The mediating processes within social learning: women’s food and water security practices in the rural Eastern Cape

The focus of this study was to explore the implicit and explicit mediating processes within the social learning of women’s food and water security practices in the rural Eastern Cape, South Africa. The study was undertaken in response to a growing problem of learning resources being decontextualised and therefore being of little relevance or use to the everyday practices of the people they were developed for. The central thesis of this study is that if the mediating processes that shape practice and learning are understood then these practices and learning can be better supported. One of the main foci of this study therefore is the concept of mediation and the importance of understanding the implicit and explicit mediating processes that shape learning and practice within the context of rainwater harvesting and food gardening practices of rural women. The study interprets these as social learning processes after the work of Lev Vygotsky and post-Vygotskian learning and activity development research, which recognises that all learning is socially mediated. This study also attempts to show that ontological factors also shape social learning processes via structural mediations (which are often also socially structured over time in history). Working within the broad framework of change oriented social learning, education for sustainability and the southern African water and food nexus the study is focused around two central research questions: 1) What are the mediating processes evident in and surrounding the learning of rainwater harvesting in the context of women’s water and food security in rural communities? And 2) How can a question-based learning resource extend the learning practices in this context? Drawing on three sensitising concepts of dialectics, reflexivity and agency, the study worked with Cultural Historical Activity Theory (CHAT), underpinned by critical realism, to reveal how the learning of rainwater and food gardening practitioners is constrained and enabled by mediating processes. The theory of mediation provided a useful theoretical lens with which to examine data generated. A case study approach was used in two sites in the rural Eastern Cape. The first was Cata village in the Amathole district and the second was a peri-urban settlement called Glenconnor in the Cacadu district. Each case study is constituted within a networked activity system. The study also used a narrative inquiry approach in order to bring to life the case studies, activity systems and some of the dynamics of social learning within the study. The methodological tools of document analysis, observations, in-depth interviews and focus group discussions were used to explore the implicit and explicit mediating processes that shape research participants’ rainwater harvesting and food gardening practices and their learning. Inductive, abductive and retroductive modes of inference were used to analyse data in and across case studies. One of the first findings of this study is that learning is embedded in and emergent from context in that it is mediated by implicit and explicit processes within each context. This makes such learning social, in the sense of social used by Vygotsky. The second finding showed that implicit and explicit mediation processes are constantly interacting in a dialectical process whether people are conscious of this interplay or not. This is an important dynamic to understand when trying to bring about societal transformation through education. Understanding the interaction between the implicit and explicit alerts researchers to the sociocultural dynamics inherent within social learning processes and therefore informs how learning resources and educational and development programmes should be designed and implemented. This study contributes to new knowledge in the environmental education field and the water knowledge sector. It makes a theoretical and empirical contribution to the body of knowledge concerned with socially mediated learning and situated learning approaches. The study illustrates how learning is embedded in context and also how learning emerges in relation to context via interactions between implicit and explicit mediation processes, and considers what this means for learning and development in the rural nexus of water and food security practices. This study also contributes to the growing body of post-Vygotskian social learning research in southern Africa that is being developed in the context of cultural historical activity theory as it shows the dialectical relationship that exists between implicit and explicit forms of mediation as these are embedded in, emergent from, and are externally mediated into activity systems in rural community contexts. This study contributes to a second area of knowledge: the water sector. With a background in anthropology which sensitised the researcher to contextual factors and approaching the study through an educational lens, the data has been worked with to surface and present the nuanced mediating processes that shape the learning and knowledge around water issues. This way of working and this focus on the socio-cultural is relatively new in the water sector in South Africa and gains significance in the light of an emergent interest in more complex social studies in the water sector which has traditionally been dominated by natural sciences and engineering. The significance of this study for rural South African women’s lives is that by understanding and taking account of their history, context, struggles and experiences, their learning and practices can be better supported through more relevant learning resources and programmes

Consciosusness in Cognitive Architectures. A Principled Analysis of RCS, Soar and ACT-R

