The use of GenAI in medical education in China and Indonesia: A comparative literature review

There is a heightened concern over undergraduate students being over‐reliant on Generative AI and using it recklessly. Reliance behaviours describe the frequencies and ways that people use AI tools for tasks such as problem‐solving, influenced by individual factors such as trust and AI literacy. One way to conceptualise reliance is that reliance behaviours are affected by the extent to which learners consciously evaluate the relative performance of AI and humans, suggesting the potential impacts of critical thinking on reliance. This study, thus, empirically investigates the relationship between critical thinking and reliance behaviours. Critical thinking includes disposition and skills. However, limited empirical studies have investigated how critical thinking influences learners' reliance behaviours when solving problems with Generative AI. Hence, the current study conducted path analyses to investigate how critical thinking is associated with reliance behaviours and how it mediates the effect of individual factors on reliance behaviours. We collected 808 survey responses on critical thinking disposition and skills, reliance behaviours (a self‐developed and validated scale, including reflective use, cautious use, thoughtless use, and collaborative use), trust towards AI, and AI literacy from undergraduates after a problem‐solving task with Generative AI. The results indicate that (1) critical thinking is positively associated with the collaborative, reflective, and cautious use of Generative AI, suggesting that these three types of use of Generative AI could be considered desirable behaviours in human–AI problem‐solving; (2) trust positively predicts thoughtless use; (3) critical thinking can offset the influence of trust on collaborative, reflective and cautious use; and (4) critical thinking can amplify the influence of AI literacy on reflective, cautious and collaborative use. This study contributes new insights into understanding the role of critical thinking in fostering desirable reliance behaviours, including reflective, cautious and collaborative use, and provides implications for future interventions when applying Generative AI for problem‐solving. Practitioner notes What is already known about this topic? Generative AI tools can potentially enhance problem‐based learning (PBL) by supporting brainstorming and solution refinement. Reliance behaviours in human‐AI collaboration are influenced by factors such as trust in AI and AI literacy. Strategy‐graded reliance emphasizes the reasoning process leading to reliance behaviours, focusing on thoughtful engagement with AI tools, and this cognitive process can be captured by critical thinking. What this paper adds? Critical thinking is positively associated with the reflective, collaborative, and cautious use of Generative AI. Critical thinking mediates the effects of trust and AI literacy on reliance behaviours, amplifying reflective, cautious and collaborative use while mitigating the thoughtless use of Generative AI. The study introduces a nuanced understanding of reliance behaviours by applying a strategy‐graded framework, emphasising cognitive engagement rather than a purely outcome‐based understanding of reliance behaviours. Implications for practice and/or policy Educational interventions could consider critical thinking when integrating AI tools in problem‐solving contexts. Students' trust in AI needs to be balanced with critical thinking skills to reduce overreliance and enhance thoughtful engagement with AI tools.

The integration of artificial intelligence (AI) in education has the potential to revolutionize teaching and learning, particularly in the development of students’ critical thinking skills. This study explores science instructors' familiarity, perceptions, and experiences with using AI to enhance students' critical thinking skills, as well as the level of institutional support for AI integration in teaching. A quantitative survey was conducted among 20 science instructors from higher education institutions in Isabela, Philippines. The findings reveal that while instructors acknowledge AI's potential to improve educational outcomes, there is a significant gap in formal AI training and literacy among educators. Positive correlations were found between AI literacy, AI integration, and critical thinking development, suggesting that as AI literacy increases, AI integration and enhancement of critical thinking skills also increase. Regression analysis identified AI integration as a significant predictor of critical thinking development. Challenges remain in the effective implementation of AI, including concerns about overreliance on AI-generated responses and the need for clear assessment guidelines. Interestingly, years of teaching experience did not significantly influence participants’ AI literacy, perceptions, or integration. This study highlights the importance of developing comprehensive AI literacy programs for educators and integrating AI into curriculum structures to balance AI-enhanced learning with human-centered pedagogy. These findings emphasize the need for thoughtful implementation and ongoing research to effectively leverage AI in promoting critical thinking skills in science education.

