Concept Of Learning Research Articles

Development of a Joyful Learning-Based Instructional Model in Javanese Script

Learning Javanese script is considered an outdated and boring lesson. This paradigm of boring and obsolete Javanese script lessons must be changed into a modern, interesting, and enjoyable learning experience. One way to do this is by developing a Joyful Learning-based model for Javanese language instruction. Joyful Learning is a concept of enjoyable learning. The development of a Joyful Learning-based model for Javanese language instruction is urgent and necessary because the learning model currently used by students needs to employ the principles of Joyful Learning, resulting in students feeling bored, tired, and unmotivated to learn. Additionally, Javanese language instruction is viewed as a good means to develop the character of the nation's children, as it contains values of morality and politeness. The research design used is the ADDIE Research and Development design, with the steps of analyzing, designing, developing, implementing, and evaluating. This study uniquely integrates traditional games into the Joyful Learning model. The result of the study is creating a Joyful Learning-based model for Javanese script instruction. The components of this model include the social system, reaction principles, support system, instructional and incidental impacts, and syntagmatic. The syntagmatic model of Joyful Learning-based Javanese script instruction includes an introduction, material delivery, games for writing sentences, games for reading paragraphs in Javanese script, formative assessment, and reflection. The learning model has been tested at SMPN 12 Semarang. The results of the school trial indicate that the Joyful Learning-based Javanese script instruction model is effective for learning.

Unifying Principles of Generalization: Past, Present, and Future.

Generalization, defined as applying limited experiences to novel situations, represents a cornerstone of human intelligence. Our review traces the evolution and continuity of psychological theories of generalization, from its origins in concept learning (categorizing stimuli) and function learning (learning continuous input-output relationships) to domains such as reinforcement learning and latent structure learning. Historically, there have been fierce debates between approaches based on rule-based mechanisms, which rely on explicit hypotheses about environmental structure, and approaches based on similarity-based mechanisms, which leverage comparisons to prior instances. Each approach has unique advantages: Rules support rapid knowledge transfer, while similarity is computationally simple and flexible. Today, these debates have culminated in the development of hybrid models grounded in Bayesian principles, effectively marrying the precision of rules with the flexibility of similarity. The ongoing success of hybrid models not only bridges past dichotomies but also underscores the importance of integrating both rules and similarity for a comprehensive understanding of human generalization.

Preservice physical education teachers’ perceptions of initial teacher education

The purpose of this study was to investigate preservice physical education teachers’ perceptions of initial teacher education and its impact on their professional lives and teachers’ identities at the end of their school placement. It was also the aim of this study to identify school placement contributing factors and key actors in the formation of professional identities. The sample was composed of 272 preservice teachers in their final year of the master's in teaching physical education at a Portuguese university. We collected data through a questionnaire that included closed- and open-ended questions regarding six aspects of the teaching profession and initial teacher education: agents of training; components of teacher education; roles of teachers; motivation for teaching; conceptions of teaching and learning; and changes experienced during this period. Quantitative data were statistically analysed for measures of central tendency, and the responses to the open-ended question were analysed through thematic content analysis. The findings revealed: that preservice teachers considered the cooperating teacher to be the most important agent of training; that the teaching practicum experience was the most important component of teacher education; that delivering universal values was an essential role of teachers; that they had an intrinsic motivation for teaching; that they perceived a constructivist approach to teaching; and that the most meaningful change they experienced during their education was an improvement in soft skills. With the results, we conclude that professional socialisation influenced how the participants performed as teachers.

Incorporating different modes in courseware for conceptual learning

ABSTRACT This quasi-experimental study aims to compare the effects of using combinations of written text, animation and narration in multimedia courseware. 114 sixth grade students assigned in three conditions were participated in the study. Three versions of the courseware with combinations of animation, text and narration were developed taking modality into account. The three groups were taught by using three different versions of the courseware. As a result, there was no significant difference between the test results for conceptual learning were found. However, students’ evaluations showed that learning from different forms of knowledge caused some slight differences in their cognitive processes. Suggestions for designers to use appropriate forms of knowledge in courseware are also included.

