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Students have learning difficulties, mainly in processes that involve attention and interpretation of written or spoken language. Technological tools allow to create computational platforms with adaptation aspects depending on the student’s characteristics. It is also important to highlight the progress of the measurement of cognitive processes such as attention through NeuroSky’s MindWave EEG sensors. This paper aims to present the results of analyzing attention levels of children with learning difficulties, based on the acquired brain waves. As a final result, an adaptive computational system that displays educational activities regarding educational profiles of children is obtained.

The Kamachiy–Idukay platform was chosen to make the validation. The platform generates the educational activities according to the students’ profile. The validation phases were identification of the test environment, the first environment required a scenario that involved students with learning difficulties, to verify the functionality of the system, when analyzing cases of the students with learning difficulties; identification of two validation criteria, type of educational activity and attention difficulties of the students; and analysis of the brain signal when children interact with the educational content.

The adaptation of contents that include music and animations generate higher levels of attention in students with difficulty. The analysis of signals from the NeuroSky sensor to determine the attentional levels in children allowed a generation of content adapted to the characteristics of the difficulty in each child.

For the validation, it was necessary at the beginning of the activity to determine the stability of the signal emitted by the NeuroSky sensor. Two cases were studied in children with difficulty and their measure of attention versus adaptive contents.

A k-means algorithm was used to establish the attention levels of the children.

Children with learning difficulties have different learning styles, which implies an adaptation of content that generates an attentional process according to their characteristics.

Evaluation content adaptation taking into account the signal brain sensor NeuroSky for learning process. The signal brain of the student when interacting with the activities is include in the student profile.

The purpose of this paper is to present Zeuss, a software-based tool designed to improve grammar learning process in elementary school children. Despite efforts by the Colombian Government, the results of the final high school test indicate that students have major deficiencies with language, grammar and reading comprehension. Several difficulties have been evidenced in activities like writing essays or understanding academic papers. Among the reasons that may lead to these results include outdated courses, overcrowded classrooms and lack of interest.

A diagnostic test is performed on third-grade elementary school students to assess the current grammar knowledge and identify areas for improvement. The test results are used to design a software-based tool called Zeuss. The authors include playful activities inspired by several pedagogic exercises found in the literature and personalization so that interaction is tailored to specific user preferences and tastes.

Zeuss has been tested with third-grade students of the Gimnasio Campestre San Francisco de Sales elementary school in Bogotá, Colombia. The results show that using the tool leads to an overall improvement in the grammar construction learning process.

Zeuss aims at improving the learning process in elementary schools helping teachers to overcome several limitations like overcrowded classrooms and outdated pedagogic strategies. Zeuss focuses specifically on the grammar learning process.

Zeuss features updated pedagogical strategies, playful activities and a personalization model to tailor the learning process and help in context. It also allows teachers to track individual and classroom progress.

This paper aims to present Accomm a software implementation of Ágora-SN, a supply network (SN) customer-oriented model integrated with an Adaptation Model. Accomm serves two purposes: as an experimental validation tool to measure the impact of Adaptation on an agribusiness SN model and as a logistic and marketing operations planning assistant.

The design of Accomm is based on the results of the Ágora-SN model that comprises the following tasks: to characterize the SN actors’ processes ( composed of multiple first-tier suppliers, a focal company and multiple first-tier customers), identifying the ones oriented to the customer; to integrate these processes into a SN model which incorporates a supplier cooperation model; and to provide an adaptation model that implements a customer profile and a context profile to improve order fulfillment.

To validate the Ágora-SN model, a prototype Accomm was created referred to a real Colombian agribusiness sector company, specifically in the floriculture sector. This prototype was validated through two methods: a usability scale and a set of scenarios that compared the application’s behavior with and without adaptation and cooperation. The application provides a better response to demand when both adaptation and cooperation are enabled.

This work was tested in an academic environment and was validated by different experts. Further tests in operational real-life environments are required to fully validate the approach.

The main contribution of this work is the integration of Adaptation into a SN model as a way to center the SN toward the customer. As an additional contribution, the validation tool Accomm is conceived as an operational planning tool for agribusiness SN.

The purpose of this paper is to describe a support system to the selection of enrichment activities in educational environment called RunayaySoft, where Runayay comes from the word Quechua that means develop and Soft as it is an informatics tool that supports the educational institutions and their students, in the selection of activities that allow foster some of their skills based on their interests, learning styles, aptitudes, multiple intelligences, preferences and so on. Moreover, it suggests institutions about the activities that they should make in their building considering student´s characteristics and the agreements that they have.

