The Effectiveness of a Blended Strategy based on Concept Mapping and Text Structure in Enhancing EFL Learners’ Writing Performance

The current study investigated the effect of a blended strategy based on concept mapping and text structure on EFL learners’ writing performance. An intact group (N = 42) of seventh level English majors at Thadiq Sciences and Humanities College, Shaqra University, KSA participated in the study in the first semester of the academic year 2016-2017. They were assigned to an experimental group and a control group, each consisting of 21 students. A writing pretest was administered to the two groups and scored by two raters using the Weir’s TEEP attribute writing scale (1990). An independent samples t-test performed on the pretest mean scores of the two groups showed that they were homogenous prior to the experiment. Concept mapping and text formatting (the proposed blended strategy) were integrated in the Advanced Writing course (Eng 413) for experimental group students. The control group received conventional instruction that did not include the proposed strategy. Independent and paired samples t-tests revealed that the experimental group outperformed the control group in all the sub-scales of Weir’s TEEP attribute writing scale, hence supporting the positive effect of concept mapping and text formatting on EFL learners’ writing performance. Pedagogical implications are offered

Incremental sentence processing is guided by a preference for agents: EEG evidence from Basque

Comprehenders across languages tend to interpret role-ambiguous arguments as the subject or the agent of a sentence during parsing. However, the evidence for such a subject/agent preference rests on the comprehension of transitive, active-voice sentences where agents/subjects canonically precede patients/objects. The evidence is thus potentially confounded by the canonical order of arguments. Transitive sentence stimuli additionally conflate the semantic agent role and the syntactic subject function. We resolve these two confounds in an experiment on the comprehension of intransitive sentences in Basque. When exposed to sentence-initial role-ambiguous arguments, comprehenders preferentially interpreted these as agents and had to revise their interpretation when the verb disambiguated to patient-initial readings. The revision was reflected in an N400 component in ERPs and a decrease in power in the alpha and lower beta bands. This finding suggests that sentence processing is guided by a top-down heuristic to interpret ambiguous arguments as agents, independently of word order and independently of transitivity

Multimodal Comprehension of Language and Graphics: Graphs with and without annotations

An experimental investigation into interaction between language and information graphics in multimodal documents served as the basis for this study. More specifically, our purpose was to investigate the role of linguistic annotations in graph-text documents. Participants were presented with three newspaper articles in the following conditions: one text-only, one text plus non-annotated graph, and one text plus annotated graph. Results of the experiment showed that, on one hand, annotations play a bridging role for integration of information contributed by different representational modalities. On the other hand, linguistic annotations have negative effects on recall, possibly due to attention divided by the different parts of a document

Selected Information Management Resources for Implementing New Knowledge Environments: An Annotated Bibliography

This annotated bibliography reviews scholarly work in the area of building and analyzing digital document collections with the aim of establishing a baseline of knowledge for work in the field of digital humanities. The bibliography is organized around three main topics: data stores, text corpora, and analytical facilitators. Each of these is then further divided into sub-topics to provide a broad snapshot of modern information management techniques for building and analyzing digital documents collections

Immersive moodboards, a comparative study of industrial design inspiration material

A recent trend in our industrial culture has been the gradual emergence of digital tools in various fields of human activity. They aim to reduce development time, cost, or to insure a low error, high quality process. Many fields have been improved thanks to this new computerized approach. This paper is centered on how industrial design could be assisted by virtual reality tools. More specifically it presents a new vision of early design methodologies through immersive technologies. It also presents the results of an experimentation aiming to compare traditional moodboards with a newly developed immersive moodboard. When analyzing and comparing the relationship of the industrial designer to a traditional and an immersive moodboard, our result highlights the fact that immerging the industrial designer in an immersive moodboard induces a high emotional activity without radically modifying the meaning of the represented trend. The moodboard data spatialization stimulates and engages the designer into interacting with the immersive moodboard. The virtual reality system provides the illusion of a potential reality, which can be used by the designer as a reflection basis for his work. We believe that delivering this immersive experience during the early design process will help the industrial designer make style related decisions.Projet CARNO

Grounding the Lexical Semantics of Verbs in Visual Perception using Force Dynamics and Event Logic

This paper presents an implemented system for recognizing the occurrence of events described by simple spatial-motion verbs in short image sequences. The semantics of these verbs is specified with event-logic expressions that describe changes in the state of force-dynamic relations between the participants of the event. An efficient finite representation is introduced for the infinite sets of intervals that occur when describing liquid and semi-liquid events. Additionally, an efficient procedure using this representation is presented for inferring occurrences of compound events, described with event-logic expressions, from occurrences of primitive events. Using force dynamics and event logic to specify the lexical semantics of events allows the system to be more robust than prior systems based on motion profile

Implementation of a dashboard for security forces data visualization

In the current model of democratic rule of law, security is assumed as a basic right of citizens. Optimal resources allocation and budgetary constraints oblige an increasingly careful strategic management, adapted to demographic reality. The SIM4SECURITY project aims to build a technological solution to support decision making regarding security, based on the development of a GIS model and in the implementation of demographic scenarios. This model will allow policy makers, leaders and forces of command units and services in the planning and rational affectation of resources adjusted to local dynamics in crime prevention and crime fighting. To communicate the SIM4SECURITY results, dashboards containing the various dimensions and perspectives of the information were elaborated and are presented. The obtained outcomes show that dashboards are an important visual tool in the decision-making process by providing meaningful insights regarding security and in the location-allocation of security forces

Inferring Group Processes from Computer-Mediated Affective Text Analysis

Political communications in the form of unstructured text convey rich connotative meaning that can reveal underlying group social processes. Previous research has focused on sentiment analysis at the document level, but we extend this analysis to sub-document levels through a detailed analysis of affective relationships between entities extracted from a document. Instead of pure sentiment analysis, which is just positive or negative, we explore nuances of affective meaning in 22 affect categories. Our affect propagation algorithm automatically calculates and displays extracted affective relationships among entities in graphical form in our prototype (TEAMSTER), starting with seed lists of affect terms. Several useful metrics are defined to infer underlying group processes by aggregating affective relationships discovered in a text. Our approach has been validated with annotated documents from the MPQA corpus, achieving a performance gain of 74% over comparable random guessers

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications