Area Of Learning Research Articles

Educational research on medical residency programs in Chile: a scoping review and analysis of the impact of the new accreditation policy

BackgroundAccrediting medical specialties programs are expected to influence and standardize training program quality, align curriculum with population needs, and improve learning environments. Despite global agreement on its necessity, methods vary widely. In the Chilean context, a recent new accreditation criteria includes research productivity in relation to educational research on resident programs, so we aimed to define it. What is the profile of publications in educational research produced by Chilean medical specialty residency programs in the last five years? Based on these results, we intend to analyze the potential impact of the new accreditation policy on medical specialty programs in Chile.MethodsWe performed a preliminary bibliometric search to identify the use of the term “resident” in literature. After that, we conducted a literature search, using a six-step approach to scoping reviews, including the appraisal of the methodological quality of the articles.ResultsBetween 2019 and 2023, an average of 6.2 articles were published yearly (19%). The bibliometric analysis revealed that the dominant thematic area of the journals was clinical, accounting for 78.1%. Most articles focused on residents (84.38%), with only two articles including graduates as participants. One university was responsible for 62.50% of the articles and participated in all multicenter studies (9.38%). Surgical specialties produced 15 research articles focused on procedural training using simulation. Psychiatry was the second most productive specialty, with 5 articles (15.63%) covering standardized patients, well-being, and mental health assessment. The most frequent research focus within residency programs over the five-year period was teaching and learning methodologies, with 19 articles representing almost 60% of the total analyzed.ConclusionsResearch on medical education in Chile’s postgraduate residency programs is limited, with most studies concentrated in a few universities. The new accreditation criteria emphasize educational research, posing challenges for many institutions to meet higher standards. Understanding unexplored areas in educational research and learning from successful programs can enhance research productivity and align efforts with accreditation expectations. Continuous evaluation and new research on residents’ satisfaction, skills acquisition, and well-being are needed to ensure training quality and accountability.

Developing a group-based psychoeducation intervention for adoptive parents and foster carers in a specialist child and adolescent mental health service setting

Children and young people in foster and adoptive families are considered more vulnerable to a high level of mental health need when compared to peers who are not care-experienced or adopted. Acceptance of this view amongst clinical providers and policy makers has necessitated the development of specialist provision and dedicated care pathways within child and adolescent mental health services. In this provision, practitioner-initiated quality improvement projects help in appraising the effectiveness of clinical interventions in local contexts, as well as identifying areas for service learning and practice reflection. This article reports on the evaluation of a mentalisation-based psychoeducation group intervention for adoptive parents and foster carers. The evaluation activity took place in a single child and adolescent mental health service setting, starting during the COVID-19 pandemic, with the intervention being implemented online via videoconferencing. In the article, after introducing the intervention (based on the Family Minds model), an analysis of clinical data collected pre- and post-intervention is reported. Few results of the analysis regarding the two pre- and post-measures reached statistical significance, indicating only changes in the magnitude of stress in the parent/carer-child system. A series of reflections are posed that consider what this finding means in developing fit-for-purpose support for adoptive parents and foster carers in child and adolescent mental health service contexts.

In an Imperfect World: Barriers and Facilitators to Educators' Evidence-Based Practice Use for Elementary-Aged Autistic Students in Inclusive Settings.

Educators' use of evidence-based practices (EBP) provides positive outcomes for autistic students in multiple areas of learning (e.g., peer interactions and academic skills) and may promote access and participation in general educational settings. However, many teachers report limited use of EBPs for their autistic students, with inconsistent fidelity. This study sought to understand barriers and facilitators educators identify to implementing EBPs with autistic students in general education classrooms. To understand educators' perspectives and experiences, we conducted a qualitative study with 81 educators who serve elementary-aged autistic students in one state. In response to interview questions based on the Consolidated Framework for Implementation Research framework, educators reported on multiple factors, including the general education environment, access to resources, training in EBPs, and professional collaboration. Implications for practice, training, and research are discussed. Specifically, we address educators' need for increased training and the availability of educator resources.

