Detección precoz de dificultades en el aprendizaje. Herramienta para la predicción del rendimiento de los estudiantes

Inspirados por las estrategias de detección precoz aplicadas en medicina, proponemos el diseño y construcción de un sistema de predicción que permita detectar los problemas de aprendizaje de los estudiantes de forma temprana. Partimos de un sistema gamificado para el aprendizaje de Lógica Computacional, del que se recolectan masivamente datos de uso y, sobre todo, resultados de aprendizaje de los estudiantes en la resolución de problemas. Todos estos datos se analizan utilizando técnicas de Machine Learning que ofrecen, como resultado, una predicción del rendimiento de cada alumno. La información se presenta semanalmente en forma de un gráfico de progresión, de fácil interpretación pero con información muy valiosa. El sistema resultante tiene un alto grado de automatización, es progresivo, ofrece resultados desde el principio del curso con predicciones cada vez más precisas, utiliza resultados de aprendizaje y no solo datos de uso, permite evaluar y hacer predicciones sobre las competencias y habilidades adquiridas y contribuye a una evaluación realmente formativa. En definitiva, permite a los profesores guiar a los estudiantes en una mejora de su rendimiento desde etapas muy tempranas, pudiendo reconducir a tiempo los posibles fracasos y motivando a los estudiantes.

Narrativa digital e infancia. La generación de los creadores colaborativos

La naturaleza de los medios y lenguajes digitales ha posibilitado el desarrollo de diferentes técnicas que, en el canon del mundo analógico, se veían limitadas. Esta combinación ha originado, en los primeros años de vida del ser humano, nuevas formas de aprender envueltas en una nueva realidad. Las técnicas de creación que adquieren los niños en espacios alejados de cualquier currículo escolar, son desarrolladas gracias a su condición de ciudadanos de un contexto de sabios digitales; condición que trae intrínseco un conocimiento en el manejo tecnológico como de manera innata, convirtiendo la narrativa digital en el medio que ellos utilizan para aprender y comunicarse. Como consecuencia, en el modelo EMEREC más individualista se abre paso una generación de creadores colaborativos otorgando, por medio de la participación infantil, una mayor potencialidad a la ley de los tres tercios.

Evaluation of the Implementation of CLIL (Content and Language Integrated Learning) Methodology in the Didactics of the English Language in Preschool Education Course Taught in the Preschool Education Teacher Undergraduate Program at the University of Alicante

Although it is known that the Spanish current Educative System promotes using the Communicate Approach to teach foreign languages in schools, other recently designed approaches are also used to help students improve their skills when communicating in a foreign language. One of these approaches is Content and Language Integrated Learning, also known as CLIL, which is used to teach content courses using the English language as the language of instruction. This approach improves the students’ skills in English as the same time as they learn content from other areas. The goal of this thesis is to present a research project carried out at the University of Alicante during the academic year 2011-2012. With this research we obtained results that provide quantitative and qualitative data which explains how the use of the CLIL methodology affects the English level of students in the “Didactics of the English Language in Preschool Education” course in Preschool Education Teacher Undergraduate Program as students acquire the contents of the course.

Evaluation of hybrid and distance education learning environments in Spain

This article describes the adaptation and validation of the Distance Education Learning Environments Survey (DELES) for use in investigating the qualities found in distance and hybrid education psycho-social learning environments in Spain. As Europe moves toward post-secondary student mobility, equanimity in access to higher education, and more standardised degree programs across the European Higher Education Area (EHEA) the need for a high quality method for continually assessing the excellence of distance and hybrid learning environments has arisen. This study outlines how the English language DELES was adapted into the new Spanish-Distance Education Learning Environments Survey (S-DELES) for use with a Bachelor of Psychology and Criminology degree program offering both distance and hybrid education classes. We present the relationships between psycho-social learning environment perceptions and those of student affect. We also present the asynchronous aspects of the environment, scale means, and a comparison between the perceptions of distance education students and their hybrid education counterparts that inform the university about the baseline health of the information and communication technologies (ICT) environment within which the study was conducted.

