The good and the bad: Acquisition of likes and dislikes in affective learning

Affective learning, the acquisition of likes and dislikes, was investigated in two experiments using verbal ratings and affective priming as indices of affective change. In both experiments, neutral geometric shapes were paired with pleasant or unpleasant pictures in a picture-picture conditioning procedure to acquire positive and negative valence. Experiment 1 found the acquisition of positive valence; however, this valence change was lost after extinction training. Experiment 2 used more salient pictures as unconditioned stimuli. Positive and negative valence was acquired during paired presentations and retained across extinction training. The results of Experiment 2 are consistent with dual process accounts, which claim that evaluative conditioning is distinct from Pavlovian conditioning because it is resistant to extinction.

Implicit learning is not subject to blocking

Explicit (aware) learning has been shown to evidence certain characteristics, such as extinction, blocking, occasion setting, and reliance on context. These characteristics have not been assessed in implicit (unaware) learning. The current study investigated whether implicit learning is subject to blocking. Participants completed a cued reaction time task, where they watched rapid presentations of a random sequence of 8 pairs of shapes, and responded to two target shapes. One target was always preceded by a cue. The experimental group completed a pretraining phase where half the cue, one shape, was followed by the target. Both experimental and control groups completed a training phase where both elements of the cue, two shapes, were followed by the target. Both aware and unaware participants evidenced learning, whereby responding was faster for cued than uncued targets. Aware participants in the experimental group responded faster to targets preceded by the pretrained element than by the other element of the cue. Control and unaware experimental participants were faster to respond to targets preceded by either element of the cue. As blocking was only evident in aware participants, but implicit learning was observed in all participants, it is concluded that implicit learning is not subject to blocking.

Heritage language loss and the implications for ethnic identity maintenance over time

Language has been seen as a central pillar to ethnic identity. When the possibility of heritage language loss becomes imminent, therefore, concern turns towards the consequences for feelings of ethnic group membership. Heritage language researchers have indicated that the heritage language is so strongly associated with the individual’s cultural background that heritage language loss could have negative implications for the sense of identity to the ethnic group. This study investigates the relationship between language and ethnic identity over time among Gaelic learners in Nova Scotia. In order to identify the specific processes of heritage language use, the Gaelic learners are compared to French (second language), learners living in the same English-speaking milieu. Path analyses reveal that, only among Gaelic learners, there is an initial separation of language and ethnic identity, but that, over time, ethnic identity is a direct outcome of language use. The results support Edwards’ (1985), contention, at least in the case of heritage languages, that language and identity are not always strongly linked. It is suggested that this may be especially true in contexts where there is little opportunity for contact with members of the heritage language group.

User-centred ontology learning for knowledge management

Automatic ontology building is a vital issue in many fields where they are currently built manually. This paper presents a user-centred methodology for ontology construction based on the use of Machine Learning and Natural Language Processing. In our approach, the user selects a corpus of texts and sketches a preliminary ontology (or selects an existing one) for a domain with a preliminary vocabulary associated to the elements in the ontology (lexicalisations). Examples of sentences involving such lexicalisation (e.g. ISA relation) in the corpus are automatically retrieved by the system. Retrieved examples are validated by the user and used by an adaptive Information Extraction system to generate patterns that discover other lexicalisations of the same objects in the ontology, possibly identifying new concepts or relations. New instances are added to the existing ontology or used to tune it. This process is repeated until a satisfactory ontology is obtained. The methodology largely automates the ontology construction process and the output is an ontology with an associated trained leaner to be used for further ontology modifications.

Dynamic iterative ontology learning

The fundamental failure of current approaches to ontology learning is to view it as single pipeline with one or more specific inputs and a single static output. In this paper, we present a novel approach to ontology learning which takes an iterative view of knowledge acquisition for ontologies. Our approach is founded on three open-ended resources: a set of texts, a set of learning patterns and a set of ontological triples, and the system seeks to maintain these in equilibrium. As events occur which disturb this equilibrium, actions are triggered to re-establish a balance between the resources. We present a gold standard based evaluation of the final output of the system, the intermediate output showing the iterative process and a comparison of performance using different seed input. The results are comparable to existing performance in the literature.

Ontologies, taxonomies, thesauri:learning from texts

The use of ontologies as representations of knowledge is widespread but their construction, until recently, has been entirely manual. We argue in this paper for the use of text corpora and automated natural language processing methods for the construction of ontologies. We delineate the challenges and present criteria for the selection of appropriate methods. We distinguish three ma jor steps in ontology building: associating terms, constructing hierarchies and labelling relations. A number of methods are presented for these purposes but we conclude that the issue of data-sparsity still is a ma jor challenge. We argue for the use of resources external tot he domain specific corpus.

An incremental tri-partite approach to ontology learning

In this paper we present a new approach to ontology learning. Its basis lies in a dynamic and iterative view of knowledge acquisition for ontologies. The Abraxas approach is founded on three resources, a set of texts, a set of learning patterns and a set of ontological triples, each of which must remain in equilibrium. As events occur which disturb this equilibrium various actions are triggered to re-establish a balance between the resources. Such events include acquisition of a further text from external resources such as the Web or the addition of ontological triples to the ontology. We develop the concept of a knowledge gap between the coverage of an ontology and the corpus of texts as a measure triggering actions. We present an overview of the algorithm and its functionalities.

Investigating EFL teacher beliefs about teaching and learning

This article reports on research into the beliefs of a group of teachers working in the field of TESOL, specifically teachers of English as a Foreign Language (EFL). In particular, the aim was to see if it is possible to identify a coherent system of beliefs about teaching and learning that may account for different approaches to teaching.

A visual interactive modelling system as a learning tool

This paper presents a case study of the use of a visual interactive modelling system to investigate issues involved in the management of a hospital ward. Visual Interactive Modelling systems are seen to offer the learner the opportunity to explore operational management issues from a varied perspective and to provide an interactive system in which the learner receives feedback on the consequences of their actions. However to maximise the potential learning experience for a student requires the recognition that they require task structure which helps them to understand the concepts involved. These factors can be incorporated into the visual interactive model by providing an interface customised to guide the student through the experimentation. Recent developments of VIM systems in terms of their connectivity with the programming language Visual Basic facilitates this customisation.