INDIVIDUAL DIFFERENCES IN FOREIGN LANGUAGE TEACHING AND LEARNING

Individual differences in foreign language learning have long been the concern of linguists and language teachers. Researches on this subject have been carried out in schools, universities and other educational institutions and great achievements have been made. As it is, there are many individual differences which affect the learning of foreign languages, such as intelligence, aptitude, motivation, personality, attitude,

How to Choose the Right Strategies： A Treatment according to Individual Orientation of Learning Styles

The learning strategies used by the successful language learners are not always the right ones for all language learners. The individual distinctions of personality, affective domain, cognition and behaviorism all lead to the different personal styles in language learning. Language learners must choose the strategies, which are appropriate for their styles.

The Application of Multiple Intelligences Theory in High School Education and Its Relationship with Students’Individualized Development

The integration of Howard Gardner’s Theory of Multiple Intelligences(MI)into high school education presents a transformative approach to student learning and development.This paper explores the application of MI theory in shaping individualized learning pathways,enhancing student self-awareness,and fostering social and emotional development.Challenges such as professional development needs,curriculum adaptation,and resource allocation are discussed alongside future trends including technological integration,interdisciplinary learning,and inclusive education models.Empirical data,although hypothetical,illustrate the potential benefits of MI-tailored education on student performance and engagement.The paper concludes with a call for collaborative efforts among educators,policymakers,and researchers to realize the potential of MI theory in creating personalized and effective educational experiences for all students.

SOCIAL OR INDIVIDUAL LEARNING？ AN AGGREGATED SOLUTION FOR COORDINATION IN MULTIAGENT SYSTEMS

There are mainly two different ways of learning for animals and humans： trying on yourself through interactions or imitating/copying others through communication/observation. How these two learning strategies differ and what roles they are playing in achieving coordination among individuals are two challenging problems for researchers from various disciplines. In multiagent systems, most existing work simply focuses on individual learning for achieving coordination among agents. The social learning perspective has been largely neglected. Against this background, this article contributes by proposing an integrated solution to decision making between social learning and individual learning in multiagent systems. Two integration modes have been proposed that enable agents to choose in between these two learning strategies, either in a t＇Lxed or in an adaptive manner. Experimental evaluations have shown that these two kinds of leaning strategies have different roles in maintaining efficient coordination among agents. These differences can reveal some significant insights into the manipulation and control of agent behaviors in multiagent systems, and also shed light on understanding the social factors in shaping coordinated behaviors in humans and animals.

Camera recognition with deep learning

In this paper,camera recognition with the use of deep learning technique is introduced.To identify the various cameras,their characteristic photo-response non-uniformity(PRNU)noise pattern was extracted.In forensic science,it is important,especially for child pornography cases,to link a photo or a set of photos to a specific camera.Deep learning is a sub-field of machine learning which trains the computer as a human brain to recognize similarities and differences by scanning it,in order to identify an object.The innovation of this research is the use of PRNU noise patterns and a deep learning technique in order to achieve camera identification.In this paper,AlexNet was modified producing an improved training procedure with high maximum accuracy of 80%–90%.DIGITS showed to have identified correctly six cameras out of 10 with a success rate higher than 75%in the database.However,many of the cameras were falsely identified indicating a fault occurring during the procedure.A possible explanation for this is that the PRNU signal is based on the quality of the sensor and the artefacts introduced during the production process of the camera.Some manufacturers may use the same or similar imaging sensors,which could result in similar PRNU noise patterns.In an attempt to form a database which contained different cameras of the same model as different categories,the accuracy rate was low.This provided further proof of the limitations of this technique,since PRNU is stochastic in nature and should be able to distinguish between different cameras from the same brand.Therefore,this study showed that current convolutional neural networks(CNNs)cannot achieve individualization with PRNU patterns.Nevertheless,the paper provided material for further research.

Possible interpretation of disciplinary issues in education

Education must go beyond the borders of the disciplines and educators must make individual learning development a top priority for education if they wish to fulfill their mission in theory and practice,and in order to promote the social development by cultivating and developing the different individual learning.While individual development is a public issue,not a personal affair,it is also a social issue.Thus,educational research bases itself on each type of development,as well as to its existence in the mosaic of social and cultural understanding of the situation.Consequently,theoretical concept and empirical study combine an intrinsic pedagogical paradigm mechanism.Furthermore as a theoretical approach to methodology,awareness of the value of education and method-related activities,pedagogy becomes a special way of seizing the world.