Every day it is more common to hear around us about the publication of studies, surveys or statistical results about the well-being of people, workers, women in a given country. Indeed, as university professors, our work cannot be independent of the level of well-being of our students. So, in this work, we propose a methodology to asses the students well-being inside a course implementation by what we call the educational well-being index (EWI). We start with a survey that gathers those factors that computing courses’ students at our university –of two different levels and majors– consider most important. Our second step is the evaluation –by a group of teachers– of the presence of those factors in different educational models of implementation of the courses. We use principal component analysis to extract, from the student data, the valuations that they expressed in the survey: the principal component of their own measurements on well-being. We work only with the coefficients of the first dimension of the principal component. The third step is a (subjective) valuation of the topics addressed in the survey when considering a particular educational model. Finally, we gather everything together to obtain a well-being index of an educational model that allows their comparison. Besides the methodology, we present and analyze the values obtained from our case study.

Several recent papers in the literature have addressed the analysis of the cost P_{n,q} of partial match search for a given fixed query q - that has s out of K specified coordinates - in different multidimensional data structures. Indeed, detailed asymptotic estimates for the main term in the expected cost P_{n,q} = E {P_{n,q}} in standard and relaxed K-d trees are known (for any dimension K and any number s of specified coordinates), as well as stronger distributional results on P_{n,q} for standard 2-d trees and 2-dimensional quadtrees. In this work we derive a precise asymptotic estimate for the main order term of P_{n,q} in quadtrees, for any values of K and s, 0 < s < K, under the assumption that the limit of P_{n,q}/n^alpha when n -> infty exists, where alpha is the exponent of n in the expected cost of a random partial match query with s specified coordinates in a random K-dimensional quadtree.

What is the role that a university should play in the spreading of cutting-edge technologies? It is argued here that one possibility is to bring focused cutting-edge technology courses in the standard curriculum. It is contended that such courses have shorter life-spans than conventional subjects and, consequently, their implementation needs to be more dynamic. These claims are backed by discussing the life-cycle of an Android course running biannually from Spring 2010 to Spring 2013 at Universitat Politecnica de Catalunya. The rise phase of this course (which lasted two semesters) was a challenging experience that motivated students and lecturers to play a cooperative and active role in the creation of true working Android applications. The course held stable for two semesters while student motivation began to fall as smart phones increasingly became everyday objects. During these two phases the course was offered as extra curricular in the undergraduate phase. Two added factors were instrumental in the decline (or fall) phase: the availability of on-line information and the fact that the course became a requirement of a master’s curriculum.

In this work we present an in-depth study of randomized relaxed K -d trees. It covers two fundamental aspects: the randomized algorithms that allow to preserve the random properties of relaxed K -d trees and the mathematical analysis of the expected performance of these algorithms. In particular, we describe randomized update algorithms for K -d trees based on the split and join algorithms of Duch et al. [1998]. We carry out an analysis of the expected cost of all these algorithms, using analytic combinatorics techniques. We show that the average cost of split and join is of the form ζ( K ) ⋅ n ϕ( K ) + o ( n ϕ( K ) ), with 1 ≤ ϕ( K ) < 1.561552813, and we give explicit formulæ for both ζ( K ) and ϕ( K ). These results on the average performance of split and join imply that the expected cost of an insertion or a deletion is Θ( n ϕ( K )−1 ) when K > 2 and Θ(log n ) for K = 2.