Learning Hierarchy Research Articles

Instructional Systems Design to Reflect ETHICS in AI’s Rules of Engagement Learning for Future Warfare

Purpose: Rules of Engagement(ROE) refer to rules or directives that define the circumstances, conditions, extent, manner, etc. of the application of force or action that can be considered provocative by the armed forces. ROE do not explain how results are achieved, but rather indicate what judgments are unacceptable. Focusing this, the purpose of this study is to propose an Instructional Systems Design(ISD) configured to reflect ethics in AI’s ROE learning for future warfare. Method: This study uses Development Research Method for develop and propose an ISD. ISD refers to the creation of guidelines into smaller units of teaching or learning. If some guidelines are created for such ISD, it would set the composition and application of ROE, and AI will learn that guidelines through deep learning. And the AI makes a decision with this in the hypothetical dilemma situation where the application of the ROE is requested. Finally, human experts review and supplement the learning results of these neural networks. The sophistication of the AI’s learning and applying ROE would be achieved by feeding back this result to the ISD. Results: This study understands that ROE would also be essential for AI or AI-equipped military robot systems. In this process, AI performs the task of making judgments related to applying ROE, which is the principle of action in specific situations. To do this, Ai’s deep learning first collects necessary information and makes decisions based on it. Next, the results of this learning are applied in a new hypothetical dilemma situation. Finally, human experts evaluation and feedback on the results are continuously made. This series of processes can be presented as a model of ISD oriented towards the moral development of AI. Conclusion: AI’s ROE learning converges to the learning of moral values. It focuses on the cognitive aspect of morality. Therefore, it would be possible to refine the cognitive moral judgment of deep learning by applying the learning hierarchy of taxonomy of educational objects and the logical test of validity of moral judgment oriented toward social justice. And the moral development of the neural network can be performed by modifying and complementing the results of human experts and feeding them back.

Learning hierarchy and displacing conviviality: time and subjectivity in the neoliberal kindergarten

ABSTRACT This article argues that reading levels, a seemingly neutral aspect of literacy instruction of neoliberal schooling, initiate students into the symbolic templates of capitalism. I explore young children’s effects, relations, and interpretation of the field of meanings surrounding reading levels and grades in a kindergarten classroom in the U.S. I demonstrate how ranking had profound yet subtle effects on children’s being and becoming by imposing development’s normative temporality in the social relations of learning, and imbuing the emotions of learning with its logic. While evaluation inculcates individualised subjectivities that are crucial to the reproduction of hierarchical relations, this process is imperfect and a site of struggle. I demonstrate how evaluation’s subjugating power contended with children’ already existing convivial ways of being and relating. I conclude that educators must reimagine learning with and through children’s perspectives so that liberatory possibilities of schooling can flourish.

Low-rank Gallus gallus domesticus chicks are better at transitive inference reasoning

A form of deductive reasoning, transitive inference, is thought to allow animals to infer relationships between members of a social group without having to remember all the interactions that occur. Such an ability means that animals can avoid direct confrontations which could be costly. Here we show that chicks perform a transitive inference task differently according to sex and rank. In female chicks, low-ranking birds performed better than did the highest ranked. Male chicks, however, showed an inverted U-shape of ability across rank, with the middle ranked chicks best able to perform the task. These results are explained according to the roles the sexes take within the group. This research directly links the abilities of transitive inference learning and social hierarchy formation and prompts further investigation into the role of both sex and rank within the dynamics of group living.

An analytical study on the hierarchy of jangdan learning for integrated education and application of classes: Focusing on secondary music textbooks of 2015 revised curriculum

