Effective Learning Research Articles

Guided listening as meaningful learning: A study of Israeli secular Jewish High School music programs

Guided listening is vital in music education, fostering self-expression, skill development, and academic achievement. Yet, its limited use in Israeli high schools creates a gap between its recognized value and practice. This mixed-method study examines guided listening integration in secular Jewish-Israeli high school music programs based on four philosophical and pedagogical approaches—esthetic, Praxial, active, and peer instruction—to understand teachers’ objectives, methodologies, implementation, and optimal learning environments. Data was collected from an online questionnaire, structured interviews, direct observations of Western Art Music History lessons, and the researcher’s reflective journal. Key findings: (1) teachers tend to use a repeated five-step teaching pattern (reviewing, lecturing, analyzing, listening while following a score, summarizing); (2) teachers usually do not write lesson plans with detailed, step-by-step guidelines; and (3) teachers use recommended guided listening approaches in a limited capacity, likely due to pressure from preparing students for exams, and the perception that such methods are not fully suitable for Israeli high school music students. The paper explores teachers’ challenges in adopting guided listening pedagogical methods while balancing curriculum demands and promoting inclusivity. It offers recommendations for policymakers and educators on professional development and curriculum revisions, emphasizing detailed lesson planning for effective learning outcomes.

Using deep learning to detect atherosclerotic plaques on carotid ultrasound images in the UK Biobank

Abstract Background Atherosclerosis is the main underlying cause of cardiovascular disease (CVD). Existing CVD risk assessment tools do not consider the burden of subclinical atherosclerosis. The presence of carotid plaques on carotid ultrasound is a well-known marker of subclinical atherosclerosis. The accumulation of population-scale data on the presence of atherosclerotic plaques, along with deep phenotyping, can allow not only to address the effectiveness of carotid ultrasound in routine clinical practice, but to shed light on the biology of atherosclerosis development. Purpose To develop an effective deep learning model for plaque detection in carotid ultrasound images in the UK Biobank. Methods We used 680 carotid ultrasound images with manually annotated plaques to train a deep learning model employing the YOLOv8 architecture. Different augmentation techniques were used to increase the generalizability of the model. The developed model was applied to automatically detect plaques in raw ultrasound images from 19,507 UK Biobank participants. Logistic and Cox regression were used to explore the associations of plaque presence and number as predicted by the model with conventional CVD risk factors and the risk of future CVD events over follow-up. To explore the genetic architecture of subclinical atherosclerosis, we conducted a genome-wide association study (GWAS) on plaque presence, followed by meta-analysis with data from the CHARGE Consortium. Results Our plaque detection model achieved high classification metrics of accuracy, sensitivity, and specificity (89.3%, 89.5%, and 89.2%, respectively) and detected atherosclerotic plaques in 44% of UK Biobank participants. As expected, plaques were more common among men than women and their prevalence increased linearly with age. Both plaque presence and number of plaques were correlated with conventional CVD risk factors including diabetes, hypertension, and hyperlipidemia, and showed strong associations with future risk of incident CVD events (Hazard Ratio for plaque presence: 1.48 [95%CI: 1.21-1.82], for 2 plaques or more: 1.65, [95% CI: 1.28-2.13]). Incorporating plaque-derived phenotypes minimally altered the C-index of the time-to-event model. GWAS meta-analysis of carotid plaque presence revealed 5 previously known loci, as well as a significant locus including the LPA gene that had not previously been associated with carotid plaque. Conclusion We have developed and implemented an efficient plaque detection model to data from the UK Biobank, which holds significant promise for studying atherosclerosis at a population-wide scale through integration with multiomics data and electronic health records.

Optimizing elderly care: a data-driven AI model for predicting polypharmacy risk using SHARE data

