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One of the problems faced by people with blindness is access to materials presented in graphical form. There are many alternative forms of providing such information, but they are very often ineffective or have certain limitations. The development of mobile devices and touch sensors enabled the development of new tools to support such people. This study presents a solution called an accessible tutoring platform, using audio-tactile graphics for people with blindness. We aimed to research the influence of the developed platform for the alternative presentation of graphics information on better memorizing, recognizing, and learning. Another goal of the research was to verify the effectiveness of the proposed method for the alternative presentation of audio-tactile graphics. The effectiveness of the proposed solution was verified quantitatively and qualitatively on two groups of blind students from primary and secondary schools with the use of a developed platform and prepared materials for learning mathematics. The obtained research results show that the proposed method of verifying students' knowledge and auto-selecting exercises with adapted audio description positively influences the improvement of learning effectiveness. [ABSTRACT FROM AUTHOR]

Recently, intelligent tutoring systems (ITSs) aid in assisting instructional procedures and help students traverse online learning resources adaptively. It has laid a strong foundation and has grown rapidly in the last several years. Web-based learning platforms make it easier for students from diverse backgrounds with varying requirements, interests, and traits to learn remotely and provide instant access to any subject area and learning method. An ITS is a computer-based system that imitates human tutors and its goal is to give students quick, personalized teaching or feedback usually without the need for human teacher intervention. The purpose of this study is to analyze the artificial intelligence (AI)-driven autonomous interactive English learning language tutoring system. The AI-powered approach utilized by Duolingo facilitates real-time feedback and adjusts to the rate of the student, including exercises that are specifically designed to enhance the English learning language. Through the system’s use, users gradually remember grammar and vocabulary by going over topics at suitable times. A total of 125 students participated in this study. This questionnaire was created to investigate important areas of students’ learning of the English language. Therefore, their feedback offers a more accurate depiction of their opinions toward learning English. Spell and grammar check in the essay are taken into account by a thorough scoring algorithm that is used to evaluate the user-centric system. The data was analyzed using SPSS software. The results indicate that by offering a scalable, user-centric system that adjusts to the demands of specific learners, Duolingo’s AI-based technology greatly improves the English language learning process. The AI-driven language tutoring systems are highlighted in this study, along with possible advancements in conversational AI and the integration of innovative learning technologies to improve the quality of learning. [ABSTRACT FROM AUTHOR]

The growth of the higher education population and different school paths to access an academic degree has increased the heterogeneity of students inside the classroom. Consequently, the effectiveness of traditional teaching methods has reduced. This paper describes the design, development, implementation and evaluation of a tutoring system (TS) to improve student's engagement in higher mathematics. The TS design was based on the Personalized System of Instruction of the Mastery Learning pedagogical approach and can be implemented in any higher education course with mathematics needs. The TS consists on small self-paced modularized units of educational contents, including tutorial videos, notes and formative e-assessment with personalized feedback. The TS ensures that the student is only allowed to proceed to the next unit after he or she achieves the required mastery criterion of the current unit. The TS was implemented in the Quantitative Methods course of an undergraduate degree and received good acceptance from students. It was also recognized that TS contributed to learning and engagement with the discipline. Through an experimental research experience, it has been shown that the imposition of restrictions on the advance to the next level by a mastery criterion leads to a significant improvement in student's engagement and performance. [ABSTRACT FROM AUTHOR]

The objective of any tutoring system is to provide resources to learners that are adapted to their current state of knowledge. With the availability of a large variety of online content and the disjunctive nature of results provided by traditional search engines, it becomes crucial to provide learners with adapted learning paths that propose a sequence of resources that match their learning objectives. In an ideal case, the sequence of documents provided to the learner should be such that each new document relies on concepts that have been already defined in previous documents. Thus, the problem of determining an effective learning path from a corpus of web documents depends on the accurate identification of outcome and prerequisite concepts in these documents and on their ordering according to this information. Until now, only a few works have been proposed to distinguish between prerequisite and outcome concepts, and to the best of our knowledge, no method has been introduced so far to benefit from this information to produce a meaningful learning path. To this aim, this article first describes a concept annotation method that relies on machine-learning techniques to predict the class of each concept--prerequisite or outcome--on the basis of contextual and local features. Then, this categorization is exploited to produce an automatic resource sequencing on the basis of different representations and scoring functions that transcribe the precedence relation between learning resources. Experiments conducted on a real dataset built from online resources show that our concept annotation approach outperforms the baseline method and that the learning paths automatically generated are consistent with the ground truth provided by the author of the online content. [ABSTRACT FROM AUTHOR]

Introduction. This article shows how computer science and cognitive neuroscience can be merged to propose an effective profiling scheme. In the area of user profiling this paper will provide the paths and trends that researches has already gone through, and how some issues are being overpassed. In other words, this work will solve effectively one issue: content personalization through the identification of an individual's learning behavior. Objective. This work will demonstrate characterizing someone's brain responses to a specific action is possible. As this research topic has to deal with different fields and there are not previous researches that conveys both. The core idea is to provide enough elements to form the foundations in both areas and propose a scheme to do so. Materials and methods. This section summarizes basic elements of interaction between learners and computers that allows us to integrate them. It will show how some responses named cognitive neuroscience variables are a good source of information for user profiling and will illustrate how this researched field especially used in neuroscience can be effectively used for this purpose. In other words, this paper is going to show the reader how some reactions to exposed actions can be tracked and characterized. Results. It discusses some issues to take into account for developing the proposed profiling scheme and shows how human brain responses can be used to acquire the necessary information to feed an intelligent profiling system. These assumptions allow researchers to account different phenomena and use them for different purposes like the one being developed in this work: Learner Profiling. Conclusiones. Algunas ventajas y desafíos del Perfilamiento de Aprendices se enumeran y se invita a los investigadores a aplicar esta tecnología en otros campos y a ampliar esta aplicación, especialmente en el contexto enseñanza-aprendizaje. [ABSTRACT FROM AUTHOR]

