Learning Process Research Articles

The most effective strategies in teaching theoretical Anatomy in Medical schools, from a student’s view

Introduction: The anatomical study cannot be limited to memorization and identification of structures. It is essential that, in a modern and dynamic approach to this discipline, contextualization is adopted, and above all, the clinical applications of what is studied, in addition to other methods such as 3D images. It is necessary to understand the student's conception of such methods – the didactic and scientific evidence at the moment – so that they can make the connection – in the present and the future – with professional life. Methodology: The research, carried out with 163 medical students from two educational institutions in Juiz de Fora, aimed to find out which methodologies were used in their anatomy course; Which one(s) among them is(are) seen as the most effective, and most facilitator(s) of the learning process and approach to clinical practice. The data obtained were processed using the SPSS program, version 20.0. Results: It was evident that the approach to anatomical content based on clinical direction, contextualization of the subject, and use of radiological images is more widespread in Medicine. The application of seminars and clinical debates was scarcely explored. The use of alternative technologies to slides was notable in the Medicine course. Medical students, markedly, advocate for contextualizations and clinical applications. Conclusions: Students, in general, recognize the effectiveness of contextualization, clinical correlations, and the use of images. Few students support the use of seminars. As much as the interviewees do not prefer more summarized theoretical classes, they would like fewer structures to lean about, with more direct books.

Returning value from the All of Us research program to PhD-level nursing students using ChatGPT as programming support: results from a mixed-methods experimental feasibility study.

We aimed to evaluate the feasibility of using ChatGPT as programming support for nursing PhD students conducting analyses using the All of Us Researcher Workbench. 9 students in a PhD-level nursing course were prospectively randomized into 2 groups who used ChatGPT for programming support on alternating assignments in the workbench. Students reported completion time, confidence, and qualitative reflections on barriers, resources used, and the learning process. The median completion time was shorter for novices and certain assignments using ChatGPT. In qualitative reflections, students reported ChatGPT helped generate and troubleshoot code and facilitated learning but was occasionally inaccurate. ChatGPT provided cognitive scaffolding that enabled students to move toward complex programming tasks using the All of Us Researcher Workbench but should be used in combination with other resources. Our findings support the feasibility of using ChatGPT to help PhD nursing students use the All of Us Researcher Workbench to pursue novel research directions.

The Impact of Digital Communication Technology on Education in the Post-Crisis Period of the Covid-19 Pandemic

This study investigates the impact of digital communication technology in the education sector of Indonesia following the Covid-19 crisis. The rapid spread of the pandemic necessitated a shift towards digital communication tools in educational institutions. However, challenges such as limited access due to concurrent usage were encountered. This qualitative research employs a post-positivist paradigm and utilizes in-depth interviews with purposefully selected informants to collect data. The findings reveal that the adoption of online media technologies, including eLearning platforms, Zoom, Google Meet, WhatsApp, Classroom, and YouTube, has significantly enhanced technological literacy among students and lecturers. Moreover, it has facilitated effective communication both offline and online, demonstrating potential for future outcome-based education. This study emphasizes the importance of appropriate technology in post-crisis education, underscoring its value as an asset in the learning process. The findings contribute to the existing body of knowledge on digital communication technology in the educational context, specifically in the Indonesian setting.

OPTIMIZING EDUCATION STUDENTS’ PUBLIC SPEAKING SKILLS AS AN EFFORT TO IMPROVE TEACHER COMPETENCE

This study aims to evaluate the improvement of future educators' public speaking skills through training focused on their final results. In the third meeting, there was a significant improvement of 71.32% in the students' public speaking skills after the post-test. This result showed a good improvement from the previous pre-test. Good public speaking skills are very important for future educators, as this will affect their competence in becoming professional teachers. The teacher's ability to explain the material briefly but comprehensively is needed so that students can understand well. This research makes an important contribution in preparing future educators to communicate effectively, avoid difficulties during the learning process, and improve their public speaking skills.

