Safety competence promotion in secondary education - A case of the Finnish NouHätä! Programme.

The Nouhätä! safety education programme has been organised in secondary schools in Finland for over 25 years. However, to date, it has not been systematically evaluated. The purpose of this quantitative survey is to provide information about good practices, benefits and limitations of the NouHätä! Programme; this has been done by answering the research question what variables explain pupils' safety competence after participating in a NouHätä! safety education programme? The results show that the best learning outcomes in safety education are achieved when training is organised in collaboration with teachers and safety experts. Practical training also seems to have a significant impact on the safety competence of pupils. The results suggest that background variables like school success and the sources of safety knowledge affect the level of pupils' safety competence. The results of the study can be used to develop the programme and other safety education programmes for children and young people.

Serious games to assess students.

This paper describes experiments where students were assessed using the Serious Games (SGs) they created. The first experiment is with students attending our "Business Games" module for the master's degree in "Innovation" at the Tunis Engineering School. The second experiment involved students enrolled in our "Introduction to Data Science" module of the master's degree in "Data Sciences" at the High Institute of Management of Tunis. We requested each section's students to design a game related to the covered module. Through innovative assessment practices, we hope to motivate students. We aimed to confirm that creating games reinforced students' mastery of the module content. At the end of the semester, students presented their games, and some of them are described here. The results of the questionnaire filled out by the students at the end of these experiments revealed that, despite their different profiles, they appreciated these experiments and their influence on mastering the modules' contents. This article introduces the SG and its use in assessment. It also discusses the importance of creating serious games by the learner and how it affects learning. Even though some students mentioned that creating their games took more time than studying for a traditional exam, they believed the experiment as a whole was positive and enjoyed the innovation. Therefore, to construct the game, students reviewed the content of the module more than once. Additionally, students asked for the experiment to continue and expand to additional modules the following year.

Intelligent recommendation system for College English courses based on graph convolutional networks.

With the rapid development of international communication, the number of English courses has shown an explosive growth trend, which has caused a serious problem of information overload, resulting in poor teaching performance of recommended English courses. To solve this problem, this paper proposes a graph convolutional neural network model based on College English course texts, students' major, English foundation and network structure characteristics. First, by analyzing the relevant data of College English courses and combining with graph neural network, an English course recommendation algorithm model based on the College English learning strategy of proximity comparison is proposed. Then, the College English texts are taken as feature input, and multi-layer graph convolutional neural network is used to process the above graph neural network structure. Attention mechanism is introduced to enhance the representation of graph features in College English skills. Finally, multi-layer attention model is used to process the courses that users have learned, and intelligent course recommendation is made by combining the multi-layer attention modeling of College English skills. The experimental data show that the proposed method achieves the best performance compared with the commonly used College English course recommendation method.

Exploring success factors and relationships in virtual learning using ISM and fuzzy MICMAC analysis.

The COVID-19 pandemic's consequences have led to a global change in educational settings towards online learning. The utilization of virtual learning (VL) has increased significantly. This study aimed to extract the success factors of VL and also examine the relationships among them. The research method involves examining factors identified in the literature review and seeking confirmation from experts using the Content Validity Index (CVI) method. Ten success factors are extracted and confirmed, including Technological, Management, Learning Capability, Pedagogical, Ethical, Resource Support, Interface Design, Evaluation, Institutional, and Study Environment. Based on the Interpretive Structural Model (ISM) method and the fuzzy matrix of cross-impact multiplications applied to classification (MICMAC), which divides the factors into five levels, the relationship between these factors is examined. Level I emphasizes the importance of evaluation mechanisms. Level II stresses integrating pedagogical, ethical, resource support, and institutional aspects. Level III highlights the alignment of learner capabilities with platform interfaces. Level IV underscores the significance of the learning environment. Lastly, Level V emphasizes the interplay between technology and management in VL's expansion. The findings of this study can be developed and customized through collaboration among instructors, learners, and institutions. Moreover, the findings from correlating success factors can be applied in practical learning experiments or utilized to develop efficient modeling manuals.

An enhanced and efficient approach for feature selection for chronic human disease prediction: A breast cancer study.