목적 본 연구는 한국의 장단학습의 현황을 분석한 후 장단학습 위계 기준을 제시하고, 학습자로 하여금 장단을 활용해 음악융합능력을 기를 수 있도록 자기주도형 학습 계획안을 제시하는 것이 목적이다. 방법 연구 방법으로는 첫째, 현행 중등학교 음악교과서에 수록된 장단학습의 위계구조 기준 유무와 방법을 전수 조사하였다. 둘째, 전수조사한 장단학습방법을 분석하여 위계에 따라 장단학습방법을 구조화하였다. 셋째, 한국의 장단을 세계 여러나라 리듬과 융합하여 활용할 수 있도록 세계 통용 기준을 제시하고, 이에 따라 장단의 박자를 계열화하였다. 넷째, 학습자로 하여금 간단한 장단을 활용한 가락짓기 프로젝트를 수행하게 함으로써, 장단의 박자와 구조를 주도적으로 습득하게 하였다. 결과 본 연구 결과는 현재 교과서의 장단학습위계 기준이 부재하거나 산발적으로 제시되어 있음을 밝혔다. 이를 해결하기 위해서 먼저, 장단의 층위를 박자의 층위 개념과 연계하여 이해할 수 있도록 기준안을 제시하였다. 이를 바탕으로 장단을 활용해 짧은 곡을 만들어 보는 프로젝트학습법을 제시하였다. 이 과정에서 기본장단과 변형장단 및 말붙임새 등의 개념을 학습자 스스로가 탑다운 방식으로 주도적으로 습득할 수 있도록 하였다. 결과적으로 학습자로 하여금 한국음악적 요소는 차용하면서도 창작의 범위는 넓힐 수 있는 역량을 부가할 수 있었다. 결론 본 연구는 한국음악교육에서 음악과 이론이 분리되어 교육되는 현실적 문제를 해결하고, 학습자들로 하여금 유목적적 자기주도 학습이 가능하도록 동기를 부여할 수 있을 것이다. 한국인도 세계시민의 일부이고, 한국음악도 세계음악에 속해있다는 개념이 확산되고 교육의 중점도 세계화로 옮겨가고 있는 만큼, 상호 이해 가능하고 협업할 수 있는 음악역량을 길러 줄 수 있을 것이다.

Toward an Adaptive Threshold on Cooperative Bandwidth Management Based on Hierarchical Reinforcement Learning.

With the increase in Internet of Things (IoT) devices and network communications, but with less bandwidth growth, the resulting constraints must be overcome. Due to the network complexity and uncertainty of emergency distribution parameters in smart environments, using predetermined rules seems illogical. Reinforcement learning (RL), as a powerful machine learning approach, can handle such smart environments without a trainer or supervisor. Recently, we worked on bandwidth management in a smart environment with several fog fragments using limited shared bandwidth, where IoT devices may experience uncertain emergencies in terms of the time and sequence needed for more bandwidth for further higher-level communication. We introduced fog fragment cooperation using an RL approach under a predefined fixed threshold constraint. In this study, we promote this approach by removing the fixed level of restriction of the threshold through hierarchical reinforcement learning (HRL) and completing the cooperation qualification. At the first learning hierarchy level of the proposed approach, the best threshold level is learned over time, and the final results are used by the second learning hierarchy level, where the fog node learns the best device for helping an emergency device by temporarily lending the bandwidth. Although equipping the method to the adaptive threshold and restricting fog fragment cooperation make the learning procedure more difficult, the HRL approach increases the method’s efficiency in terms of time and performance.

The Effects of Online Learning on EFL Students’ Academic Achievement during Coronavirus Disease Pandemic

<p style="text-align:justify">Coronavirus disease (COVID-19) Pandemic changed education conditions worldwide forcing all the parties involved to adapt to a new system. This study aimed to collect information related to the effects of teaching English online on English as a Foreign Language (EFL) students’ achievement. Data were collected from EFL teachers and students enrolled in three different Ecuadorian Universities (Technical University of Ambato, Higher Polytechnic School of Chimborazo, and University of Cuenca) from five different levels: A1, A2, B1, B1+, and B2. This preliminary paper reports the results of 480 students regarding four major sections: pedagogical practice and assessment, learning outcomes, affective factors and perceptions of students about the advantages and disadvantages of online learning during the pandemic COVID-19; considering the Hierarchy of online learning needs of Justin Shewell. An online survey questionnaire with 17 questions and a 5-point Likert scale was applied. The Cronbach's Alpha test presented 0.84 and 0.73 level of reliability. The Kolmogorov Smirnov’s statistic and, the Kendall's Tau_b tests, and the Levene's test for homogeneity of variances were performed with the SPSS statistical program. The results made evident that online learning affects academic achievement in EFL students during the COVID-19 pandemic, which was confirmed after analyzing four main areas: pedagogical practices and assessment, learning outcomes, affective factors and students’ perceptions about the advantages and disadvantages of online learning. The importance of online learning was highlighted since it has been understood as a tool to face the emergency produced by the COVID-19 pandemic.</p>

The student as lecturer: building confidence, collaboration, and community in first year undergraduate law lectures

ABSTRACT Should first year undergraduate students be involved in the delivery of lectures? This paper reports on the development of a project to instil student leadership in large group learning (lectures). The initiative draws from an experimental student-run lecture in the spring of 2018, when the six undergraduate co-authors took the opportunity to stand in as the lecturer in a core first year module. The results of that experiment led us, in 2019, to explore formal opportunities for student leadership in first year lectures. In this model, the teacher–student relationship becomes one of collaboration: the lecturer mentors rather than presents. Our findings contribute to the literature on student-led teaching, corroborating accounts that report greater participation and collaboration as a result of student-led teaching. The novelty of our model is that it reimagines learning roles, positioning students as lecturers at the point where students first encounter material and at an early stage of undergraduate study. Dismantling traditional learning hierarchies in this way has the potential to encourage a collaborative relationship between teachers and learners, nurturing student confidence and fostering a stronger learning community. This paper is an extension of such a collaboration, being written collectively by six undergraduate students and our lecturer.