IMPROVING HISTORY LEARNING OUTCOMES THROUGH "TALKING STICK" MODEL LEARNING IN CLASS XI STUDENTS OF SMA NEGERI 3 MEDAN

This research aims to improve the history learning outcomes of class XI students at SMA Negeri 3 Medan through the application of the "Talking Stick" learning model. The research method used is classroom action research (PTK) with two cycles, each consisting of planning, implementation, observation and reflection stages. The research subjects were 35 class XI IPS students. Data was collected through learning results tests, observations and interviews. The research results show that the application of the "Talking Stick" model significantly improves students' history learning outcomes. In the first cycle, the average student score increased from 68.5 to 75.2, and in the second cycle, it increased again to 82.4. Apart from increasing grades, there is also an increase in student activity and participation in the learning process. Students become more active in discussions and dare to express their opinions. The "Talking Stick" model has proven effective in increasing students' understanding and engagement in history subjects. Based on these findings, it is recommended that history teachers at SMA Negeri 3 Medan and other schools consider using the "Talking Stick" learning model as an alternative learning strategy to improve student learning outcomes. In addition, further research is recommended to examine the application of this model to different subjects and educational levels

COVID-19 Educational Side Effects: Pre-service EFL Teachers' Use of Digital Education Tools

Recent research has revealed the complexities of incorporating technology tools into lessons, despite the creation of several platforms and applications for education (Wen & Hua, 2020). The radical shift from traditional to online learning during the COVID-19 pandemic compelled teachers and students to develop technical skills to adapt to this new reality. This study explores the impact of this phenomenon on the perspectives of Pre-Service (PS) English language teachers (students in a teacher-training program), regarding the use of technology to support their own English language learning (ELL) process. To achieve this, an explanatory sequential mixed-method approach was employed. A questionnaire consisting of seven Likert scale statements and six open-ended questions was administered to 32 PS teachers from the English Language B.A program at a major public university in Southeast Mexico. Subsequently, eight participants were interviewed. The results indicated that despite most participants having prior knowledge of technological tools and educational platforms before the pandemic, they did not utilize them to support their ELL. However, the findings also revealed a positive response from participants towards continuing to use digital platforms due to perceived benefits experienced during Emergency Remote Teaching. These findings provide additional evidence concerning English learning and teaching and how classes can be more effective and significant using platforms and applications if classrooms are well equipped.

Implementation of Digital Visualization Tools in Education Concerning Business Process Administration

The integration of innovative technologies, such as digital twin one, is directly contributing to the evolution of the educational system, enables students to practice and learn them in an inclusive way of all areas, one of which is in the business sector. This study helps students in the field of education for the administration of business processes, enhance curriculum and increase faculty competency to the proper level with state-of-the-art technological developments with help of Digital Visualization Resources. On the other hand, enterprises should gain the competitive edge in the current dynamic marketplace by enhancing customer satisfaction, reducing costs, and increasing efficiency through the integration of digital technologies. Furthermore, such technologies make the learning process easier, interactive, interesting and more efficient than any form of traditional learning methods by creating customized content for the students as well as meeting of their specific needs and skills in the administration of business processes. Received: 2 June 2024 / Accepted: 25 July 2024 / Published: 29 July 2024

Research on Project-Based Teaching Strategies for the Chinese Curriculum of International Baccalaureate (IB) based on the SAMR Model