Advanced Personal Budget Analytics: Combining Optical Character Recognition and Natural Language Processing for Automated Budget Categorization and Insight Extraction

A budget tracking system is a tool designed to help users monitor their financial resources, categorize expenses and control their financial resources. An Intelligent Personal Budget Analysis System is designed to redefine personal finance management. IntelliFinance is a user- friendly app designed for seamless and efficient daily expense management removing the necessity for conventional paper documentation. This project inculcates the concepts of Computer Vision, Machine Learning and Data Analytics, aims to surpass traditional budget tracking by incorporating innovative features such as receipt scanning and analysis. The project is implemented using Android Studio and Firebase, incorporating advanced features such as Optical Character Recognition (OCR) to capture receipt images, extract text, and process it for further analysis. Firebase ML Kit is utilized for scanning and text recognition, while Natural Language Processing (NLP) is applied for categorizing the extracted text. The system provides a personal budget analysis that enhances the accuracy of financial tracking by offering users a comprehensive overview of their spending habits, complemented by detailed reports and visualizations. Ultimately, this project serves as a financial companion, empowering users to take control of their finances, make informed decisions, and achieve their financial goals.

The Effect of Steam Approach to Economics Media Based on Bima Local Wisdom in Elementary Schools

The purpose of this article is to contribute new learning concepts about critical thinking in social sciences, especially economics, as well as the belief that social character is not developed in Indonesian schools. We investigated how primary school teachers self-reported applying what they had learned about economics to their daily social views. With the aid of educational media, this experimental study aimed to ascertain the extent to which the STEAM method influences the meaning of studying economics from early in life. According to the findings, very few pupils comprehend how economics affects both the environment and them in day-to-day living. Not only did we discover that the STEAM technique had a significant effect on pupils' thinking processes. However, they also discover the impact of their characters. There are significant differences in the level of understanding of learning, one of which is influenced by local wisdom. The implications of these findings for sharpening primary school pupils' comprehension of social science courses are explored. We suggest that social science learning be implemented using many of the latest approaches. Focusing on improving character based on local culture is not enough to use the traditional approach that has been implemented so far.

Didactic and Psychological Principles of Successful Design of Serious Games

In this paper, a systematic, evidence-based overview of didactic and psychological design principles is provided, which have a significant impact on the learning success of Serious Games. Design criteria are described that relate to the structure of games, the principle of learning through play, interaction regarding usability and playability, as well as motivation with the necessary game incentives. Furthermore, perspectives on the future development of Serious Games are outlined, focusing particularly on the implementation of concepts of adaptive e-learning and AI-supported learning.

Learning by doing: a role theoretical approach to learning of inter-governmental organizations

ABSTRACT Inter-governmental organizations (IGOs) have proliferated since World War II and have evolved into significant social actors shaping global governance. It contends that IGOs, through roles, contribute to the dense network of social expectations, adding a nuanced layer beyond the structural aspects of the international system. The article asserts that IGOs, confronted with changing global dynamics, engage in organizational role learning (ORL) to manage state role conflicts and contribute to international order. While existing scholarship often references roles descriptively, this article advocates for a roles-based perspective, positioning it within the social constructivist paradigm. The article introduces the concept of organizational role learning (ORL) and applies it to case studies on ASEAN and the African Union, revealing shifts in role conceptions and emphasizing the crucial role of ORL in maintaining organizational efficacy. The study contributes to understanding the intricate interplay between IGOs, their roles, and the evolving global landscape.

Enhancing real-time urban drainage network modeling through Crossformer algorithm and online continual learning

This study presents an innovative approach to real-time modeling of urban drainage networks, leveraging a highly accurate coupled one- and two-dimensional hydrodynamic model to generate a training dataset for node water levels. By employing global states inferred from monitoring points as model inputs, this study overcomes the limitations imposed by the scarcity of monitoring data and the challenge of capturing all node levels. The Crossformer algorithm, which simultaneously accounts for correlation at both temporal and feature scales, is applied to enhance the precision of simultaneous water level predictions across the network. Comparative analysis of different prediction patterns reveals that extending predictions based on a high-accuracy infrastructure offers more benefits than direct modifications to the algorithm's structure. In addition, this paper pioneered the application of online continuous learning concepts to update the prediction model in real time, achieving a balanced integration of measured and simulated data. Consequently, this paper establishes a complete monitoring-predicting-updating real-time simulation system for urban drainage networks.

