Individual Learning Capabilities Research Articles

랜덤포레스트(Random Forest)를 활용한 초·중·고등학생의 정보역량 영향요인 탐색

Objectives The main purpose of this study is to identify factors that improve information competency in elemen-tary, middle, and high school students and quantitatively evaluate their influence. For this purpose, the Random Forest algorithm among the ensemble series of machine learning was utilized. Random Forest is an ensemble technique based on decision trees that reduces the risk of overfitting and has high prediction accuracy and stabil-ity, so it is used in various research and practice. In this study, various variables that affect information competency were extracted based on survey data from elementary, middle, and high school students. Complex interactions between variables were analyzed, and key variables that had a particularly significant impact on information capa-bilities were identified. In addition, Shap Value was used to quantitatively evaluate the influence of each major var-iable, with the goal of clearly understanding the relative importance and influence of each variable.
 Methods To fulfill the objectives of this study, we used publicly available data from the National Information Agency, extracting data from 1,469 elementary, middle, and high school students for model training and evaluation. A total of 20 explanatory variables were selected, including information utilization, social relationships, and the level of usage of information-sharing services.
 Results The final model built in this study showed performance metrics of Accuracy 0.721, Precision 0.716, Recall 0.723, and F1 Score 0.711. The key influencing variables were identified as digital device usage efficacy, attitudes toward digital technology, information utilization, social relationships and information-sharing services, social capital, information production and sharing levels, usage level of lifestyle services, and digital enablers.
 Conclusions The advent of the digital society due to the Fourth Industrial Revolution has made information literacy an essential core competency, playing a crucial role in enhancing individual learning capabilities as well as general competitiveness in everyday life. According to the results of this study, in order to improve the information literacy of elementary, middle, and high school students, education in software and hardware (SW·HW), training in in-formation reproduction through digital device usage, and fostering a positive attitude toward digital technology are necessary.

Performance of ChatGPT on Registered Nurse License Exam in Taiwan: A Descriptive Study.

(1) Background: AI (artificial intelligence) chatbots have been widely applied. ChatGPT could enhance individual learning capabilities and clinical reasoning skills and facilitate students' understanding of complex concepts in healthcare education. There is currently less emphasis on its application in nursing education. The application of ChatGPT in nursing education needs to be verified. (2) Methods: A descriptive study was used to analyze the scores of ChatGPT on the registered nurse license exam (RNLE) in 2022~2023, and to explore the response and explanations of ChatGPT. The process of data measurement encompassed input sourcing, encoding methods, and statistical analysis. (3) Results: ChatGPT promptly responded within seconds. The average score of four exams was around 51.6 to 63.75 by ChatGPT, and it passed the RNLE in 2022 1st and 2023 2nd. However, ChatGPT may generate misleading or inaccurate explanations, or it could lead to hallucination; confusion or misunderstanding about complicated scenarios; and languages bias. (4) Conclusions: ChatGPT may have the potential to assist with nursing education because of its advantages. It is recommended to integrate ChatGPT into different nursing courses, to assess its limitations and effectiveness through a variety of tools and methods.

The Effect of Technology Readiness on Individual Absorptive Capacity Toward Learning Behavior in Australian Universities

Recipient's absorptive capacity (ACAP) is a barrier to knowledge transfer in organizations. The technology readiness (TR) dimensions measure an individual's technological beliefs and aligns with the individual's ACAP. The purpose of this research is to study if technological beliefs have a causal effect onto individual learning capability and behaviour. University's knowledge transfer makes them an ideal context for this research. Through surveying individuals and conducting statistical analysis, the authors provide empirical evidence that there is a causal effect from the TR dimensions to individuals ACAP and their technological learning behaviour at the individual level. The findings could potentially help leverage technology to address said recipient's ACAP. It would also benefit the development of new technologies, in particular in e-learning and tailoring pedagogy.

