Teacher agency is a set of actions that a teacher takes beyond what is generally expected of them. The concept merits examination, as agency can bolster teachers’ ability to set and achieve professional development goals. To better understand how to study, and use, this relatively new concept in the academic literature, a systematic review of 164 publications written by researchers from 41 countries was conducted in order to document the research approaches used to study teacher agency, the participants whose agency was documented in a school setting, the methodology used and the type of analysis performed. The study found that teacher agency has been documented qualitatively in the form of case studies comprising interviews of a small number of individuals, with no consensus in terms of interview protocol. In most cases, the results are analyzed using emergent coding. The way that agency is documented varies but is most often underpinned by an ecological approach.

The accuracy of assessing the capabilities of the process and product in chemical practice activities requires appropriate measurement procedures to be followed. It is crucial to identify the components that can introduce bias while measuring student abilities during the measurement process. This study aims to identify the components or criteria used by teachers to assess student performance in practicum activities and analyze the quality of the rubrics developed. The study was conducted with the participation of three raters, 27 high school students, and nine assessment criteria. A quantitative descriptive approach was employed using the many-facet Rasch model (MFRM) analysis for measurement. The results of the MFRM analysis show no significant measurement bias, with data measurement facets fitting the MFRM model. The reliability of all the facets meets the criteria, and the scale predictor functions appropriately. While all students can easily pass four out of nine items, five items can only be partially passed by students. The assessment criteria that require special attention include communication skills, tools and assembly, interpretation, cleanliness, and accuracy when performing practicums. These criteria provide feedback for teachers and students to ensure successful practicum activities. The Discussion section of this study delves into the findings and their implications.

This study aimed to investigate the relationship between teacher professional development, quality of lecture design, student engagement, teacher technical skills, pedagogical content knowledge and teacher satisfaction in using Artificial Intelligence (AI)-Powered Facilitator for designing lectures. The study used a non-random sample technique, and 208 participants answered a survey via Google Form after one semester, using a 5-point Likert scale to rate their responses. The structural equation model was used to analyze the data, and six factors were included in the study. The study confirmed hypotheses that teacher professional development, quality of lecture design, student engagement, and pedagogical content knowledge have a positive effect on teacher satisfaction. However, the study also revealed that teacher technical skills have a negative effect on teacher satisfaction, and pedagogical content knowledge has no significant effect. The proposed conceptual model explained 55.7% of the variance in teacher satisfaction Theoretical and practical implications were also discussed. These findings provide insights into the factors that contribute to teacher satisfaction in utilizing AI-Powered Facilitator for designing lectures and could inform the development of effective teacher training programs.

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.

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.

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.