Strengthening teacher competence through joyful learning and innovative learning media training

A needs assessment at Muhammadiyah Middle School 9 Tanggulangin revealed that teachers struggle with creating interactive learning environments and developing innovative teaching materials. To address these challenges, a training program was conducted to enhance teachers' pedagogical skills, creativity, and motivation. The program consisted of two key activities: joyful learning training and training in the development of creative and innovative learning media. The process included several stages: preparation (needs assessment, program design, material development, and pre-test), implementation (intensive training on joyful learning and innovative media development), and evaluation. The training involved 12 teachers (4 men and 8 women). The results showed significant improvements in teachers' understanding of joyful learning concepts and their ability to create creative and innovative learning materials. This program highlights the importance of adopting innovative and enjoyable teaching strategies to enhance teacher competence and improve student learning experiences. The initiative demonstrated that targeted training could effectively address the challenges teachers face, leading to better educational outcomes.

Learning to support self-regulation: empowering preschool teachers through understanding by design and blended learning

ABSTRACT In this study, preschool teachers’ self-regulation knowledge and practices were improved through a professional development program. The program was crafted using the Understanding by Design framework to facilitate the transfer of learned concepts into the classroom. A blended learning approach with synchronous and asynchronous components was used to accommodate time and location constraints. The program covered executive functions, metacognition, emotion regulation, and motivation regulation in five modules. Program effectiveness was assessed using a nested mixed-method design. The study included 68 preschool teachers from 26 Turkish cities. Pre- and post-tests were used to collect quantitative data, while electronic survey forms and focus group interviews were used to collect qualitative data. The program significantly increased teachers’ use of metacognition and emotional-motivational regulation practices. Teachers’ belief in children’s control potential improved, resulting in significant shifts in their understanding and application of self-regulation.

Integrating Digital Assistive Technologies Into Care Processes: Mixed Methods Study.

Current challenges in patient care have increased research on technology use in nursing and health care. Digital assistive technologies (DATs) are one option that can be incorporated into care processes. However, how the application of DATs should be introduced to nurses and care professionals must be clarified. No structured and effective education concepts for the patient-oriented integration of DATs in the nursing sector are currently available. This study aims to examine how a structured and guided integration and education concept, herein termed the sensitization, evaluative introduction, qualification, and implementation (SEQI) education concept, can support the integration of DATs into nursing practices. This study used an explanatory, sequential study design with a mixed methods approach. The SEQI intervention was run in 26 long-term care facilities oriented toward older adults in Germany after a 5-day training course in each. The participating care professionals were asked to test 1 of 6 DATs in real-world practice over 3 days. Surveys (n=112) were then administered that recorded the intention to use DATs at 3 measurement points, and guided qualitative interviews with care professionals (n=12) were conducted to evaluate the learning concepts and effects of the intervention. As this was a pilot study, no sample size calculation was carried out, and P values were not reported. The participating care professionals were generally willing to integrate DATs-as an additional resource-into nursing processes even before the 4-stage SEQI intervention was presented. However, the intervention provided additional background knowledge and sensitized care professionals to the digital transformation, enabling them to evaluate how DATs fit in the health care sector, what qualifies these technologies for correct application, and what promotes their use. The care professionals expressed specific ideas and requirements for both technology-related education concepts and nursing DATs. Actively matching technical support, physical limitations, and patients' needs is crucial when selecting DATs and integrating them into nursing processes. To this end, using a structured process such as SEQI that strengthens care professionals' ability to integrate DATs can help improve the benefits of such technology in the health care setting. Practical, application-oriented learning can promote the long-term implementation of DATs.

Federated learning of medical concepts embedding using BEHRT.

Electronic health record data is often considered sensitive medical information. Therefore, the EHR data from different medical centers often cannot be shared, making it difficult to create prediction models using multicenter EHR data, which is essential for such models' robustness and generalizability. Federated learning (FL) is an algorithmic approach that allows learning a shared model using data in multiple locations without the need to store all data in a single central place. Our study aims to evaluate an FL approach using the BEHRT model for predictive tasks on EHR data, focusing on next visit prediction. We propose an FL approach for learning medical concepts embedding. This pretrained model can be used for fine-tuning for specific downstream tasks. Our approach is based on an embedding model like BEHRT, a deep neural sequence transduction model for EHR. We train using FL, both the masked language modeling (MLM) and the next visit downstream model. We demonstrate our approach on the MIMIC-IV dataset. We compare the performance of a model trained with FL to one trained on centralized data, observing a difference in average precision ranging from 0% to 3% (absolute), depending on the length of the patients' visit history. Moreover, our approach improves average precision by 4%-10% (absolute) compared to local models. In addition, we show the importance of the usage of pretrained MLM for the next visit diagnoses prediction task. We find that our FL approach reaches very close to the performance of a centralized model, and it outperforms local models in terms of average precision. We also show that pretrained MLM improves the model's average precision performance in the next visit diagnoses prediction task, compared to an MLM without pretraining.

