This qualitative study examines the experiences of pre-service high school biology teachers in the Mekong Delta, Vietnam, focusing on the challenges and transformative learning experiences encountered during their school-based internship. It aims to explore the dichotomy between specialized biology knowledge and practical applicability in high school teaching and uncover the significance of fostering student engagement through innovative strategies and the role of mentor teachers in guiding pre-service teachers. Semi-structured interviews were used to collect data from pre-service biology teachers who completed a school-based internship in the Mekong Delta. Thematic analysis was employed to analyze the interview data. The study highlights the challenges of bridging the gap between theoretical knowledge and classroom practice, emphasizing the importance of innovative teaching strategies for student engagement. It recognizes the role of mentor teachers in guiding and enhancing the skills of pre-service teachers in creating effective learning environments. Findings suggest the need for curriculum reforms that balance specialized biology knowledge and practical pedagogical skills. The study emphasizes the importance of experiential learning through teaching apprenticeships to better prepare pre-service teachers for their professional journey.

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.

Our research aim is to describe how Preservice Teachers (PSTs) can rehearse and prepare for leading productive talks in mathematics and other subjects. Based on literature and previous research on what constitutes productive talks, we focus on questions and talk moves in this case study, where we follow three groups of PSTs during their practicum, practicing conducting productive talks in mathematics. Our research questions are: What kinds of questions do PSTs ask? What kinds of talk moves do they use? How do these questions and talk moves contribute to the PSTs breaking the IRE (Initiation–Response–Evaluation) pattern and moving towards more productive mathematics talks with complex exchanges of questions and responses? And furthermore: How can we use these findings to improve teacher education in this field? We find that leading productive talks in the mathematics classroom is a challenging task, but there is variation between our three groups in what they struggle with. In accordance with previous research, we also find that the third turn in the exchange, following up after a question and a response is a crucial point in the conversation. One recommendation for teacher education is that video filming and analysing classroom talks might help PSTs to become conscious of and improve on this point. Further research is needed both on long term effect of such practice and focus, and on other ways to improve classroom talks in mathematics and other subjects.

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.

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.

This study explores the impact of artificial intelligence (AI) integration on students' educational experiences. It investigates student perceptions of AI across various academic aspects, such as module outlines, learning outcomes, curriculum design, instructional activities, assessments, and feedback mechanisms. It evaluates the impact of AI on students' learning experiences, critical thinking, self-assessment, cognitive development, and academic integrity. This research used a structured survey distributed to 300 students through Microsoft Forms 365, yet the response rate was 29.67%. A structured survey and thematic analysis were employed to gather insights from 89 students. Thematic analysis is a qualitative method for identifying and analysing patterns or themes within data, providing insights into key ideas and trends. The limited response rate may be attributed to learners' cultural backgrounds, as not all students are interested in research or familiar with AI tools. The survey questions are about AI integration in different academic areas. Thematic analysis was used to identify patterns and themes within the data. Benefits such as enhanced critical thinking, timely feedback, and personalised learning experiences are prevalent. AI tools like Turnitin supported academic integrity, and platforms like ChatGPT and Grammarly were particularly valued for their utility in academic tasks. The study acknowledges limitations linked to the small sample size and a focus on undergraduate learners only. The findings suggest that AI can significantly improve educational experiences. AI provides tailored support and promotes ethical practices. This study recommends continued and expanded use of AI technologies in education while addressing potential implementation challenges.

This study examines the emotional labor of early childhood educators and its relationship with interactions involving children and parents, with a focus on emotional regulation and demographic influences. This study aimed to investigate the impact of emotional regulation strategies and demographic variables on educators’ emotional well-being during professional interactions. A quantitative approach was adopted, with data collected through structured questionnaires. The analysis concentrated on emotion suppression and surface acting in relation to well-being. Results indicated that teachers experienced considerable emotional burden, with emotion suppression being more prevalent than surface acting, particularly in interactions with parents. Fifty-three percent of educators reported a high emotional burden in parent-related suppression, compared to 38% in interactions with children. Additionally, 38% reported high suppression in self-regulation, while 29% experienced no burden from surface acting. Emotion suppression in parent interactions had the most significant impact on well-being (standardized coefficient = 0.4044, p < .001), followed by education level (coefficient = 0.1646, p < .001). Factors such as generation, teaching experience, salary, and certification were not statistically significant. The model explained 18.7% of the variance in emotional well-being. These findings align with existing literature that highlights the emotional burden of teaching and the psychological toll of unaddressed regulation challenges. Therefore, culturally and contextually appropriate suppression-management training, together with enhanced institutional support, is essential to reduce the emotional burden on Indonesian early childhood educators.