Background: The current rapid development demands educators to possess innovative behaviour. Presently, in the environment of rapid technological growth and borderless global communication, teachers with innovative behaviour are capable of facing each painful challenge that confronts the education system; therefore, it is essential to understand the factors influencing the innovative behaviour of teachers. Purpose: To identify the influence of teachers’ self-efficacy and school administrators’ transformational leadership practices on teachers’ innovative behaviour. Method: A quantitative approach using a cross-sectional survey design with a sample of 1415 teachers from four states in Malaysia, and the data were statistically analysed using SPSS^® version 26.0 for Windows™ (IBM Corporation, New York, NY, USA). Result: Multiple Regression Analysis found that teachers’ self-efficacy and school administrators’ transformational leadership practices both had a significant influence on teachers’ innovative behaviour by contributing 47.0% of the variance in teachers’ innovative behaviour. Conclusion: The findings suggested that teachers’ self-efficacy and school administrators’ transformational leadership practices both play a role in influencing teachers’ innovative behaviour. Therefore, the stakeholders need to consider the aspects of self-efficacy and transformational leadership practices of school administrators in drafting policies and related programmes to improve teachers’ innovative behaviour.

Intending to analyze structural relationships between measured variables and latent constructs, researchers tend to adopt structural equation modeling (SEM) through either “covariance-based SEM” (CB-SEM) or “variance-based SEM” (VB-SEM)/“partial least squares SEM” (PLS-SEM) by using numerous statistical applications. Nevertheless, the reviews on understanding the optimal choice of proprietary statistical software packages in SEM approaches are scarce despite its immense importance in sustaining education. Therefore, a systematic review would be obligated to scrutinize the empirical studies to fill this gap. By employing the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines, a total of 47 publications that met the inclusion criteria were obtained. To extract articles from August 2018 to 2022, Scopus, Web of Science (WoS), and The Education Resources Information Center (ERIC) databases were adopted. The findings imply that six types of proprietary statistical software packages emerged as an optimal choice: Lisrel, Amos, Mplus, SmartPLS, R package (plspm), and WarpPLS. Despite the widespread usage of a variety of statistical applications, SmartPLS and AMOS were rigorously utilized in VB-SEM/PLS-SEM and CB-SEM, respectively. This review is important for practitioners to discover which statistical tools are relevant to use and to identify gaps in order to sustain mathematics education for the future.

Computational thinking is a strategy of thinking to tackle complex problems. There is a paucity of conceptualization and instruments that cogitate on computational thinking disposition and attitudes. This study reacts to these constraints by establishing an instrument to test computational thinking related dispositions and attitudes. The computational thinking disposition Instrument is an indicator of student’s disposition towards computational thinking in daily life. The objective of this study is to investigate the psychometric features using Rasch model. Data of 535 form four computer science students in Malaysia were obtained. Instrument consists of 55 core measures in three domains: cognitive, affective and conative. The Rasch analysis indicated good psychometric features of the instrument. In these three domains no items showed disordered thresholds and the reliability was good. As a result, the Rasch analysis provides basis for cautious optimism permitting more detailed and finer level investigation of the instrument.

Introduction: Analytical thinking, which involves deeply understanding and dissecting information, is crucial in today’s data-rich society. In education, it develops students’ ability to think deeply, deconstruct problems, and evaluate evidence to enhance academic performance and critical thinking skills. However, past research has not thoroughly examined the patterns of analytical thinking studies, particularly in terms of year and country classifications, which are essential for identifying research trends and gaps.Methods: Hence, this study aims to classify studies on analytical thinking by year and country using Systematic Literature Review, because this data is useful for understanding research trends. By using a methodology according to PRISMA, the research process was divided into four key stages: searching, screening, analyzing, and summarizing. A total of 21 relevant articles were carefully selected and analyzed in depth through targeted searches on main databases such as Web of Science, Scopus, and Google Scholar.Results: The main findings reveal a clear trend of increasing research on analytical thinking in mathematics, with notable peaks in 2021, and Indonesia emerging as the leading contributor in this area.Discussion: This finding has important implications for shaping educational policies and curriculum development, particularly in countries aiming to foster analytical thinking skills in students. Future research should broaden the scope by incorporating more disciplines and diverse theoretical frameworks, enhancing the application and impact of analytical thinking across fields.

Evaluating candidates’ answers in speaking skill is difficult and rarely explored. This task is challenging and can bring inconsistency in the rating quality among raters, especially in speaking assessments. Severe raters will bring more harm than good to the results that candidates receive. Many-faceted Rasch measurement (MFRM) was used to explore the differences in teachers’ rating severity based on their rating experience, training experience, and teaching experience. The research uses a quantitative approach and a survey method to enlist 164 English teachers who teach lower secondary school pupils, who were chosen through a multistage clustered sampling procedure. All the facets involving teachers, candidates, items, and domains were calibrated using MFRM. Every teacher scored six candidates’ responses in a speaking test consisting of three question items, and they were evaluated across three domains, namely vocabulary, grammar, and communicative competence. Results highlight that the rating quality was different in terms of teachers’ rating experience and teaching experience. However, training experience did not bring any difference to teachers’ rating quality on speaking test. The evidence from this study suggests that the two main factors of teaching and rating experience must be considered when appointing raters for the speaking test. The quality of training must be improved to produce a rater with good professional judgment. Raters need to be supplied with answer samples with varied levels of candidates’ performance to practice before becoming a good rater. Further research might explore any other rater bias that may impact the psychological well-being of certain groups of students.

This study aimed to examine the influence of Adversity Quotient (AQ) on the academic achievement among Malaysian polytechnic students. A total of 1,845 students from five polytechnics in Malaysia participated in this study and these polytechnic was selected from five different zones, namely Nouthern, Southern, Eastern, Western and Borneo. The samples for the study was selected using the proportionate clustered multistage stratified sampling technique. Data collected for this study was analyzed using regression analysis and the results showed that the findings of the analysis showed that AQ contributed only 0.9% (r = .098) changes in the variance of academic achievement score. AQ still has the potential to be studied from the other perspective of the success factor in the polytechnic students as a whole.