Comparison of AESA and LAESA search algorithms using string and tree-edit-distances

Although the success rate of handwritten character recognition using a nearest neighbour technique together with edit distance is satisfactory, the exhaustive search is expensive. Some fast methods as AESA and LAESA have been proposed to find nearest neighbours in metric spaces. The average number of distances computed by these algorithms is very low and does not depend on the number of prototypes in the training set. In this paper, we compare the behaviour of these algorithms when string and tree-edit-distances are used.Work partially supported by the spanish CICYT TIC2000-1599-C02 and TIC2000-1703-CO3-02

Improving classification using a Confidence Matrix based on weak classifiers applied to OCR

This paper proposes a new feature representation method based on the construction of a Confidence Matrix (CM). This representation consists of posterior probability values provided by several weak classifiers, each one trained and used in different sets of features from the original sample. The CM allows the final classifier to abstract itself from discovering underlying groups of features. In this work the CM is applied to isolated character image recognition, for which several set of features can be extracted from each sample. Experimentation has shown that the use of CM permits a significant improvement in accuracy in most cases, while the others remain the same. The results were obtained after experimenting with four well-known corpora, using evolved meta-classifiers with the k-Nearest Neighbor rule as a weak classifier and by applying statistical significance tests.This work was partially supported by the Spanish CICyT through the project TIN2013-48152-C2-1-R, the Consejería de Educación de la Comunidad Valenciana through Project PROMETEO/2012/017 and a FPU fellowship (AP2012-0939) from the Spanish Ministerio de Educación Cultura y Deporte

El Arte de coordinar actividades colaborativas con un solo clic

El rol del profesor cambia cuando hace uso de las TIC, su figura tiende a planificar y guiar situaciones de aprendizaje más que a ser un mero transmisor de información como en el pasado. El disponer del conocimiento necesario sobre las herramientas adecuadas para realizar la labor de seguimiento y control es fundamental para descongestionar al docente en estas labores. Una vez se planifica una asignatura el seguimiento de la misma es muy importante por lo que este artículo presenta una forma innovadora de gestionar la distribución, control y evaluación de actividades para un gran número de alumnos en clases presenciales masificadas. Pretende ser una guía para adquirir unas nociones básicas hacia la automatización de las tareas de coordinación basadas en servicios gratuitosWeb 2.0 de Google y una orientación para saber qué servicios usar cuando queremos automatizar procesos repetitivos.SUMMARY -- The teacher’s role has changed with the introduction of ICT, it tends to plan and guide learning situations rather than being a mere transmitter of information as in the past. Nowadays, teachers must also know how to use the latest management and monitoring tools in order to relieve their daily work. Once a course is planned, track the same is very important, so this paper presents an innovative way to manage the distribution, monitoring and evaluation of activities for large numbers of students in overcrowded classes. This text also intends to be a guide on how to automate coordination tasks and repetitive processes using Web 2.0 and the free services of Google

A new iterative algorithm for computing a quality approximate median of strings based on edit operations

This paper presents a new algorithm that can be used to compute an approximation to the median of a set of strings. The approximate median is obtained through the successive improvements of a partial solution. The edit distance from the partial solution to all the strings in the set is computed in each iteration, thus accounting for the frequency of each of the edit operations in all the positions of the approximate median. A goodness index for edit operations is later computed by multiplying their frequency by the cost. Each operation is tested, starting from that with the highest index, in order to verify whether applying it to the partial solution leads to an improvement. If successful, a new iteration begins from the new approximate median. The algorithm finishes when all the operations have been examined without a better solution being found. Comparative experiments involving Freeman chain codes encoding 2D shapes and the Copenhagen chromosome database show that the quality of the approximate median string is similar to benchmark approaches but achieves a much faster convergence.This work is partially supported by the Spanish CICYT under project DPI2006-15542-C04-01, the Spanish MICINN through project TIN2009-14205-CO4-01 and by the Spanish research program Consolider Ingenio 2010: MIPRCV (CSD2007-00018)

Influence of personality and modality on peer assessment evaluation perceptions using Machine Learning techniques

The successful instructional design of self and peer assessment in higher education poses several challenges that instructors need to be aware of. One of these is the influence of students’ personalities on their intention to adopt peer assessment. This paper presents a quasi-experiment in which 85 participants, enrolled in the first-year of a Computer Engineering programme, were assessed regarding their personality and their acceptance of three modalities of peer assessment (individual, pairs, in threes). Following a within-subjects design, the students applied the three modalities, in a different order, with three different activities. An analysis of the resulting 1195 observations using ML techniques shows how the Random Forest algorithm yields significantly better predictions for three out of the four adoption variables included in the study. Additionally, the application of a set of eXplainable Artificial Intelligence (XAI) techniques shows that Agreeableness is the best predictor of Usefulness and Ease of Use, while Extraversion is the best predictor of Compatibility, and Neuroticism has the greatest impact on global Intention to Use. The discussion highlights how, as it happens with other innovations in educational processes, low levels of Consciousness is the most consistent predictor of resistance to the introduction of peer assessment processes in the classroom. Also, it stresses the value of peer assessment to augment the positive feelings of students scoring high on Neuroticism, which could lead to better performance. Finally, the low impact of the peer assessment modality on student perceptions compared to personality variables is debated.This work has been partially funded by the University of Alicante’s Redes-I3CE de investigación en docencia universitaria del Instituto de Ciencias de la Educación (REDES-I3CE-2020-5069), by the EU Erasmus+ Programme (EduTech (609785-EPP-1-2019-1-ES-EPPKA2-CBHE-JP) and SkoPS (2020-1-DE01-KA226HE-005772) projects), by the Spanish Ministry of Science and Innovation (Access@IoT (PID2019-111196RB-I00) project), by the GVA (AICO/2020/143) project, and by the UCLM group cofinanced with ERDF funds (research grant 2021-GRIN-30993)

