research productivity was determined through a researcher-made survey instrument. Meanwhile, the qualitative study focused on the faculty members’ research writing and publication challenges, which were gathered through focus group discussions. Results showed average research self-efficacy and low research productivity among faculty members. Research self-efficacy significantly predicted research productivity regarding refereed and indexed publications, paper presentations, and bibliometrics. Further, themed findings showed that the faculty members encountered challenges such as a lack of research exposure, time constraints, lack of institutional support, and publication pressure. The study may serve as an inference for higher education institutions in designing faculty development plans and in-service training programs to capacitate its members.