This paper reviews how usability has been defined in the context of the digital library, what methods have been applied and their applicability, and proposes an evaluation model and a suite of instruments for evaluating usability for academic digital libraries. The model examines effectiveness, efficiency, satisfaction, and learnability. It is found that there exists an interlocking relationshi...

We consider the exact learnability of subclasses of Boolean formulas from membership queries alone. We show how to combine known learning algorithms that use membership and equivalence queries to obtain new learning results only with memberships. In particular we show the exact learnability of read-k monotone formulas, Sat-k O(log n)-CDNF, and O(p log n)-size CDNF from membership queries only.

The conclusions of a three months learnability and usability study of Taligent Application frameworks are presented in terms of a preparatory guide for a novice user. It has been known that learnability of large object-oriented systems poses a serious obstacle to adoption of object-oriented technology. Taligent frameworks face this obstacle in particular. This paper was written to help you plan...

In a simple, forward looking linear stochastic model we investigate the impact of heterogeneity in expectations formation on the speed of convergence of the learning process of agents towards equilibrium. We …nd that even when heterogeneity does not a¤ect learnability in term of its asymptotic outcome, it can still have an important impact on the learnability of an equilibrium in terms of the s...

We consider the following statistical estimation problem: given a family F of real valued functions over some domain X and an i.i.d. sample drawn from an unknown distribution P over X , find h ∈ F such that the expectation EP (h) is probably approximately equal to sup{EP (h) : h ∈ F}. This Expectation Maximization (EMX) problem captures many well studied learning problems; in fact, it is equiva...

For supervised classification problems, it is well known that learnability is equivalent to uniform convergence of the empirical risks and thus to learnability by empirical minimization. Inspired by recent regret bounds for online convex optimization, we study stochastic convex optimization, and uncover a surprisingly different situation in the more general setting: although the stochastic conv...

We apply a complexity theoretic notion of feasible learnability called "polynomial learnability" to the evaluation of grammatical formalisms for linguistic description. We show that a novel, nontrivial constraint on the degree of "locality" of grammars allows not only context free languages but also a rich class of mildly context sensitive languages to be polynomially learnable. We discuss poss...

We propose a mathematical model for learning the high density areas of an un known distribution from unlabeled random points drawn according to this distri bution While this type of a learning task has not been previously addressed in the Computational Learnability literature we believe that this it a rather basic problem that appears in many practical learning scenarios From a statistical theo...

This article concerns assessors’ use of predictions applicants’ ability to learn when assessing admission tests for specialist music teacher education in Sweden. The data consist stimulated-recall interviews with video-recorded as stimuli, and the analyses are based on discourse psychology a focus variations, functions, effects statements about learning opportunities. results highlight several ...