Abstract Background Polypharmacy (PP), which rises with age, is a growing public health challenge, affecting health outcomes and escalating healthcare expenditure. Leveraging the comprehensive European coverage and longitudinality of the Survey of Health, Ageing, and Retirement in Europe (SHARE) study, we aim to assess PP prevalence patterns and identify the most effective machine learning (ML) model for predicting long-term PP risk, as a foundation for a scalable predictive tool. Methods We used data from participants aged above 50 who were present in wave 6 and at least one of the subsequent three waves of the SHARE study, aiming to predict PP risk at 2, 4, and 6-year intervals. PP was defined as the concurrent use of five or more medications. We analyzed PP prevalence trends and selected the predictor variables from wave 6 using LASSO regression analysis. We evaluated eight ML models, namely, ANN, SVM, DT, RF, GB, XGBoost, LightGBM, and CatBoost, using a rigorous cross-validation strategy to ensure robustness and reliability. Results Our analysis reveals an upward trend in PP prevalence across the surveyed countries, with aggregate figures rising from 34.03% (95% CI 33.1-34.9) in wave 7 to 36.75% (95% CI 35.6-37.9) in wave 8, reaching 39.91 (95% CI 38.9-40.9) in wave 9. Additionally, using the Categorical Boosting ML model to predict PP resulted in overall accuracies of 75.08%, 73.7%, and 71.65% and recall rates of 72.83%, 70.48%, and 67.96% for the 2, 4, and 6-year intervals, respectively. Conclusions This study reveals a rising trend of PP across European countries and demonstrates the potential of using longitudinal data and ML to enhance PP prediction. The tool developed represents a step forward in risk stratification, which would be particularly beneficial in practical settings where family physicians or pharmacists could employ the tool to monitor elderly patients, predict and thus prevent PP, and reduce the negative health and economic impact associated with it. Key messages • The integration of machine learning with longitudinal data presents a significant advance in polypharmacy risk prediction. • The tool we developed highlights the potential translational impact of our findings.

Efficient and effective ensemble broad learning system based on structural diversity

Ensemble Broad Learning Systems (ENBLS) have received considerable attention from researchers and experienced rapid development due to its outstanding performance in handling complex data. A study has revealed that when ENBLS is trained with multiple independent storages, the issue of memory consumption is inevitable. To address this issue, this paper proposes an Ensemble Broad Learning Systems based on structural diversity (EBLSSD). This method effectively reduces the model memory consumption while maintaining superior performance. In EBLSSD, the scaling vectors are trained by constraining the scaling vectors of the current model and those of other existing models. These vectors are used to search for hidden paths of subnetworks within the network, extracting different network structures for integration. By preserving the scaling vectors during the storage process, memory pressure is reduced. EBLSSD introduces diversity from the perspective of network structure, which reduces cooperation between nodes and the risk of model overfitting, thereby enhancing model performance. The feasibility and effectiveness of the proposed algorithm is validated by experimental results on public datasets.

A novel training session: mixed reality evisceration surgery webinar.

Evisceration surgery is an important part of an ophthalmologist's skillset but is an uncommon procedure. Therefore, it is important for training ophthalmologists to have adequate knowledge and confidence in this procedure to maximise learning opportunities. Mixed reality involves the intertwining of real and virtual environments and has been used successfully in surgical training. To improve participants' knowledge of the relevant anatomy, steps and confidence in performing evisceration surgery using an extended reality online webinar coupled with conventional teaching. The teaching session comprised of a short lecture introducing evisceration and explaining mixed reality technology including the Microsoft HoloLens headset. This was followed by a 3D demonstration of the orbit and globe, then the live evisceration procedure on a porcine cadaver, with the surgeon's point of view via the headset. There was expert live running commentary during the procedure with the use of virtual signposts on relevant anatomy. Participants were encouraged to be interactive and given the ability to share their annotations on-screen. Ten doctors ranging from Foundation year 1 to Ophthalmology specialist training year 3 attended the 90-min session and completed pre- and post- session questionnaires (5-point Likert scales). Results showed statistically significant improvements in the knowledge, steps and confidence in performing the evisceration surgery (paired two-sample T-tests, SPSS version 29). This study has demonstrated that utilisation of mixed reality with conventional teaching methods can provide a useful initial learning experience which may facilitate effective further learning of the evisceration surgery in a wet-lab or patient setting.

Developing mobile augmented reality in picture book for teaching English for young learners

An effective language and learning process must contain interactive, fun, challenging, motivating aspects and provide more space for students to develop their creativity and independence, according to students' talents and interests; thus, appropriate teaching media can be as assisting tools. When selecting media, you need to consider several things, namely learning objectives, effectiveness, easy to obtain, students, use, not rigid, cost, and quality. One of the developments in learning media that is currently still new is learning media using Augmented Reality. This research aims to develop Augmented Reality-based text book learning media for English language learning. Developing text-book media using an application with a barcode scanner on text-books. This application displays 4D images or animations that have sound and movement so that it will help students to understand English texts. The research method used is the research and development method (Research & Development) while the product development model used is the ADDIE model (Analysis, Design, Development, Implementation, & evaluation. After developemnt anf evalution phase, the findings reveals that the outcome of teaching material product is deemed highly valid and appropriate for teaching English to yong learners, especially for primary school in this research context, as it was supported by the result of validation phase with media experts, subject matter experts, and student trials. Additionally, reflecting on the result of this study, the pedagogical implications of this result discussed further in this research.

Analysis of Students' Critical Thinking Skills Through the Pakem Learning Model in Science Subject Class VI SD Negeri 78 Palembang

Critical thinking ability is a high-level thinking ability that aims to make reasonable decisions to help the problem solving process actively and skillfully in analyzing, applying and evaluating information obtained or resulting from observations of elementary school students. The learning model is one of the important things in creating an active, creative, effective and enjoyable learning process. The PAKEM model is an appropriate model to use in the learning process. This research aims to determine the critical thinking abilities of class VI students using the PAKEM model in science learning at SD Negeri 78 Palembang. This research uses an experimental method with a quantitative approach. The subjects in this research are 25 VIC class elementary school students. Data collection techniques in this research use observation, tests, interviews and documentation. Data analysis techniques use the normality test, homogeneity test and T-Test. The results of this research found that there were 8 students with high critical thinking skills, with a score range of 85-100, getting a percentage of 32%. Medium critical thinking ability, totaling 12 students, with a score range of 75-80, got a percentage of 48% and low critical thinking ability, totaling 5 students, with a score range of 65-70, got a percentage of 20%. The results of the critical thinking skills of class VIC students using the PAKEM model in science learning at SD Negeri 78 Palembang overall students reached 82.4% in the good category.

Enhancing Digital Education: A Model for Effective Mobile Learning Implementation in Malaysian Higher Education

This study investigates the implementation of mobile learning (m-learning) services in the smart environment at Kolej Poly-Tech MARA (KPTM) in Malaysia, focusing on establishing effective practices for digital education. Despite the potential of m-learning as an educational tool, its adoption in Malaysia remains limited, with the COVID-19 pandemic highlighting the need for innovative approaches to learning. The research employs a mixed methods approach, gathering quantitative data from 365 respondents, including students, lecturers, and administrators, through Likert-scale questionnaires distributed via Google Forms. Qualitative data were obtained through interviews with 10 selected participants. The study identifies existing practices in m-learning, explores its benefits, and examines challenges faced during implementation. Utilizing descriptive analysis, one-way ANOVA, Independent T-Test, and Regression Correlation, the findings reveal a positive perception of m-learning among stakeholders, alongside challenges related to infrastructure and training. The primary contribution of this research is the development of a model of good practice that provides guidelines for KPTM and other higher education institutions aiming to enhance the quality of mobile learning services. This model emphasizes the importance of accessibility, professional development, and stakeholder collaboration, positioning KPTM toward a more effective digital education landscape. Overall, the study underscores the critical role of m-learning in fostering flexible and engaging learning environments while addressing the barriers to its implementation in Malaysia.

Technology Adaption in Distance Teacher Training: The Impact of Demographic Factors on Learners’ Technology Adaption

Understanding how demographic characteristics influence students' technology adaptation is crucial for effective online learning. This study explored the impact of these characteristics on distance education (DE) students' technology adaptation at a sub-Saharan African university. Using a descriptive survey design with a high-reliability score (Cronbach’s Alpha = 0.898), data were collected from 200 DE students across 14 study centres. The study tested seven hypotheses, employing statistical analyses like ANOVA, t-tests, and post hoc tests. Results revealed that while gender and employment status did not significantly affect technology adaptation, age, academic programme, academic level, and study centre did. Students aged 26-35 adapted better, with those in Mathematics and English programs showing higher adaptation scores compared to those in the Postgraduate Diploma in Education (PGDE) program. Additionally, higher-level students and those from well-resourced study centres demonstrated superior adaptability. The study suggests providing targeted support based on age, academic programme, and study centre resources to enhance technology adaptation in DE. To further improve students' technology proficiency, the study recommends that DE institutions offer regular training sessions and workshops to help students navigate online platforms, use digital libraries, and maximize productivity tools.

NLP Applications in Vocabulary Acquisition

This paper examines the transformative role of Natural Language Processing (NLP) in vocabulary acquisition for English as a Second Language (ESL) learners. With advancements in NLP technologies, innovative applications have emerged that foster effective vocabulary learning through personalized and context-rich experiences. The study explores various NLP-driven tools, such as context-aware learning systems, personalized vocabulary lists, and interactive games, that enhance engagement and retention. By analyzing the effectiveness of these tools, this research underscores the limitations of traditional vocabulary teaching methods and illustrates how NLP can provide dynamic, tailored support to meet individual learners’ needs. Furthermore, the paper highlights the significance of real-time feedback mechanisms, such as speech recognition, in promoting accurate pronunciation. Ultimately, this investigation aims to demonstrate that NLP technologies offer a more engaging, efficient, and effective approach to vocabulary acquisition, significantly improving ESL learners’ language proficiency and overall communicative competence.

Bringing interactive elements into classes: Augmented reality-based learning media development for electrical measurement subjects in vocational education

This study aims to develop and evaluate Augmented Reality (AR)-based learning media to improve student interest at SMKN 1 Kuantan Mudik. AR, which integrates virtual objects into the real world, is expected to enrich the learning experience through innovative visual and interactive elements. This research employs a Research and Development (R&D) which includes preliminary research, prototype creation, student response assessment, and systematic reflection. The AR-based learning media prototype was developed using Assemblr Edu software and evaluated by media experts, content specialists, and students. The validation results indicate that the media is highly viable, receiving a score of 92.7% from content experts and media specialists. Student trials produced ratings of 88.9% for effectiveness and 90.3% for engagement. The findings demonstrate that AR-based learning media significantly enhance student interest and involvement in the learning process. This study concludes that augmented reality learning media substantially improve educational experiences in vocational settings, showing potential for broader implementation across various subjects. However, this research is limited to expert validation processes and primarily focuses on student responses rather than measuring learning outcomes. This study is anticipated to provide a foundation for developing more comprehensive and effective learning media.

Enhancing English as a Foreign Language (EFL) learning in Saudi Arabia: the academic contribution of YouTube in EFL learning and cultural awareness

The incorporation of technology in English as a Foreign Language (EFL) classroom has drastically transformed conventional learning models by offering innovative ways to boost students’ engagement and improve learning outcomes. This study investigates the impact of using YouTube as an educational tool to enhance EFL instruction in Saudi Arabia. A total of 200 EFL students were divided into two groups: An experimental group which used You Tube as a source of learning and another group which used normal curriculum. A mixed-methods approach was employed, combining quantitative data from a paired-sample t-test with qualitative feedback from students. The results for paired-sample t-test computations revealed a statistically significant difference (p = 0. 003) across the proficiency level indicating improvement in students’ speaking and listening skills at higher proficiency levels. Of the qualitative answers, motivational and participation enhancement were overemphasized. The research points that the integration of YouTube in EFL classrooms can lead to a remarkable increase in language learning especially in the learning area of listening and speaking abilities among the students. These results offer practical implications for educators seeking to integrate multimedia tools into their teaching strategies to promote more interactive and effective learning experiences.

Impact of Virtual Learning on Student Performance and Engagement in Remote Hilly Areas of Uttarakhand

The rapid shift to virtual learning during the COVID-19 pandemic brought significant changes to the education system, especially in geographically challenging regions like the remote hilly areas of Uttarakhand, India. This study explores how these shifts affected high school students' academic performance and engagement in virtual classrooms, given the unique challenges posed by limited infrastructure and connectivity. This study investigates the impact of virtual learning on student performance and engagement in the remote hilly areas of Uttarakhand, India. With the sudden shift to virtual education during the COVID-19 pandemic, schools in these regions faced unique challenges due to their geographic isolation, lack of internet access, and frequent power outages. The study aims to assess how these conditions have influenced the effectiveness of virtual learning and its impact on students' academic outcomes and engagement levels. A total of 51 high school students from 05 government schools in remote areas of Uttarakhand participated in this research. Data was collected through structured questionnaires, focusing on students’ experiences with virtual learning, their academic performance before and after the shift, and their engagement with online classes. The study used both quantitative and qualitative methods, including descriptive statistics, logistic regression, and MANOVA, to analyze the data. Findings indicate that while virtual learning provided an essential educational lifeline during the pandemic, students in remote areas encountered significant barriers that hindered their learning experiences. Limited internet access and frequent electricity cuts were among the primary obstacles reported. Despite these challenges, a majority of students found virtual classrooms useful for maintaining continuity in their education. The study also reveals that virtual learning positively influenced student engagement, particularly in subjects that incorporated interactive content. However, the overall academic performance showed mixed results, with some students struggling due to the absence of traditional classroom interaction and practical learning opportunities. This research highlights the need for improved infrastructure and policy interventions to support virtual education in remote regions. It concludes that while virtual learning has potential, addressing technological and logistical barriers is crucial for ensuring equitable and effective learning experiences for all students in such areas.

Enhancing Engagement in Learning Management Systems using Gamification Framework

The rapidly evolving landscape of higher education demands innovative approaches to engage learners effectively within Learning Management Systems (LMS). This article presents a conceptual framework of gamification explicitly designed for higher education to enhance learner engagement within LMS platforms. Drawing inspiration from game design elements, principles, and motivational theory support, the framework strategically integrates points, badges, and leaderboards to create an interactive and motivating learning environment. The primary objective is to leverage intrinsic motivation, fostering active participation and a deeper understanding of course material. By implementing this framework, higher education institutions can enhance the educational experience for learners, improve retention rates, and cultivate a passion for lifelong learning. This article discusses the gamification framework's theoretical foundation, practical implementation, and potential benefits. It provides insights for educators and administrators seeking to transform their LMS into engaging and effective learning environments in higher education.

The Complexity Of School-Based Management In Improving Teacher Quality

This research discusses the complexity of school-based management as a strategy to improve teacher quality. In the ever-evolving era of education, the role of school-based management becomes crucial in creating an effective learning environment. The concept of complexity is applied to describe the dynamics, interactions and challenges involved in managing teachers together in an educational environment. This study uses a qualitative approach with a focus on the implementation of school-based management and its impact on co-teachers at SD Negeri 3 Tirtanadi. Data were collected through interviews, observation and document analysis related to education policy. The research findings show that the complexity of school-based management includes factors such as leadership, stakeholder engagement, professional development and organisational culture. The results provide deep insights into how schools can effectively manage these complexities to improve teacher quality. The practical implications of this research involve crafting education policies that support the implementation of school-based management, empowering school leadership and strengthening collaboration among stakeholders. As such, this research makes a significant contribution to the understanding of the complexities of school-based management as a strategic endeavour in improving teacher quality in the contemporary education era.

Efficient and Compressed Deep Learning Model for Brain Tumour Classification With Explainable AI for Smart Healthcare and Information Communication Systems

ABSTRACTThe detection of brain tumours presents a significant challenge in the medical domain, where prompt and precise diagnosis is crucial as patient outcomes depend on it. Conventional deep neural networks perform well in carrying out various imaging tasks within the healthcare sector; however, their effectiveness often falls short of expectations in practical applications due to the substantial computational resources required and issues with reliability. In this research, an optimised and effective deep learning model founded on the DenseNet‐169 architecture is introduced for the classification of magnetic resonance imaging brain tumours, which is particularly advantageous for smart healthcare systems and information and communication technology (ICT) settings with limited computational capabilities. The model compression methodologies, including pruning and quantization, have been employed to significantly diminish the dimensions and intricacy of the model while achieving a classification accuracy of 97.07%. Furthermore, this endeavour necessitates the enhancement of the model's interpretability through the utilisation of explainable artificial intelligence methodologies such as Gradient‐weighted Class Activation Mapping (Grad‐CAM) and SHapley Additive exPlanations (SHAP), which will aid clinicians in highlighting crucial areas of the images and validating feature importance concerning the decisions rendered by the model. A comparative performance evaluation is conducted against DenseNet‐169, ResNet‐50 and various other models to delineate the superior efficacy of our model, rendering it exceptionally adept for knowledge‐driven, real‐time brain tumour diagnosis within smart healthcare and ICT systems where resources are constrained.

The effect of PBL integrated RMS on biological literacy and critical thinking ability of high school students

