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.

Learning motivation and self-regulated learning are prominent and essential characteristics to possess in this time of change, leading to lifelong learners. The aim of this study was to investigate the impact of the ADMIRE program on the learning motivation and self-regulated learning behavior of undergraduate students. The research consisted of a quasi-experimental design conducted for two months. The participants were divided into two homogenous groups including the intervention group (n = 85) and the control group (n = 79). Data were collected before and after the intervention using the learning motivation scale and self-regulated learning behavior scale. Finally, data were analyzed using MANOVA. The study results revealed that the ADMIRE program made a significant impact on the learning motivation and self-regulated learning behavior. Therefore, it can be concluded that the use of the ADMIRE program can lead to greater learning motivation and self-regulated learning behavior in the intervention group compared to the control group. The ADMIRE program gives students the opportunity to participate in initiatives to reach the desired learning outcomes. Instructors can also use the ADMIRE program during the process of proactive learning in various forms.

This study sought to investigate the current state of innovative teaching research and identify emerging themes and trends in the field from 2013 to 2023. The Scopus database was searched for the term “innovative teaching,” resulting in 1005 documents. After manual screening, 903 articles were exported in the BibTeX format for further processing in Bibliometrix using three bibliometric analysis types: network analysis, science mapping, and performance analysis. Performance analysis revealed bursts in publication output in 2015 and 2021, with a moderate boost in 2018. Ten top-cited journal papers were identified. The citation rates were low between 2019 and 2021, but there has been an upturn since 2022. The top keywords included simulation and nursing education, and there was a shift in research topics from broad educational concepts to more specific approaches, such as e-learning. Innovative teaching has been predominantly investigated in higher education, particularly in nursing education, with themes like “teaching/learning strategies” suggesting an emphasis on enhancing teaching practices not just through technology infusion. This study can aid educators and researchers in staying current with innovative teaching developments and inform their teaching practices.

The swift widespread shift from face-to-face to emergency remote teaching (ERT) due to the COVID-19 pandemic was accompanied by numerous technical, psychological, and pedagogical challenges and prompted educators to look for ways to improve their performance to preserve the high quality of learning. One way to do this is for teachers to adopt charismatic behaviours. This study aims at investigating the concept of and factors determining teachers’ charisma and its connection with students’ intrinsic motivation and perceived learning in a synchronous online learning setting during ERT. The questionnaires measuring students’ intrinsic motivation, perceived learning, and teachers’ charisma were used to collect the responses from Ukrainian university students who reported on their online learning experienced amid the COVID-19 pandemic. The Varimax rotation method was applied to determine the factors of charisma. Correlation analyses established a connection between students’ intrinsic motivation and perceived learning and teachers’ charisma as well as each factor of charisma independently. The research is the first of its kind done in an online learning setting in an Eastern European cultural context. The research validates some previous findings done in a face-to-face teaching context. The current study also established the connection between humor and empathy as a factor of charismatic teaching.

The study aimed to explore the self-directed learning readiness model and its relationship with various factors such as emotional intelligence, transformational parenting, need-supportive teaching style, and self-efficacy as potential mediators. The research was conducted with 415 junior high school students in Surabaya, Indonesia. To ensure the reliability and validity of the instruments used in the study, confirmatory factor analysis was performed. The loading factor values of all the items in the instruments were found to be greater than .50 indicating a satisfactory level of validity. Additionally, the reliability coefficient of all the instruments exceeded .90 demonstrating good internal consistency. Analysis using structural equation modeling (SEM) demonstrated that the theoretical model of self-directed learning readiness was consistent with empirical conditions because it meets the standard value of goodness of fit. Furthermore, through the indirect effect tests, it was discovered that need-supportive teaching style, emotional intelligence, and transformational parenting significantly influenced self-directed learning readiness, with self-efficacy acting as a mediator. Among the factors examined, self-efficacy was found to have the greatest impact in explaining readiness for self-directed learning readiness.

