Learning Component Research Articles

A Narrative Review of the Use of Formative Assessment in China's University Education

Education is a key factor in the realization of self-worth and national progress. How to train and develop the young generation is the fundamental problem of education. Assessment is important to develop education, because it drives students learning. At present, terminal assessment has always been a key part of education system, which pays too much attention to the overall outcome but ignores the students subjectivity and initiative in the learning process. This kind of assessment suppresses students creativity. Therefore, it is necessary to explore a new assessment system more suitable for modern teaching. Formative assessment is an assessment conducted over a period of time. It means that students are evaluated during the learning process, not just after the learning process. It collects information on children with a view to using it from time to time to guide and shape their learning. Formative assessment, on the other hand, is an assessment method that involves using a variety of assessment tools to assess various components of learning, including not only thought processes but also behaviors, personality traits, and flexibility. Formative assessments are also conducted over time. This approach will be more comprehensive and representative of the learner as a whole. It begins with teachers and administrators making decisions about learners' year-end grades and promotions.

The Effect of Using Gamification to Improve EFL Students' Academic Performance

This paper aims to determine whether there is evidence that gamified instruction can be effective in improving EFL students' academic achievement. The aim of the research is to establish how effective gamification is as a method against more traditional types of education and what areas of the English language—for example, reading comprehension, grammar, and vocabulary—are most effectively promoted via the integration of gamification into the classroom environment. The sample included 120 fourth graders from public schools in Jordan, where 60 children were to form the gamified instruction group and another 60 to form the standard instruction group. Pretests and posttests of English language skills using standardized tools measured students at two different times: before and after the instructional interventions. These tests are the main instruments utilized for data collection and analysis. Independent t-test, one-way ANOVA, and one-way MANOVA tests were performed to test the variation and holistic impact of the instructional methods on different components of language learning. The experimental findings support that the gamified instruction group scored significantly higher than the regular instruction group at post-intervention. More specifically, the students of the game-based group scored an average of 74.44 (SD= 7.93) on the posttest, compared to 69.31 (SD = 6.14) for those of the control group.The result for the T-test yields t = 4.05 and p < 0.001, hence showing that the gamified group had significantly better results. The classroom gamification usage made noteworthy gains in students' vocabulary, grammar, and reading comprehension abilities. One-way ANOVA results were vocabulary, F = 22.65, p < 0.001; grammar, F = 15.78, p < 0.001; and reading comprehension, F = 18.93, p < 0.001. MANOVA supported this finding that the Wilks' Lambda value was 0.62, with an F-value of 20.45 and a p-value less than 0.001, indicating that gamified training was of benefit overall in enhancing English language competence. The results of this research come with a very exciting revelation, such as gamified instruction being an excellent means of teaching English as a foreign language since it enhances students' interest and performance in class.

The Effect of Using Gamification to Improve EFL Students' Academic Performance

This paper aims to determine whether there is evidence that gamified instruction can be effective in improving EFL students' academic achievement. The aim of the research is to establish how effective gamification is as a method against more traditional types of education and what areas of the English language—for example, reading comprehension, grammar, and vocabulary—are most effectively promoted via the integration of gamification into the classroom environment. The sample included 120 fourth graders from public schools in Jordan, where 60 children were to form the gamified instruction group and another 60 to form the standard instruction group. Pretests and posttests of English language skills using standardized tools measured students at two different times: before and after the instructional interventions. These tests are the main instruments utilized for data collection and analysis. Independent t-test, one-way ANOVA, and one-way MANOVA tests were performed to test the variation and holistic impact of the instructional methods on different components of language learning. The experimental findings support that the gamified instruction group scored significantly higher than the regular instruction group at post-intervention. More specifically, the students of the game-based group scored an average of 74.44 (SD= 7.93) on the posttest, compared to 69.31 (SD = 6.14) for those of the control group.The result for the T-test yields t = 4.05 and p < 0.001, hence showing that the gamified group had significantly better results. The classroom gamification usage made noteworthy gains in students' vocabulary, grammar, and reading comprehension abilities. One-way ANOVA results were vocabulary, F = 22.65, p < 0.001; grammar, F = 15.78, p < 0.001; and reading comprehension, F = 18.93, p < 0.001. MANOVA supported this finding that the Wilks' Lambda value was 0.62, with an F-value of 20.45 and a p-value less than 0.001, indicating that gamified training was of benefit overall in enhancing English language competence. The results of this research come with a very exciting revelation, such as gamified instruction being an excellent means of teaching English as a foreign language since it enhances students' interest and performance in class.

Data mining for the Analysis of Content Interaction in web-based Learning and Training Systems

The process of data mining is exploring databases for useful information and extracting it. Analysis how people interact with websites is the main goal of web usage mining, a subfield of data mining. The main, unobtrusive, and objective way to evaluate Web-based training and learning systems, namely how users engage with course materials, is web use mining. Many mining methods were developed with the classroom in mind, and we will showcase and explain them all. In order to prove effectiveness and improve instructional design as required, it is crucial to analyse and evaluate how learners behave in learning and training technology systems. This is particularly true when there are several interactive learning and training components accessible. We take a look at methods for figuring out what we want to learn, how we're going to learn it, and how our habits change as we go.

Classification of painting styles based on the difference component

The digitisation and classification of artwork are crucial tasks in the management of art collections. However, the scarcity of some styles makes it difficult to obtain sufficient and representative samples in deep learning models, leading to sub-optimal classification performance. This study proposed a difference component for few-shot learning to improve the classification accuracy of existing models on few-shot data. First, the method pre-processes the sample data by permuting limited samples with sufficient data to generate related samples. Subsequently, sets of positive and negative samples with the same scale are generated, containing and not containing the limited samples. Second, a difference component model is constructed to learn the non-linear division among samples contained in the related samples. This is then combined with the existing classification model to determine whether the related samples contain limited samples. Finally, the types of each sample contained in related samples are analysed based on the types of related samples. The results of the multiple experiments demonstrate that the difference component can effectively learn the differential features between combinations of artworks. The combination of the existing classification model and the proposed difference component model has been demonstrated to effectively improve the classification accuracy of few-shot works. In addition, the classification result was superior to that of other baseline methods used for few-sample learning.

Addressing challenges in diagnosis and management of rare disease through interprofessional education

Rare diseases represent a significant public health challenge due to their complexity and lack of resources. One way to improve care for patients with rare disease is to educate healthcare professionals on the diverse and unique needs of patients with rare disorders. An interprofessional education (IPE) event was created for healthcare students based on the Interprofessional Education Collaborative’s ‘IPE Core Competencies', mainly targeting two specific competencies: (1) interprofessional communication and (2) teams and teamwork. The IPE event included direct instruction, case-based learning, and narrative medicine components using the rare disease nephropathic cystinosis as a model of a rare complex disorder. Pre- and post-event survey data were collected to assess the participants' knowledge acquisition and perceived confidence in caring for patients with a rare disease as part of an interprofessional healthcare team and included open-ended questions regarding qualities of an interprofessional team member, and key takeaways from the event. Enrollment included 163 graduate-level healthcare students from nine different disciplines. The survey data showed improved understanding of the importance of rare disease research (p < 0.001), ability to identify supportive resources for patients (p < 0.001), confidence in being part of an interprofessional team caring for a patient with rare disease (p < 0.001) and value of education about rare disease (p = 0.009). When asked to describe features of effective interprofessional teams, common traits included strong communication skills, empathy, compassion, understanding, collaboration, and respect. This work demonstrates that utilizing an interprofessional model in educating health professional students about rare diseases successfully enhanced learners’ confidence in their ability to be part of an interprofessional team caring for patients and families impacted by rare disease, and given the total prevalence of rare diseases, may have a significant impact on healthcare as a whole.

Self-Regulated Learning Level of University Students and Educational Revelation

Self-regulated learning is a crucial component of students' competitiveness and is strongly linked to their academic achievement and performance. The study, which involved polling 309 Chinese university students, revealed that their level of self-regulated learning fell within the average range. Specifically, the analysis of the average scores for several self-regulated learning components revealed that participants exhibited the greatest requirement for social and environmental resources. In contrast, their motivation to learn scored the lowest. To enhance student support and guidance, the teacher's perspective offers educational recommendations to improve students' self-regulated learning skills and foster their overall development in the learning journey.

Management of Arabic Language Learning Based on Self-Regulated Learning and Its Application at The Modern Islamic Boarding School

The background of the research shows that the strategy carried out by the modern Islamic boarding school in the implementation of Arabic language learning management based on self-regulated learning is a distinctive scientific phenomenon. This study examines the application of self-regulated learning-based Arabic language learning management. As a field research through qualitative research with a phenomenological paradigm, the research data was obtained through interviews, observations, documentation, and reference searches to be further processed and analyzed through reduction, exposure, and conclusion of data. The study results show that the components of self-regulated learning, which in this case consist of motivation regulation, planning, effort regulation, attention focusing, task strategies, using additional resources, and self-instruction, can be identified which are applied to sit students as creative learning subjects. The conclusion shows that applying various self-regulated learning components contributes to shaping students' creativity in participating in Arabic language learning.