It does a diagnostic for identifying which characteristics are going to be considered to students and institutions. Then, it generates adaptive profiles with the aim of generating suggestions of enrichment activities that allow to boost some of their skills. For the students were considered their preferences, learning style, aptitude, multiple intelligences and interests. In the case of institutions were the agreements, resources and activities that they develop. Based on this information, it defines the relations for the generation of suggestions of activities toward students, where it does the prioritization of which activities should be considered.

For validating the system, it was done as a functional prototype that generates suggestions to students, as well as educative institutions, through a satisfaction test student assess if they agree or disagree with the suggestions given. With that assessment, it is validated the relationship between student’s characteristics, activity and institution are related for generating activities suggestions.

RunayaySoft generates adaptive profiles for the students, activity and institution. Each profile has information that allows adapt an advice toward students and institutions.

RunayaySoft considers student’s characteristics, activities and educational institutions for generating suggestions for enrichment activities that allow to boost some of their skills. Many times, when activities are generated in educative institutions, they are not considered a learner’s needs and characteristics. For that reason, the system helps institutions to identify activities that should be done in their facilities or with those institutions which they have agreements when the institutions that students come from do not have the required resources.

RunayaySoft suggests enrichment activities to students as well as educative institutions. For students, it suggests disciplinary areas where they can boost their skills; for each disciplinary area are recommended activities based on their preferences. Once students select the disciplinary area and activities, the system suggests educative institutions activities that they can do. If the institutions do not have the necessary facilities, the system shows with which other institutions they can set agreements. Moreover, it supports educative institutions to identify enrichment clusters, where it clusters students based on similar interest, allowing institutions to identify the activities that they should focus on.

This paper aims to present a detailed description of Tukuchiy, a framework to dynamically generate adapted user interfaces. Tukuchiy is based on Runa-Kamachiy, a conceptual integration model that combines human–computer interaction (HCI) standards to create user interfaces with user-centered concepts usually addressed by adaptation.

The first step was the definition of three profiles: user, context and interface. These profiles contain information, such as user disabilities, location characteristics (e.g. illumination) and preferences (e.g. interface color or type of system help). The next step is to define the rules that ensure usability for different users. All of this information is used to create the Tukuchiy framework, which generates dynamic user interfaces, based on the specified rules. The last step is the validation through a prototype called Idukay. This prototype uses Tukuchiy to provide e-learning services. The functionality and usability of the system was evaluated by five experts.

To validate the approach, a prototype of Tukuchiy, called Idukay, was created. Idukay was evaluated by experts in education, computing and HCI, who based their evaluation in the system usability scale (SUS), a standard usability test. According to them, the prototype complies with the usability criteria addressed by Tukuchiy.

This work was tested in an academic environment and was validated by different experts. Further tests in a production environment are required to fully validate the approach.

Tukuchiy generates adapted user interfaces based on user and context profiles. Tukuchiy uses HCI standards to ensure usability of interfaces that dynamically change during execution time. The interfaces generated by Tukuchiy adapt to context, functionality, disabilities (e.g. color blindness) and preferences (usage and presentation) of the user. Tukuchiy enforces specific HCI standards for color utilization, button size and grouping, etc., during execution.

This paper aims to present a detailed description of Agents for Enriching Services (AES), an agent-oriented framework that allows adapting a service in an information system. AES provides an adaptation logic that can be instantiated and extended to be useful in different domains. In previous works, we presented the adaptation mechanism of AES, which considers context aspects such as location, infrastructure; user aspects such as preferences and interests; and device aspects such as hardware and software features.

The first step was the definition of different profiles, mainly user and context profiles. Then the adaptation mechanism was defined, which considers these profiles. With this mechanism, the adaptation filters to apply them to the initial queries was specified. Finally, feedback was provided, which included implicit and explicit information from the user and the system. AES is an agent-based framework implemented in Java, using the multi-agent platform BESA and a rule-based engine Drools.

AES can be used as the starting point to adapt services by enriching them considering different stimulus whether they come from the environment, devices or user preferences.

This work was tested in an academic environment and was only applied to enhance queries by using keywords. AES uses the query mechanism implemented in the system that invokes it.

This paper focuses on: an integrated view of AES including its formal description and details about its implementation. Particularly, it includes an exhaustive and formal definition of the filters used to create the adaptation rules and three different scenarios of the application of AES to adapt content according to user and context features. Finally, a comparison analysis is presented to highlight the strengths of our framework, specially its capacity of integration with systems that require providing user- and context-oriented services.

The purpose of this paper is to describe UWIRS (Ubiquitous Web Information Retrieval Solution), an agent‐based Web Information Retrieval (WIR) solution designed taking into account the unique features of the World Wide Web (WWW) and the limitations of existing WIR solutions for ubiquitous environments.