In the digital era, there have been significant changes in international students’ Chinese language learning patterns and methods. The integration of information technology and project-based teaching not only promotes the demand for applications and learning media but also provides new opportunities to enhance student’s critical thinking abilities. However, project-based teaching of information technology and Chinese is prone to the misconception of seeking the most suitable application or learning medium for verification. The SAMR (Substitution, Augmentation, Modification and Redefinition) model is an educational model based on Bloom’s taxonomy of educational objectives for “creative” teaching. This information technology-integrated teaching method provides students with diverse learning experiences. The Chinese language course of the International Baccalaureate (IB) aims to cultivate students’ profound understanding of literature, language, and culture by providing a critical exploration learning experience in the field of language and literature. It encourages students to explore similarities and differences between different cultures, delve into topics or works of interest, and conduct independent language and literature research projects. The project-based learning approach helps students meet their further academic research and personal growth skills needs, cultivating them as language users and lifelong learners who are willing to explore and have critical thinking skills. The application exploration of the SAMR model in project-based teaching proposes relevant suggestions for the integration of information technology and Chinese teaching in the digital era and provides some new focus points for effective strategies and paths of IB Chinese teaching: encouraging teachers to improve students’ skills in collaboration, communication, creativity, and critical thinking (4C) through advanced teaching at four different levels of SAMR model, flexible use of teaching rounds, creation of GRASPS teaching evaluation scenarios, and design of conceptual driving tasks, in order to achieve the improvement of language and literature construction and application abilities, and further promote the collaboration and autonomy of IB Chinese project-based learning process.

Interpretable machine learning boosting the discovery of targeted organometallic compounds with optimal bandgap

Organometallic compounds (OMCs) have attracted tremendous attention in various fields, such as photovoltaic cell and high-k dielectric application, due to their beneficial properties. Despite their potential, the progression of OMCs into industrial applications is hindered by the limited databases available for their properties and the absence of efficient surrogate models. To address this, in this study, optimally selected feature-based surrogate models for predicting the electronic properties of OMCs are constructed via various multiscale features and extensive database. To this end, high-throughput calculation was performed to obtain electronic properties of more than 18k materials generally known as organometallics, augmenting around 12k organic materials obtained from the public open data set, OMDB-GAP1. For generating features closely related to OMCs, descriptors encapsulating the information ranging local to global, also other widely-used composition-, structure-based features (more than 3.5k in total) were employed. Among these descriptors, we identified 48 critical features that elucidates the physicochemical underpinnings of OMCs’ properties, suggesting their impact on the properties of OMCs. The light gradient boosting machine model achieved high-accuracy predictions across the entire database with just 1 % of the total descriptors, sufficiently compared to the entire sets (decreased of around 0.01 by R2 score and 0.01 eV by MAE). Furthermore, the efficacy of active learning process was demonstrated to find OMCs with optimal properties rapidly. As a result, expected improvement outperforms other methods by identifying 69 % of the target materials only searching 46 % of the total search space. Our constructed platform with a high-throughput calculated database can pave the way for the rapid screening of OMCs for the targeted industrial application, and suggest a comprehensive grasp of the intrinsic properties of OMCs and related compounds.

Student Ultrasound Education, Current Views and Controversies; Who Should be Teaching?

Acquiring diagnostic ultrasound competencies and skills is crucial in modern health care, and achieving the practical experience is vital in developing the necessary anatomy interpretation and scan acquisition skills. However, traditional teaching methods may not be sufficient to provide hands-on practice, which is essential for this skill acquisition. This paper explores various modalities and instructors involved in ultrasound education to identify the most effective approaches. The field of ultrasound instruction is enriched by the diverse roles of physicians, anatomists, peer tutors, and sonographers. All these healthcare professionals can inspire and empower the next generation of ultrasound practitioners with continuous training and support. Physicians bring their clinical expertise to the table, while anatomists enhance the understanding of anatomical knowledge through ultrasound integration. Peer tutors, often medical students, provide a layer of social congruence and motivation to the learning process. Sonographers provide intensive practical experience and structured learning plans to students. By combining different instructors and teaching methods, success can be achieved in ultrasound education. An ultrasound curriculum organized by experts in the field can lead to more efficient use of resources and better learning outcomes. Empowering students through peer-assisted learning can also ease the burden on faculty. Every instructor must receive comprehensive didactic training to ensure high-quality education in diagnostic ultrasound.