Changes and challenges in the highly dynamic world of education require postgraduate students to manage their learning well and create something from their creative thinking according to the needs of the field. One of them is the activity of students in developing integrated natural science teaching materials is very necessary because learning at the primary level still uses integrated or thematic learning. Furthermore, students also need to be encouraged to be adaptive to these challenges by empowering their independence in learning. The ability to manage learning and creativity to create something new is highly prioritized for college graduates to contribute generously to their environment. This study aims to describe the empowerment of self-regulated learning and student creativity in developing natural science teaching materials in collaboration through community-based project learning. This study used a quasi-experimental design with a single-subject design type. The instruments used to retrieve data are creativity assessment rubrics and self-regulated learning questionnaires. The conclusion is that students are intrinsically and extrinsically motivated to fulfill the given tasks. Learning is essential for increasing competence, and learning strategies have been adjusted to the material's complexity or the difficulty level of the studied content. The aspect of student creativity in developing Integrated Science teaching materials shows the existence of change from stage one to the next and good categories.

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.

Psychosocial and educational intervention approaches employ diverse treatment frameworks, most of which involve delivering some form of feedback to participants about their behavior. General conceptions of feedback are well-known to underlie mainstream therapeutic and educational approaches. Recently emerging ‘smart’ approaches also rely on feedback principles. However, little scholarship is available to stitch together evolving strands of feedback principles and no literature characterizes explicitly the diverse landscape of feedback practices employed in education or intervention science. This paper reviews intrinsic conceptions of feedback along with diverse cases of its use in intervention and education. Based on our consideration, we present a typology of feedback modalities that we hope will enrich the efforts of interventionists and educators to design treatment and educational frameworks incorporating feedback.

This study aims to analyse the relationship between critical thinking and the learning experience provided by instructors through active learning models, specifically Project-based Learning (PjBL) and Simulation-based Learning (SBL), to the potential achievement of academic performance in undergraduate students. The main analysis technique employed in this research was logistic regression, with additional analysis techniques including discriminant validity, EFA, as well as Kendall’s and Spearman’s correlation, serving as a robustness check. The results of this study indicate significant correlations and effects of critical thinking (CT) on academic performance. Higher levels of CT are associated with a greater likelihood of achieving academic excellence, as indicated by the cum laude distinction, compared to not attaining this distinction. Experiences of receiving PjBL (0.025; 6.816) and SBL (0.014; 14.35) predicted the potential for improving academic performance to reach cum laude recognition, relative to not achieving this distinction. Furthermore, other intercept factors need to be considered to achieve cum laude compared to not achieving cum laude. We recommend that policymakers in higher education, instructors, and others focus on enhancing critical thinking and utilizing both Pub and SBL as learning models to improve students’ academic performance.

Service-learning (SL) emphasizes the fusion and integration of community service and academic learning, while Physical Education (PE) is oriented towards community health and well-being, aligning with Sustainable Development Goals. The study's primary objective is to discern the benefits perceived by PE students when engaged in SL courses and to test the correlation between benefits and the motivational climate they experience. Additionally, the research explores potential gender-specific variations in students' attitudes. The research was conducted with a survey on a sample of 58 students responding to a Motivational Climate in Physical Education Scale (MPCES) and the SErvice LEarning Benefit Scale (SELEB), which assesses the motivation of students and their perceptions of SL benefits. Descriptive statistics was used to analyse the data. Pearson's correlation coefficient was used to test the relationship between the core constructs - SL benefits and student motivation, and t-tests to evaluate gender differences in SL benefits. Key findings underscore that students primarily perceived the greatest advantages from SL in the domain of knowledge application, with comparatively lower scores in general life skills. Notably, female students, on the whole, exhibited higher ratings in both SL benefits and student motivation compared to their male counterparts. Nonetheless, specific exceptions emerged in certain sub-scales, including social relatedness and ego climate within the MPCES scale, as well as critical thinking within the SELEB scale. According to the results, it is suggested that cultivating a student-centered learning environment can augment engagement and motivation in the realm of physical education (PE). Furthermore, the delineated gender differences offer valuable insights for educators, highlighting the need for tailored approaches to accommodate the diverse preferences and requirements of male and female students.