Computer-aided diagnosis (CAD) systems play a vital role in modern research by effectively minimizing both time and costs. These systems support healthcare professionals like radiologists in their decision-making process by efficiently detecting abnormalities as well as offering accurate and dependable information. These systems heavily depend on the efficient selection of features to accurately categorize high-dimensional biological data. These features can subsequently assist in the diagnosis of related medical conditions. The task of identifying patterns in biomedical data can be quite challenging due to the presence of numerous irrelevant or redundant features. Therefore, it is crucial to propose and then utilize a feature selection (FS) process in order to eliminate these features. The primary goal of FS approaches is to improve the accuracy of classification by eliminating features that are irrelevant or less informative. The FS phase plays a critical role in attaining optimal results in machine learning (ML)-driven CAD systems. The effectiveness of ML models can be significantly enhanced by incorporating efficient features during the training phase. This empirical study presents a methodology for the classification of biomedical data using the FS technique. The proposed approach incorporates three soft computing-based optimization algorithms, namely Teaching Learning-Based Optimization (TLBO), Elephant Herding Optimization (EHO), and a proposed hybrid algorithm of these two. These algorithms were previously employed; however, their effectiveness in addressing FS issues in predicting human diseases has not been investigated. The following evaluation focuses on the categorization of benign and malignant tumours using the publicly available Wisconsin Diagnostic Breast Cancer (WDBC) benchmark dataset. The five-fold cross-validation technique is employed to mitigate the risk of over-fitting. The evaluation of the proposed approach's proficiency is determined based on several metrics, including sensitivity, specificity, precision, accuracy, area under the receiver-operating characteristic curve (AUC), and F1-score. The best value of accuracy computed through the suggested approach is 97.96%. The proposed clinical decision support system demonstrates a highly favourable classification performance outcome, making it a valuable tool for medical practitioners to utilize as a secondary opinion and reducing the overburden of expert medical practitioners.

Pre-class mode "flipped" again: Making videos instead of just watching them.

"Flipped classroom" has subverted the traditional classroom teaching model and is believed to have a positive impact on knowledge acquisition and skill training for higher education students. The pre-class learning phase is considered a key factor in the success of flipped classrooms. However, currently, the pre-class learning phase of flipped classrooms mainly relies on video watching, which makes students passive receivers. Teachers need to invest a lot of time and resources in developing online videos, which greatly increases students' learning time and tasks. This also hinders the promotion of this teaching model. This study designs a pre-active learning strategy based on student participation in video production and a flipped classroom teaching model, and uses questionnaire surveys and interviews to observe students' reactions, explore its impact on students' satisfaction, and empirically analyze the path it affects students' satisfaction. We found that in the pre-class phase, the greater the ease of use and usefulness perceived by students in video production, the higher the students' satisfaction. Perceived enjoyment and perceived value are important intermediary paths. In addition, based on the research results, this study proposes suggestions for a flipped classroom teaching model based on video production. The results of this study will provide important references for the pre-class learning phase of flipped classrooms.

A social network analysis of college students' online learning during the epidemic era: A triadic reciprocal determinism perspective.

The way in which college students learn online has dramatically altered due to the COVID-19 pandemic. Using the triadic reciprocal determinism (TRD) theory, this study aimed to identify the key factors influencing college students' online learning experience through sentiment analysis, text mining, and social network analysis (SNA). Macro- and micro-level parsing was conducted on the SNA model, which was divided into core, mantle, and shell layers to determine the most influential factors in the core layer. This study found that learners' personal factors, learning behaviors, and related elements in the online learning environment significantly influenced the learning outcomes of college students enrolled in online courses. Additionally, this study explored the distribution of SNA model elements in the mantle and peripheral shell layers, which also impact the online learning experience of college students. Overall, this study provides a comprehensive overview of the various factors affecting college students' online learning experience, and highlights the importance of considering these factors when designing online learning environments for college students.

Faculty Worldviews: The Challenge of Diversity and Silos.

While much has been written about diversity and worldviews, too often an openness and respect for diversity of perspectives in teaching-learning seem veiled in calls for sameness in thinking about the world, education, and events. In this column, the author explores the issue of diversity of faculty perspectives in the teaching-learning of nursing. Thoughts are shared from the humanbecoming teaching-learning model, exploring the notion of synergistic patterning in creating a rich tapestry of teaching-learning of nursing.

The evolution of anesthesiology education: Embracing new technologies and teaching approaches.

