Diseño y desarrollo de un sistema basado en Learning Analytics para evaluar la competencia de trabajo en equipo.Design and development of a Learning Analytics System to evaluate group work competence

La adquisición de la competencia grupal es algo básico en la docencia universitaria. Esta tarea va a suponer evaluar diferentes factores en un número elevado de alumnos, lo que puede supone gran complejidad y un esfuerzo elevado. De cara a evitar este esfuerzo se puede pensar en emplear los registros de la interacción de los usuarios almacenados en las plataformas de aprendizaje. Para ello el presente trabajo se basa en el desarrollo de un sistema de Learning Analytics que es utilizado como herramienta para analizar las evidencias individuales de los distintos miembros de un equipo de trabajo. El trabajo desarrolla un modelo teórico apoyado en la herramienta, que permite relacionar las evidencias observadas de forma empírica para cada alumno, con indicadores obtenidos tanto de la acción individual como cooperativo de los miembros de un equipo realizadas a través de los foros de trabajo. Abstract — The development of the group work competence is something basic in university teaching. It should be evaluated, but this means to analyze different issues about the participation of a high number of students which is very complex and implies a lot of effort. In order to facilitate this evaluation it is possible to analyze the logs of students’ interaction in Learning Management Systems. The present work describes the development of a Learning Analytics system that analyzes the interaction of each of the members of working group. This tool is supported by a theoretical model, which allows establishing links between the empirical evidences of each student and the indicators of their action in working forums.

Formation of temporal-feature maps by axonal propagation of synaptic learning

Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.

Recruitment and replacement of hippocampal neurons in young and adult chickadees: an addition to the theory of hippocampal learning.

We used [3H]thymidine to document the birth of neurons and their recruitment into the hippocampal complex (HC) of juvenile (4.5 months old) and adult blackcapped chickadees (Parus atricapillus) living in their natural surroundings. Birds received a single dose of [3H]thymidine in August and were recaptured and killed 6 weeks later, in early October. All brains were stained with Cresyl violet, a Nissl stain. The boundaries of the HC were defined by reference to the ventricular wall, the brain surface, or differences in neuronal packing density. The HC of juveniles was as large as or larger than that of adults and packing density of HC neurons was 31% higher in juveniles than in adults. Almost all of the 3H-labeled HC neurons were found in a 350-m-wide layer of tissue adjacent to the lateral ventricle. Within this layer the fraction of 3H-labeled neurons was 50% higher in juveniles than in adults. We conclude that the HC of juvenile chickadees recruits more neurons and has more neurons than that of adults. We speculate that juveniles encounter greater environmental novelty than adults and that the greater number of HC neurons found in juveniles allows them to learn more than adults. At a more general level, we suggest that (i) long-term learning alters HC neurons irreversibly; (ii) sustained hippocampal learning requires the periodic replacement of HC neurons; (iii) memories coded by hippocampal neurons are transferred elsewhere before the neurons are replaced.

Distance Education and the Evolution of Online Learning in the United States

Online education is no longer a trend, rather it is mainstream. In the Fall of 2012, 69.1% of chief academic leaders indicated online learning was critical to their long-term strategy and of the 20.6 million students enrolled in higher education, 6.7 million were enrolled in an online course (Allen & Seaman, 2013; United States Department of Education, 2013). The advent of online education and its rapid growth has forced academic institutions and faculty to question the current styles and techniques for teaching and learning. As developments in educational technology continue to advance, the ways in which we deliver and receive knowledge in both the traditional and online classrooms will further evolve. It is necessary to investigate and understand the progression and advancements in educational technology and the variety of methods used to deliver knowledge to improve the quality of education we provide today and motivate, inspire, and educate the students of the 21st century. This paper explores the atioevolution of distance education beginning with correspondence and the use of parcel post, to radio, then to television, and finally to online education.

The aid of machine learning to overcome the classification of real health discharge reports written in Spanish

Hospitals attached to the Spanish Ministry of Health are currently using the International Classification of Diseases 9 Clinical Modification (ICD9-CM) to classify health discharge records. Nowadays, this work is manually done by experts. This paper tackles the automatic classification of real Discharge Records in Spanish following the ICD9-CM standard. The challenge is that the Discharge Records are written in spontaneous language. We explore several machine learning techniques to deal with the classification problem. Random Forest resulted in the most competitive one, achieving an F-measure of 0.876.

Certification of payment from Oliver Prescott, 1747 September 23

Handwritten certificate of payment for a new red and plaid gown purchased by Harvard sophomore Oliver Prescott in 1747. The certificate is witnessed by upperclassmen Artemas Ward, Jacob Cushing, and Timothy Pond.