This study aims to analyze the effects of working memory capacity and learning styles of prospective mathematics teachers on their ability to solve higher-order thinking problems. In the present study, learning style was considered students' tendency to learn visually or verbally. In addition, the types of higher-order thinking skills (HOTS) problems are complex and non-complex. Multiple regression tests were used to analyze the effects of learning style and working memory capacity. An ANOVA test was also conducted to analyze the ability of each group to solve each HOTS problem. In addition, one hundred twenty-six prospective mathematics teachers voluntarily participated in this study. The study found that learning styles only affected visual problems while working memory capacity (WMC) only affected the ability to solve complex problem-solving skills. Furthermore, WMC affected the ability to solve complex HOTS problems, not non-complex ones. The ability of visual students to solve HOTS problems will greatly increase when the problems are presented in visual form. On the other hand, the obstacle for visual students in solving verbal problems was to present the problem appropriately in visual form. The obstacle for students with low WMC in solving complex HOTS problems was to find a solution that met all the requirements set in the problem.

The world eagerly anticipates advancements in AI technologies, with substantial ongoing research on the potential AI applications in the domain of education. The study aims to analyse publications about the possibilities of artificial intelligence (AI) within higher education, emphasising their bibliometric properties. The data was collected from the Scopus database, uncovering 775 publications on the subject of study from 2000 to 2022, using various keywords. Upon analysis, it was found that the frequency of publications in the study area has risen from 3 in 2000 to 314 in 2022. China and the United States emerged as the most influential countries regarding publications in this area. The findings revealed that “Education and Information Technologies” and the “International Journal of Emerging Technologies in Learning” were the most frequently published journals. “S. Slade” and “P. Prinsloo” received the most citations, making them highly effective researchers. The co-authorship network primarily comprised the United States, Saudi Arabia, the United Kingdom, and China. The emerging themes included machine learning, convolutional neural networks, curriculum, and higher education systems are co-occurred with AI. The continuous expansion of potential AI technologies in higher education calls for increased global collaboration based on shared democratic principles, reaping mutual advantages.

This research aimed to explore the influence of a robotic program using the robot kit "RoboBuilder RQ+110" on students' attitudes toward effective communication. The study used a quantitative research design and involved 475 grade 4 (10 years old) students from Malaysia's Selangor and Malacca states. A quasi-experimental research (pre-test & post-test) approach with control and experimental groups was adopted, and the data were analyzed with inferential statistical test and repeated measures analysis of variance (ANOVA) using SPSS 25 software at 0.05 significance level. Questionnaires were administered to collect data from the experimental and control groups. The results showed statistically significant changes (α ≤ .05) in attitudes toward effective communication for the experimental group that received a robotics program compared with the control group. The study results suggest that innovative technological tools or programs such as robotics programs are recommended as innovative science, technology, engineering, and mathematics (STEM) program rooted in constructivism to improve students' attitudes toward effective communication.

Understanding graphs in the dynamics of market (DM) is a challenge to learners; its teaching demands a specific kind of teacher’s knowledge. This study aims to examine the topic-specific pedagogical content knowledge (TSPCK) of experienced economics teachers in teaching graphs in DM to enhance learners’ understanding of the topic. It reports using a qualitative approach underpinned by the TSPCK framework for teaching specific topics developed by Mavhunga. Data were collected through classroom observations and analyzed thematically using a case study of two economics teachers. The study revealed that adopting a step-by-step approach and the use of worked graphical examples promote an understanding of graphs in DM. It also established that active learning is preferable to the predominant chalk-and-talk (lecture) method of teaching graphs in DM. The study proposed a Dynamics of Market Graphical Framework (DMG-Framework) to enable teachers, particularly pre-service teachers in lesson delivery, to enhance learners’ understanding of graphs in DM. The result of this study will broaden the international view in the teaching of graphs in DM.