Background and aims: Medical education requires regular reforms to include emerging best practices and technologies, while also critically evaluating effectiveness of traditional didactic teaching methods. This manuscript examines the challenges and opportunities associated with modernizing the anesthesiology curriculum. Methods: Narrative review of literature on innovations in medical education, with a specific emphasis on anesthesiology training. Results: Educators face difficulties implementing new teaching approaches and evaluating their effectiveness. However, active learning methods, blended with selected traditional techniques, can enhance learner engagement and competencies. Self-directed learning and simulations prepare students for real-world practice, while flipped classrooms and online platforms increase accessibility. Conclusions: A blended approach, integrating interactive technology alongside modified lectures and seminars, may optimize anesthesiology education. Despite the promise of improved pedagogies, further research is required to assess outcomes. By embracing innovation while retaining certain foundational methods, programs can equip anesthesiologists with modern skills. This evolution is key to meeting the needs of 21st-century anesthesia care needs. Remaining at the forefront of this transformation will be vital in preparing competent future anesthesiologists through state-of-the-art education.

Mapping the educational Frontier: Unleashing the Potential of artificial intelligence talents through cooperative planning in the Guangdong-Hong Kong-Macao greater bay area.

The Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has become an important hub for technological innovation and economic development in China. With the growing demand for artificial intelligence (AI) and big data technology talents, it is essential to develop educational cooperation within the GBA to develop a talent pool that can meet the changing needs in the region. This paper focuses on the development of dynamic demand for AI talents and proposes a strategic planning framework for educational cooperation in the GBA. We use the research idea of common attributes and key chain clustering-factor association selection-analysis of the driving force and subordination among factors-the key characteristics of AI talents. Using collinear analysis of citations and grounded theory methods, an operational definition of the influencing factors of AI talent literacy characteristics is constructed. Using the Interpretative Structural Modeling(ISM) and MICMAC (Matrice d'Impacts Croises-Multipication Applique A Classement), analyze and identify the driving force and subordination of the influencing factors of key traits of talents, and present the combined effect of multi-level factors of key traits of talents. Combined with the educational differences and complementary advantages in the GBA, five strategies and seven implementation suggestions for the GBA's AI talent education cooperation plan are formulated to establish a collaborative ecosystem that promotes the growth and integration of AI in the GBA.

Desafíos para la enseñanza de ciencias médicas en condiciones de contingencia

La pandemia de COVID-19 contribuyó a la afectación del proceso tradicional de formación de profesionales de la salud, por lo que fueron implementados, de forma abrupta, ajustes y modificaciones que garantizaran la continuidad del proceso de enseñanza-aprendizaje. El objetivo de la revisión bibliográfica consiste en una actualización de las adecuaciones en los métodos de enseñanza en los diferentes escenarios docentes durante las diferentes etapas de contingencia. La revisión incluyó publicaciones, en su mayoría del período 2019-2021, y se emplearon principalmente las bases de datos ESBCO, CUMED y SciELO. Como resultado de la investigación, se plantea la complementación de las clases presenciales por otras modalidades a distancia, ya sea de tipo virtual o en línea: una forma de semipresencialidad, con un mayor empleo de las redes sociales y plataformas virtuales. En conclusión, la enseñanza de ciencias médicas en tiempos de contingencia constituye un reto, ya que ha sido necesario pasar de la enseñanza presencial tradicional a otras modalidades, con énfasis en las tecnologías de la información y de la comunicación, y así reorganizar la educación para garantizar la formación de profesionales de la salud.

The pandemic of COVID-19 contributed to affect the traditional training process of the health professionals, which is why adjustments and modifications were abruptly implemented to guarantee the continuity of the teaching-learning process. The objective of the bibliographical review is to update the adequacy in the teaching methods in the different teaching scenarios during the different contingency stages. The review included publications, mostly from the period 2019-2021, and database used were mainly EBSCO, CUMED and SciELO. As a result of the research, it is proposed the complementation of face-to-face classes by other remote modalities, either virtual or online: a semi-face-to-face form, with a bigger employment of the social networks and virtual platforms. In conclusion, the teaching of medical sciences in times of contingency is a challenge, since it has been necessary to move from traditional face-to-face education to other forms, with emphasis on information and communication technologies, and thus reorganize education to ensure the training of health professionals.

The Art of Teaching-Learning the Humanbecoming Paradigm.

In this column, the author argues that art, literary, visual, and performing should be requisite concepts in nurse curricula, and describes her personal journey teaching-learning the humanbecoming paradigm.

Optimizing boiler combustion parameters based on evolution teaching-learning-based optimization algorithm for reducing NOx emission concentration.