Generative AI (GenAI) is a disruptive technology likely to generate a major impact on faculty and learners in medical education. This work aims to measure the perception of GenAI among medical educators and to gain insights into its major advantages and concerns in medical education. A survey invitation was distributed to medical education faculty of colleges of allopathic and osteopathic medicine within a single university during the fall of 2023. The survey comprised 12 items, among those assessing the role of GenAI for students and educators, the need to modify teaching approaches, GenAI's perceived advantages, applications of GenAI in the educational context, and the concerns, challenges, and trustworthiness associated with GenAI. Responses were obtained from 48 faculty. They showed a positive attitude toward GenAI and disagreed on GenAI having a very negative effect on either the students' or faculty's educational experience. Eighty-five percent of our medical schools' faculty responded to had heard about GenAI, while 42% had not used it at all. Generating text (33%), automating repetitive tasks (19%), and creating multimedia content (17%) were some of the common utilizations of GenAI by school faculty. The majority agreed that GenAI is likely to change its role as an educator. A perceived advantage of GenAI in conducting more effective background research was reported by 54% of faculty. The greatest perceived strengths of GenAI were the ability to conduct more efficient research, task automation, and increased content accessibility. The faculty's major concerns were cheating in home assignments in assessment (97%), tendency for blunder and false information (95%), lack of context (86%), and removal of human interaction in important feedback processes (83%). The majority of the faculty agrees on the lack of guidelines for safe use of GenAI from both a governmental and an institutional policy. The main perceived challenges were cheating, the tendency of GenAI to make errors, and privacy concerns.The faculty recognized the potential impact of GenAI in medical education. Careful deliberation of the pros and cons of GenAI is needed for its effective integration into medical education. There is general agreement that plagiarism and lack of regulations are two major areas of concern. Consensus-based guidelines at the institutional and/or national level need to start to be implemented to govern the appropriate use of GenAI while maintaining ethics and transparency. Faculty responses reflect an optimistic and favorable outlook on GenAI's impact on student learning.

Critical thinking skills (CTS) are essential in medical education. Problem-based learning (PBL) effectively develops CTS, with generative AI (e.g., ChatGPT) offering enhancement potential. This study investigates how a tutor-managed ChatGPT-PBL model: (1) reconfigures tutor/peer roles and CTS compared to traditional PBL; (2) establishes predictive relationships between tutor/peer roles and CTS and (3) confirms optimal operational parameters for tutor-managed ChatGPT to enhance CTS. A quasi-experimental study assigned 170 medical students to either a ChatGPT-PBL or a traditional PBL group. Data from a 31-item survey assessing tutor and peer roles and CTS, along with learning logs and tutor observations for 36 participants, recorded AI engagement metrics (e.g., query frequency, multi-source validation, comparative questioning). The intervention used a pre-defined "3-2-60 Rule" (≥3 queries/session, ≥2 authoritative sources/claim, >60% comparative framing), derived from existing literature, to guide ChatGPT engagement. Interrelationships were examined. ChatGPT-PBL improved CTS outcomes, enhancing tutor-guided constructive/self-directed/contextual/collaborative learning and peer-driven information processing/communication/critical analysis. Regression identified collaborative learning and information processing as CTS predictors in both approaches, but ChatGPT shifted their influence: collaborative learning's role decreased while information processing's increased. High adherence to the "3-2-60 Rule" correlated with CTS gains, with high-engagement groups (>3 queries, ≥2 sources, comparative framing) outperforming peers. Tutor-managed ChatGPT reconfigures tutor/peer roles in PBL to enhance CTS development. Structured peer-ChatGPT-tutor interactions (following the 3-2-60 rule) contributed to enhancing CTS. Given ChatGPT's socioemotional limitations, future implementations should embed adversarial ChatGPT tasks and ethical transparency protocols.