UWIRS can offer recommendation services by using the Multi‐Agent Vizier Recommendation Framework (Vizier). Vizier was designed under a generic approach and therefore can provide services to information retrieval applications so these may offer product recommendations that consider several adaptation/personalization dimensions (e.g. user dimension, context, among others).

Overall, the main challenge resides on: location, retrieval, integration and presentation of information from the WWW, quickly and accurately, to satisfy a user's singular information needs.

In UWIRS, agents cooperate in order to retrieve personalized information, considering user needs, goals, preferences and contextual features. UWIRS's agents are responsible for: interpreting user input and adding adaptation information by means of a query enrichment process; identifying and selecting the appropriate data sources taking into consideration the Profile Set (composed of User, Device and Information‐Provider Profiles); executing query routing and the information retrieval process; integrating and filtering the retrieved results; and lastly, coherent presentation of quality and relevant ubiquitous information (anytime, anywhere and anyhow) that satisfies the user's particular information needs and constraints associated to his/her access device.

This article aims to propose an adaptation algorithm that combines the analytical hierarchy process (AHP), a rule-based system, and a k-means clustering algorithm. Informatic tools are very useful to enhance the learning process in the classroom. The large variety of these tools require advanced decision-making techniques to select parameters, such as student profiles and preferences, to adjust content and information display, according to specific characteristics and necessities of students. They are part of the Kamachiy–Idukay (KI), a platform to offer adaptative educational services to students with learning difficulties or disabilities.

The design and implementation of the adaptation algorithm comprises the following phases: utilization of the AHP to determine the most important student parameters, parameter to take into account in the adaptation process, such as preferences, learning styles, performance in language, attention and memory aspects and disabilities; designing the first part of the adaptation algorithm, based on a rule-based system; designing the second part of the adaptation algorithm, based on k-means clustering; integration of the adaptation algorithm to KI; and validation of the approach in a primary school in Bogotá (Colombia).

The main approach is the application of computational techniques, namely, rule-based systems and k-means clustering, plus an AHP prioritization at design time to yield a system to support the teaching–learning process for students with disabilities or learning difficulties.

The algorithm found several groups of students with specific learning difficulties that required adapted activities. The algorithm also prioritized activities according to learning style and preferences. The results of the application of this system in a real classroom yielded positive results.

The algorithm performs adaptation for students with mild disabilities or learning difficulties (language, attention and memory). The algorithm does not address severe disabilities that could greatly affect cognitive abilities.

The main contribution of this paper is an adaptation algorithm with the following distinctive characteristics, namely, designed utilizing the AHP, which ensures a proper prioritization of the student characteristics in the adaptation process, and utilizes a rule-based system to identify different adaptation scenarios and k-means clustering to group students with similar adaptation requirements.

The purpose of this paper is to propose Kamachiy-Mayistru (KM), an adaptive module to support teaching to people with learning difficulties. In Colombia, learning disabilities and difficulties are frequent in the integration classroom. Proper learning can be achieved as long as teaching strategies and didactic tools are the most adequate to the specific student characteristics and follow the suggestions given by experts for each learning difficulty. This module assists the teacher to prepare a course taking into account the disability profile, the student profile and pedagogical model suggestions. In this way, the student can learn utilizing the format and didactic tools more appropriate to their specific necessities.

The design and implementation of the KM comprises the following phases: identify the most important student, teacher, difficulties and course parameters to take into account in the adaptation process; design the data model that supports activity adaptation, based on student characteristics and difficulties; implement the platform; and validate the approach through a case study of teachers and their students with difficulties.

The application of KM in the case study indicated the effectiveness of KM to assist teachers in organizing course activities for students with and without disabilities or difficulties.

KM addresses specific student difficulties: attention, memory and languages. KM does not address severe cognitive disabilities. Regarding the validation, it is recommended to pursue new case studies to further demonstrate the effectiveness of the approach in a broader population.

The main approach in KM is to suggest activities or pedagogical strategies to teachers to best support learning in students with difficulties or disabilities. The core of KM is an algorithm, called “Adapt Course”, that takes as input student and disability profiles, the course contents and the pedagogical model and creates course structures that are specially tailored to each student.

This model recommends teachers different activities, based on the specific student difficulties, to create personalized courses. It is able to address specific educational issues that are associated with learning difficulties and disabilities, such as educational integration, through content organization and personalized information display, which are based on the inherent characteristics of each student in the classroom.

It is based on a conceptual model that provides the essential architecture to design and implement virtual learning environments for students with learning difficulties or disabilities.