WSSGCN: Wide Sub-stage Graph Convolutional Networks

Graph Convolutional Networks (GCNs) have emerged as a potent tool for learning graph representations, finding applications in a plethora of real-world scenarios. Nevertheless, a significant portion of deep learning research has predominantly concentrated on enhancing model performance via the construction of deeper GCNs. Regrettably, the efficacy of training deep GCNs is marred by two fundamental weaknesses: the inadequacy of conventional methodologies in handling heterogeneous networks, and the exponential surge in model complexity as network depth increases. This, in turn, imposes constraints on their practical utility. To surmount these inherent limitations, we propose an innovative approach named the Wide Sub-stage Graph Convolutional Network (WSSGCN). Our method is an outcome of meticulous observations drawn from classical and graph convolutional networks, aimed at rectifying the constraints associated with traditional GCNs. Our strategy involves the conception of a staged convolutional network framework that mirrors the fundamental tenets of the step-by-step learning process akin to human cognition. This framework prioritizes three distinct forms of consistency: response-based, feature-based, and relationship-based. Our approach involves three tailored convolutional networks capturing node/edge, subgraph, and global features. Additionally, we introduce a novel method to expand graph width for efficient GCN training. Empirical validation on benchmarks highlights WSSGCN’s superior accuracy and faster training versus conventional GCNs. WSSGCN triumphs over traditional GCN constraints, significantly enhancing graph representation learning.

Application of speech recognition algorithm based on interactive artificial intelligence system in English video teaching system

Social robots are intelligent programs that can autonomously run, automatically publish information, and interact on social media platforms. This article focuses on the speech recognition algorithm of interactive artificial intelligence systems, combined with the Hanning window function and the Vitit algorithm, and explores its application value in English video teaching systems through detailed experiments. Adopting speech feature extraction technology provides strong support for the subsequent recognition process. The application of Hanning window function has a positive impact on speech signal preprocessing. The most indispensable algorithm in speech recognition models is the Vitit algorithm, which successfully solves the problem of time variation and continuity of speech signals. This study successfully applied speech recognition algorithms based on interactive artificial intelligence systems to English video teaching systems. By combining speech feature extraction, Hanning window function, and Vitit algorithm, a system with strong recognition ability and interactivity was constructed. The English video teaching system aims to improve students’ learning process. By combining interactive artificial intelligence speech recognition technology with English video teaching, it can improve students’ experience in learning English and also meet their personalized learning habits.

Efektivitas Layanan Informasi dengan Teknik Role Playing untuk Meningkatkan Motivasi Belajar Siswa SMAN 2 Palembayan

Learning motivation is a very important factor in the learning process. High learning motivation can encourage students to undertake learning activities and will have an impact on student learning achievement. The study aims to look at the effectiveness of the implementation of information services with role-playing techniques to improve student learning motivation. This study uses a quantitative approach, with the kind of research Quasi Experiment project The Non Equivalent Control Group. As for the population in this study is the whole of students SMAN 2 Palembayan classes X and XI, sampling using purposive samplings, then sampled are classes XIF2 and XIF3. The technique used in the data collection is by spreading questionnaires in the form of motivational learning racket, further analysed using the comparison of the gain score table and the Mann U Whitney 2 Independent Sample Test. The results of this study show that the implementation of information services with role-playing techniques can improve student learning motivation.