Artificial intelligence for load forecasting: A stacking learning approach based on ensemble diversity regularization

State-of-art artificial intelligence (AI) has made great breakthroughs in various industries. Ensemble learning mixed with various predictors provides a considerable solution for electric load forecasting in power system. In our paper, the generalization error of ensemble learning is statistically decomposed to exhibit the significance of base-learner diversity. A diversity regularized Stacking learning approach is proposed to solve the electric load forecasting issue. In our model, the input features are comprehensively selected by various tree-based embedded methods to understand the feature contribution. The robust candidate base-learners are extracted from sub-model pool depending on diversity regularization besides the individual learning capability. Mutual information theory and hierarchical clustering quantitatively assess the dissimilarity degree among base-leaners by exploiting error distribution. The Stacking ensemble framework is utilized to avoid the over-fitting occurrence by employing leave-one-out data splitting procedure for raw dataset block. At last, various cases from different time horizons or geographical scopes are deployed to verify the validity of the model. The case shows that the diversity regularized Stacking learning has better prediction performance compared with the traditional ensemble model or single model. Load forecasting results become more accurate and stable when elaborately selecting base-learners portfolio.

Examining Resource Based Learning and Individual Learning Capabilities in Todays’ Scenario

The immense use of web based resources is an undeniable truth in today’s learning scenario. Resource-based learning has gained momentum in leaps and bounds. Resource-based learning aids in the academic and holistic development of students by taking into account their capabilities, their styles of learning and their needs. RBL empowers the student to analyze and organize digital material. It also enables the learner to develop critical thinking skills and gives them the confidence to sift from the plethora of information available, the skill to ferret out what they need and what is needed for them. This skill will go a long way in empowering them to utilize the varied resources that is available on hand in various forms be it print or electronic. Such training in thinking will help them to approach any topic in a number of learning styles. The authors of this research paper, have attempted to understand the impact of resource based learning on teachers, keeping in view Gagne’s (1985) theory of levels of learning. Teachers from traditional background of teaching methods involving classroom interface, were approached and their views on the new methods popularized by RBL were obtained by means of a self-administered online questionnaire. The objective of the study was to analyze the attitudinal responses of the teachers towards RBL and whether they viewed it as a beneficial exercise for students as against traditional methods of learning.

Cockroaches Show Individuality in Learning and Memory During Classical and Operant Conditioning.

Animal personality and individuality are intensively researched in vertebrates and both concepts are increasingly applied to behavioral science in insects. However, only few studies have looked into individuality with respect to performance in learning and memory tasks. In vertebrates, individual learning capabilities vary considerably with respect to learning speed and learning rate. Likewise, honeybees express individual learning abilities in a wide range of classical conditioning protocols. Here, we study individuality in the learning and memory performance of cockroaches, both in classical and operant conditioning tasks. We implemented a novel classical (olfactory) conditioning paradigm where the conditioned response is established in the maxilla-labia response (MLR). Operant spatial learning was investigated in a forced two-choice task using a T-maze. Our results confirm individual learning abilities in classical conditioning of cockroaches that was reported for honeybees and vertebrates but contrast long-standing reports on stochastic learning behavior in fruit flies. In our experiments, most learners expressed a correct behavior after only a single learning trial showing a consistent high performance during training and test. We can further show that individual learning differences in insects are not limited to classical conditioning but equally appear in operant conditioning of the cockroach.

Individual Learning Capability and its Association to Organisational Learning

This paper investigates individual learning capability (ILC) and its relationship to organisational learning (OL) as well as its contribution to the creation of learning organisations (LOs). As there is high complexity, debate and ambiguity regarding these concepts, it becomes necessary to create an integrated framework to capture the interrelationships that exist. Going through an extensive literature review, the various approaches to learning are critically evaluated and a new integrated framework is created that incorporates the various levels of learning. The proposed framework exhibits the most important dimensions of individual learning, such as social intelligence, task intelligence and mental intelligence as well as the learning style preference. These dimensions determine ILC which consequently influences OL. The proposed framework would serve as the basis for creating a more valid model to evaluate the level of OL.