A Study on the Exploration of Factors Involving Conceptual Hierarchy in Geography Learning: Focused on Urban Chapter in Middle School Social Studies

A Study on the Exploration of Factors Involving Conceptual Hierarchy in Geography Learning: Focused on Urban Chapter in Middle School Social Studies

Competence in Cybercrime: A Review of Existing Laws

Transformational cyber security and training programmes are urgently required to produce individuals and workforce capable of addressing company risks posed by existing and emerging cyber threats. This paper presents a cyber security model of India and give an analytical approach to the competence with the crime, a continuous hierarchy of learning. The chapter combines the cyber-security domain, academic development, and the pyramid of learning continuum, as well as cyber-security standards from state, to create a model of cyber-security skills appropriate for people’s education and the broader workforce. This fundamental approach to building cyber skills and training programmes results in trained individuals and workers who can reduce cyber hazards in the business environment throughout the globe. In popular culture, such experts are sometimes depicted as lone hackers. Cybersecurity specialists, on the other hand, must communicate with a variety of people all of the time. They must also have a high level of personal integrity. The practise of cyber hunting is a different approach to traditional cyber security, in which technologies and human intelligence are used to discover potential threats. Using firewall, antivirus, and intrusion detection software, this strategy seeks to detect penetration and prevent hacker penetration.

Analysis of the effects of a game-based review system integrated with the hierarchy of learning on learning outcomes in an elementary social science course

ABSTRACT Social science education aims to enable people to acquire the knowledge and abilities necessary to lead a normal social life. However, social science is often neglected in basic education compared with languages and mathematics, thus affecting students’ learning motivation and achievements. In this study, a digital game-based review system was designed for fourth-grade students in Taiwan taking a social science course. The students could review the unit content through the completion of game tasks. The concepts of the forgetting curve, hierarchy of learning, and formative assessment were incorporated into the game design to solidify memory and optimize learning effectiveness. The effects of the game on learning effectiveness, motivation, attitude, and interest were investigated, and learning behavior patterns were assessed through lag sequential analysis. The findings may serve as a reference for improving elementary school social science education.

Şeyhulislâm Feyzullah Efendi, the Ḥanafī Mufti of Jerusalem and the Rise of the Provincial Fatāwā Collections in the Eighteenth Century

Abstract The article examines the rise of standardized collections of fatāwā issued by officially appointed provincial Hanafi muftis across the Ottoman Empire in the long eighteenth century. The article focuses on the earliest compilation, that of the Jerusalemite Ḥanafī mufti, ʿAbd al-Raḥīm b. Abī al-Luṭf. This compilation was commissioned by the famous chief imperial mufti Feyzullah Efendi. The article then traces the proliferation of the standardized fatāwā compilation over the course of the eighteenth century, from Medina to the Balkans. This essay seeks to examine the emergence of local/provincial compilations of fatāwā over the eighteenth century as yet another chapter in the long intervention of the Ottoman dynasty (through its learned hierarchy) in the regulation of the doctrines of the Ḥanafī madhhab at the imperial and provincial levels. Focusing on Feyzullah Efendi’s initiative and its aftermath may cast light on specific venues and practices in which this intervention took place in a particular historical moment.

The Emotional Universe of Insecure Scholars in the Early Modern Ottoman Hierarchy of Learning

Life is tough for many in the increasing precarity of today's academy. Despite all the degrees received, courses taught, grants awarded, conferences attended, articles published, resumes polished, and networks established, many people aspiring to a thriving academic career are now denied the opportunity to prosper in a stable position and to secure a settled life. Given the shrinking academic job market worldwide, especially for humanities and social science disciplines, it is no wonder that over the last two decades quit-lit written by disillusioned members of the academy has grown to such an extent that it now comprises a particular genre. From personal social media accounts to newspapers and websites circulating recent news about academics’ life across and beyond the United States, a wide array of platforms daily reveals the gloomy perspectives and emotional reactions of nontenured academic laborers overwhelmed by the uncertainties and insecurities that mark their professional and private lives.

