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This study examines the utilization of ChatGPT by pre-service mathematics teachers during the 5E lesson planning process, focusing on its affordances, constraints, and potential as a supportive tool in education. Twenty-one pre-service mathematics teachers, selected through purposive sampling, participated in the study. Data collection included 5E lesson plans, ChatGPT interaction transcripts, and participant interview responses, which were analyzed using content analysis within the framework of the instrumental approach. ChatGPT was utilized for lesson planning across categories addressing instructional and pedagogical content, encompassing fourteen distinct purposes distributed across the stages of the 5E lesson plan design: five for the engagement stage, five for exploration, six for explanation, five for elaboration, and four for evaluation. Interviews revealed both the affordances and constraints of ChatGPT, noting that while it provided creative and practical ideas, it often required well-structured prompts to yield relevant results. Despite its challenges, participants expressed their intention to use ChatGPT professionally to enhance lesson planning and instructional practices. ChatGPT is a valuable yet evolving tool for fostering innovation and efficiency in mathematics education, with implications for teacher training and future research on AI integration.

This paper investigated the integration of a Lesson Study Model (LSM) into distance STEM education during the COVID-19 pandemic. The study focused on six dimensions: (1) STEM education in distance learning, (2) Lesson Study (LS), (3) lesson planning processes, (4) challenges of lesson planning, (5) evaluation and assessment methods, and (6) strategies, methods, and techniques. The sample consisted of 24 science teachers recruited using criterion sampling, which is a purposive sampling method. A case study, which is a qualitative research method, was the design of choice. Data were collected through interviews, videotapes, and expert observations. The data were analyzed using inductive content analysis. Themes, categories, and codes were developed in accordance with the research purpose. Participants had positive opinions about the LSM, STEM education, and distance learning. Participants stated that the LSM activities within distance learning contributed to pedagogy and content knowledge in the STEM education process. The challenges faced by participants were unfavorable environmental conditions, time management issues, and a lack of knowledge and experience in lesson planning. Expert observations and videotapes corroborate these results, indicating that the LSM integrated with STEM education results in higher quality STEM lesson planning and teaching. Moreover, distance learning platforms are promising ways to ensure the professional development of teachers during the pandemic.

Artificial intelligence (AI) and machine learning (ML) are poised to have a substantial impact in the health care space. While a plethora of web-based resources exist to teach programming skills and ML model development, there are few introductory curricula specifically tailored to medical students without a background in data science or programming. Programs that do exist are often restricted to a specific specialty. We hypothesized that a 1-month elective for fourth-year medical students, composed of high-quality existing web-based resources and a project-based structure, would empower students to learn about the impact of AI and ML in their chosen specialty and begin contributing to innovation in their field of interest. This study aims to evaluate the success of this elective in improving self-reported confidence scores in AI and ML. The authors also share our curriculum with other educators who may be interested in its adoption. This elective was offered in 2 tracks: technical (for students who were already competent programmers) and nontechnical (with no technical prerequisites, focusing on building a conceptual understanding of AI and ML). Students established a conceptual foundation of knowledge using curated web-based resources and relevant research papers, and were then tasked with completing 3 projects in their chosen specialty: a data set analysis, a literature review, and an AI project proposal. The project-based nature of the elective was designed to be self-guided and flexible to each student's interest area and career goals. Students' success was measured by self-reported confidence in AI and ML skills in pre and postsurveys. Qualitative feedback on students' experiences was also collected. This web-based, self-directed elective was offered on a pass-or-fail basis each month to fourth-year students at Emory University School of Medicine beginning in May 2021. As of June 2022, a total of 19 students had successfully completed the elective, representing a wide range of chosen specialties: diagnostic radiology (n=3), general surgery (n=1), internal medicine (n=5), neurology (n=2), obstetrics and gynecology (n=1), ophthalmology (n=1), orthopedic surgery (n=1), otolaryngology (n=2), pathology (n=2), and pediatrics (n=1). Students' self-reported confidence scores for AI and ML rose by 66% after this 1-month elective. In qualitative surveys, students overwhelmingly reported enthusiasm and satisfaction with the course and commented that the self-direction and flexibility and the project-based design of the course were essential. Course participants were successful in diving deep into applications of AI in their widely-ranging specialties, produced substantial project deliverables, and generally reported satisfaction with their elective experience. The authors are hopeful that a brief, 1-month investment in AI and ML education during medical school will empower this next generation of physicians to pave the way for AI and ML innovation in health care.