This report analyses the aplicability of the principles of consciousness developed in the ASys project to three of the most relevant cognitive architectures. This is done in relation to their aplicability to build integrated control systems and studying their support for general mechanisms of real-time consciousness.\ud To analyse these architectures the ASys Framework is employed. This is a conceptual framework based on an extension for cognitive autonomous systems of the General Systems Theory (GST).\ud A general qualitative evaluation criteria for cognitive architectures is established based upon: a) requirements for a cognitive architecture, b) the theoretical framework based on the GST and c) core design principles for integrated cognitive conscious control systems

Discovering the Impact of Knowledge in Recommender Systems: A Comparative Study

Recommender systems engage user profiles and appropriate filtering techniques to assist users in finding more relevant information over the large volume of information. User profiles play an important role in the success of recommendation process since they model and represent the actual user needs. However, a comprehensive literature review of recommender systems has demonstrated no concrete study on the role and impact of knowledge in user profiling and filtering approache. In this paper, we review the most prominent recommender systems in the literature and examine the impression of knowledge extracted from different sources. We then come up with this finding that semantic information from the user context has substantial impact on the performance of knowledge based recommender systems. Finally, some new clues for improvement the knowledge-based profiles have been proposed.Comment: 14 pages, 3 tables; International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.3, August 201

NAIS: Neural Attentive Item Similarity Model for Recommendation

Item-to-item collaborative filtering (aka. item-based CF) has been long used for building recommender systems in industrial settings, owing to its interpretability and efficiency in real-time personalization. It builds a user's profile as her historically interacted items, recommending new items that are similar to the user's profile. As such, the key to an item-based CF method is in the estimation of item similarities. Early approaches use statistical measures such as cosine similarity and Pearson coefficient to estimate item similarities, which are less accurate since they lack tailored optimization for the recommendation task. In recent years, several works attempt to learn item similarities from data, by expressing the similarity as an underlying model and estimating model parameters by optimizing a recommendation-aware objective function. While extensive efforts have been made to use shallow linear models for learning item similarities, there has been relatively less work exploring nonlinear neural network models for item-based CF. In this work, we propose a neural network model named Neural Attentive Item Similarity model (NAIS) for item-based CF. The key to our design of NAIS is an attention network, which is capable of distinguishing which historical items in a user profile are more important for a prediction. Compared to the state-of-the-art item-based CF method Factored Item Similarity Model (FISM), our NAIS has stronger representation power with only a few additional parameters brought by the attention network. Extensive experiments on two public benchmarks demonstrate the effectiveness of NAIS. This work is the first attempt that designs neural network models for item-based CF, opening up new research possibilities for future developments of neural recommender systems

Implicit and explicit learning in ACT-R

A useful way to explain the notions of implicit and explicit learning in ACT-R is to define implicit learning as learning by ACT-R's learning mechanisms, and explicit learning as the results of learning goals. This idea complies with the usual notion of implicit learning as unconscious and always active and explicit learning as intentional and conscious. Two models will be discussed to illustrate this point. First a model of a classical implicit memory task, the SUGARFACTORY scenario by Berry & Broadbent (1984) will be discussed, to show how ACT-R can model implicit learning. The second model is of the so-called Fincham task (Anderson & Fincham, 1994), and exhibits both implicit and explicit learning

Interactive Spaces. Models and Algorithms for Reality-based Music Applications

Reality-based interfaces have the property of linking the user's physical space with the computer digital content, bringing in intuition, plasticity and expressiveness. Moreover, applications designed upon motion and gesture tracking technologies involve a lot of psychological features, like space cognition and implicit knowledge. All these elements are the background of three presented music applications, employing the characteristics of three different interactive spaces: a user centered three dimensional space, a floor bi-dimensional camera space, and a small sensor centered three dimensional space. The basic idea is to deploy the application's spatial properties in order to convey some musical knowledge, allowing the users to act inside the designed space and to learn through it in an enactive way