A Reconstruction of the Learning Hierarchy of Middle School Probability and Statistics Section: Focusing on 2015 Revision Mathematics Curriculum of Korea

A Reconstruction of the Learning Hierarchy of Middle School Probability and Statistics Section: Focusing on 2015 Revision Mathematics Curriculum of Korea

Statistical Properties of Musical Creativity: Roles of Hierarchy and Uncertainty in Statistical Learning.

Creativity is part of human nature and is commonly understood as a phenomenon whereby something original and worthwhile is formed. Owing to this ability, humans can produce innovative information that often facilitates growth in our society. Creativity also contributes to esthetic and artistic productions, such as music and art. However, the mechanism by which creativity emerges in the brain remains debatable. Recently, a growing body of evidence has suggested that statistical learning contributes to creativity. Statistical learning is an innate and implicit function of the human brain and is considered essential for brain development. Through statistical learning, humans can produce and comprehend structured information, such as music. It is thought that creativity is linked to acquired knowledge, but so-called “eureka” moments often occur unexpectedly under subconscious conditions, without the intention to use the acquired knowledge. Given that a creative moment is intrinsically implicit, we postulate that some types of creativity can be linked to implicit statistical knowledge in the brain. This article reviews neural and computational studies on how creativity emerges within the framework of statistical learning in the brain (i.e., statistical creativity). Here, we propose a hierarchical model of statistical learning: statistically chunking into a unit (hereafter and shallow statistical learning) and combining several units (hereafter and deep statistical learning). We suggest that deep statistical learning contributes dominantly to statistical creativity in music. Furthermore, the temporal dynamics of perceptual uncertainty can be another potential causal factor in statistical creativity. Considering that statistical learning is fundamental to brain development, we also discuss how typical versus atypical brain development modulates hierarchical statistical learning and statistical creativity. We believe that this review will shed light on the key roles of statistical learning in musical creativity and facilitate further investigation of how creativity emerges in the brain.

Back to basics? A critical reflection on the use of frequency-building and Precision Teaching to support pupil intervention in foundational curricular learning

Precision Teaching (PT) presents as a systematic educational approach used to monitor and evaluate pupil performance, as underpinned by data-based decision making. As part of the implementation process, PT emphasises the importance of frequency-building to promote behavioural fluency for the learner. This article seeks to critically examine the potential application of frequency-building and PT in Irish mainstream primary schools to support pupil intervention in foundational curricular learning. Particular focus is placed on core academic subjects, in light of the national governmental drive to increase literacy and numeracy standards for all. This article provides an overview of the PT approach to intervention, with reference to recent Irish developments in the field spanning research and practice. The application of frequency-building and PT within a special education context is considered, particularly for pupils struggling to move beyond the ‘acquisition’ stage of the learning hierarchy. The author critically considers the alignment of PT with key tenets of the guidelines from the Department of Education and Skills (2017a) for supporting pupils with special educational needs in mainstream schools. Finally, limitations of PT-related research are forwarded, with reference to applied research in the field. Based on cumulative findings, the author advocates for a balanced and contextualised approach to fluency-focused instruction within schools, in light of the learning hierarchy and alternate, non-behaviourist approaches to teaching and learning.

EEG-Based Driving Fatigue Detection Using a Two-Level Learning Hierarchy Radial Basis Function.

Electroencephalography (EEG)-based driving fatigue detection has gained increasing attention recently due to the non-invasive, low-cost, and potable nature of the EEG technology, but it is still challenging to extract informative features from noisy EEG signals for driving fatigue detection. Radial basis function (RBF) neural network has drawn lots of attention as a promising classifier due to its linear-in-the-parameters network structure, strong non-linear approximation ability, and desired generalization property. The RBF network performance heavily relies on network parameters such as the number of the hidden nodes, number of the center vectors, width, and output weights. However, global optimization methods that directly optimize all the network parameters often result in high evaluation cost and slow convergence. To enhance the accuracy and efficiency of EEG-based driving fatigue detection model, this study aims to develop a two-level learning hierarchy RBF network (RBF-TLLH) which allows for global optimization of the key network parameters. Experimental EEG data were collected, at both fatigue and alert states, from six healthy participants in a simulated driving environment. Principal component analysis was first utilized to extract features from EEG signals, and the proposed RBF-TLLH was then employed for driving status (fatigue vs. alert) classification. The results demonstrated that the proposed RBF-TLLH approach achieved a better classification performance (mean accuracy: 92.71%; area under the receiver operating curve: 0.9199) compared to other widely used artificial neural networks. Moreover, only three core parameters need to be determined using the training datasets in the proposed RBF-TLLH classifier, which increases its reliability and applicability. The findings demonstrate that the proposed RBF-TLLH approach can be used as a promising framework for reliable EEG-based driving fatigue detection.

