APPLICATION OF BURHANI REASONING BY ABID AL-JABIRI IN DEVELOPING MI CURRICULUM

This research examines the implementation of the concept of Burhani reasoning by Abid al-Jabiri in the curriculum development of Madrasah Ibtidaiyah (MI) School. Through a qualitative approach and case study method, this research explores how Burhani reasoning has been successfully applied by teachers, principals, and students in MI. Data collection techniques through in-depth interviews, participatory observation, and curriculum documentation study. The research results show that Burhani reasoning has been successfully applied in the MI curriculum and the integration of teaching methods based on Burhani reasoning with traditional methods has been successful. This has an impact on increasing students' critical and logical thinking abilities. This study suggests the importance of continuous training for teachers in applying Burhani reasoning in teaching and suggests further research to see the long-term impact of the implementation of Burhani reasoning on student learning outcomes. In conclusion, the application of Burhani reasoning has been proven to improve the quality of education in MI

Online Learning and Planning in Cognitive Hierarchies

Complex robot behaviour typically requires the integration of multiple robotic and Artificial Intelligence (AI) techniques and components. Integrating such disparate components into a coherent system, while also ensuring global properties and behaviours, is a significant challenge for cognitive robotics. Using a formal framework to model the interactions between components can be an important step in dealing with this challenge. In this paper we extend an existing formal framework [Clark et al., 2016] to model complex integrated reasoning behaviours of robotic systems; from symbolic planning through to online learning of policies and transition systems. Furthermore the new framework allows for a more flexible modelling of the interactions between different reasoning components

The acoustic designer: Joining soundscape and architectural acoustics in architectural design education

This article discusses the integration of acoustic design approaches into architectural design education settings. Solving architectural acoustic problems has been for centuries one of the primary aims of theories and experiments in acoustics. Recent contributions offered by the soundscape approach have highlighted broader desirable aims which acoustic designers should pursue, fostering ecological reasoning on the acoustic environment and its perception as a whole. Drawing from the available literature, some examples are brought to show the integration of architectural acoustics and soundscape approaches into the realm of architectural design education, highlighting the significance of specific design situations and aural training techniques in learning contexts

Implementation of Al-Qur'an Integration in the Teaching and Learning Process

In the Qur'an, knowledge is seen as something special that makes humans superior to other creatures. The importance of instilling religious and spiritual values ​​in general learning is to increase faith and piety to God Almighty in respecting the universe. The research aims to see how the integration of the Qur'an is implemented in the teaching and learning process, in which the Qur'an is science based on revelation, the hadith of the prophet, and the ijtihad of the scholars, while general science is based on human reasoning based on empirical data, through research. This research uses a qualitative descriptive approach with a phenomenological research type. In this study, the sampling technique used was snowball and purposive. The procedures and techniques used in collecting data in this study are qualitative: observation, FGD, and documentation. The stages of this study presented three stages, namely 1) the pre-field stage, 2) the fieldwork stage, and 3) the data analysis stage. The result of the research is that integrating the Al-Qur'an in the teaching and learning process can be applied well, with efforts to provide training related to the integration of the Al-Qur'an. Implementing Al-Qur'an integration is carried out by internalizing Al-Qur'an values ​​through studies in learning that can be carried out with curriculum integration, learning integration, and integration of Islamization of science

Critical thinking focus applied on student-centered approach

The implementation of the student-centered approach in the classroom allowed the design of active didactic spaces for learning and the exercise of potential critical thinking, besides the technical and scientific objectives. This paper presents the pedagogical techniques applied to trigger the integration of the routine of thinking critically on the thematic issues of a course unit. The reasoning method used to exercise the potential critical thinking and observe the students’ change of attitude is also presented.info:eu-repo/semantics/publishedVersio

e-LION: Data integration semantic model to enhance predictive analytics in e-Learning.

The surge in online education emphasizes Learning Management Systems' (LMSs) crucial role in organizing learning resources and enabling teacher-learner communication. COVID-19 accelerated this, spiking engagement and substantial learning data. Academic institutions now have extensive data for comprehensive analysis to inform educational planning. However, integrating this diverse, sizable dataset from heterogeneous sources with semantic inconsistencies is challenging. Standardized integration schemes are needed for efficient utilization in machine learning models. Semantic web technologies offer a promising framework for semantic integration of e-learning data, enabling systematic consolidation, linkage, and advanced querying. We propose the e-LION (e-Learning Integration ONtology) semantic model to consolidate diverse e-learning knowledge bases and enhance analytical capabilities. Populated with real-world data from various LMSs, focusing on Software Engineering courses from the University of Malaga (Spain) and the Open University Learning, we validate it through four in-depth case studies. Advanced semantic querying techniques feed predictive models, perform time-series forecasting of student interactions based on final grades, and develop SWRL reasoning rules for student behavior classification. Validation study results are highly promising, suggesting e-LION as an ontological mediator scheme for integrating future semantic models within the e-learning domain. This opens exciting possibilities for leveraging the e-LION model to enhance educational planning, predictive modeling, and behavioral analysis, ultimately advancing e-learning through effective semantic integration and diverse learning-related data utilization.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Combining Inductive and Deductive Reasoning for Query Answering over Incomplete Knowledge Graphs

Current methods for embedding-based query answering over incomplete Knowledge Graphs (KGs) only focus on inductive reasoning, i.e., predicting answers by learning patterns from the data, and lack the complementary ability to do deductive reasoning, which requires the application of domain knowledge to infer further information. To address this shortcoming, we investigate the problem of incorporating ontologies into embedding-based query answering models by defining the task of embedding-based ontology-mediated query answering. We propose various integration strategies into prominent representatives of embedding models that involve (1) different ontology-driven data augmentation techniques and (2) adaptation of the loss function to enforce the ontology axioms. We design novel benchmarks for the considered task based on the LUBM and the NELL KGs and evaluate our methods on them. The achieved improvements in the setting that requires both inductive and deductive reasoning are from 20% to 55% in HITS@3

Deep and cognitive learning applied to Precision Medicine: the initial experiments linking (epi)genome to phenotypes-disease characteristics

Present-day era of Big Data provides the unique opportunity to develop innovative approaches for data analysis to find new insights into specialized fields of biomedical research such as Precision Medicine [1]. Precision Medicine is defined as the integration of molecular research with clinical data in order to deliver better diagnoses and treatments tailored to the individual characteristics of each patient. Advanced analysis of health related data that is specific to a given individual must focus on both clinical information (e.g. clinical reports, medical images, patient histories) and biological data (e.g. gene and protein sequences, functions and pathways). This wealth of information has the potential to inspire systematic ways of making sense from the massive and heterogeneous stream of data and providing a unified view. In the regards, Deep Learning (DL) [2] and Cognitive Computing (CC) [3] are two branches of Artificial Intelligence (AI) representing convenient choices to tackle the problem of Big Data integration for Precision Medicine. DL comprises several machine learning techniques modeling multiple representations of data through many layers of nonlinear processing units. CC is a cross-disciplinary technology for adaptive and contextual knowledge representation and reasoning through sophisticated analytics aiming to mimic human learning mechanisms