Background: An ongoing challenge for medical education in the twenty-first century is determining the best method to foster problem-solving and critical thinking in learners. These higher-order aptitudes help to prepare medical doctors for practice in a rapidly evolving health system. In medical education, Problem-Based Learning (PBL) is an instructional pedagogy in which pupils are challenged to seek answers to authentic patient scenarios in small groups. PBL techniques are proposed as one method to enhance pupils’ learning abilities including critical thinking and problem-solving. Aim: This systematic review was conducted to search for evidence from the past fifteen years of literature, demonstrating the capability of PBL to improve critical thinking and problem-solving skills for medical students. Review Question: Is there evidence to support the capability of PBL to improve problem solving and critical thinking skills in medical students? Methods: The search process was conducted through electronic databases on publications related to the impact of PBL, particularly, on two fundamental skills; critical thinking and problem-solving for medical students. The search process was restricted to publicationsbetween January 1, 2005 and December 31, 2019. Four electronic databases were searched, namely; Medline, PubMed, EMBASE and Scopus. The Best Evidence Medical Education (BEME) guidelines were utilised to guide the way this systematic review was conducted. Quality assessment was performed through rating the evaluation methods of the included studies. This rating was through employing a five-point Likert scale (1= strongly disagree to 5= strongly agree) for each study in relation to three items; the appropriateness of study design, the implementation of the study as well as the appropriateness of data analysis. The rating for each study was then mapped to a grade from grade 1 (low) to grade 5 (high), which aligns with the BEME strength of the study findings. Results: Searching the four aforementioned databases produced 657 publications, including 249 duplicates. Therefore, 408 publications were screened based on their titles against inclusion and exclusion criteria, leaving 86 articles to screen their abstracts. A further 9 articles were manually obtained such that a total of 95 articles were obtained for a review of their abstracts. Forty-one met the criteria for full text review. Following the full text review, twenty-nine articles were excluded. Therefore, twelve studies were included in this systematic review. The BEME strength of study findings were as follows; only two of the reviewed studies were graded as grade 5, four were graded as grade 4, and six were graded as grade 3. Of the twelve studies reviewed, only five studies provided evidence in support of the capability of PBL to improve critical thinking and problem-solving skills among medical students. Two of these five studies were graded as grade 5 and two were graded as grade 4, while one was graded as grade 3. Discussion: The available evidence in this systematic review provided limited support of the claim that PBL improves medical students’ critical thinking and problem-solving aptitudes. Only five studies provided evidence in support of this claim, while the remaining seven studies did not. Two of these seven studies assessed only the knowledge, comprehension, and application domains, as their evaluation of problem-solving and critical thinking abilities was based on student perspectives. A further two of these seven studies, where the description provided either for case-analysis tests or modified essay questions, did not give an actual indication for measuring critical thinking and problem-solving skills. Another two of these seven studies did not describe their written tests i.e. case-analysis tests and proxy questions that are purported to measure higher-order skills, including critical thinking and problem-solving. This prevented the use of the findings from these two studies as evidence to support the specified review question. The remaining study reported that PBL students’ scores in the final assessment did not improve significantly (p>0.05) compared to the initial assessment. Conclusion: There is very little published evidence over the last fifteen years supporting the claim that PBL improves critical thinking and problem-solving skills in medical students. Therefore, recent practice is not based on evidence. As such, investigations are required to legitimise the claims that PBL improves critical thinking and problem-solving skills for medical students. Key words: Problem-Based Learning, Critical Thinking and Problem-Solving Skills, Medical Students

For prospective elementary education teachers, critical thinking and collaboration skills in project-based science learning can impact environmental awareness. Critical thinking and collaboration skills can affect prospective teachers' environmental awareness differently, especially in science learning with environmental material. This research aims to determine the effect of critical thinking and collaboration skills on environmental awareness. Correlational research was used to determine the relationship between the two variables. Research data was obtained from 114 prospective Elementary Education teachers at UIN Maulana Malik Ibrahim Malang through project-based learning. Assessment of critical thinking skills was based on reports or essays from projects undertaken. The collaboration instrument was based on rubrics and peer questionnaires. The environmental awareness instrument used a 27-item questionnaire. The questionnaire was measured using a Likert scale of 1 (strongly disagree) – 4 (strongly agree). The data obtained was tested using SEM to determine the effect of critical thinking and collaboration skills on environmental awareness. The research results show that critical thinking and collaboration skills positively affect environmental awareness. This is indicated by a P-value for critical thinking skills is 0.047 0.05 and a P-value for collaboration skills is 0 0.05. Collaboration skills have a stronger effect on environmental awareness than critical thinking skills (path coefficients = 0.766). Indicators of collaboration skills tend to emphasize the aspect of caring more about others and the surrounding environment. The suggestion for further research is needed to see the effects of other variables on environmental awareness in project-based science learning, such as creative thinking and communication skills.