Abstract: With the development of the Semantic web the use of ontologies as a formalism to describe knowledge and information in a way that can be shared on the web is becoming common. The explicit conceptualization of system components in a form of ontology facilitates knowledge sharing, knowledge reuse, communication and collaboration and construction of knowledge rich and intensive systems. Semantic web provides huge potential and opportunities for developing the next generation of e-learning systems. In previous work, we presented tutoring system named Protus (PRogramming TUtoring System) that is used for learning the essence of Java programming language. It uses principles of learning style identification and content recommendation for course personalization. This paper presents new approach to perform effective personalization highly based on Semantic web technologies performed in new version of the system, named Protus 2.0. This comprises the use of an ontology and adaptation rules for knowledge representation and inference engines for reasoning. Functionality, structure and implementation of a Protus 2.0 ontology as well as syntax of SWRL rules implemented for on-the-fly personalization will be presented in this paper. [Copyright &y& Elsevier]

Three groups participated in a study on the added value of mobile technology for learning English as a second language for primary school students. The first group had classroom lessons in English about zoo animals and their characteristics. The second group took classroom lessons and worked with a mobile application on location in a public zoo. The third group received the same treatment as the second but, as an extension, was allowed to take the mobile application home for a fortnight. A pre- and a posttest were conducted to measure the individual change in mastery of a set of targeted English words. The results showed that the group which took the mobile phone home improved the most. However, when the additional learning time, spent apart from school, of this third group was controlled for, the superior performance of the group disappeared. The results indicate that students are motivated to use the application in their spare time and that this benefits their learning. The conclusion is that formal school learning can be augmented by learning in an informal context, away from school. [Copyright &y& Elsevier]

Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper, we describe a recommendation module of a programming tutoring system - Protus, which can automatically adapt to the interests and knowledge levels of learners. This system recognizes different patterns of learning style and learners’ habits through testing the learning styles of learners and mining their server logs. Firstly, it processes the clusters based on different learning styles. Next, it analyzes the habits and the interests of the learners through mining the frequent sequences by the AprioriAll algorithm. Finally, this system completes personalized recommendation of the learning content according to the ratings of these frequent sequences, provided by the Protus system. Some experiments were carried out with two real groups of learners: the experimental and the control group. Learners of the control group learned in a normal way and did not receive any recommendation or guidance through the course, while the students of the experimental group were required to use the Protus system. The results show suitability of using this recommendation model, in order to suggest online learning activities to learners based on their learning style, knowledge and preferences. [Copyright &y& Elsevier]

Satellite images are increasingly being used to monitor environmental temporal changes. The general approach is to compare old images to recent ones acquired from a satellite in order to detect changes that occurred during the period between which these images were taken. An important step in this overall process is the acquisition of image data that will best allow assessing the temporal changes. This acquisition requires some expertise in order to select images from satellite sensors that use the appropriate spectral band for a forest application. For instance, a sensor suitable for classifying urban images will not necessarily be appropriate for forest mapping, because buildings reflect electromagnetic waves differently from trees and hence show a different spectrum with the same sensor. In this paper, we present an emerging Image Data Selection Assistant (IDSA) that uses an expert system combined with intelligent tutoring to help users in choosing images for updating forest maps, while at the same time teaching them how to best select images depending on the task. [ABSTRACT FROM AUTHOR]

Traditional architecture is an important topic, not only for finding local identities from traditional heritages but also for representing the traditional identities. It is especially true because locality issues are critical in this global era. Nevertheless, the structure of traditional Korean architecture has not been fully explored in a systematical or computational manner. Furthermore, this information is not managed efficiently even though the technology for managing information effectively is quite widely available and the information could be used in many application areas. Currently, all but a few experts keep their knowledge exclusively and transfer it to few people in a limited and traditional manner. This study thus selects the Internet as an educational environment for practical reasons and explores a way of structuring construction knowledge and building information of traditional Korean architecture. That will be the first step to manage information of traditional architecture. In order to simulate traditional buildings in advanced and intelligent ways, we apply a computer technique, called data modeling. We develop a robust data model to effectively represent the building. For data modeling, we select a well-known building, Buseoksa Muryangsujun as a prototype, which is one of the oldest wooden structures in Korea. We first build an accurate three-dimensional model of the building, and then analyze its building components and their connectivity by focusing on the capital order system, called Gongpo. We also suggest a user interface model operated through the data model. The interface provides several components and functionality such as viewing each architectural component, simulating the components'' connectivity interactively, and retrieving architectural information. The study shows a diagram of the wooden construction data model and some rules to explain components'' connectivity, and a user interface model. This is currently being integrated into the KotaView system based on two environments: a web-based solid modeler(called WebMod) and a web-based VR engine (Active World™, EON™). [Copyright &y& Elsevier]