Maslow's Hierarchy in Virtual Learning or "Do Students Dream of Electropatients?"

In this work an attempt is made to consider virtual (digital, information) technologies of distance learning in medical education from the point of view of Maslow's hierarchy of needs theory and to assess the possibilities of satisfying all the needs of an individual within the digital educational environment. Such analysis helps to assess the quality and effectiveness of the virtual textbook from the perspective of the learners, which opens up new opportunities for its improvement.

Relative effectiveness of celebrity and product match-up for two high consumer involvement situations

PurposeThe study attempted to gauge the relative effectiveness of celebrity and product image match-up in comparison to non-celebrity attractive endorsers for two distinct high involvement situations. Also, due to the expected demographic diversity among target consumers, the study aimed at assessing the impact of respondent's age and gender on the effectiveness of image match-up.Design/methodology/approachBuilding on the three-order hierarchy model, two experiments were conducted (utilising celebrity and non-celebrity endorsers) for two high involvement hierarchies, i.e. standard learning and dissonance/attribution. Through fictitious print advertisement, the experiments assessed the effectiveness of the match-up in terms of consumer attitudes towards advertisement and brand and intentions to purchase.FindingsThe match-up consistently and significantly outperformed non-celebrity attractive endorser in case of standard learning hierarchy. The same conclusion was not established for dissonance/attribution hierarchy due to the lack of significant results. The findings also suggest that the match-up subdues the impact of consumer's gender and age on consumer attitudes only in case of standard learning hierarchy.Research limitations/implicationsThe study provides interesting theoretical implication by challenging a widely held postulation about the applicability of celebrity and product match-up under high involvement.Practical implicationsThe research provides the practitioners with a better understanding of important issues, mainly, whether to use a celebrity endorser and selecting the right celebrity, especially if high involvement is expected.Originality/valuePrevious research concerning celebrity endorsements has largely considered consumer involvement as unitary, i.e. either high or low. However, the multifaceted aspect of consumer involvement is well established in the field of consumer psychology. The present research, therefore, is a pioneering attempt as it studies the effectiveness of match-up for two distinct high involvement situations. Moreover, unlike the majority of previous studies that have focused on the performance of “celebrity match” versus “celebrity mismatch”, the impact of match-up was studied in comparison to a non-celebrity attractive endorser.

Fuzzy logic and Gagné learning hierarchy for assessing mathematics skills.

This study developed a fuzzy logic and Gagné learning hierarchy (FL-GLH) for assessing mathematics skills and identifying learning barrier points. Fuzzy logic was used to model the human reasoning process in linguistic terms. Specifically, fuzzy logic was used to build relationships between skill level concepts as inputs and learning achievement as an output. Gagné learning hierarchy was used to develop a learning hierarchy diagram, which included learning paths and test questions for assessing mathematics skills. First, the Gagné learning hierarchy was used to generate learning path diagrams and test questions. In the second step, skill level concepts were grouped, and their membership functions were established to fuzzify the input parameters and to build membership functions of learning achievement as an output. Third, the inference engine generated fuzzy values by applying fuzzy rules based on fuzzy reasoning. Finally, the defuzzifier converted fuzzy values to crisp output values for learning achievement. Practical applications of the FL-GLH confirmed its effectiveness for evaluating student learning achievement, for finding student learning barrier points, and for providing teachers with guidelines for improving learning efficiency in students.

Assessing intervention of satisfaction and switching costs in the perceived service quality-customer loyalty link

The purpose of this research is two-fold. First, it aims to recognise perceived service quality measuring items aligned with express delivery services (EDS) in a business-to-business (B2B) context. Second, to develop a conceptual framework by linking customer perceived service quality, satisfaction, switching costs (procedural and relational) and loyalty based on relationship marketing theory, prospect theory and standard learning hierarchy attitude theory. It is hypothesised that customer satisfaction and switching costs mediate service quality and customer loyalty link simultaneously. The hypotheses are tested from the data collected from corporate customers of EDS. Then perceived EDS-quality is classified into two dimensions - EDS technical quality (EDS-TQ) and EDS functional quality (EDS-FQ). EDS-FQ comprises of three sub-dimensions namely - staff expertise quality, custom-make quality and problem-solving quality. The results confirm the mediating role of customer satisfaction and procedural switching costs; however, the mediation role of relational switching costs is not supported. Practical implications and limitations of this study are discussed along with the scope for future research.