Student responsibility after using SE in gymnastics as support for the MBKM curriculum

Background Problems: Responsibility is an important part for students to study at university. In the learning process, students arrive late to take part in learning and do not complete assignments or even do not do them. By using Sport Education (SE) students are given assignments in a role to be responsible for the success of learning. SE has a strong connection to the Merdeka Belajar-Kampus Merdeka (MBKM) curriculum with students as the center of learning. Research Objectives: The aim of this research is to find out the responsibilities of each subscale according to the student's role after using SE and to test the effect of using SE on student responsibilities. Methods: The research method uses experimentation with a one-shot case study design. The participants involved in this research were 53 students at one of the universities in the sports studies program in Indramayu who were taken using convenience sampling techniques. The research instrument used the Contextual Self-Responsibility Questionnaire for sports program students. The data analysis technique uses statistical descriptions to determine the mean and standard deviation and tests hypotheses using the one-sample t test. Finding/Results: This research provides new findings regarding student responsibilities using SE at university level, especially in Indonesia as a support for the MBKM curriculum. Conclusion: This research concludes that there is an influence after using SE on student responsibility. Further investigation is needed regarding the administration of pretests, the existence of comparison classes, and the development of instruments to facilitate all roles according to the characteristics of roles in SE.

Addressing the elephant in the room: engaging students in ChatGPT conversations on assessments

ABSTRACT The development of technology presents opportunities and challenges for the education system. This study investigates the integration of ChatGPT into higher education, focusing on tourism studies. Using a duoethnography approach, the study explores the experiences of two tourism educators who incorporate ChatGPT into their pedagogy and assessment methods. Results reveal that acknowledging students’ mixed responses towards ChatGPT encourages open discussions, while collaborative efforts in creating and assessing AI-driven assignments significantly enhance the learning process. Moreover, encouraging students to utilise ChatGPT responsibly promotes a sense of stewardship and ethical awareness, collectively enhancing educational experiences. The study presents key propositions for the effective incorporation of ChatGPT into higher education, along with practical implications for educators to leverage the potential of generative AI to enrich student learning experiences. It highlights the importance of adapting technological advancements while upholding ethical and pedagogical standards, offering insights into the effective use of AI in academic contexts.

Simulation of interaction E-learning mode in political courses based on virtual reality and digital entertainment environment

E-learning is a social network learning method that greatly promotes the dissemination of knowledge. Students can use mobile network terminals for video learning and also share their learning materials, making the learning process interactive and entertaining. This article is based on virtual reality technology and studies the effectiveness of the interactive E-learning mode for political courses in the digital entertainment environment. This online teaching method benefits students and teachers a lot with its unique advantages, and is unanimously favored by experts and scholars. These courses not only provide students with a comprehensive understanding of Marxism, but also help them develop a correct world outlook, values, and ethics. Meanwhile, in the current digital technology environment, interactive online learning has the characteristics of virtualization and entertainment. Students can comment on social hot topics and share their favorite content through various media platforms. The results indicate that the application of artificial intelligence and virtual reality technology in the interactive e-learning mode of political networks has important advantages.

English learners’ beliefs about L2 speaking fluency: Insights from elicited metaphor analysis

AbstractSecond language (L2) learners hold different learning beliefs that influence their interpretation of classroom experiences and their L2 learning process. Developing a thorough understanding of such beliefs is therefore imperative. This article reports the representations of Iranian English‐as‐a‐foreign‐language (EFL) learners’ beliefs about L2 speaking fluency as revealed by elicited metaphors and follow‐up interviews. A group of 24 Iranian EFL learners majoring in teaching English as a foreign language were asked to conceptualize L2 speaking fluency through metaphor. Learners’ metaphorical representations were examined using metaphor analysis and organized into eight metaphor themes through thematic analysis. The findings suggest that metaphor is a suitable tool for gaining insight into learners’ beliefs about L2 speaking fluency and capturing its complex, multifaceted nature. Various aspects were conceptualized, which revealed that learners had a deep understanding of L2 speaking fluency and could represent its multifaceted nature in the learning process. Additionally, this research sheds light on contextual factors that might contribute to learners’ beliefs. The findings fill a gap in research concerning EFL learners’ beliefs about L2 speaking fluency and have useful implications for L2 teachers, learners, and researchers.