E!Canasta: A card game to teach ATP synthesis and metabolic regulation in biochemistry classes.

Understanding ATP formation is essential for learning metabolism and is central to grasping metabolic processes as a whole. However, due to the high level of abstraction, the number of intermediate substrates, the connections, and integrated regulation, its comprehension often poses a challenge. This and the fact that traditional teaching methods struggle when dealing with highly abstract concepts, game-based strategies present a more concrete and dynamic alternative, which led to the creation of E!Canasta (card game). Developed based on Canasta and adapted in order to improve the learning of concepts, including some of pathway's regulation and integration, E!Canasta motivates students and promotes engagement in a fun activity. Students assemble a sequence of cards representing the glycolysis, acetyl-CoA, Krebs cycle, and electron transport chain, which correspond to the card suits. Strategically, some of the cards hold special feats that simulate some aspects of metabolic regulation and integration (to give or take away points). At the end of the game, points are added up for sequences and cards with positive or negative effects. The game was played with two classes of students enrolled in biochemistry as part of their graduations (86 players). Student perception on gameplay, motivation and understanding was measured through an anonymous Likert scale questionnaire, with very positive results in all questions. Statistically significant correlations were observed regarding the perceived comprehension of pathways and their regulation, and in linking motivation with a positive gaming experience, showcasing that E!Canasta demonstrates considerable educational potential, along with an enjoyable experience for learning ATP synthesis.

The effect of mind mapping on the level of student learning success in the Pancasila course: a study on students of the UNY English department

The quality of a nation's human resources can be measured from the learning achievements of students. Learning achievement is an indicator of student learning success and also an indicator of educator success in conducting learning. Learning success reflects the success of students in mastering learning concepts expressed by grades. One way to increase student understanding of concepts is by applying mind mapping. This study aims to determine the effect of mind mapping on the success rate of student learning in the Pancasila course. The method used in this research is Pre-Experimental with One Group Pretest-Posttest Design. The research sample consisted of 36 students majoring in English literature at UNY by choosing purposive sampling. Analysis of the learning outcomes obtained shows that the value of ha is accepted which means that the effect of applying mind mapping has on student learning success in the Pancasila course. While the Gain value (the average increase as an indicator of learning success) obtained results of 0.33 in the medium category. The implication of this research is as a source of information or a reference for educators that the application of mind mapping in learning can increase learning success.

The Ludo-Learning Matrix: A Framework for Understanding Learning in Games

Games have been widely recognized as methods of making learning more engaging. This has proven to be very attractive to those attempting to get complex fields such as cybersecurity training to a wider audience. Unfortunately, there is a failure to understand that each type of game serves a different educational purpose, leading to the situation where the games are being selected incorrectly and are failing to fulfill their promise. To address this issue, key concepts in learning and games were identified from the literature and then operationalized into an analytical framework. The concepts of player agency, message broadcasting, the transfer of learning and the type of challenges present in the game were selected. This generated a framework that is player-focused rather than content-focused and could be applied to any potential learning game. To validate the framework, three cybersecurity games were selected and analyzed using a ludo-textual approach. Cyberciege, a single player game aimed at university students, Spoofy, a kids’ web browser game and Tallinn Soldier, a seminar wargame, were selected to give as wide a sample as possible. The paper goes on to report on the results of the analysis and discuss how this may be used to examine and design learning games for cybersecurity in the future. Each of the selected games focus on different mechanisms for learning and engagement, highlighting the design tradeoffs that were made in the creation of the game. The proposed analytical framework can be applied not just to cybersecurity training games but theoretically to understanding any game that has learning as its objective.