Some reflections on the impact of globalization in the teaching and learning of English in socalled “expanding circle” countries

This article deals with the ongoing debate on the complex role of English as an International Language, be it understood as a homogeneous entity (one language with an international role [EIL]) or a heterogeneous one (different varieties (WE or ELF) grouped under one label, «English») as well as on the implications of this «globalising» status for its teaching in non-native settings. Given the complexity of this phenomenon, whose study is still in its infancy, we attempt neither to provide definitive answers nor adopt a prescriptive attitude, but simply contribute to the discussion and clarification of this, to some extent, emergent, controversial situation.

Sentiment classification for early detection of health alerts in the chemical textile domain

In the chemical textile domain experts have to analyse chemical components and substances that might be harmful for their usage in clothing and textiles. Part of this analysis is performed searching opinions and reports people have expressed concerning these products in the Social Web. However, this type of information on the Internet is not as frequent for this domain as for others, so its detection and classification is difficult and time-consuming. Consequently, problems associated to the use of chemical substances in textiles may not be detected early enough, and could lead to health problems, such as allergies or burns. In this paper, we propose a framework able to detect, retrieve, and classify subjective sentences related to the chemical textile domain, that could be integrated into a wider health surveillance system. We also describe the creation of several datasets with opinions from this domain, the experiments performed using machine learning techniques and different lexical resources such as WordNet, and the evaluation focusing on the sentiment classification, and complaint detection (i.e., negativity). Despite the challenges involved in this domain, our approach obtains promising results with an F-score of 65% for polarity classification and 82% for complaint detection.

Development and psychometric testing of the clinical learning environment, supervision and nurse teacher evaluation scale (CLES+T): The Spanish version

Background: The Clinical Learning Environment, Supervision and Nurse Teacher scale is a reliable and valid instrument to evaluate the quality of the clinical learning process in international nursing education contexts. Objectives: This paper reports the development and psychometric testing of the Spanish version of the Clinical Learning Environment, Supervision and Nurse Teacher scale. Design: Cross-sectional validation study of the scale. Setting: 10 public and private hospitals in the Alicante area, and the Faculty of Health Sciences (University of Alicante, Spain). Participants: 370 student nurses on clinical placement (January 2011–March 2012). Methods: The Clinical Learning Environment, Supervision and Nurse Teacher scale was translated using the modified direct translation method. Statistical analyses were performed using PASW Statistics 18 and AMOS 18.0.0 software. A multivariate analysis was conducted in order to assess construct validity. Cronbach’s alpha coefficient was used to evaluate instrument reliability. Results: An exploratory factorial analysis identified the five dimensions from the original version, and explained 66.4% of the variance. Confirmatory factor analysis supported the factor structure of the Spanish version of the instrument. Cronbach’s alpha coefficient for the scale was .95, ranging from .80 to .97 for the subscales. Conclusion: This version of the Clinical Learning Environment, Supervision and Nurse Teacher scale instrument showed acceptable psychometric properties for use as an assessment scale in Spanish-speaking countries.

The Influence of Gender, Intellectual Ability, Academic Self-Concept, Self-Regulation, Learning Strategies, Popularity and Parent Involvement in Early Adolescence

The present study examined the predictive effects of gender, intellectual ability, self-concept, motivation, learning strategies, popularity and parent involvement on academic achievement. Hiearchical regression analysis were performed with six steps in which each variable was included, among a sample of 1398 high school students (mean age = 12.5; standard deviation = .67) of eight education centers from the province of Alicante (Spain). The results revealed significant predictive effects of all of the variables, explaining 59.1% of the total variance.

Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced

Statistical machine translation (SMT) is an approach to Machine Translation (MT) that uses statistical models whose parameter estimation is based on the analysis of existing human translations (contained in bilingual corpora). From a translation student’s standpoint, this dissertation aims to explain how a phrase-based SMT system works, to determine the role of the statistical models it uses in the translation process and to assess the quality of the translations provided that system is trained with in-domain goodquality corpora. To that end, a phrase-based SMT system based on Moses has been trained and subsequently used for the English to Spanish translation of two texts related in topic to the training data. Finally, the quality of this output texts produced by the system has been assessed through a quantitative evaluation carried out with three different automatic evaluation measures and a qualitative evaluation based on the Multidimensional Quality Metrics (MQM).