How to reduce a boiler's NOx emission concentration is an urgent problem for thermal power plants. Therefore, in this paper, we combine an evolution teaching-learning-based optimization algorithm with extreme learning machine to optimize a boiler's combustion parameters for reducing NOx emission concentration. Evolution teaching-learning-based optimization algorithm (ETLBO) is a variant of conventional teaching-learning-based optimization algorithm, which uses a chaotic mapping function to initialize individuals' positions and employs the idea of genetic evolution into the learner phase. To verify the effectiveness of ETLBO, 20 IEEE congress on Evolutionary Computation benchmark test functions are applied to test its convergence speed and convergence accuracy. Experimental results reveal that ETLBO shows the best convergence accuracy on most functions compared to other state-of-the-art optimization algorithms. In addition, the ETLBO is used to reduce boilers' NOx emissions by optimizing combustion parameters, such as coal supply amount and the air valve. Result shows that ETLBO is well-suited to solve the boiler combustion optimization problem.

Galería de imágenes de tumores malignos como herramienta didáctica en oncología / Gallery of malignancies images as didactic tool in oncology i: en

Introducción: Los tumores malignos son afecciones prevalentes que exigen un diagnóstico temprano para un tratamiento oportuno. La confección de una galería de imágenes como medio de enseñanza con la tecnología digital constituye una herramienta de aprendizaje de incuestionable valor en la especialidad de oncología. Objetivo: Confeccionar una galería de imágenes digitales de tumores malignos como medio de enseñanza alternativo para la docencia de residentes y profesionales de enfermería. Métodos: Se realizó una innovación tecnológica en el Hospital Oncológico Docente Provincial Conrado Benítez García de Santiago de Cuba, durante el bimestre enero-febrero del 2023. El objeto de estudio y el campo de acción fueron los recursos del aprendizaje y las imágenes digitalizadas sobre tumores malignos, respectivamente. Se combinaron los métodos de investigación teóricos (sistematización, vivencial y analítico sintético) y empíricos (análisis documental y encuesta en forma de cuestionario a informantes clave). Resultados: Como medio de enseñanza alternativo para la docencia médica y de enfermería, manualmente se confeccionó una galería digital con 164 imágenes de tumores malignos que incluían casi todas las localizaciones. Los expertos en informática, especialistas, residentes y enfermeras valoraron de muy adecuado el producto informático, basado en la cientificidad y la didáctica tecnológica para la formación académica integral. Conclusiones: La galería de imágenes digitales constituye una herramienta didáctica, motivacional, atractiva e interesante para el aprendizaje de las neoplasias malignas; es un recurso ilustrativo y utilitario para la docencia médica y del profesional de enfermería.

Introduction: Malignancies are prevalent affections that demand an early diagnosis for an opportune treatment. The making of an images gallery as teaching means with digital technology constitutes a learning tool of unquestionable value in the oncology specialty. Objective: To make a gallery of malignancies digital images as alternative teaching means for the residents and nursing professionals. Methods: A technological innovation was carried out in Conrado Benítez García Provincial Teaching Oncological Hospital in Santiago de Cuba, during the January-February two-month period, 2023. The study object and action field were the learning resources and the digital images on malignancies, respectively. The theoretical investigation methods (systematizing, experiential and analytic synthetic) and empiric (documental analysis and interviews in questionnaire form to key informants) were combined. Results: As alternative teaching means for medical and nursing teaching, a digital gallery was manually made with 164 malignancies images that included almost all the localizations. Computer science experts, specialists, residents and nurses valued as very appropriate the computer product, based on the scientificity and the technological didactics for the integral academic training. Conclusions: The gallery of digital images constitutes a didactic, motivational, attractive and interesting tool for learning of malignancies; it is an illustrative and utilitarian resource for medical and nursing professional teaching.

Resultados de una estrategia para la internacionalización en el desarrollo de la educación médica superior desde la experiencia Cuba - México

La internacionalización de las universidades cubanas favorece el cumplimiento de la misión de la educación superior, propicia que la universidad sea cada vez más innovadora y contribuye, de esa manera, al logro de los objetivos de desarrollo sostenible propuestos en la Agenda 2030. La internacionalización constituye una gran fuerza para el desarrollo de una universidad moderna fundamentada en esquemas de formación: ante todo humanista, de alto nivel, con gran sensibilidad social, lo que sólo se puede alcanzar con el desarrollo de Instituciones de Educación Superior de mayor trascendencia académica, en el contexto internacional. Con estos fundamentos se realizó una investigación con el objetivo de sistematizar los resultados de una estrategia para la internacionalización de la educación médica superior. Se enmarca en un convenio de colaboración entre instituciones de Cuba y México y la creación de una red académica, que impulsa actividades de investigación y docencia en pre y posgrado. Se trata de una investigación de naturaleza documental. La revisión de textos, en formato impreso y digital, se orientó al análisis de los resultados de la experiencia de Cuba- México, en los ámbitos: intercambio académico, movilidad docente, participación en proyectos científicos colaborativos y formación doctoral, que se materializan en los resultados obtenidos.

