This paper describes first results in the field of the development of an efficient survey to evaluate quality of e-learning activities. The research intends to evaluate not only quality in use but also quality in learning. It represents an attempt to produce and organize survey questions that allow evaluating not only the easiness in managing a learning product but also its usefulness and learn...

A number of natural models for learning in the limit is introduced to deal with the situation when a learner is required to provide a grammar covering the input even if only a part of the target language is available. Examples of language families are exhibited that are learnable in one model and not learnable in another one. Some characterizations for learnability of algorithmically enumerable...

Lexicalized Well-Founded Grammar (LWFG) is a recently developed syntacticsemantic grammar formalism for deep language understanding, which balances expressiveness with provable learnability results. The learnability result for LWFGs assumes that the semantic composition constraints are learnable. In this paper, we show what are the properties and principles the semantic representation and gramm...

Tesar (2013) develops the notion of output-drivenness, provides guarantees that OT grammars satisfy it, and demonstrates its learnability implications. This squib discusses the extension of Tesar’s theory to a representational framework with partial phonological features. It considers a hierarchy of notions of output-drivenness of increasing strength which can be defined within this extended fr...

The notion of learnability plays a central role in learning theory and continues to be an active topic of study. As noted in the last lecture, it is related to the notion of statistical consistency, with origins in theoretical computer science. Over the next few lectures, we will study various models of learnability related to the probably approximately correct (PAC) learning model introduced i...

In this work we study the learnability of stochastic processes with respect to the conditional risk, i.e. the existence of a learning algorithm that improves its next-step performance with the amount of observed data. We introduce a notion of pairwise discrepancy between conditional distributions at different times steps and show how certain properties of these discrepancies can be used to cons...

A striking cross-linguistic generalisation about the semantics of determiners is that they never express nonconservative relations. To account for this one might hypothesise that the mechanisms underlying human language acquisition are not compatible with nonconservative determiner meanings. We stress that the crosslinguistic generalisation alone should not be taken as decisive evidence for thi...

This builds on previous work in which we have developed diagramming principles based on theories of structural object perception. We call these geon diagrams. We have previously shown that such diagrams are easy to remember and to analyze. To evaluate our hypothesis that geon diagrams should also be easy to understand we carried out an empirical study to evaluate the learnability of geon diagra...

Previous studies on usability of graphical design-widgets, like menus and buttons, proposed the use of speech and non-speech (earcons and auditory icons) for solving their usability problems. In this paper we investigate speech as an input metaphor to enhance learnability, or the ability to use a system with no prior knowledge, in order to design interfaces using a multimodal interface design t...