The COVID-19 crisis has forced education systems around the world to switch hurriedly from learning in class to learning via online technology. One of the common platforms worldwide for teaching online was zoom. Working under uncertain conditions and facing rapid changes are characteristics of the twenty-first century. Coping adaptively with these challenges requires teachers to apply twenty-first century skills such as creativity and metacognition in their teaching. The purpose of the present study was to examine whether teachers integrate metacognition and creativity in their online lessons more than in classroom instruction. To examine the research question, we analyzed 50 lesson reports (25 for each learning environment) using a mixed-method design model. We used a performance assessment that was based on a creativity metacognitive teaching reports index. Teachers reported greater use of the 'debugging' metacognitive component in online lessons than in classroom lessons. Also, an online environment could provide a suitable platform for promoting students' learning process and encourage teachers to be more creative in terms of diversifying their teaching methods and developing student’s creativity. However, the originality component of creativity was less pronounced in online lesson reports. These results can contribute to the field of blended learning and to the literature dealing with the adaptation of teaching to learning environments in the twenty-first century in general and during pandemics in particular.

Technology has permeated many sectors of contemporary life, including education. Seamless learning combines technology and education to allow educational practitioners to overcome constraints such as place, distance, and time. Student-teachers should master a variety of knowledge, not just about subjects relevant to their major but also about pedagogy; consequently, they need to master pedagogical competencies. In this experimental study, a pretest–posttest design is used to investigate the influence of seamless learning as a learning technique in lesson plan preparation. The participants in this research were student-teachers at a teacher training institution in Surabaya, Indonesia. The purpose of this study was to investigate how implementing seamless learning helps improve student-teacher abilities in lesson planning. This study demonstrated that, of the five factors utilized, there was no negative effect of seamless learning on the variable observed; on the contrary, all variables showed positive and substantial influences in improving student-teacher abilities in designing lesson plans.

This study focuses on teacher development through the continually action workshop of technology-enhanced integration STEM framework. The primary goal was the ambition to integrate active learning activity into national teacher training for gifted classrooms, which is provided by The Institution for the Promoting of Teaching Science and Technology—with teaching practice, aligned with professional development on teacher’s understanding of STEM activity. The study aims to identify how teachers develop their understanding of Raiwa-STEM activity, which is shown in their lesson plans. Therefore, the study focused on developing 900 in-service teachers who were science, mathematics and computer teachers that participated in this national teacher training. Data sources throughout the research project consisted of Lesson Plan Assessment, Semi-structure interviews, and document analysis. Interpretive framework was used to analyze the data. Research findings indicate that these research participants who were the teachers work closely with gifted students that have developed their understanding on the Raiwa-STEM activity. Collaboration work among teachers from different subjects encourages them to understand how the STEM activity looks like and how it transfers into an active classroom. After the teachers have experienced with Raiwa activities, they were assigned to develop their classroom implementations which were shown in their Raiwa-STEM lesson plans. From data analysis the teachers can design a connecting STEM lesson into student’s daily life, and create evaluation and assessment of the STEM classroom. The development of teachers’ understanding and practice is presented in their lesson plans that are produced during training. 75.90 % of the total STEM Lesson plans are of a good level. Moreover, the study also indicates the importance of co-working among teachers from different expertise areas in sub activities preparation that can build interdisciplinary connection of STEM concepts. Raiwa is an example of interdisciplinary instruction which can provide stud ents the use of technology-integrated knowledge and the potential of STEM-focused education to provide all students with the opportunities of STEM experience.

A lesson plan is an action plan that shows how to achieve the objectives of a lesson step by step in a certain period of time in the teaching of a subject. Lesson planning is one of the important elements of teacher education. However, research shows that pre-service teachers have problems in lesson planning. Artificial intelligence can produce solutions to the problems experienced by pre-service teachers. For this purpose, pre-service teachers need to be able to use this tool effectively, recognize its possibilities and limitations, and approach it with a critical perspective. The purpose of this research is to determine what support Microsoft Copilot offers to pre-service teachers in preparing lesson plans for reading education in Turkish lessons and how they evaluate this support. The method of the research is case study. The study group consists of 24 students. The data were collected through reflective diaries, lesson plans, and interviews. Descriptive and content analysis were applied to the data. As a result of the research, it was determined that teacher candidates sought support for every stage of the course. Both positive and negative opinions emerged in the same codes regarding the support offered by Copilot. Accessing the source sites, activity ideas, overall plan, and images are the codes where positive opinions are concentrated, while text creation, subject area knowledge, and question/rubric preparation are the codes where negative opinions are concentrated. Participants stated that attention should be paid to the accuracy and adequacy of the content and the accuracy of the questions and to give sufficient detail when requesting information. These results show that Copilot should be improved in terms of Turkish. However, the results also suggest that AI tools should be included in teacher education despite their limitations. Pre-service teachers evaluate the outcomes of the program with their prior knowledge. This approach is important for the development of pedagogical content knowledge and better lesson planning. План уроку – це план дій, який показує, як крок за кроком досягти цілей уроку за певний проміжок часу при викладанні предмета. Планування уроку є одним з важливих елементів педагогічної освіти. Однак дослідження показують, що вчителі-початківці мають проблеми з плануванням уроків. Штучний інтелект може запропонувати рішення проблем, з якими стикаються вчителі-початківці. Для цього вчителі повинні вміти ефективно використовувати цей інструмент, критично підходити до його використання, усвідомлювати його можливості та обмеження. Мета цього дослідження – визначити, яку підтримку Microsoft Copilot пропонує вчителям-початківцям у підготовці планів уроків для навчання читання на уроках турецької мови і як вони оцінюють цю підтримку. Метод дослідження – кейс-стаді. Дослідницька група складалась із 24 студентів. Дані були зібрані за допомогою щоденників рефлексії, планів уроків та інтерв’ю. До даних було застосовано описовий та контент-аналіз. У результаті дослідження було визначено, що кандидати на посаду вчителя шукали підтримки на кожному етапі курсу. В одних і тих самих кодах з’явились як позитивні, так і негативні відгуки про підтримку, яку пропонував «Copilot». Доступ до сайтів-джерел, ідеї для занять, загальний план та зображення – це ті коди, де сконцентровані позитивні відгуки, тоді як створення тексту, знання предметної області та підготовка запитань/рубрик – це ті коди, де сконцентровані негативні відгуки. Учасники зазначили, що слід звернути увагу на точність і адекватність змісту та точність запитань, а також надавати достатню кількість деталей при запиті інформації. Ці результати показують, що «Copilot» потребує вдосконалення для турецької мови. Однак результати також свідчать про те, що інструменти штучного інтелекту мають бути додані до програми підготовки вчителів, незважаючи на їхні обмеження. Учителі-практики оцінюють результати програми, спираючись на свої попередні знання. Такий підхід є важливим для розвитку знань педагогічного змісту та кращого планування уроків.