<p>&lt;p style=&quot;text-align:justify&quot;&gt;In the early stages of adopting online learning, both learners and teachers displayed resistance, but the COVID-19 pandemic has forced a widespread shift to digital learning. To facilitate this transition, there is a growing focus on highlighting the effectiveness of online learning, which directly impacts learning outcomes. This study investigates online learning effectiveness through an integrated framework that considers online assessment practices and online course design as independent variables, with online learning support as a moderating variable. Understanding the effectiveness of online learning is crucial as hybrid learning becomes the &amp;quot;new norm&amp;quot; in education, combining online and offline methods for teaching the digital generation. Using a quantitative research design involving 232 students at Universiti Kebangsaan Malaysia, the study found that online assessment practices and course design significantly influence students perceived learning outcomes in an online learning environment. Additionally, online learning support positively moderates this relationship. These findings offer a comprehensive perspective on how online assessment practices, course design, and support systems contribute to the quality of higher education in Malaysia amidst evolving educational practices.&lt;/p&gt;</p>

This article investigates artificial intelligence (AI) implementation in higher education (HE) from experts' perspectives. It emphasises the view of AI's involvement in administrative activities in higher education, experts' opinions concerning the influence of the incorporation of AI on learning and teaching, and experts' views on applying AI specifically to assessment, academic integrity, and ethical considerations. The study used a qualitative method based on an unstructured qualitative interview with open-ended questions. The participants were thirteen individuals currently involved with higher education institutions and had various talents related to AI and education. Findings stress that implementing AI technology in administrative roles within higher education institutions is essential since it cuts costs, addresses problems efficiently and effectively, and saves time. The findings also revealed that AI plays a vital role in learning and teaching by speeding up the learning process, engaging learners and tutors, and personalising learning depending on the learner's needs within an entirely intelligent environment. AI can produce an accurate, objective, and suitable level of assessment. AI aids students in developing a stronger sense of integrity in their academic work by guiding them through AI-powered applications. AI must adhere to ethical laws and policies, ensuring its potential negative aspects are not overlooked or left unchecked.

Students’ mastery goal orientation tends to decline over the course of compulsory school, especially after the transition to lower secondary school. According to stage-environment fit theory, secondary school is less accommodating to students' needs, interests, and abilities than primary school. In consequence, the perceived person-environment fit declines as well. It is assumed that a strong sense of classroom community in primary school can counteract a potential decline in both of these important individual aspects. Using data from the Swiss longitudinal research project WiSel (“Wirkungen der Selektion”; “Effects of Tracking”), we conducted a latent growth curve model (LGCM) to examine the correlation between the development of students' mastery goal orientation and the development of their person-environment fit during the transition from primary school to lower secondary school. Perceived classroom community was assumed to benefit from these developments. The results show that both mastery goal orientation and person-environment fit decrease during the transition to lower secondary school. A strong sense of classroom community in fifth grade leads to a smaller decline in both constructs. Implications for educational practice are discussed.

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.

Research in higher education has revealed a significant connection between executive functions (EF) and study success. Previous investigations have typically assessed EF using either neuropsychological tasks, which provide direct and objective measures of core EF such as inhibition, working memory, and cognitive flexibility, or self-report questionnaires, which offer indirect and subjective assessments. However, studies rarely utilize both assessment methods simultaneously despite their potential to offer complementary insights into EF. This study aims to evaluate the predictive capabilities of performance-based and self-reported EF measures on study success. Employing a retrospective cohort design, 748 first-year Applied Psychology students completed performance-based and self-report questionnaires to assess EF. Maximum likelihood correlations were computed for 474 students, with data from 562-586 first-year students subsequently subjected to hierarchical regression analysis, accommodating pairwise missing values. Our results demonstrate minimal overlap between performance-based and self-reported EF measures. Additionally, the model incorporating self-reported EF accounted for 13% of the variance in study success after one year, with the inclusion of performance-based EF raising this proportion to 16%. Self-reported EF assessments modestly predict study success. However, monitoring levels of self-reported EF could offer valuable insights for students and educational institutions, given that EF play a crucial role in learning. Additionally, one in five students reports experiencing significant EF difficulties, highlighting the importance of addressing EF concerns for learning and study success.

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.