The Role of Generative Learning Strategy in Bridging the Gap between High and Low Achievers in Genetics Studies in Sefwi-Wiawso Municipality, Ghana

The study sought to investigate the use of the Generative Learning Strategy (GLS) in bridging the performance gap between high- and low-achieving students in genetics in Ghana's Western North region's capital, Sefwi-Wiawso Municipality. The study adopted an embedded research design involving the quasi-experimental pretest/posttest groups with a sample size of 106 SHS 3 Biology students. Two intact classes were randomly selected, treated as one group and exposed to the same treatment conditions. The Genetic Concepts Test and a semi-structured interview guide collected the quantitative and qualitative data, respectively. The GCT's internal consistency was 0.784, indicating a preferable internal consistency. The quantitative data was analyzed using the SPSS version 26, by employing descriptive and inferential statistics. The study found no significant performance difference between high and low achievers after using the GLS. The approach improved the lower achievers’ performance. The interview results revealed that Senior High School Biology students perceived that the Generative Learning Strategy improved the understanding, motivation, retention and self-directed learning of genetic concepts, thereby enhancing their learning outcomes. The study recommended that SHS Biology teachers employ the Generative Learning Strategy in teaching genetic concepts to bridge the performance gap between high and low achievers.

The Game of Dominoes as Teaching-learning Method of Basic Concepts of Differential Calculus

This paper will present teaching-learning mathematics strategies, specifically differential calculus in a variable, through a fun and competitive space in which action is manifested by the student and not only the repetition of information by the teacher. This action refers to motivate, problematise, summarise, and coordinate a dominoes game whose thematic cards are designed around the basic and main contents of differential calculus. The strategies for teaching this area are diverse and precisely the game of dominoes is one of the most used strategies in the practice of mathematics because it stimulates logical reasoning and mental skills. The objective is to identify the way in which the game of dominoes affects the learning and understanding of fundamental concepts of differential calculus in a variable by means of experimentation carried out on students of the first semester of the School of Engineering and Sciences of Technological of Monterrey. Finally, the results of this study will be presented and the use of this strategy in other topics around mathematics will be recommended to facilitate logical and meaningful learning in students.

Ai] Explore!: An Educational Game for Developing Programming Skills and Algorithmic Thinking

The game [ai] explore! was developed to introduce the algorithm behind the popular science exhibition. The idea behind the [ai] explore! exhibition was to show the application of mathematics and computer science in solving real engineering problems by creating the exhibit using the mathematical algorithm Heat Equation Driven Area Coverage (HEDAC). The algorithm is based on scientific research and has many applications: exploration and search in unknown space, painting, planning agricultural spraying, scanning 3D objects, etc. The exhibits show the process by which the algorithm paints objects with a virtual brush and explores their shape. By surveying the high school students, it was shown that new mathematical and engineering results can be explained and turned into a playable game. After playing the game, students respond positively to the game presented and state that they have a good understanding of the HEDAC algorithm presented and how it works. This motivated us to investigate [ai] explore! as an educational game for teaching mathematics and computer science. The aim of the research described in this paper is to investigate the potential of the developed game as an educational game. The game-based learning (GBL) approach is increasingly used to increase student motivation and engagement in STEM lessons. The main research question is: How do primary school teachers and students perceive the usefulness of the game [ai] explore! in supporting teaching and learning of computer science concepts? We have developed and implemented teaching scenarios on how the game [ai] explore! can be used as an educational game in computer science lessons. We show that the game has great potential to teach primary school students programming. In addition, the game promotes algorithmic thinking and computational thinking skills in general, which are valuable not only in computer science but also in other fields such as mathematics, where a systematic and analytical approach to problem-solving is required.

Tiers of Engagement: Achieved Learning From Business Simulations Reflected in Economics Students’ Experiences

This article investigates the impact of a business simulator in an online economics course, focusing on the relationship between student engagement and reflections on learning. Utilizing a mixed-methods approach, our study analyzes responses from 328 students who used the "Hubro Business Simulator" in a flexible online bachelor's program in economics and administration. Students provided reflections on the simulator as a learning activity, application of theoretical concepts and practical relevance. Qualitative analysis of 1640 responses further explored the depth of students' reflections, categorized into different tiers of engagement based on their responses. This analysis builds on Self-Regulated Learning (SRL) and motivational theory. The study sought to determine whether students reporting higher levels of engagement exhibited deeper metacognitive reflections compared to their less engaged peers. Findings support a link between the level of engagement and the depth of reflection. Students with higher engagement levels were more likely to reflect on specific ways in which the simulator had supported their learning and understanding of theoretical concepts. This paper discusses the limitations and implications of these findings for enhancing game-based learning interventions, emphasizing the need to foster higher engagement levels to improve educational outcomes in online learning environments. The study contributes to the literature on game-based learning by providing a large empirical study on how business simulators can foster higher-order thinking and deeper learning reflections among economics students. It also highlights the role of engagement in using business simulators as learning tools, offering insights that could improve the learning design and implementation in similar online and flexible learning program contexts.