The present study is an extension of studies that measure pre-service teachers’ Technological Pedagogical Content Knowledge (TPACK) confidence. It provides new perspectives on pre-service teachers’ TPACK by shifting the focus to concrete concerns and strengths indicated by pre-service teachers. The target group consists of a cohort of first-year pre-service teachers (N = 86) from a Finnish university. The data used in this study were 86 lesson plans with integrated technology written by first-year pre-service teachers, with a specific section where students outlined their confident and challenging areas in the lesson plan. These sections were analysed quantitatively through the theoretical lens of TPACK. Four TPACK areas were found confident, challenging or both confident and challenging for students. For these first-year pre-service teachers, pedagogical knowledge played the most important role, and the outcomes concretize specific aspects of pedagogical knowledge that can be addressed to develop TPACK in teacher education. The results provide important perspectives on pre-service-teachers’ development of TPACK, revealing the important position of pedagogical knowledge and detailed perspectives on how pre-service teachers view their readiness to use ICT in education.

PurposeDespite numerous kinds of research regarding the potential of lesson study (LS) in internship and microteaching in teacher education curricula, studies examining the adaptation of LS in the lesson planning (LP) course have not been established. To fill this gap, this study aims to explore the perceptions of pre-service biology teachers of an adapted LS in the LP course toward their instructional design skills and teaching competency.Design/methodology/approachThis study opted for basic qualitative studies. The participants were eleven pre-service biology teachers in their third year who had already taken a LP course. Data were collected through semi-structured interviews. Collected data were then transcribed and thematically analyzed using grounded theory and focused on participants' perceptions about the development of their teaching competency in lesson planning through LS.FindingsThe findings revealed that participants appreciated the planning and consultation phases, teaching practice, peer observation as well as observer feedback from the reflection phase in supporting the development of their basic teaching skills. There was also a change in their perceptions related to the concept of teaching.Originality/valueThe findings of this study offer insight regarding the benefits and challenges of involving pre-service biology teacher students in the LS for biology teacher education programs with a focus on the method or LP course.

The current study aimed to sightsee the effectiveness of Mathematical knowledge for teaching (MKT) through lesson planning and technological pedagogical content knowledge (TPACK) on Rwandan mathematics tutors in teachers' training colleges. A quasi-experimental research design was used with a control and an experimental group. The experimental group received the intervention on developing MKT through the lesson plan and TPACK, while the control group used a standardized format lesson plan templates as their primary method for preparing instructional materials. In both groups, we analyzed 88 lesson plans in three stages (before, during, and after intervention). The collected lessons were analyzed using a standardized and validated Lesson Plan Analysis Protocol (LPAP). The result revealed that, before the intervention, teachers in both groups struggled with preparing an effective lesson, with an average of 57.8% and 54% in the control and experimental groups, respectively, indicating that the prepared lesson could not be effectively taught. During the intervention, tutors in the experimental group were facilitated to improve their lesson preparation. In this regard, the average was increased to 61.37% in the experimental group, compared to 57.67% in the control group. Moreover, the post-intervention results revealed significant divergence in the two groups' performance, with an average of 82.40% (indicating a very good lesson plan that can be taught) in the experimental group and 59.73% (a fair lesson plan) in the control group. The inferential results showed a statistically significant difference in lesson preparation between Mathematics tutors in the experimental and control groups ( p  < 0.05) in favor of the experimental group during and after intervention. The research underscores the need for educational stakeholders and continuous professional development organizers to incorporate TPACK in lesson planning during teacher training to promote a more comprehensive and forward-looking approach to tutor preparation.