An introduction to the constraints-led approach to learning in outdoor education

Participation in outdoor education is underpinned by a learner's ability to acquire skills in activities such as canoeing, bushwalking and skiing and consequently the outdoor leader is often required to facilitate skill acquisition and motor learning. As such, outdoor leaders might benefit from an appropriate and tested model on how the learner acquires skills in order to design appropriate learning contexts. This paper introduces an approach to skill acquisition based on ecological psychology and dynamical systems theory called the constraints-led approach to skills acquisition. We propose that this student-centred approach is an ideal perspective for the outdoor leader to design effective learning settings. Furthermore, this open style of facilitation is also congruent with learning models that focus on other concepts such as teamwork and leadership

Dynamic mapping strategies for interactive art installations: an embodied combined HCI HRI HHI approach

This paper proposes a theoretical framework for dealing with the paradigm of interactivity in new media art, and how the broad use of the term in different research fields can lead to some misunderstandings. The paper addresses a conceptual view on how we can implement interaction in new media art from an embodied approach that unites views from HCI, HRI and HHI. The focus is on an intuitive mapping of a multitude of sensor data and to extend upon this using the paradigm of (1) finite state machines (FSM) to address dynamic mapping strategies, (2) mediality to address aisthesis and (3) embodiment to address valid mapping strategies originated from natural body movements. The theory put forward is illustrated by a case study

Affordances, context and sociality

Affordances, i.e. the opportunity of actions offered by the environment, are one of the central research topics for the theoretical perspectives that view cognition as emerging from the interaction between the environment and the body. Being at the bridge between perception and action, affordances help to question a dichotomous view of perception and action. While Gibson’s view of affordances is mainly externalist, many contemporary approaches define affordances (and micro-affordances) as the product of long-term visuomotor associations in the brain. These studies have emphasized the fact that affordances are activated automatically, independently from the context and the previous intention to act: for example, affordances related to objects’ size would emerge even if the task does not require focusing on size. This emphasis on the automaticity of affordances has led to overlook their flexibility and contextual-dependency. In this contribution I will outline and discuss recent perspectives and evidence that reveal the flexibility and context-dependency of affordances, clarifying how they are modulated by the physical, cultural and social context. I will focus specifically on social affordances, i.e. on how perception of affordances might be influenced by the presence of multiple actors having different goals

Learning to Act Properly: Predicting and Explaining Affordances from Images

We address the problem of affordance reasoning in diverse scenes that appear in the real world. Affordances relate the agent's actions to their effects when taken on the surrounding objects. In our work, we take the egocentric view of the scene, and aim to reason about action-object affordances that respect both the physical world as well as the social norms imposed by the society. We also aim to teach artificial agents why some actions should not be taken in certain situations, and what would likely happen if these actions would be taken. We collect a new dataset that builds upon ADE20k, referred to as ADE-Affordance, which contains annotations enabling such rich visual reasoning. We propose a model that exploits Graph Neural Networks to propagate contextual information from the scene in order to perform detailed affordance reasoning about each object. Our model is showcased through various ablation studies, pointing to successes and challenges in this complex task

Models of' and 'Models for': On the Relation Between Mechanistic Models and Experimental Strategies in Molecular Biology

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this contribution, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and they are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ suggest new types of material manipulations and they are important not because of their explanatory force, but because of the interventionist strategies they afford. This is a distinction between aspects of the same model; in molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analyzing the discovery and characterization of restriction-modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in a cognitive disposition of the modeler towards the model. A modeler will look at a model as a ‘model of’ if he/she is interested in its explanatory force, or as a ‘model for’ if the interest is in the material manipulations it can possibly afford

Models of' and 'Models for': On the Relation Between Mechanistic Models and Experimental Strategies in Molecular Biology

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this contribution, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and they are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ suggest new types of material manipulations and they are important not because of their explanatory force, but because of the interventionist strategies they suggest. This is a distinction between aspects of the same model; in molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analyzing the discovery and characterization of restriction-modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. In particular, I claim that the evaluation and development of models as either ‘models of’ or ‘models for’ is grounded in different cognitive dispositions, which prescribe different virtues for models

Models of' and 'Models for': On the Relation Between Mechanistic Models and Experimental Strategies in Molecular Biology

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this contribution, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and they are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ suggest new types of material manipulations and they are important not because of their explanatory force, but because of the interventionist strategies they afford. This is a distinction between aspects of the same model; in molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analyzing the discovery and characterization of restriction-modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in a cognitive disposition of the modeler towards the model. A modeler will look at a model as a ‘model of’ if he/she is interested in its explanatory force, or as a ‘model for’ if the interest is in the material manipulations it can possibly afford

Models of' and 'Models for': On the Relation Between Mechanistic Models and Experimental Strategies in Molecular Biology

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this contribution, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and they are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ suggest new types of material manipulations and they are important not because of their explanatory force, but because of the interventionist strategies they suggest. This is a distinction between aspects of the same model; in molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analyzing the discovery and characterization of restriction-modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. In particular, I claim that the evaluation and development of models as either ‘models of’ or ‘models for’ is grounded in different cognitive dispositions, which prescribe different virtues for models

Leveling transparency via situated intermediary learning objectives (SILOs)

When designers set out to create a mathematics learning activity, they have a fair sense of its objectives: students will understand a concept and master relevant procedural skills. In reform-oriented activities, students first engage in concrete situations, wherein they achieve situated, intermediary learning objectives (SILOs), and only then they rearticulate their solutions formally. We define SILOs as heuristics learners devise to accommodate contingencies in an evolving problem space, e.g., monitoring and repairing manipulable structures so that they model with fidelity a source situation. Students achieve SILOs through problem-solving with media, instructors orient toward SILOs via discursive solicitation, and designers articulate SILOs via analyzing implementation data. We describe the emergence of three SILOs in developing the activity Giant Steps for Algebra. Whereas the notion of SILOs emerged spontaneously as a framework to organize a system of practice, i.e. our collaborative design, it aligns with phenomenological theory of knowledge as instrumented action