The internationalization of Cuban universities favors the fulfillment of the mission of higher education, encourages the university to be increasingly innovative and thus contributes to the achievement of the sustainable development goals proposed in the 2030 Agenda. Internationalization constitutes a great force for the development of a modern university based on training schemes: above all humanistic, high level, with great social sensitivity, which can only be achieved with the development of Higher Education Institutions of greater academic significance, in the international context. With these foundations, an investigation was carried out with the objective of systematizing the results of a strategy for internationalization of higher medical education. It is part of a collaboration agreement between institutions in Cuba and Mexico and the creation of an academic network, which promotes research and teaching activities in undergraduate and postgraduate courses. This is an investigation of a documentary nature, in which the review of texts, in printed and digital format, was oriented to the analysis of the results of the Cuba-Mexico exchange experience, in the areas: academic exchange, teacher mobility , participation in collaborative scientific projects and doctoral training, which materialize in the results obtained. From the critical and contrasted reading, the systematization was carried out.

La educación a distancia en la Enseñanza Técnica Superior de Prótesis Estomatológica: experiencias de 2 cursos

Introducción: La asignatura Introducción a la Metodología de la Investigación, para la Enseñanza Técnica Superior de Prótesis Estomatológica, de la Facultad de Estomatología de La Habana, se incorporó a la educación a distancia, durante el curso 2021-2022. Objetivo: Describir la experiencia en la ejecución de la asignatura con el uso del aula virtual de la Institución. Material y Métodos: Se realizó una investigación de tipo descriptiva, retrospectiva, acerca de las experiencias en el proceso de enseñanza-aprendizaje, durante los cursos 2021-2022 y 2022-2023. Resultados: Se cumplieron los objetivos metodológicos de la asignatura, se debatieron los temas propuestos en los foros, se aclararon las dudas utilizando las herramientas interactivas de la plataforma y la atención al alumno fue personalizada. Conclusiones: Se logró impartir por primera vez con éxito, la asignatura, se digitalizaron los objetos de aprendizaje por temas, se diseñaron actividades para la evaluación del aprendizaje, y se obtuvieron calificaciones satisfactorias.

Introduction: The subject Introduction to Research Methodology, for the Higher Technical Education of Stomatological Prosthetics, of the Faculty of Stomatology of Havana, was incorporated into distance education, during the 2021-2022 academic year. Objective: Describe the experience in the execution of the subject with the use of the Institution's virtual classroom. Material and Methods: A descriptive, retrospective research was carried out on the experiences in the teaching-learning process, during the 2021-2022 and 2022-2023 academic years. Results: The methodological objectives of the subject were met, the topics proposed in the forums were debated, doubts were clarified using the platform's interactive tools, and student attention was personalized. Conclusions: The subject was successfully taught for the first time, the learning objects were digitized by topic, activities were designed for the evaluation of learning, and satisfactory grades were obtained.

Optimizing Image Classification: Automated Deep Learning Architecture Crafting with Network and Learning Hyperparameter Tuning.

This study introduces ETLBOCBL-CNN, an automated approach for optimizing convolutional neural network (CNN) architectures to address classification tasks of varying complexities. ETLBOCBL-CNN employs an effective encoding scheme to optimize network and learning hyperparameters, enabling the discovery of innovative CNN structures. To enhance the search process, it incorporates a competency-based learning concept inspired by mixed-ability classrooms during the teacher phase. This categorizes learners into competency-based groups, guiding each learner's search process by utilizing the knowledge of the predominant peers, the teacher solution, and the population mean. This approach fosters diversity within the population and promotes the discovery of innovative network architectures. During the learner phase, ETLBOCBL-CNN integrates a stochastic peer interaction scheme that encourages collaborative learning among learners, enhancing the optimization of CNN architectures. To preserve valuable network information and promote long-term population quality improvement, ETLBOCBL-CNN introduces a tri-criterion selection scheme that considers fitness, diversity, and learners' improvement rates. The performance of ETLBOCBL-CNN is evaluated on nine different image datasets and compared to state-of-the-art methods. Notably, ELTLBOCBL-CNN achieves outstanding accuracies on various datasets, including MNIST (99.72%), MNIST-RD (96.67%), MNIST-RB (98.28%), MNIST-BI (97.22%), MNST-RD + BI (83.45%), Rectangles (99.99%), Rectangles-I (97.41%), Convex (98.35%), and MNIST-Fashion (93.70%). These results highlight the remarkable classification accuracy of ETLBOCBL-CNN, underscoring its potential for advancing smart device infrastructure development.