Development of powerpoint-based learning media to improve student learning outcomes on the material of economic science concepts at MA Hamid Rusydi MalangDevelopment of powerpoint-based learning media to improve student learning outcomes on the material of economic science concepts at MA Hamid Rusydi Malang

Introduction: Introduction: Learning resources are an important component of learning. The purpose of this study is to analyze the feasibility, viability, effectiveness, or extent of development of PowerPoint-based learning resources on the topic of conceptual economics in MA Hamid Rasidi Malang. Methods: The research methodology was developed using two types of data, quantitative and qualitative. Finding: The development of this learning tool was adapted from the development model of Borg and Gall (2003), which has 10 phases, but the researchers implemented eight phases due to time, energy, and cost implications. The eight phases are: research and data collection, planning, product format development, initial testing, product revision, intensive field testing, final product revision, implementation, and deployment. The study found that based on feasibility testing by six reviewers, the validity level of the learning media product averaged 96% high feasibility from two subject matter experts, 97% high feasibility from two language experts, 91% high feasibility from two media experts, two social studies teachers. The average feasibility was 96% high from MA. Hamid Rasidi Malang and MA. Said Malang, and 91% high from the students of MA. Hamid Rasidi Malang and MA. Nasional Malang. Conclusion: Malang students indicated that the initial test results before the use of the PowerPoint-based materials were highly effective with an average of 92%, and the results after the use of the PowerPoint-based materials were highly effective with an average of 98%. This indicates that the developed product can be used in social studies and is practical and effective.

MFF-DTA: Multi-scale feature fusion for drug-target affinity prediction

Accurately predicting drug-target affinity is crucial in expediting the discovery and development of new drugs, which is a complex and risky process. Identifying these interactions not only aids in screening potential compounds but also guides further optimization. To address this, we propose a multi-perspective feature fusion model, MFF-DTA, which integrates chemical structure, biological sequence, and other data to comprehensively capture drug-target affinity features. The MFF-DTA model incorporates multiple feature learning components, each of which is capable of extracting drug molecular features and protein target information, respectively. These components are able to obtain key information from both global and local perspectives. Then, these features from different perspectives are efficiently combined using specific splicing strategies to create a comprehensive representation. Finally, the model uses the fused features to predict drug-target affinity. Comparative experiments show that MFF-DTA performs optimally on the Davis and KIBA data sets. Ablation experiments demonstrate that removing specific components results in the loss of unique information, thus confirming the effectiveness of the MFF-DTA design. Improvements in DTA prediction methods will decrease costs and time in drug development, enhancing industry efficiency and ultimately benefiting patients.

BASIC REQUIREMENTS FOR THE DEVELOPMENT OF A SYSTEM OF EXERCISES FOR WORKING WITH TEXTS IN THE PROCESS OF STUDYING THE SUBJECT «FOREIGN LANGUAGE FOR PROFESSIONAL PURPOSES» FOR THE SPECIALTY OF «PUBLIC MANAGEMENT AND ADMINISTRATION»

The successful professional activity of a good specialist requires mastery of a foreign language at the level of daily communication, as well as a significant amount of lexical material in the field of professional activity and its free operation. It is of peculiar need for the professionals in the sphere of public management and administration. The ways of mastering the language of professional communication are the same as in the general education course. The additional requirements are caused by the need of mastering professional vocabulary. Reading as a means of communication has significant practical value for specialists in public management and administration as they deal with documents and misunderstandings can cause problems. In this regard, the study of the English language is lbased on the reading of professional texts should be given as much attention as possible. This type of speech activity should be singled out as a dominant component of professional English language learning, That is why preparing students for independent reading, teaching them to read correctly and to perceive what they read is the matter of peculiar interest. For the successful implementation of the set goals, it is very important from the very beginning of education to create the right attitude of students to reading as a type of language activity that has its own specific communicative task, as a means of obtaining information. When choosing material for reading, it is worth taking into account such requirements for a text as the modernity of the work, accessibility, exemplarity, meaningfulness, versatility, compliance with the level of students’ training, etc. The motivation of students’ reading activity and activity will depend on the completeness of these conditions. Independent work in reading can become an effective factor that ensures the enrichment of the active vocabulary of the future specialist. This will increase students’ motivation to learn a foreign language. Work on individual reading can make the process of forming lexical competence more effective. It is advisable to use developments for the teacher in combination with methodical recommendations for students. Intensive independent and classroom work of students with a professional text significantly improves the quality of foreign language learning.