Does the global activity limitation indicator measure participation restriction? Data from the European Health and Social Integration Survey in Spain

Purpose The global activity limitation indicator (GALI) is the only internationally agreed and harmonised participation restriction measure. We examine if GALI, as intended, is a reflective measure of the domains of participation; furthermore, we determine the relative importance of these domains. Also, we investigated the consistency of response to GALI by age and gender and compared the performance of GALI with that of self-rated health (SRH). Methods We used Spanish data from the European Health and Social Integration Survey and selected adults aged 18 and over (N = 13,568). Data analysis, based on logistic regression models and Shapley value decomposition, were also stratified by age. The predictors of the models were demographic variables and restrictions in participation domains: studies, work, mobility, leisure and social activities, domestic life, and self-care. The GALI and SRH were the response variables. Results GALI was strongly associated with all participation domains (e.g. for domestic life, adjusted OR 24.34 (95% CI 18.53–31.97) in adult under 65) and performed differentially with age (e.g. for domestic life, adjusted OR 13.33 (95% CI 10.42–17.03) in adults over 64), but not with gender. The relative importance of domains varied with age (e.g. work was the most important domain for younger and domestic life for older adults). The results with SRH were parallel to those of GALI, but the association of SRH with participation domains was lowest. Conclusions GALI reflects well restrictions in multiple participation domains and performs differently with age, probably because older people lower their standard of good functioning.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Natur

Automatic detection of inconsistencies between numerical scores and textual feedback in peer-assessment processes with machine learning

The use of peer assessment for open-ended activities has advantages for both teachers and students. Teachers might reduce the workload of the correction process and students achieve a better understanding of the subject by evaluating the activities of their peers. In order to ease the process, it is advisable to provide the students with a rubric over which performing the assessment of their peers; however, restricting themselves to provide only numerical scores is detrimental, as it prevents providing valuable feedback to others peers. Since this assessment produces two modalities of the same evaluation, namely numerical score and textual feedback, it is possible to apply automatic techniques to detect inconsistencies in the evaluation, thus minimizing the teachers’ workload for supervising the whole process. This paper proposes a machine learning approach for the detection of such inconsistencies. To this end, we consider two different approaches, each of which is tested with different algorithms, in order to both evaluate the approach itself and find appropriate models to make it successful. The experiments carried out with 4 groups of students and 2 types of activities show that the proposed approach is able to yield reliable results, thus representing a valuable approach for ensuring a fair operation of the peer assessment process

Aprendizaje de algoritmia mediante desafíos de programación

Esta presentación describe las características de un sistema de autoevaluación de código, similar a los utilizados en los concursos de programación, que permite a los estudiantes aplicar los conocimientos teóricos de la disciplina de algoritmia para resolver problemas prácticos y, a la vez, reforzar las competencias generales de programación adquiridas en cursos previos. La experiencia de varios cursos en su aplicación demuestra que la utilización de un sistema competitivo introduce un aliciente adicional para la realización de los ejercicios.Peer Reviewe

Estrategias para programar la detección de plagios en actividades basadas en texto

La detección de plagios en los trabajos entregados por los alumnos es un problema que ha existido tradicionalmente cuando se entregaban en formato papel pero que en los últimos años se ha incrementado debido a la gran cantidad de información que existe en Internet, a la facilidad para encontrarla usando buscadores y a la entrega electrónica de los trabajos o actividades (ciberplagio). Incluso existen plataformas en Internet que estructuran y ofrecen gratuitamente los trabajos para que se puedan descargar. En este artículo se proponen varias estrategias orientadas a implementar un programa para uso personal que detecte uno de los tipos de plagio más extendidos actualmente como es copiar y pegar fragmentos de textos de Internet. Estas propuestas se estudian para la detección de plagio en trabajos de diferente índole, incluyendo memorias, diapositivas y páginas web. El sistema devuelve un índice de coincidencia por entrega, de esta forma el profesor puede identificar claramente las copias y centrar su esfuerzos en revisar solamente el contenido de las tareas originales.Detection of plagiarism in students’ homework is a problem that already existed when they were submited in paper form. In recent years, it has increased due to the large amount of information available on the In-ternet, to the ease of use of search engines to find infor-mation, and to the electronic submission (cyberplagiarism). There are even Internet platforms that prepare and offer free homework to be downloaded. This article proposes several strategies to implement a program for personal use to detect one of the currently most widespread types of plagiarism as is copying and pasting fragments of texts from the Internet. These proposals are targeted to detect plagiarism in papers of different type, including reports, slides and web pages. This system returns an matching index for each delivery, thus teachers can clearly identify copies and focus efforts on reviewing only original works