Search results for "learning."
showing 10 items of 6527 documents
Different mechanisms underlie implicit visual statistical learning in honey bees and humans
2020
International audience; The ability of developing complex internal representations of the environment is considered a crucial antecedent to the emergence of humans’ higher cognitive functions. Yet it is an open question whether there is any fundamental difference in how humans and other good visual learner species naturally encode aspects of novel visual scenes. Using the same modified visual statistical learning paradigm and multielement stimuli, we investigated how human adults and honey bees ( Apis mellifera ) encode spontaneously, without dedicated training, various statistical properties of novel visual scenes. We found that, similarly to humans, honey bees automatically develop a comp…
A Musical Pattern Discovery System Founded on a Modeling of Listening Strategies
2004
Music is a domain of expression that conveys a paramount degree of complexity. The musical surface, composed of a multitude of notes, results from the elaboration of numerous structures of different types and sizes. The composer constructs this structural complexity in a more or less explicit way. The listener, faced by such a complex phenomenon, is able to reconstruct only a limited part of it, mostly in a non-explicit way. One particular aim of music analysis is to objectify such complexity, thus offering to the listener a tool for enriching the appreciation of music (Lartillot and SaintJames, 2004). The trouble is, traditional musical analysis, although offering a valuable understanding …
Depression Assessment by Fusing High and Low Level Features from Audio, Video, and Text
2016
International audience; Depression is a major cause of disability world-wide. The present paper reports on the results of our participation to the depression sub-challenge of the sixth Audio/Visual Emotion Challenge (AVEC 2016), which was designed to compare feature modalities ( audio, visual, interview transcript-based) in gender-based and gender-independent modes using a variety of classification algorithms. In our approach, both high and low level features were assessed in each modality. Audio features were extracted from the low-level descriptors provided by the challenge organizers. Several visual features were extracted and assessed including dynamic characteristics of facial elements…
Mediated learning materials: visibility checks in telepresence robot mediated classroom interaction
2021
Videoconferencing is increasingly used in education as a way to support distance learning. This article contributes to the emerging interactional literature on video-mediated educational interaction by exploring how a telepresence robot is used to facilitate remote participation in university-level foreign language teaching. A telepresence robot differs from commonly used videoconferencing set-ups in that it allows mobility and remote camera control. A remote student can thus move a classroom-based robot from a distance in order to shift attention between people, objects and environmental structures during classroom activities. Using multimodal conversation analysis, we focus on how partici…
Exploring the Effect of Teaching Methods on Students’ Learning of School Informatics
2015
School informatics is a relatively new subject in comparison to mathematics and science. As a result, there is much less research on the area of informatics didactics. Likewise, there is lack of theoretical grounding of the field and associated teaching methods and learning processes. The lack of research in the field of school informatics makes it difficult to identify which methods are effective to teach the subject. In addition, despite the emphasis on a set of well-defined topics, the informatics curriculum makes few suggestions as to which didactical skills teachers need to acquire in order to teach these topics. In fact, school informatics education is still in its infancy. It lacks t…
Predicting perceived visual complexity of abstract patterns using computational measures: The influence of mirror symmetry on complexity perception
2017
Visual complexity is relevant for many areas ranging from improving usability of technical displays or websites up to understanding aesthetic experiences. Therefore, many attempts have been made to relate objective properties of images to perceived complexity in artworks and other images. It has been argued that visual complexity is a multidimensional construct mainly consisting of two dimensions: A quantitative dimension that increases complexity through number of elements, and a structural dimension representing order negatively related to complexity. The objective of this work is to study human perception of visual complexity utilizing two large independent sets of abstract patterns. A w…
Assessing 4th Grade Students’ Computational Thinking through Scratch Programming Projects
2020
Computational thinking (CT) has been introduced in primary schools worldwide. However, rich classroom-based evidence and research on how to assess and support students’ CT through programming are particularly scarce. This empirical study investigates 4th grade students’ (N = 57) CT in a comparatively comprehensive and fine-grained manner by assessing their Scratch projects (N = 325) with a framework that was revised from previous studies to aim towards enhancing CT. The results demonstrate in detail the various coding patterns and code constructs the students programmed in assorted projects throughout a programming course and the extent to which they had conceptual encounters with CT. Notab…
Combining Biophysical Modeling and Machine Learning to Predict Location of Atrial Ectopic Triggers
2018
The search for focal ectopic activity in the atria triggered from non-standard regions can be time consuming. The use of body surface potential maps to plan the intervention can be helpful, but require an advance processing of the data, that usually involves to solve an ill-posed inverse problem. In addition, changes in maps due to pathological substrate such as fibrosis might affect the expected electrical patterns. In this work, we use a machine learning approach to relate ectopic focus activity in different atrial regions with body surface potential maps, and consider the effects of fibrosis in various densities and distributions. Results show that as fibrosis increases over 15% the syst…
Class Noise and Supervised Learning in Medical Domains: The Effect of Feature Extraction
2006
Inductive learning systems have been successfully applied in a number of medical domains. It is generally accepted that the highest accuracy results that an inductive learning system can achieve depend on the quality of data and on the appropriate selection of a learning algorithm for the data. In this paper we analyze the effect of class noise on supervised learning in medical domains. We review the related work on learning from noisy data and propose to use feature extraction as a pre-processing step to diminish the effect of class noise on the learning process. Our experiments with 8 medical datasets show that feature extraction indeed helps to deal with class noise. It clearly results i…
Estimation and visualization of confusability matrices from adaptive measurement data
2010
Abstract We present a simple but effective method based on Luce’s choice axiom [Luce, R.D. (1959). Individual choice behavior: A theoretical analysis. New York: John Wiley & Sons] for consistent estimation of the pairwise confusabilities of items in a multiple-choice recognition task with arbitrarily chosen choice-sets. The method combines the exact (non-asymptotic) Bayesian way of assessing uncertainty with the unbiasedness emphasized in the classical frequentist approach. We apply the method to data collected using an adaptive computer game designed for prevention of reading disability. A player’s estimated confusability of phonemes (or more accurately, phoneme–grapheme connections) and l…