With the advent of the distinctive characterization of academic languagein the past thirty years, there has been atremendous move in the ESL/EFL world towardsformulatinginstructional techniques compatible with the very nature of these skills. As a part of this effort, this studyinvestigated the role of content and language integrated learning (CLIL) approach in achieving these ends. The study e...

Computational methods for discovering the preferences of individuals are useful in many applications. In this paper, we propose a method for learning valued preference structures, using a natural extension of so-called pairwise classification. A valued preference structure can then be used in order to induce a ranking, that is a linear ordering of a given set of alternatives. This step is reali...

Traditionally, the principal goal of educational assessments is to evaluate students’ academic achievement or proficiency in comparison to their peers or against promulgated standards. Both classical test theory (CTT) and item response theory (IRT) modeling frameworks provide measurement in the form of a summative estimate of the outcome variable. In recent years, understanding and exploring th...

We propose a temporal segmentation and procedure learning model for long untrimmed and unconstrained videos, e.g., videos from YouTube. The proposed model segments a video into segments that constitute a procedure and learns the underlying temporal dependency among the procedure segments. The output procedure segments can be applied for other tasks, such as video description generation or activ...

In this paper we present an investigation into whether and how decision procedures can be learnt and built automatically. Our approach consists of two stages. First, a refined brute-force search procedure applies exhaustively a set of given elementary methods to try to solve a corpus of conjectures generated by a stochastic context-free grammar. The successful proof traces are saved. In the sec...

This paper describes a method which, under certain circumstances, allows to automatically learn or adjust similarity measures. For this, ideas of connectionist learning procedures, in particular those related to Hebbian learning, are combined with a Case-Based Reasoning engine.

Acquiring new skills is an ability which would be very useful for a robot to possess. One conceivable method whereby a robot could learn new skills is if a teacher with expert knowledge of those skills could demonstrate these skills to the learning robot, in a variety of different settings. What is required would be that the robot does not merely learn to mimic the teacher exactly, as the teach...