Individual learning capability and its association to organisational learning

This paper investigates individual learning capability (ILC) and its relationship to organisational learning (OL) as well as its contribution to the creation of learning organisations (LOs). As there is high complexity, debate and ambiguity regarding these concepts, it becomes necessary to create an integrated framework to capture the interrelationships that exist. Going through an extensive literature review, the various approaches to learning are critically evaluated and a new integrated framework is created that incorporates the various levels of learning. The proposed framework exhibits the most important dimensions of individual learning, such as social intelligence, task intelligence and mental intelligence as well as the learning style preference. These dimensions determine ILC which consequently influences OL. The proposed framework would serve as the basis for creating a more valid model to evaluate the level of OL.

Linking unlearning with service quality through learning processes in the Spanish banking industry

Knowledge, like other resources, can quickly become obsolete. Thus, actors in an economy must constantly update their knowledge to keep pace with ongoing changes in their operational environment. This study explores unlearning's influence on two forms of learning (i.e., exploration and exploitation of knowledge). The study also adopts a dynamic management focus to analyze the influence of these two individual learning capabilities and their ability to help firms align technology knowledge and relational knowledge. This study reaches important conclusions on unlearning's role in knowledge management. The study examines learning processes and knowledge stocks (i.e., technology and relational knowledge) that practitioners (managers) within service firms generate through their relationships with customers. This study explores how an unlearning context can help service firms align learning processes (i.e., exploration and exploitation) through an empirical study of 150 managers in the Spanish banking industry.

Improved Personalized E-Course Composition Approach using Modified Particle Swarm Optimization with Inertia-Coefficient

One of the main problems associated with the authoring of ecourses, for e-learning systems, is that the current compositionapproaches do not support ‘personalized-learning’ or in other words, the current composition approaches fail to take into consideration the difference in individual learning-capabilities and the background knowledge of the individual learners and thus do not provide materials that exactly meet the demands of the individual learners. In order to provide solution for this problem, in the past, various e-course composition approaches had proposed to use various methods of computational-optimization techniques like Genetic Algorithm and Particle swarm optimization. The primary purpose of this paper is to propose an improved personalized e-course composition approach using modified particle swarm optimization algorithm (MPSO) with inertia-coefficient, which intends to serve as an effective solution to the afore-mentioned problem. Various simulation-based experiments were conducted and the results of these experiments have been furnished at the end of this paper. These results demonstrate that our proposed approach is an effective solution to the problem of ‘personalized-learning’. In addition, these graphs compare our proposed approach with an existing approach which uses Basic particle swarm optimization algorithm (BPSO). These comparisons demonstrate the efficiency of our proposed model.

Spatial memory in the Morris water maze and activation of cyclic AMP response element-binding (CREB) protein within the mouse hippocampus

We investigated the spatio-temporal dynamics of learning-induced cAMP response element-binding protein activation/phosphorylation (pCREB) in mice trained in a spatial reference memory task in the water maze. Using immunohistochemistry, we examined pCREB immunoreactivity (pCREB-ir) in hippocampal CA1 and CA3 and related brain structures. During the course of spatial learning over Days 1-9, pCREB-ir progressively increased in hippocampal neurons whereas its level in the dorsal striatum decreased. No significant changes were observed in the prelimbic cortex and lateral amygdala. Mice killed at various time points after the last training session demonstrated two waves of pCREB-ir in CA1 and an early transient CREB phosphorylation in area CA3, lateral amygdala, and prelimbic cortex. We show that CREB phosphorylation and downstream gene Zif268 activation remained sustained in CA1 and CA3 for at least 24 h after extended training (Days 8-9) but not during early training (Day 3). The present results indicate that the strong CA1 CREB phosphorylation observed immediately after training was not related strictly to learning or to memory. In contrast, at 15 min after training, the changes in CA1 CREB phosphorylation state were specifically related to individual learning capability. We suggest that hippocampal-learning specificity of CREB is reflected best by duration, rather than magnitude, of CREB phosphorylation.

Special issue on emerging trends in soft computing: memetic algorithms

In the last few decades, evolutionary algorithms (EAs) have gradually established a strong foothold as powerful search methods in many complex disciplines ranging from arts & design, business & finance to science & engineering. Although well established as credible and powerful search tools, researchers in this area are now facing new challenges of increasing computational needs in today’s applications. The popularity and success of EAs lie in the ease of implementation, generality of the concept and their ability to converge close to the global optimal design. Nevertheless, traditional EAs generally suffer from excessively slow convergence to locate a precise enough solution efficiently due to the lack of individual learning capabilities. This often limits the practicality of EAs on many large-scale real world problemswhere the computational time is a crucial consideration. One of the recent most important and successful areas of research that has spawned from evolutionary computations

Rheumatoid arthritis patients’ education – contents and methods

The purpose of this study is to describe the contents and methods used by rheumatology nurses when they educate their patients with rheumatoid arthritis. Rheumatology nurses have an important role in educating patients with rheumatoid arthritis. However, there is a lack of knowledge on the content provided and the methods used by rheumatology nurses. The sample was drawn in using stratified random sampling and the data were collected from 80 rheumatology nurses with a questionnaire in 2003-2004 (response rate was 65.2%). The data were analysed using descriptive and non-parametric statistical tests. Medical treatment was the most commonly taught issue, as 76% of rheumatology nurses gave information on anti-rheumatic drugs prescribed to the rheumatoid arthritis patients and blood tests (64%) which must be taken as follow-up controls. Only 45% of the nurses discussed self care at home. Individual oral patient education (88%) and written materials by the local hospitals or drug industries (71%), were the most commonly used methods. Patients with rheumatoid arthritis were educated mostly in special health care units. A rheumatology nursing course did not have an effect on the chosen contents or methods when educating rheumatoid arthritis patients. It is important that rheumatology nurses teach more self-care abilities to patients with rheumatoid arthritis and use also the other teaching methods than oral individual method such as group sessions, teleinformatics and internet. The contents of rheumatology nursing course should be developed further to stress the importance of appropriate teaching methods and to point out the importance of self care abilities for patients. The results provided useful insight into education of patients with rheumatoid arthritis. Nurses should avoid the routine teaching programmes. They should take time to discuss with their patients and plan together the contents and methods, that education of patients with rheumatoid arthritis is based on patients' information needs and their individual learning capabilities.

Olfactory learning-related NCAM expression is state, time, and location specific and is correlated with individual learning capabilities

The notion that long-term synaptic plasticity is generated by activity-induced molecular modifications is widely accepted. It is well established that neural cell adhesion molecule (NCAM) is one of the prominent modulators of synaptic plasticity. NCAM can be polysialylated (PSA-NCAM), a reaction that provides it with anti-adhesion properties. In this study we have focused on NCAM and on its polysialylated state, and their relation to learning of an olfactory discrimination task, which depends on both the piriform (olfactory) cortex and hippocampus. We trained rats to distinguish between pairs of odors until rule learning was achieved, a process that normally lasts 6-8 days. At four time points, during training and after training completion, synaptic NCAM and PSA-NCAM expression were assessed in the piriform cortex and hippocampus. We report that NCAM modulation is specific to PSA-NCAM, which is upregulated in the hippocampus one day after training completion. We also report a correlation between the performance of individual rats in an early training stage and their NCAM expression, both in the piriform cortex and hippocampus. Since individual early performance in our odor discrimination task is correlated with the performance throughout the training period, we conclude that early NCAM expression is associated with odor learning capability. We therefore suggest that early synaptic NCAM expression may be one of the factors determining the capability of rats to learn.

Information dynamics, learning and knowledge creation in organizations

Managers in a wide array of organizations are concentrating on knowledge creation as a way to achieve competitiveness. Organizational knowledge, they hope, enables them to bring innovative products/services continuously in the marketplace. However, many are finding it difficult to understand how organizations create knowledge. By using the concepts of individual learning capability and the learning culture of organizations, the present study shows how the sum of individual knowledge does not equate to organizational knowledge. This distinction between individual knowledge and organizational knowledge is an important one, as a majority of studies do not clearly show how individual knowledge is different from organizational knowledge. The study also offers a set of suggestions to managers to develop a learning culture in the organizations.