Mitigating generative AI inaccuracies in soil biology

Artificial Intelligence (AI) is revolutionizing the field of health sciences, reshaping how we teach, learn, and practice medicine. As AI technologies become increasingly integrated into healthcare systems, their impact on health sciences education cannot be overstated. From personalized learning experiences to advanced diagnostic training, AI is poised to enhance the quality and accessibility of education for future healthcare professionals. However, this transformation also raises critical questions about ethics, equity, and the future role of educators in an AI-driven world. The transformative role of Artificial Intelligence (AI) in health sciences education is increasingly recognized as a pivotal factor in shaping the future of medical training and practice. As AI technologies continue to evolve, their integration into educational curricula presents both opportunities and challenges that must be carefully navigated to enhance the learning experience for future healthcare professionals. One of the most significant contributions of AI to health sciences education is its ability to personalize learning. Traditional teaching methods often follow a one-size-fits-all approach, which can leave some students struggling to keep up while others are not sufficiently challenged. AI-powered platforms, such as adaptive learning systems, analyze individual student performance and tailor content to meet their unique needs. For example, tools like Osmosis and AMBOSS use AI to provide customized study plans, ensuring that students focus on areas where they need the most improvement (Topol, 2019). This personalized approach not only improves learning outcomes but also fosters a more inclusive educational environment. AI is also transforming clinical training by simulating real-world scenarios. Virtual patient simulations, powered by AI, allow students to practice diagnosing and treating conditions in a risk-free environment. These simulations can replicate rare or complex cases that students might not encounter during their clinical rotations. For instance, platforms like Touch Surgery and SimX use AI to create immersive surgical and emergency care simulations, providing students with hands-on experience before they enter the operating room (McGaghie et al., 2011). Such tools bridge the gap between theory and practice, preparing students for the complexities of modern healthcare. Moreover, AI is enhancing the role of educators by automating administrative tasks and providing data-driven insights into student performance. Grading, attendance tracking, and even curriculum design can be streamlined using AI, allowing educators to focus on mentoring and engaging with students. AI-driven analytics can also identify at-risk students early, enabling timely interventions to support their academic success (Wartman & Combs, 2018). By augmenting the capabilities of educators, AI empowers them to deliver more impactful and student-centered teaching. AI's potential to revolutionize health sciences education lies in its ability to personalize learning experiences and improve educational outcomes. For instance, AI-driven tools can facilitate realistic simulations and automated assessments, allowing students to engage in practical scenarios that mimic real-world clinical situations (Santos & Lopes, 2024). This capability not only enhances the learning process but also prepares students for the complexities of patient care in a technology-driven environment (Grunhut et al., 2022). Furthermore, the incorporation of AI into curricula can foster critical thinking and decision-making skills, essential for navigating the ethical dilemmas that arise in medical practice (Grunhut et al., 2022). Despite the promising applications of AI in education, the integration of these technologies into medical curricula has been slow. A scoping review highlighted that many medical schools have yet to adopt AI training, primarily due to a lack of systematic evidence supporting its implementation (Lee et al., 2021). Additionally, concerns regarding data protection and the ethical implications of AI use in healthcare education have been raised, indicating a need for comprehensive AI education that addresses these issues (Veras et al., 2023; Frehywot & Vovides, 2023). Students have expressed a desire for more robust training in AI, emphasizing the importance of understanding its role in healthcare delivery and decision-making processes (Ahmad et al., 2023; Derakhshanian et al., 2024). Moreover, the rapid advancement of AI technologies necessitates continuous curriculum updates to keep pace with emerging trends. As noted in recent literature, the integration of AI into biomedical science curricula should include subjects related to informatics, data sciences, and digital health (Sharma et al., 2024). This approach not only equips students with the necessary skills to utilize AI effectively but also prepares them for the evolving landscape of healthcare, where AI will play an integral role in diagnostics, treatment personalization, and patient management (Santos & Lopes, 2024; Secinaro et al., 2021). However, the implementation of AI in health sciences education is not without challenges. Ethical considerations surrounding AI's impact on healthcare equity and the potential for bias in AI algorithms must be addressed (Frehywot & Vovides, 2023; Han et al., 2019). Ensuring that AI technologies are used responsibly and equitably in education and practice is crucial to avoid exacerbating existing disparities in healthcare access and outcomes (Rigby, 2019). Furthermore, the lack of faculty expertise in AI poses a significant barrier to its integration into medical education, highlighting the need for targeted training and resources for educators (Derakhshanian et al., 2024). However, the integration of AI into health sciences education is not without challenges. Ethical concerns, such as data privacy and algorithmic bias, must be addressed to ensure that AI tools are used responsibly. Additionally, there is a risk of over-reliance on AI, potentially undermining the development of critical thinking and clinical judgment skills. Educators must strike a balance between leveraging AI’s capabilities and preserving the human elements of teaching and learning. Equity is another pressing issue. While AI has the potential to democratize education, access to these technologies remains uneven. Institutions in low-resource settings may struggle to adopt AI-driven tools, exacerbating existing disparities in global health education. Policymakers and educators must work together to ensure that the benefits of AI are accessible to all, regardless of geographic or socioeconomic barriers. In conclusion, AI is a powerful tool that holds immense promise for transforming health sciences education. By personalizing learning, enhancing clinical training, and supporting educators, AI can help prepare the next generation of healthcare professionals to meet the demands of an increasingly complex healthcare landscape. However, its integration must be guided by ethical principles and a commitment to equity, However, the successful integration of AI into educational curricula requires a concerted effort to address ethical concerns, update training programs, and equip both students and faculty with the necessary knowledge and skills. As the healthcare landscape continues to evolve, embracing AI in education will be essential for fostering a new generation of healthcare providers who are adept at leveraging technology to improve patient care. As we embrace this technological revolution, we must remember that AI is not a replacement for human expertise but a complement to it. The future of health sciences education lies in the synergy between human ingenuity and artificial intelligence.

