Search

Timeliness of this work is determined by the necessity to improve the educational process, to introduce to students and researchers a methodology of effective processing and systematization of text based content. Taking into consideration the vast bulk of accumulated theoretical and empirical knowledge on the psychology of attention, the timeliness of this work is determined also by the need to reconsider this material, to bring in adequate corrective amendments as well as to refine the taxonomy of attentional characteristics. One of the best methods for handling such problems is the practice of mind mapping (MMing), which is an effective way of presentation, connection and compression of thoughts and information. Our research target is the usage of MMing for the content analysis of psychological texts as exemplified by the educational module «Attention characteristics». Our dominant approach to the investigation into this problem is mind mapping. The results of the research presented in the paper enable us, on one hand, to take a fresh look at the issue of the classification of the attentional characteristics and, on the other hand, to provide students and researchers with an example of correct analysis, synthesis and systematization of abundant textual information flow. The main outcomes of our research are the following: (1) the classification of the attentional characteristics upon the criterion of the number of the objects of attention and its focusing on the different number of the objects of attention, (2) the classification upon the criteria of temporality and static/dynamic character of attention, as well as (3) the classification upon the criterion of the possibility of the voluntary regulation of the attentional characteristics. Practical relevance of the research results presented in the paper, lies (1) in the demonstration of the mind mapping potential for the content-analysis of textual material (as exemplified with the classification of the attentional characteristics), (2) in the introducing of the template, which can help the educator not only make easier the explanation of the topics of the educational module ―Cognitive processes‖ in the course of General psychology, but also provide students with clear instruction as to the material for their selfstudying. [ABSTRACT FROM AUTHOR]

Gesture plays an important role for recognizing lecture activities in video content analysis. In this paper, we propose a real-time gesture detection algorithm by integrating cues from visual, speech and electronic slides. In contrast to the conventional “complete gesture” recognition, we emphasize detection by the prediction from “incomplete gesture”. Specifically, intentional gestures are predicted by the modified hidden Markov model (HMM) which can recognize incomplete gestures before the whole gesture paths are observed. The multimodal correspondence between speech and gesture is exploited to increase the accuracy and responsiveness of gesture detection. In lecture presentation, this algorithm enables the on-the-fly editing of lecture slides by simulating appropriate camera motion to highlight the intention and flow of lecturing. We develop a real-time application, namely simulated smartboard, and demonstrate the feasibility of our prediction algorithm using hand gesture and laser pen with simple setup without involving expensive hardware. [ABSTRACT FROM PUBLISHER]