Understanding Transformative Learning and Transformative Tourism

This study focuses on two major areas of transformative learning and transformative tourism. The study aims to understand how transformative learning theory developed by Jack Mezirow was first introduced to the academia and then adopted in the field of tourism. Transformative travel and tourism is an emerging paradigm in the travel industry, characterized by travel experiences that lead to profound personal growth, self-discovery, and societal benefits. This paper explores the intersections of transformative learning theory and transformational tourism experiences through a qualitative research approach. By synthesizing secondary data from diverse contexts and empirical studies, the study examines how transformative learning processes manifest in the context of travel and tourism. The theoretical framework draws on Mezirow’s transformative learning theory, emphasizing critical reflection and perspective learning. This study is based on a general review through thematic analysis of narratives. The research identifies mechanisms that facilitate transformative experiences during travel. The literatures highlight on novelty seeking, escapism, freedom, self-efficacy, the transformation of consciousness, self-development and personal growth, and subjective wellbeing which is an outcome of transformative travel. This study explores the concepts of transformation, transformative learning, transformational tourism, tourism motivation, tourism destination image, marketing, authenticity, satisfaction, and transformative experiences.

Towards a Multimodal WordNet for Language Learning in Bulgarian

In this paper we present some modifications to and extensions of a Wordnet for Bulgarian designed to make it more appropriate for applications in the area of language learning. However, in order to support education, we need to ensure the appropriate selection of sets of synonyms (synsets) from BTB- Wordnet, depending on the education level of the learners, and various types of exercises based on integration of the learning topic and semantic information within Wordnet. For this purpose, our focus is mainly on the combination of the lexemes (lemmas), with their meanings and examples, and the specially designed pictures as illustrations of those meanings within the synsets. We report on our preliminary results.

Pressure ulcer prevention for people with long-term neurological conditions (LTNCs) who self-manage care and live at home

AimTo develop a Theory of Change (ToC) pathway to facilitate the development of a multi-component intervention package supporting pressure Ulcer (PU) risk identification and management, in partnership with people with Long Term Neurological Conditions (LTNC) who self-manage care and live at home, their informal carers and PAs. MethodsA participatory approach, with extensive input from those whose lives are the focus of the research, was used throughout the 4 interlinked work packages (WP):•WP1 – Development of two co-operative Inquiry Groups (CIGs)•WP2 - Semi-structured interviews and/or app participation•WP3– Professional and strategic stakeholder engagement•WP4–Systems mapping and Theory of Change (ToC pathway developmentIterative data analysis was undertaken with emerging findings from each WP informing subsequent stages of the study. FindingsOverall, 74 participants contributed across the 4 WPs, incorporating 31 Service Users (SU), 8 carers, 9 Personal Assistants (PAs) and 26 professional stakeholders. We identified 8 key themes related to PU prevention, incorporating, learning, safe routines, third sector and peer support, navigating complex systems, adapting and reacting to change, perceptions of risk, risk negotiation and supporting roles. The findings indicate systemic and professional barriers which hamper people's ability to self-care and seek help. ConclusionsThe study highlights the complexities and impact of managing PU prevention activities at home for people with LTNC and areas of learning for health professionals and systems. By understanding these complexities we developed a systems map, identified resource requirements and illustrated a Theory of Change (ToC) pathway, to underpin future work to develop and user test an interactive, multi-component intervention.

Economic and Management Sciences Teachers’ Experiences of Teaching Financial Literacy: Implications for Teacher Training

This paper reports on economic and management sciences (EMS) teachers’ experiences of teaching the financial literacy component in this learning area. It also provides a holistic understanding of their challenges and professional development needs in this integrated field. A qualitative case study approach was used to allow for an in-depth understanding of EMS teachers’ views and experiences. Data were collected through open-ended questionnaires and semi-structured interviews. Purposive sampling was used to select information-rich participants from selected government secondary schools in Gauteng province, South Africa. Participants in the study included grades 8 and 9 EMS teachers. A thematic analysis approach was used to analyze data collected from the open-ended questionnaires and interview responses. The findings show that, due to poor training, EMS teachers continue to experience challenges in integrating the financial literacy component. Consequently, teachers default to fragmented approaches to teaching EMS, which undermines government initiatives aimed at realizing social transformation objectives through the EMS curriculum. The study recommends an implicit approach to teacher development programs by incorporating EMS teachers’ views, experiences, and specific needs as well as contexts. The research contributes to the literature on commerce education in South Africa by offering ways in which education can be transformative and how the quality of teaching financial literacy in EMS can improve.

Computer vision in the food industry: Accurate, real-time, and automatic food recognition with pretrained MobileNetV2

In contemporary society, the application of artificial intelligence for automatic food recognition offers substantial potential for nutrition tracking, reducing food waste, and enhancing productivity in food production and consumption scenarios. Cutting-edge technologies such as Computer Vision and Deep Learning are highly beneficial, enabling machines to learn automatically, thereby facilitating automatic visual recognition. Despite some research in this field, the challenge of achieving accurate automatic food recognition quickly remains a significant research gap. Some models have been developed and implemented, but maintaining high performance swiftly, with low computational cost and low access to expensive hardware accelerators, is still an area that needs further exploration and improvement. This study employs the pre-trained MobileNetV2 model, which is cost-efficient and fast, for automatic food recognition on the public Food11 dataset, comprising 16643 images. It also utilizes various tools and techniques such as dataset understanding, transfer learning, data augmentation, regularization, dynamic learning rate, hyperparameter tuning, and consideration of images in different sizes to cut time and enhance the model’s performance and robustness. These techniques aid in choosing appropriate metrics, achieving better performance, avoiding overfitting and accuracy fluctuations, speeding up the model, and increasing the generalization of findings, making the study and its results applicable to real-world applications. Despite MobileNetV2′s simpler structure and fewer trainable parameters compared to some deep-dense models in the deep learning area, it quickly achieved approximately 92.97 % accuracy. This underscores the model’s potential for implementation in real-world applications, which is the main intention of this study.

Contribution to School Design through Assessment of Corridor Conditions in Foundation Schools in Erbil, Iraq

School buildings are essential in catering to children’s psychological and educational needs. They enable children to learn, teach, play, and interact with peers. The corridor space within a school’s structure is also significant, serving multiple purposes. The community in Erbil, Iraq, has expressed concerns about the economic challenges of constructing and designing new school buildings. Therefore, this research aimed to identify unused spaces in these corridors to ensure usability and flexibility while reducing the cost of building construction. A comprehensive approach was taken to achieve this, employing both qualitative and quantitative analysis techniques. The qualitative analysis was conducted through surveys and documentation to provide an intense understanding of the issues. This research employed two distinct quantitative methods: first, the study used the Revit engineering software to compare the circulation ratio of pre-existing buildings with that recommended by the BB 103 guidelines, and second, student feedback was collected through a questionnaire to provide a holistic view of the situation. This study found that the built-up corridor area in the L-shaped school accounted for 34% of the total area, 11.5 percentage points more than the BB 103 guideline. Meanwhile, the built-up corridor area in the O-shaped school was 20.5 percentage points higher than the recommendation. According to the student feedback, the extra corridor space in the selected schools is not being efficiently utilized. Therefore, the proposed redesigns for the L-shaped and O-shaped schools focus on eliminating traditional corridors and integrating outdoor spaces to create functional areas, enhancing natural lighting and ventilation. These redesigned concepts ensure cost-effective, adaptable, and engaging educational spaces that support the well-being and academic success of students. This paper recommends that school designers and architects re-evaluate existing school designs with a focus on reducing corridor spaces and prioritizing outdoor learning areas. By adopting these strategies, schools can improve space utilization, foster healthier and more efficient learning environments, and promote sustainability.

AutoRL-Sim: Automated Reinforcement Learning Simulator for Combinatorial Optimization Problems

Reinforcement learning is a crucial area of machine learning, with a wide range of applications. To conduct experiments in this research field, it is necessary to define the algorithms and parameters to be applied. However, this task can be complex because of the variety of possible configurations. In this sense, the adoption of AutoRL systems can automate the selection of these configurations, simplifying the experimental process. In this context, this work aims to propose a simulation environment for combinatorial optimization problems using AutoRL. The AutoRL-Sim includes several experimentation modules that cover studies on the symmetric traveling salesman problem, the asymmetric traveling salesman problem, and the sequential ordering problem. Furthermore, parameter optimization is performed using response surface models. The AutoRL-Sim simulator allows users to conduct experiments in a more practical way, without the need to worry about implementation. Additionally, they have the ability to analyze post-experiment data or save them for future analysis.

The Use of Deep Learning in Open Learning: A Systematic Review (2019 to 2023)

No records of systematic reviews focused on deep learning in open learning have been found, although there has been some focus on other areas of machine learning. Through a systematic review, this study aimed to determine the trends, applied computational techniques, and areas of educational use of deep learning in open learning. The PRISMA protocol was used, and the Web of Science Core Collection (2019–2023) was searched. VOSviewer was used for networking and clustering, and in-depth analysis was employed to answer the research questions. Among the main results, it is worth noting that the scientific literature has focused on the following areas: (a) predicting student dropout, (b) automatic grading of short answers, and (c) recommending MOOC courses. It was concluded that pedagogical challenges have included the effective personalization of content for different learning styles and the need to address possible inherent biases in the datasets (e.g., socio-demographics, traces, competencies, learning objectives) used for training. Regarding deep learning, we observed an increase in the use of pre-trained models, the development of more efficient architectures, and the growing use of interpretability techniques. Technological challenges related to the use of large datasets, intensive computation, interpretability, knowledge transfer, ethics and bias, security, and cost of implementation were also evident.

Effects of integration interdisciplinary learning on student learning outcomes and healthcare-giving competence: a mixed methods study

BackgroundInterdisciplinary collaboration is known to foster professional innovation and enhance student learning across different domains. However, the research on the effectiveness of integration of interdisciplinary learning in pediatric nursing education is limited. Therefore, this study aimed to examine the effectiveness of integrating game-based learning, an interdisciplinary approach to teaching, into pediatric nursing education’s play courses.MethodsWe used a mixed methods study with pre-test/post-test quantitative analyses and a descriptive qualitative analysis of students’ reflection journals. Data were collected between August 2019 and July 2020 to gauge course effectiveness. Quantitative data obtained from the questionnaires were analyzed using a t-test, correlation, and regression analysis. Qualitative data using students’ reflective journals were collected and analyzed using content analysis. One hundred and three second-year nursing students enrolled in a four-year nursing program. Nursing students attended classes in university classrooms and served learning in a kindergarten or hospital in Northern Taiwan.ResultsThe subscales of Students’ Learning Outcome in knowledge, abilities, and attitudes showed significantly higher mean post-test scores compared to pre-test scores: 26.15 (SD = 3.35) vs. 16.82 (SD = 4.49), p < .001; 18.03 (SD = 2.13) vs. 11.43 (SD = 2.95), p < .001; and 12.90 (SD = 2.12) vs. 8.72 (SD = 2.52), p < .001. Furthermore, scores on the Service-Learning Abilities Scale indicated a significant increase in communication, problem-solving, knowledge application, and cross-cultural competence. Integrating instruction to improve problem-solving skills and knowledge application predicts student learning outcomes. Qualitative findings revealed nursing students’ reflections on integrating different learning areas, communication, problem-solving, and practical knowledge skills.ConclusionsIntegration of interdisciplinary learning effectively stimulates learning among nursing students and enhances their knowledge, abilities, and attitudes toward therapeutic play, benefiting children’s health. Our findings demonstrate that integration of interdisciplinary learning significantly enhances nursing students’ healthcare-giving competence, particularly in communication, problem-solving, knowledge application, and cross-cultural competence as measured by the Service-Learning Scale. Integrating social service with integration of interdisciplinary learning exposes nursing students to diverse challenges and needs, thereby enhancing their communication skills, knowledge application, and problem-solving abilities. Nursing students can blend knowledge and skills through integrated learning, which is crucial for nursing career preparation.Trial registrationN/A. It was a survey on educational activities.

StochCA: A novel approach for exploiting pretrained models with cross-attention

Utilizing large-scale pretrained models is a well-known strategy to enhance performance on various target tasks. It is typically achieved through fine-tuning pretrained models on target tasks. However, naï ve fine-tuning may not fully leverage knowledge embedded in pretrained models. In this study, we introduce a novel fine-tuning method, called stochastic cross-attention (StochCA), specific to Transformer architectures. This method modifies the Transformer’s self-attention mechanism to selectively utilize knowledge from pretrained models during fine-tuning. Specifically, in each block, instead of self-attention, cross-attention is performed stochastically according to the predefined probability, where keys and values are extracted from the corresponding block of a pretrained model. By doing so, queries and channel-mixing multi-layer perceptron layers of a target model are fine-tuned to target tasks to learn how to effectively exploit rich representations of pretrained models. To verify the effectiveness of StochCA, extensive experiments are conducted on benchmarks in the areas of transfer learning and domain generalization, where the exploitation of pretrained models is critical. Our experimental results show the superiority of StochCA over state-of-the-art approaches in both areas. Furthermore, we demonstrate that StochCA is complementary to existing approaches, i.e., it can be combined with them to further improve performance. We release the code at https://github.com/daintlab/stochastic_cross_attention.

Past, present, and future of hybrid plasmonic waveguides for photonics integrated circuits

This article addresses the past, present, and future status of hybrid plasmonic waveguides (HPWs). It presents a comprehensive review of HPW-based photonic integrated circuits (PICs), covering both passive and active devices, as well as potential application of on-chip HPW-based devices. HPW-based integrated circuits (HPWICs) are compatible with complementary metal oxide semiconductor technology, and their matched refractive indices enables the adaptation of existing fabrication processes for silicon-on-insulator designs. HPWs combine plasmonic and photonic waveguide components to provide strong confinement with longer propagation length Lp of HP modes with nominal losses. These HPWs are able to make a trade-off between low loss and longer Lp, which is not possible with independent plasmonic and photonic waveguide components owing to their inability to simultaneously achieve low propagation loss with rapid and effective all-optical functionality. With HPWs, it is possible to overcome challenges such as high Ohmic losses and enhance the functional performance of PICs through the use of multiple discrete components. HPWs have been employed not only to guide transverse magnetic modes but also for optical beam manipulation, wireless optical communication, filtering, computation, sensing of bending, optical signal emission, and splitting. They also have the potential to play a pivotal role in optical communication systems for quantum computing and within data centers. At present, HPW-based PICs are poised to transform wireless chip-to-chip communication, a number of areas of biomedical science, machine learning, and artificial intelligence, as well as enabling the creation of densely integrated circuits and highly compact photonic devices.

Exploring challenges in learning and study skills among first-year medical students: a case study

BackgroundDespite being high-achieving students, many medical students face academic challenges, particularly during their first year of study. Research indicates that self-regulated learning, involving metacognitive processes and adaptive strategies, can positively influence academic achievement. This study aimed to assess the early learning and study skills of first-year medical students in an international medical school with the goal of developing a learner-centered educational intervention to promote self-regulated learning.MethodsWe conducted a retrospective analysis of the Learning and Study Skills Inventory (LASSI) questionnaire that was administered annually each August to first-year medical students from 2019 to 2022. The distribution of students across different percentile ranges for each selected variable was determined for each year and all years collectively. Students were counted within distinct percentile brackets (50th and below, between 51st and 75th, and above 75th ) for each variable.ResultsA total of 147 students completed the LASSI questionnaire over the 4-year time period. Using academic resources was the greatest concern, with 67% of students in the 50th or below percentile, followed by selecting the main idea (56%), motivation (51%), and concentration (50%). Attitude scored highest across all cohorts, scoring between 21.55 ± 0.73 and 26.49 ± 0.34. In comparing mean scores of LASSI variables across all cohorts, attitude, motivation, test-taking strategies, time management, and the use of academic resources differed significantly (p < 0.05).ConclusionLASSI data can provide an early picture of students’ support needs. We posit that early identification of student learning and study skills and areas of struggle can inform personalized educational interventions and programs to support first-year medical students.

Architectural Synergy: Investigating the Role of Artificial Neural Networks in Enabling Deep Learning

Convolutional Neural Networks (CNNs) have transformed the area of deep learning by demonstrating exceptional abilities in a range of tasks, including object identification, picture identification, and natural language processing. Yet, study and investigation into the complex interactions between various architectural elements inside CNNs known as architectural synergy remain continuing. This study addresses the consequences of architectural synergy for improving model performance, scalability, and reliability, and examines how it enables deep learning using CNNs. Using an extensive examination of extant literature and real-world implementation cases, we clarify the processes that underlie architectural synergy and underscore its capacity to enhance the capabilities of CNN-powered models. We hope to further our knowledge of the fundamental ideas behind the effectiveness of CNNs in deep learning by illuminating this important area of neural network architecture learning tasks.