This paper examines the correlation of mathematical critical thinking and creative thinking skills towards students' mathematical achievements. A total of 115 eighth grade students from three schools in Sleman Regency were involved as the subject of this research. Data were obtained from the results of critical thinking skills test, the results of creative thinking skills test, and the results of mathematical achievement test on the learning material that students had studied in the previous semester. The instrument for testing critical thinking skills was the essay questions which measure the aspects of critical thinking skills, namely inference, analysis, evaluation, and interpretation, while the instrument for creative thinking skills test was also the essay questions which measure the aspects of creative thinking skills, namely originality, flexibility, and fluency. Besides, the data for the students' mathematical achievements were obtained from the report of mathematics achievement test prepared by the Mathematics Teachers' Working Group. The correlation of these variables was analyzed through multiple regression test. The analysis resulted a positive relationship between the mathematical critical thinking and creative thinking skills towards the mathematical achievement indicated by the regression coefficient R = 0.721 and R2 = 0.52. These values showed that the influence of mathematical critical thinking and creative thinking skills on the students' mathematical achievements was 52%, whereas 48% was influenced by other factors. Then, the coefficient value of creative thinking variable was β1 = 0.363 and the coefficient value of critical thinking variable was β2 = 0.477. These values indicated that if the creative thinking skill increases by one unit, the mathematical achievement increases by 0.363, on the other hand, if the critical thinking skill increases by one unit, the mathematical achievement increases by 0.477.

