Due to irregular daytime routines, chronotype changes, side jobs and exam periods, after the COVID-19 pandemic, university students are trying to find new balances in their everyday life. The aim of the present study is to analyze the impact of daytime chronotype and hour preferences for the circadian rhythm on academic achievement among university students, considering their sleep habits and class frequencies in daytime and nighttime classes. Furthermore, this study aimed to analyze the differences in chronotype preferences with regard to age, sex, and academic schedule students are attending. A sample of 87 university second-year Psychology and Management students attending the academic year 2021/2022 after the governmental relief measures of the COVID-19 pandemic completed a 13-item questionnaire on sleep habits and preferences. Further variables encompassed sleep behaviors, such as age, sex, daytime and nighttime classes, as well as academic achievement. The results of the study showed that university students had a higher preference for the morningness type. Additionally, chronotype traits explained 30% (values from regression analysis) of academic achievement but did not directly impact academic results. The sleep–wake cycle diverged among age groups because the youngest participants (19–21 years old) and older participants (35–44 years old) reported higher academic scores during the first semester and the full academic year. No significant differences were identified with respect to sex. There is a lack of literature explaining the effect of sleep hours on academic achievement among students after stay-at-home rules during the COVID-19 pandemic. Thus, it is imperative to understand the difficulties students face with regard to their studying hours, working shifts, and daytime or nighttime classes to create a sustainable university system that attends to students’ needs and necessities.

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.

The Attraction-Selection-Attrition (ASA) model is a prominent framework for supporting employee retention, stating that organisations attract, select, and retain people who share their values. However, the ASA model only extends to the end of the recruitment stage and lacks clarity on how to assist newcomers in the assimilation process when they first join the organisation. This research proposed a refinement of the ASA paradigm by incorporating the assimilation process of new hires into the new school culture and environment. This study employed a qualitative research approach by interviewing ten participants about the retention process from high teacher retention international schools in Malaysia. Thematic data analysis revealed a new paradigm, 'Attraction-Selection-Onboarding-Retention (ASOR), ' designed to increase teacher retention in international schools. The ASOR model could assist school administrators and human resource managers working in a related setting in properly engaging the workforce to increase teacher retention. This would benefit school sustainability, performance and the local community's economy.

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.

It is known that the COVID-19 pandemic led to learning losses among students both domestically and internationally. Therefore, situational and casual factors were examined to discover and understand them so that learning loss could be reduced or recovered from. This research aimed to: (a) study learning loss situation; and (b) develop and examine the causal model of learning loss among lower secondary school students affected by the pandemic. The sample included 650 Grade 7-9 students selected by multi-stage random sampling. The data was collected using a self-developing questionnaire as a research instrument. The data was analyzed using descriptive statistics, independent samples t-test, ANOVA, and structural equation modeling (SEM) through the LISREL program. The findings were: (a) Lower secondary school students had an average academic achievement learning loss at the moderate level with the highest mean of learning loss in mathematics (M=3.012, SD=1.074), and an average learning characteristics learning loss at the medium level (M=2.824, SD=0.842). Several situational factors had a different effect depending on the school size with a statistical significance of .05.; and (b) the causal model showed the learning loss of grade 7-9 students was consistent with the empirical data (χ2=46.885, df=34, p= .069, GFI=0.991, AGFI=0.964, CFI=0.999, RMSEA=0.024, SRMR=0.014).

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.

Given the insufficient involvement of business investments in adult education, this study focused on the factors that motivate managers and entrepreneurs to invest in continuing education. For this purpose, we conducted a systematic literature review of studies referenced in Scopus and Web of Science since 2015. The factors for training were classified into four levels: personal, organizational, industry-related, and national. The results indicated that the inside firm-related determinants are the most studied and essential. A consensus emerged in the relevant literature on the positive impact of a supportive workplace culture, a learning orientation, formalized human resource development practices, and employee voice. The long-term orientation of managers and the perception of employees’ flexibility and adaptability to change also play a role. The study highlights the increasing pressure from regulations and market competition, as well as the (in)capability of universities to provide training tailored to the specific needs of companies. Although institutional factors appeared to predominate, economic considerations also influence training decisions; the latter means that the two underlying theories – institutional theory and human capital theory – complement each other when explaining employers' incentives to invest in training.

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>

Mathematics test items in International Large-Scale Assessments (ILSAs) such as the Programme of International Student Assessment (PISA) and the Trends in International Mathematics and Science Study (TIMSS) are nested in contexts defined in their assessment framework (e.g., the Personal, Occupational, Societal, and Scientific contexts in PISA). This study followed the item-writing activities of four tertiary mathematics instructors in the Philippines as they constructed context-based mathematics items. They were tasked to write four items each, following a set of specifications for PISA content and context categories. The data consisted of transcripts from the focus-group discussion which was conducted days after the task. The transcripts were then analyzed using thematic analysis. The results of this study showed that the phenomenon of item-writing in the context of writing PISA-like mathematics items had two themes: the phases of item-writing and the dimensions of item-writing. Findings showed that the respondents struggled to find realistic contexts and that they engaged in a problem-solving task likened to solving a puzzle as they attempted to satisfy the content, context, and process categories in the table of specifications (TOS). This study contributes to filling in the research gap on item-writing activities, particularly those of mathematics teachers in the Philippines- a country whose recent mathematical performance in the PISA 2018, TIMSS 2019, and PISA 2022 was nothing short of dismal.

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.

Since psychological satisfaction is influenced by the interaction between individuals and their environment, it is necessary to create a cooperative climate at the organizational level and strengthen collective innovativeness at the individual level to improve teachers' job satisfaction. Therefore, the study investigated whether collective innovativeness can be mediated by the school climate to enhance teacher job satisfaction. This study extensively examined survey data with a sample of 3,976 teachers in Shanghai through Structural Equation Modeling, obtained from Teaching and Learning International Survey (TALIS). The findings revealed that teachers' collective innovativeness served as a significant mediator between school climate and job satisfaction. Furthermore, higher levels of collective innovativeness among teachers amplified the influence of school climate on their job satisfaction. These findings show that schools should strive to foster a collaborative school climate and provide support for teachers in implementing innovative and collaborative teaching activities with the aim of enhancing their job satisfaction. Above all, efforts are needed to support teachers' active and cooperative practice capabilities in building teacher-student relationships.

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.

Digital competence entails the healthy, safe, and responsible use of digital technologies to take engage in society, to learn, work and to interact with. However, the use of digital devices is not exempt of risks. The objectives of this study were to analyze the mediating effect of fear of missing out (FoMO) on phubbing and nomophobia, and to explore the perception of the use of Internet-connected devices among 522 Spanish university students, with an average age of 27.11 years. The 80.8% are women and 68.2% study degrees related with Educational Sciences. A mixed-methods approach was used, combining bivariate correlation with structural equation modelling (SEM), and qualitative content analysis. SEM analysis revealed that FoMO had a significant effect on nomophobia and phubbing. Qualitative content analysis underlined that the time spent, problematic use, and sense of dependence were the main concerns for participants. It is emphasized that the plethora of ICT opportunities exposes individuals to risk contexts, necessitating media education to mitigate psychological and social consequences stemming from Internet risks.