Creating indoor learning areas to implement the Early Childhood Care and Education Curriculum

Background: A safe and inclusive indoor learning environment reflects different ways of knowing, actuality and thinking. In the Early Childhood Care and Education (ECCE) context, indoor learning areas influence the exploration of teaching and learning activities.Aim: This article explored rural ECCE teachers’ experiences of creating indoor learning areas as required by the National Curriculum Framework (NCF) for children from birth to 4 years.Setting: Six purposively selected teachers from the three rural ECCE centres in KwaZulu-Natal province that transitioned to using the NCF participated in the study.Methods: A qualitative case study located within the interpretive paradigm was employed. Data that were inductively analysed were collected through semi-structured interviews with two teachers in each of the three centres. Transformative learning theory underpinned the study.Results: The study found that six teachers who desired to learn from each other engaged in a collaborative learning venture within their centres and complied with the NCF to create indoor learning areas in the interest of young children.Conclusion: The study argues that teachers shifted their insights from the challenges to achieving the objectives of the NCF. Thus, it questioned the assumption that rural teachers lack the knowledge to design learning areas.Contribution: Rural ECCE teachers are committed to learning for the development of young children.

How do undergraduate nursing students learn to care for families and informal caregivers? A qualitative study with a grounded theory approach

BackgroundNurses play a crucial role in caring for families of ill individuals in care, requiring high-quality relational and communication skills to care for them. Yet these skills remain underutilized, leading to reported issues of inadequate inclusion and communication. Education is crucial to enhance nurses' competencies in caring for families and informal caregivers. AimTo explore the learning process of undergraduate nursing students to care for families and informal caregivers. DesignQualitative study with a grounded theory approach. SettingsBachelor's degree in nursing from two off-sites of a university and four local health units collaborating with the university in North Italy. Participants15 undergraduate nursing students, 10 nurse preceptors, and 10 nurse clinical teachers. MethodsWe adopted initial and theoretical sampling and conducted semi-structured interviews from December 2023 to January 2024, lasting 16 to 62 min. The interviews were audio-recorded, transcribed verbatim, and analysed through open, selective, and theoretical coding. ResultsWe developed a theory of learning for undergraduate nursing students in caring for families and informal caregivers, comprising two themes, “Learning areas” and “Learning antecedents,” and nine categories. Learning areas involve five stages of learning to care for families and informal caregivers and the most frequent opportunities to interact with families and informal caregivers. The five stages are “Seeing and considering families and informal caregivers”, “Assessing the families' and informal caregivers' needs and resources”, “Preparing for and planning intervention with families and informal caregivers”, “Acting with families and informal caregivers”, “Reflecting on the intervention with families and informal caregivers”. Learning antecedents encompass student characteristics, interpersonal relationships, and the clinical training setting. ConclusionsIn this study, we delineate a five-stage learning process for undergraduate nursing students to care for families and informal caregivers, influenced by individual, interpersonal, and contextual factors. We emphasised the importance of relational skill development, tailored learning experiences, and supportive mentorship in enhancing students' preparedness to engage with and support families in healthcare settings. The developed theory provides a foundational framework for designing educational interventions to optimise nursing students' capacities in this domain.

Local Coherence and Subject Continuity: An Analysis Within the Centering Theory

Writing, which include complex processes influenced by many factors, are the least supported linguistic skills in the social context outside the learning environment compared to other learning areas. For this reason, practices in schools are important in the development of writing skills. As these practices aim to ensure that students gain awareness of the functioning of the language system and produce texts that are compatible with the discourse features shaped in line with communicative purposes, students are taught how to make choices compatible with the text type. Therefore, theories and approaches that describe how to make necessary choices to improve writing skills are one of the most important components of teaching effective writing skills. In terms of teaching writing, centering theory is essential as it provides descriptions for the discourse-compatible choices and the establishment of coherence relations needed for text production. Therefore, the aim of the study is to discuss why the centering theory should be taken into account in the practices for the development of writing skills based on the literature, and to describe how the traces of local text coherence and subject continuity are used in conjunction with the principles and concepts set forth by the centering theory

Evaluating the efficacy of computer games-based learning intervention in enhancing English speaking proficiency

The use of learning games in education, particularly for second language (L2) acquisition, has gained significant traction recently, establishing game-based learning as a notable academic discipline. This study examines how computer game-based learning influences ESL undergraduates’ speaking abilities, comparing traditional teaching methods with game-based teaching techniques. The study employed action research utilizing a control-experimental groups technique with a sample of 60 learners. Data were collected through observation sessions, interviews, as well as pre-tests and post-tests on English speaking skills. Upon comparing the scores of the control and experimental groups, the experimental group showed greater improvement in speaking skills. This study provides significant insights into the area of game-based learning using computers, particularly among international students in ESL contexts.