Perception Differences between Families and Teachers on the Integral Development of the Child and the Educational Process

Educational development should be balanced among the different agents that make-up the entirety of the educational community (students, teachers, families, and external agents), with a prominent role of the family and teachers. However, it seems that reality does not comply with these principles, leading to a decrease in educational effectiveness. Therefore, the aim of this study is to analyze the perceptions of the legal guardian/family (LG), and the class tutor/teacher (CT), on the comprehensive development of students and on the global educational process, in order to clarify their role in this process. For this purpose, students aged 3–8 years were selected and the views of their families and teachers were compared (n = 820 observations), both in terms of the five areas that make-up the comprehensive development of the individual (cognitive, social, emotional, moral, and motor) and in regard to other determining variables that affect the global educational process (adaptive, cultural, digital, and school-type areas). The results show significant differences in the perceptions between both groups, with LGs rating all areas higher, except for the adaptive area, which was rated higher by CTs. The conclusions and the factors that explain these results, highlighting technical training as the most important determining factor, could serve as a starting point to bring the vision of both educational agents closer, which would result in an improvement in the communication channels between teachers and families, and in the optimization of the teaching and learning process itself.

Optimization of swimming mode for elongated undulating fin using multi-agent deep deterministic policy gradient

Optimizing speed and propulsive efficiency are the most crucial survival skills for biomimetic robots. This paper investigates a swimming mode controller inspired by the black Knifefish to govern the fast-swimming gait with high propulsive efficiency for an elongated undulating fin robot. The proposed swimming mode controller is composed of a couple of Hopf oscillator-based central pattern generators (CPG) to generate the moving gait of robotic fish and a novel variant of Reinforcement Learning (RL) known as Multi-Agent Deep Deterministic Policy Gradient (MA-DDPG) for optimizing the propulsive efficiency. The proposed swimming controller facilitates the autonomous optimization of the oscillatory amplitude of the robotic fish to improve its propulsive efficiency. The proposed MA-DDPG demonstrates an aptitude for functioning within mixed cooperative-competitive environments. Furthermore, it effectively mitigates the drawback of zero amplitude in the updating process of conventional reinforcement learning (RL) methodologies. These findings highlight the potential utility of the MA-DDPG in optimizing the performance of multi-agent systems in dynamic, real-world scenarios. The simulation results show that the undulating fin robot reaches a maximum thrust of 0.9 N with a propulsive efficiency of 12.48 %, which is higher than that of traditional reinforcement learning methods.

Intelligent Learning Platform with Deep Neural Network for Korean Language Teaching in Universities

Intelligent learning represents a dynamic approach to education that provides innovative technologies and personalized methodologies to enhance learning outcomes. Intelligent teaching adapts instruction to the individual needs, preferences, and progress of each student. This approach enables educators to tailor curriculum delivery, identify areas for improvement, and provide timely feedback, fostering a more engaging and effective learning environment. Moreover, intelligent teaching promotes collaborative learning experiences and encourages critical thinking skills, preparing students for success in an increasingly digital and interconnected world. This paper proposed a framework of Generative Platform-Oriented Intelligent Deep Neural Network (GPoIDNN) for Korean language teaching in Universities. The proposed GPoIDNN network comprises a social media platform for the promotion of Korean language teaching among students. With the GPoIDNN platform, a Generative network is implemented for the analysis of the factors involved in Language teaching in universities. The platform considered for the proposed model is Weibo for acquiring in-depth information about the language learning process. Upon the estimated features GPoIDNN uses the Generative Deep Neural Network platform for the classification and examination of the student performance. With the Weibo platform in social media, the Generative network constructs the intelligent teaching system for the Korean language teaching process in University students. The examination of student performance demonstrated that the proposed GPoIDNN model improves the student learning of Korean language with improved by 73% through the intelligent model. Further, the keywords and opinions classified with the GPoIDNN model exhibits a higher classification rate of 0.98 based on the opinion of the students in the universities.