Relationship between Volunteerism and Empathy among Adolescents in Rwanda

Purpose: The aim of the study was to assess the relationship between volunteerism and empathy among adolescents in Rwanda. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study indicated that engaging in volunteer activities enhances adolescents' empathy levels, as these experiences expose them to diverse social situations and perspectives. Adolescents who volunteer tend to develop a greater understanding and sensitivity towards the needs and emotions of others. This empathy growth is attributed to the direct interactions and responsibilities involved in volunteering, which foster emotional and cognitive empathy. Moreover, the sense of purpose and fulfillment derived from helping others further reinforces empathetic behaviors. Overall, volunteerism serves as a significant developmental tool in nurturing empathy among adolescents, promoting their social and emotional well-being. Implications to Theory, Practice and Policy: Social learning theory, empathy development theory and theory of planned behavior may be used to anchor future studies on assessing the relationship between volunteerism and empathy among adolescents in Rwanda. In practice, schools and community organizations should design volunteer programs that are both structured and reflective to maximize empathy development. Policymakers should prioritize integrating volunteerism into the educational curriculum as a key component of social-emotional learning.

Conformations of KRAS4B Affected by Its Partner Binding and G12C Mutation: Insights from GaMD Trajectory-Image Transformation-Based Deep Learning.

Binding of partners and mutations highly affects the conformational dynamics of KRAS4B, which is of significance for deeply understanding its function. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) and principal component analysis (PCA) were carried out to probe the effect of G12C and binding of three partners NF1, RAF1, and SOS1 on the conformation alterations of KRAS4B. DL reveals that G12C and binding of partners result in alterations in the contacts of key structure domains, such as the switch domains SW1 and SW2 together with the loops L4, L5, and P-loop. Binding of NF1, RAF1, and SOS1 constrains the structural fluctuation of SW1, SW2, L4, and L5; on the contrary, G12C leads to the instability of these four structure domains. The analyses of free energy landscapes (FELs) and PCA also show that binding of partners maintains the stability of the conformational states of KRAS4B while G12C induces greater mobility of the switch domains SW1 and SW2, which produces significant impacts on the interactions of GTP with SW1, L4, and L5. Our findings suggest that partner binding and G12C play important roles in the activity and allosteric regulation of KRAS4B, which may theoretically aid in further understanding the function of KRAS4B.

AVATAR: Adversarial self-superVised domain Adaptation network for TARget domain

This paper introduces AVATAR (adversarial self-supervised domain adaptation network for target domain), a novel unsupervised domain adaptation method designed to address the challenge of transferring knowledge from a well-labeled source domain to an unlabeled target domain. AVATAR’s key contributions lie in its unique combination of adversarial learning and self-supervised learning techniques, which enhance the model’s adaptability and accuracy in new, unlabeled environments. The technical innovations of AVATAR include a domain adversarial learning component that reduces domain discrepancy by aligning source and target domain features in a shared feature space, a self-supervised learning module that leverages pseudo-labels and instance weights to refine target domain discrimination boundaries, and a sample selection strategy guided by within-cluster distances to focus on aligning informative samples while mitigating the impact of outliers. By integrating these components, AVATAR provides a comprehensive framework for tackling complex unsupervised domain adaptation tasks, particularly when the domain gap is significant. The method balances domain-invariant feature learning with domain-specific adjustments, enabling effective adaptation to dynamically changing environments. Extensive experiments on multiple benchmark datasets demonstrate AVATAR’s superior performance compared to existing domain adaptation methods, especially in scenarios with limited labeled target domain data. These results highlight AVATAR’s potential as a versatile and robust solution for domain adaptation challenges in various real-world applications.

Adversarial Missingness Attacks on Causal Structure Learning

Causality-informed machine learning has been proposed as an avenue for achieving many of the goals of modern machine learning, from ensuring generalization under domain shifts to attaining fairness, robustness, and interpretability. A key component of causal machine learning is the inference of causal structures from observational data; in practice, this data may be incompletely observed. Prior work has demonstrated that adversarial perturbations of completely observed training data may be used to force the learning of inaccurate causal structural models (SCMs). However, when the data can be audited for correctness (e.g., it is cryptographically signed by its source), this adversarial mechanism is invalidated. This work introduces a novel attack methodology wherein the adversary deceptively omits a portion of the true training data to bias the learned causal structures in a desired manner (under strong signed sample input validation, this behavior seems to be the only strategy available to the adversary). Under this model, theoretically sound attack mechanisms are derived for the case of arbitrary SCMs, and a sample-efficient learning-based heuristic is given. Experimental validation of these approaches on real and synthetic data sets, across a range of SCMs from the family of additive noise models (linear Gaussian, linear non-Gaussian, and non-linear Gaussian) demonstrates the effectiveness of adversarial missingness attacks at deceiving popular causal structure learning algorithms.

