Learner autonomy : the first language/ second language : some reflections on the nature and role of metalinguistic knowledge

Learner autonomy is classically defined as "the ability to take charge of one's learning" (Holec 1981:3). Such an ability presupposes a positive attitude towards the process, content and goals of learning, and is sustained and strengthened by a developing capacity for "detachment, critical reflection, decision-making, and independent action" (little 1991:4). The freedom that characterizes the autonomous learner is not absolute, but conditional and constrained. Learning, whether developmental/ experiential or formal, is always embedded in an interactive, social process (self- instruction entails an internalization of this process, so that our capacity for learning on our own develops out of our experience of learning in interaction with others; cf. Uttle 1991:5). This explains the paradox that learner autonomy can be fully understood as a theoretical construct and effectively pursued as a pedagogical goal only when we take full account of the social context in which learning takes place. The argument in favour of fostering learner autonomy has been conducted in both social and psychological terms. In adult education, for example, there has been a tendency to stress "the need to develop the individual's freedom by developing those abilities which will enable him to act more responsibly in running the affairs of the society in which he lives" (Holec 1981:1.). The link between educational purpose and political ideal could scarcely be plainer. Other explorations of the theory and practice of learner autonomy, by contrast, have focussed on the psychological dimension of learning, emphasizing that we can only ever learn on the basis of what we already know, and that no two individuals have exactly the same store of knowledge.peer-reviewe

The attitudes and behaviour of adolescent road users : an application of the theory of planned behaviour

The Theory of Planned Behaviour (TPB) was used as a framework to study the attitudes of adolescent road users towards four target behaviours: (1) cycle helmet use, (2) using nearby crossings, (3) crossing from between parked cars, and (4) challenging traffic. Four questionnaires, one for each of the behaviours, were designed based on pilot work. Each questionnaire contained items to measure the TPB variables, self-reported behaviour, and general exposure and demographic characteristics (e.g. age and gender). A total of 2,457 children aged 11-16 completed the questionnaires; 564 respondents completed the 'cycle helmet use' questionnaire; 657 respondents completed the 'using nearby crossings' questionnaire; 619 respondents completed the 'crossing from between parked cars' questionnaire; and 617 completed the 'challenging traffic' questionnaire. Multivariate analyses were conducted for each of the behaviours to explore how adolescents' attitudes, subjective norms, perceived control, behavioural intentions and self-reported behaviour differed as a function of demographic variables. Correlation and multiple regression analyses were then conducted to test the relationships in the TPB and to identify beliefs underpinning adolescents' attitudes that could be targeted in road safety interventions. This report describes all aspects of the study and discusses the theoretical and practical implications

Aerial social force model: a new framework to accompany people using autonomous flying robots

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.We proposed a novel Aerial Social Force Model (ASFM) that allows autonomous flying robots to accompany humans in urban environments in a safe and comfortable manner. To date, we are not aware of other state-of-the-art method that accomplish this task. The proposed approach is a 3D version of the Social Force Model (SFM) for the field of aerial robots which includes an interactive human-robot navigation scheme capable of predicting human motions and intentions so as to safely accompany them to their final destination. ASFM also introduces a new metric to fine-tune the parameters of the force model, and to evaluate the performance of the aerial robot companion based on comfort and distance between the robot and humans. The presented approach is extensively validated in diverse simulations and real experiments, and compared against other similar works in the literature. ASFM attains remarkable results and shows that it is a valuable framework for social robotics applications, such as guiding people or human-robot interaction.Peer ReviewedPostprint (author's final draft

On The Incorporation Of The Personality Factors Into Crowd Simulation

Recently, a considerable amount of research has been performed on simulating the collective behavior of pedestrians in the street or people finding their way inside a building or a room. Comprehensive reviews of the state of the art can be found in Schreckenberg and Deo (2002) and Batty, M., DeSyllas, J. and Duxbury, E. (2003). In all these simulation studies, one area that is lacking is accounting for the effects of human personalities on the outcome. As a result, there is a growing emphasis on researching the effects of human personalities and adding the results to the simulations to make them more realistic. This research investigated the possibility of incorporating personality factors into the crowd simulation model. The first part of this study explored the extraction of quantitative crowd motion from videos and developed a method to compare real video with the simulation output video. Several open source programs were examined and modified to obtain optical flow measurements from real videos captured at sporting events. Optical flow measurements provide information such as crowd density, average velocity with which individuals move in the crowd, as well as other parameters. These quantifiable optical flow calculations provided a strong method for comparing simulation results with those obtained from video footage captured in real life situations. The second part of the research focused on the incorporation of the personality factors into the crowd simulation. Existing crowd models such as HelbingU-Molnar-Farkas-Vicsek (HMFV) do not take individual personality factors into account. The most common approach employed by psychologists for studying personality traits is the Big Five factors or dimensions of personality (NEO: Neuroticism, Extroversion, Openness, Agreeableness and Conscientiousness). In this research forces related to the personality factors were incorporated into the crowd simulation models. The NEO-based forces were incorporated into an existing HMFV simulated implemented in the MASON simulation framework. The simulation results were validated using the quantification procedures developed in the first phase. This research reports on a major expansion of a simulation of pedestrian motion based on the model (HMFV) by Helbing, D., I. J. Farkas, P. Molnár, and T. Vicsek (2002). Example of actual behavior such as a crowd exiting church after service were simulated using NEO-based forces and show a striking resemblance to actual behavior as rated by behavior scientists

Robot companion: a social-force based approach with human awareness-navigation in crowded environments

Robots accompanying humans is one of the core capacities every service robot deployed in urban settings should have. We present a novel robot companion approach based on the so-called Social Force Model (SFM). A new model of robot-person interaction is obtained using the SFM which is suited for our robots Tibi and Dabo. Additionally, we propose an interactive scheme for robot’s human-awareness navigation using the SFM and prediction information. Moreover, we present a new metric to evaluate the robot companion performance based on vital spaces and comfortableness criteria. Also, a multimodal human feedback is proposed to enhance the behavior of the system. The validation of the model is accomplished throughout an extensive set of simulations and real-life experiments.Peer ReviewedPostprint (author’s final draft

Modelling Social Interaction between Humans and Service Robots in Large Public Spaces

With the advent of service robots in public places (e.g., in airports and shopping malls), understanding socio-psychological interactions between humans and robots is of paramount importance. On the one hand, traditional robotic navigation systems consider humans and robots as moving obstacles and focus on the problem of real-time collision avoidance in Human-Robot Interaction (HRI) using mathematical models. On the other hand, the behavior of a robot has been determined with respect to a human. Parameters for human-human interaction have been assumed and applied to interactions involving robots. One major limitation is the lack of sufficient data for calibration and validation procedures. This paper models, calibrates and validates the socio-psychological interaction of the human in HRIs among crowds. The mathematical model is an extension of the Social Force Model for crowd modelling. The proposed model is calibrated and validated using open source datasets (including uninstructed human trajectories) from the Asia and Pacific Trade Center shopping mall in Osaka (Japan).In summary, the results of the calibration and validation on the multiple HRIs encountered in the datasets show that humans react to a service robot to a higher extend within a larger distance compared to the interaction range towards another human. This microscopic model, calibration and validation framework can be used to simulate HRI between service robots and humans, predict humans' behavior, conduct comparative studies, and gain insights into safe and comfortable human-robot relationships from the human's perspective