This research is motivated by the findings of problems in economics learning including: in economics learning students are passive; lack of critical thinking activity and creativity; teacher-centered learning (teacher centered); The learning model used by teachers tends to be monotonous. This research aims to determine the implementation of the model problem based learning to develop students' critical thinking skills in economics learning. The research method is a case study with a qualitative approach, data is collected through interviews, observation and documentation of the implementation of learning to develop critical thinking skills. The results of the research show that planning economic learning using models problem based learning to develop highly structured and systematic critical thinking skills. Implementation of economic learning with models problem based learning Overall, it has succeeded in creating a learning environment that supports the development of students' critical and analytical thinking skills. Assessment of economic learning with models problem based learning has been designed and implemented well, so that students' critical thinking, problem solving and collaboration skills develop optimally. Supporting factors for learning economics with models problem based learning really supports the development of students' critical thinking skills. Factors inhibiting economic learning with models problem based learning developing critical thinking skills is a very serious challenge. Efforts to overcome barriers to economic learning with models problem based learning can develop students' critical thinking skills effectively.

Monotonous learning activities and a lack of development of critical thinking skills in students cause low critical and creative thinking skills. Based on this, the purpose of this study is to analyze the effect of STEAM Based Learning with Loose Part Media on the Critical Thinking and Creative Thinking Skills of Group B Children. The research method employed in this study is a quasi-experimental design. The design of this study employs a post-test-only control group design. The population in this study consisted of 5-to 6-year-old kindergarten students, with a sample size of 30 students. In this study, the sampling technique employed was purposive sampling, with a total sample of 30 students. The method used in collecting data was a test. The instrument used for data collection was a checklist sheet with a rating scale. The data analysis technique used the t-test. The results of the study showed a significant difference between the experimental group and the control group in terms of critical thinking skills. The average difference value (indicates that the average score of children's critical thinking skills in the experimental group given treatment is higher than that of the control group. Second, there is a significant difference between the experimental group and the control group in terms of creative thinking skills. The average difference value indicates that the average score of the children's creative thinking skills in the experimental group, given the treatment, is higher than that of the control group. It is concluded that the STEAM approach, assisted by Loose Parts media, has a positive effect on improving critical and creative thinking skills in children in Group B.

This research is the tendency of students who only received learning material sourced from teachers through lectures, so that students are less active in the learning process more towards teacher centered. Because during the learning process in the classroom only emphasize knowledge of low-level thinking, students should be able to develop the ability of critical thinking and argumentation skills of students during the learning process so that it will get used to argue and higher level thinking. This study aimed to analyze the implementation of PBL models to improve the ability of critical thinking and argumentation skills as well as to determine the relationship between the ability of critical thinking skills and argumentation skills. The method used Nonequivalent Control Group Design. The population in this study is the class X.1 and X.2 Senior High School PGRI 1 Majalengka in 2015/2016 school year and totaling 47 students. Sampling was done by using cluster random sampling, were divided into 2 groups: PBL model class with 24 students and other class are not using PBL as many as 23 students. Instruments in this research is the description of critical thinking skills and argumentation skills test, observation sheets and questionnaires for students. Hypothesis test using parametric statistical tests in this case to test the hypothesis of implementation PBL models to enhance the critical thinking skills using Manova test was obtained p <0.05 is 0.01 <0.05, which means there is an increased implementation of the PBL model of critical thinking skills of students and hypothesis test of� implementation PBL model to enhance argumentation skills of was obtained p <0.05 is 0.03 <0.05, which means there is an increased implementation of the PBL model of argumentation skills of the students, as well as the correlation coefficient to determine the relationship of critical thinking skills and the skills of argumentation studied through the PBL model obtained p <0.05 is 0.049, which means there is an interaction between critical thinking skills and argumentation skillsKeywords: PBL Model; Critical Thinking Skills; Argument Skills