This study aimed to determine the effect of Problem-Based Learning (PBL) integrated Reading, Mind Mapping, and Sharing (RMS) on biological literacy and critical thinking skills in biotechnology material. This type of research is Quasi-Experimental with pre-test-post-test experiments and a control group design. The researcher conducted the research because most of the students who became respondents considered biotechnology material less attractive, so students' understanding and activeness could have been more optimal in the learning process. The research samples were 72 students of class X MIPA at SMA Negeri 2 Kota Serang, Banten. The research sample was divided into two groups: the experimental group that applied the PBL integrated RMS model and the control group that applied the PBL model. The research instruments used were biological literacy ability tests and critical thinking ability tests. Biological literacy skills were measured using biological literacy-based multiple-choice test instruments, while critical thinking skills were measured using essay test instruments. The hypothesis test used was MANOVA statistical analysis. The results of statistical tests showed a significant effect of PBL integrated with RMS on biological literacy and critical thinking skills on biotechnology material with a significance value of 0.000 < α. Students with an integrated RMS learning model are more effective than those with a PBL learning model, which is indicated by the post-test value being higher than the pre-test value. This research contributes to the field of biology education by showing that the PBL learning model integrated with RMS can be an effective alternative learning model to improve students' biological literacy and critical thinking skills. The findings of this study are expected to be useful for biology teachers

The Effect of Historical Places Through Virtual Museums on Students' Academic Achievement And Attitudes Towards The Course In Social Sciences Course Concept Teaching

This research, 7. the classroom social studies course was conducted in order to determine the effect of historical sites on students' academic achievements and attitudes towards the course through virtual museums in concept teaching. In line with the aim, 20 concepts included in the social studies curriculum were selected. A 20-question academic achievement test was prepared and applied to be applied to students in relation to these concepts. In addition, a 35-item attitude scale was applied to determine the students' attitudes towards the Social studies course. The study group of the research consists of 40 7th grade students (20 experimental, 20 control). The study was carried out over a total period of 3 weeks. The experimental group was taught concepts through virtual museums in historical places, and the control group was taught according to the Social Studies curriculum. SPSS, which is a statistical analysis program, was used for the analysis of quantitative data. In the measurements related to the research, dependent and independent variable t test, mean, standard deviation values were calculated. According to the results of the analysis, it has been determined that the use of virtual museums with historical sites in social studies course concept teaching enables more effective learning compared to traditional methods and creates significant differences in students' attitudes towards social studies course.

Penerapan Teori Behavioristik Classical Conditioning Oleh I.P Pavlov dalam Pembelajaran IPA Siswa Kelas 5 Sekolah Dasar

This research was conducted in response to a number of difficulties faced as well as the low level of interest in learning from grade 5 elementary school students in the context of science learning. This study focuses on the science learning ability of grade 5 students in elementary schools in response to the results of PISA 2018, Indonesian Education Report Card Data, and AKM Scores which show the low level of students' science literacy skills. Using the Nonequivalent Pretest Posttest Control Group design, experimental research was conducted to evaluate the impact of the application of Behavioristic Classical Conditioning Theory by I.P Pavlov in science learning. Class V students were divided into experimental and control groups with the Cluster Random Sampling Technique. The test method was used to collect science learning ability data, and the data analysis used the Polled Variance T test due to homogeneous data variance. The results showed a significant difference in science learning ability between the group that applied the Behavioristic Classical Conditioning Theory and the control group. The implications of this research provide a solid foundation for designing effective learning strategies in the future, focusing on curriculum development and learning approaches that can enhance students' understanding and interest in learning. As an effort to improve the quality of science learning in elementary schools, this research provides significant conceptual and applicative contributions.

A new approach to business ethics education: Virtual reality-based flipped learning

Paying attention to business ethics and educating ethical leaders and employees can impact organizational performance. Effective professional ethics education and learning can prevent administrative corruption, embezzlement and fraud in organizations. On the other hand, the development of digital technologies has created transformations in educational processes and methods. Evaluating the effectiveness of innovative teaching methods will greatly help the learning process of individuals and educational planning of business schools. Flipped learning is an educational approach in which students learn about course content before class. Accordingly, the aim of this research is to evaluate the impact of virtual reality (VR)-based flipped learning compared to the traditional method of teaching business ethics. This study was applied and quasi-experimental. Among business students of Shiraz University, 135 people were randomly divided into three groups. The first experimental group underwent training with the flipped learning method based on VR and the second experimental group underwent training with the traditional method and the third group was the control group. The control group didn't receive training and was selected only for the purpose of comparison with experimental groups. Pretest and posttest designs were used and the results of the three groups were compared using the Tukey test. The results showed that the two groups that received business ethics education had a significant difference compared to the control group. An important finding of this study revealed that among the two teaching methods, VR-based flipped learning had a greater impact on students' business ethics compared to the traditional teacher-centered approach. Accordingly, university managers and business ethics course instructors can facilitate the learning process using VR-based flipped learning. Designing simulation software for ethical scenarios is also a suitable solution for teaching business ethics.