Utilization of Quiz Kreator in Student Achievement Assessment in Elementary School

Background. The world of education is inseparable from various learning components. The utilization of technology cannot be separated from the world of education. One of them is the use of Quiz Kreator for student achievement assessment in elementary schools. Quiz Kreator is one of the online applications used to create quizzes, including multiple choice quizzes and true false quizzes. Purpose. This study aims to determine how student achievement in elementary schools after using the Quiz Kreator application in the learning process. Method. The researcher used quantitative research methods, namely by distributing questionnaires to elementary school students. The questionnaire was distributed online. Results. The results showed that the use of Quiz Kreator in assessing student achievement in elementary schools has a positive impact on students. The use of Quiz Kreator as an assessment tool that is well designed and relevant to the material being taught, can improve student achievement. Quiz Kreator can provide assessment results automatically and accurately. This can also help teachers in assessing student achievement more objectively. Conclusion. the use of Quiz Kreator in assessing student achievement in elementary schools can be utilized well. The use of this Quiz Kreator application can improve student achievement in the learning process.

Leadership development research and scholarship.

The term leadership development is often used in the field of education, management, and business, yet in the context of the leadership learning framework (LLF), it takes on a specific meaning as the innermost, human facets of leadership learning. In addition to the current scholarship around leadership development as a key component of leadership learning, this article will explore leadership development's evolution-from its interconnection with leader development, the use of training and education to foster it, to its growth self-awareness within group dynamics. This evolution will be considered in the contexts of both education and organizations. Finally, questions and recommendations for future scholarship in leadership are posed for both researchers and practitioners.

Three‐layer deep learning network random trees for fault detection in chemical production process

AbstractWith the development of technology, the chemical production process is becoming increasingly complex and large‐scale, making fault detection particularly important. However, current detection methods struggle to address the complexities of large‐scale production processes. In this paper, we integrate the strengths of deep learning and machine learning technologies, combining the advantages of bidirectional long‐ and short‐term memory neural networks, fully connected neural networks, and the extra trees algorithm to propose a novel fault detection model named three‐layer deep learning network random trees (TDLN‐trees). First, the deep learning component extracts temporal features from industrial data, combining and transforming them into a higher‐level data representation. Second, the machine learning component processes and classifies the features extracted in the first step. An experimental analysis based on the Tennessee Eastman process verifies the superiority of the proposed method.

The Application of Genre-Based Teaching Methods in Expository Reading Instruction for High School English

Expository writing is a crucial component of English learning, particularly prominent in the English tests taken by high school students, where this genre carries significant weight. Given its importance, teachers should enhance their guidance on reading expository texts in the classroom, employing genre-based teaching methods to enable students to master the characteristics of expository writing. Through detailed instruction, ensure that students can thoroughly comprehend the information conveyed in expository texts, thereby elevating their overall English reading skills and analytical abilities.

Note similarities affect syntactic stability in zebra finches.

The acquisition of an acoustic template is a fundamental component of vocal imitation learning, which is used to refine innate vocalizations and develop a species-specific song. In the absence of a model, birds fail to develop species typical songs. In zebra finches (Taeniopygia guttata), tutored birds produce songs with a stereotyped sequence of distinct acoustic elements, or notes, which form the song motif. Songs of untutored individuals feature atypical acoustic and temporal structure. Here we studied songs and associated respiratory patterns of tutored and untutored male zebra finches to investigate whether similar acoustic notes influence the sequence of song elements. A subgroup of animals developed songs with multiple acoustically similar notes that are produced with alike respiratory motor gestures. These birds also showed increased syntactic variability in their adult motif. Sequence variability tended to occur near song elements which showed high similarity in acoustic structure and underlying respiratory motor gestures. The duration and depth of the inspirations preceding the syllables where syntactic variation occurred did not allow prediction of the following sequence of notes, suggesting that the varying duration and air requirement of the following expiratory pulse is not predictively encoded in the motor program. This study provides a novel method for calculation of motor/acoustic similarity, and the results of this study suggest that the note is a fundamental acoustic unit in the organization of the motif and could play a role in the neural code for song syntax.