Introduction and Purpose: Emotional intelligence and critical thinking are both basic elements of achievement of success, especially when they are raised in education area and in medical education. Thus, it seems that the students with higher ability in critical thinking and emotional intelligence certainly achieve better academic achievement compared to those who lack such characteristics. Current research was conducted aiming at investigating critical thinking and emotional intelligence skills and relationship with students’ academic achievement in the last year of nursing in Zahedan University of Medical Sciences during 2016- 2017. Materials and Methods: This research is descriptive – analytical research of cross-sectional type. Research statistical population included all senior nursing students of Zahedan University of Medical Sciences (n=50), and total counting was used as sampling method. The California Critical Thinking Skills Test (CCTST) and Bar-On model of emotional-social intelligence (ESI), which has already been used in Iran, were used to collect data. Therefore, their validity and reliability is confirmed. In this study, Cronbach’s alpha coefficient was used to determine reliability of the questionnaires. Reliabilities were calculated for the Emotional Intelligence Questionnaire (0.891), critical thinking questionnaire (0.924) and academic achievement questionnaire (0.883). In addition, in order to measure the academic achievement, GPA of two last semesters was considered as the criterion. Descriptive statistics and inferential statistics were used to analyse the data. SPSS (22) and Smart PLS software were used. Findings: Findings showed that there is significant relationship between critical thinking and emotional intelligence skills and academic success of senior nursing students in terms of marital status. In addition, findings indicated significant relationship between critical thinking skills and academic achievement of senior nursing students. In addition, results showed there is relationship between emotional intelligence and academic achievement of senior nursing students. Discussion and Conclusion: Considering significant relationship between critical thinking and academic success of senior nursing students as well as significant relationship between emotional

Theory-informed and evidence-based educational offerings promote student learning and equity but are time-consuming and require health professions educators to have content expertise in inclusive instructional design. While -generative AI (GAI) offers the potential to overcome these barriers, educators must learn to effectively leverage GAI tools for evidence-based instructional design. In this work, the authors piloted and evaluated a 2-part experiential learning activity to equip educators to effectively engage with GAI for instructional design purposes. The authors implemented the GAI innovation in the graduate-level "Teaching 100" course (enrollment n = 27) at Harvard Medical School September-November 2023. Educators used GAI to annotate their lesson plans to identify application of, and opportunities to incorporate, evidence-based principles of teaching and learning. The 2-part assignment provided scaffolded instruction on prompt engineering and engaged learners in metacognitive reflection on AI-generated content. The authors evaluated the effectiveness of the GAI innovation according to the Kirkpatrick Model: descriptive analysis of self--reflections evaluated educators' subjective experience (Level 1) and planned behavioral changes (Level 3), while quantification of prompt quality pre-/post-instruction measured educators' learning (Level 2). Among educators who completed the 2-part assignment (n = 17/27, 62% completion rate), the quality of -educator-generated AI prompts improved following instruction in prompt engineering: pre-instruction 1.4 (1.2) (mean [SD]) vs post-instruction 4.0 (0.8). The difference in means (2.6 points) was statistically significant (P < .0001, 95% CI [1.9, 3.3]). Metacognitive reflections revealed specific actions educators planned to pursue to implement GAI feedback to improve their instructional design. Educators reported that AI-based assignments enhanced their learning. The authors are developing a stand-alone, interactive GAI tool to be broadly deployed as a faculty development instructional design resource. This future work will yield a scalable solution to the challenge of developing AI literacy among health professions educators to leverage GAI for theory-informed and evidence-based instructional design.

The purpose of this study was to analyze the effectiveness of STEM-PjBL learning on students' critical thinking, creative thinking, communication, and collaboration (4C) skills. This research is quantitative with a one-group pretest-posttest design. The research samples were 106 class XI State Senior High School 16 Semarang students. Quantitative data on critical thinking skills were analyzed using the N-gain test, while other data were analyzed descriptively. The results showed increased students' critical thinking skills based on the N-gain test. The paired sample t-test results in the SPSS 28 program obtained a significance value/Sig. (2-tailed) of 0.001, there were differences in critical thinking skills before and after STEM-PjBL learning. STEM-PjBL learning effectively trained students' creative, collaborative, and communicative thinking skills with high categories. This learning effectively trained students' critical thinking, creative thinking, communication, and collaboration skills