Paradoxical Rhythms in Teaching-Learning: Glimpsing the Utterable-Unutterable.

In this column, the utterable-unutterable in teaching-learning is explored. Through the lens of the paradoxical rhythms of the humanbecoming teaching-learning model, insights are gleaned from a story shared of an experience in the teaching-learning of nursing. Further understandings emerge from reflecting on the thoughts of others in the literature. From this consideration, suggestions are offered to guide nurse faculty in honoring the richness of the utterable-unutterable in teaching-learning.

The impact and the challenges of implementing a faculty development program on health professions education in a Brazilian Medical School: a case study with mixed methods.

PURPOSE: Faculty development in health professions education is still challenging in developing countries like Brazil. Work overload and the lack of financial support hinder faculty members' participation. Ribeirão Preto Medical School founded its Center for Faculty Development in 2016. Since then, an essential skills module (ESMo) on health professions education (HPE) has been offered regularly to faculty members and preceptors of seven undergraduate programs. This case study aims to evaluate the impact of this Essential Skills Module on the educational practices of participants two years after attending the module and the challenges faced during the process. METHOD: The study used a mixed-method approach with a description of the demographic and professional profile data of the ESMo participants. Immediate post-ESMo perceptions (satisfaction and learning) of the participants were determined with structured instruments. Two years later, a semi-structured interview was conducted and recorded to determine the long-term effects (application of learning and behavior changing as an educator). NVIVO® software was used to store and systematize the thematic discourse analysis with a socio-constructivist theoretical framework interpretation. RESULTS: One hundred forty-six participants were included: 86 (59%) tenured faculty members, 49 (33,5%) clinical preceptors, and 11 (7,5%) invited teachers. Most were female (66%), and 56% had teaching experience shorter than ten years. 52 (69%) out of 75 eligible participants were interviewed. The immediate reaction to participating in the module was quite positive and 80% have already implemented an educational intervention in their daily activities. Discourses thematic analysis showed five emerging themes appearing in different frequencies: Changes in teaching activities (98%); Lack of previous pedagogical training (92.3%); Commitment and enthusiasm towards teaching (46.15%); Overlapping functions inside the institution (34.6%) and Challenges for student assessment (23%). CONCLUSION: This first in-depth evaluation of the long-term effects of a faculty development intervention in a Brazilian Health Profession Education school showed that participation positively changed participants' teaching & learning practices. These interventions consistently fostered a community of practice and valued faculty development processes in local and national scenarios.

Undergraduate nurses' reflections on visual thinking learning to construct inductive reasoning through situated patient pictures: A mixed-method study.

BACKGROUND/OBJECTIVE: Deductive logic has often been used to develop critical thinking. However, inductive logical thinking, essential to care decision-making, has yet to be emphasized. This study aimed to explore visual thinking learning among undergraduate nursing students by asking them to draw situated patient pictures in order to integrate theoretical knowledge and promote inductive logical thinking. METHODS: A mixed-methods research design was used to obtain quantitative and qualitative data from a convenience sample of 100 students. The study was conducted in a Taiwanese university from September 2022 to January 2023. In the quantitative component, learners' views of situated patient pictures were captured based on 15 paired identifiers and two questions: (a) What word should be used in describing the situated patient's picture? (b) How strongly do you feel about the selection? Written feedback was analyzed using qualitative content analysis. RESULTS: Quantitative analysis identified specific, unpretentious, humorous, harmonious, conservative, realistic, rational, entire, image performance, professional performance, understandable, expressive, static performance, rigorous, and profuse with a reasonable degree of choice. Qualitative analysis identified four stages in participants' development of inductive reasoning through situated patient pictures and visual thinking learning. These were: exploration, intuition, theme, and logic and creation. CONCLUSIONS: The results suggest that visual thinking learning is a practical pedagogical approach to increasing learners' communication abilities, group cooperation, theoretical knowledge integration, and logical thinking. Neither educators nor learners required any artistic skills. Nonetheless, participants demonstrated creativity and innovation through continuous visual thinking learning.