Theoretical models of the role of visualisation in learning formal reasoning

Although there is empirical evidence that visualisation tools can help students to learn formal subjects such as logic, and although particular strategies and conceptual difficulties have been identified, it has so far proved difficult to provide a general model of learning in this context that accounts for these findings in a systematic way. In this paper, four attempts at explaining the relative difficulty of formal concepts and the role of visualisation in this learning process are presented. These explanations draw on several existing theories, including Vygotsky's Zone of Proximal Development, Green's Cognitive Dimensions, the Popper-Campbell model of conjectural learning, and cognitive complexity. The paper concludes with a comparison of the utility and applicability of the different models. It is also accompanied by a reflexive commentary[0] (linked to this paper as a hypertext) that examines the ways in which theory has been used within these arguments, and which attempts to relate these uses to the wider context of learning technology research

Learning through work experience

How students learn and develop through work experience is here analysed. We draw upon contemporary learning theory, recent developments in the adult education and curriculum theory in developing a critique of current thinking and explore how far this provides the basis for a new pedagogic model for supporting learning through work experience. We discuss the concept of 'context' and the learning which occurs within and between the different contexts of education and work and argue that most models of work experience have either ignored the influence of context upon learning or have approached this issue mechanistically. New curriculum frameworks are needed to and to allow work in all of its forms to be used as a basis for the development of knowledge, skills and identity. We present a typology of work experience which identifies models of work experience, including a model which embodies the concept of 'connectivity'. We suggest that this may provide the basis for a productive and useful relationship between formal and informal learning

Adaptive Intelligent Tutoring System for learning Computer Theory

In this paper, we present an intelligent tutoring system developed to help students in learning Computer Theory. The Intelligent tutoring system was built using ITSB authoring tool. The system helps students to learn finite automata, pushdown automata, Turing machines and examines the relationship between these automata and formal languages, deterministic and nondeterministic machines, regular expressions, context free grammars, undecidability, and complexity. During the process the intelligent tutoring system gives assistance and feedback of many types in an intelligent manner according to the behavior of the student. An evaluation of the intelligent tutoring system has revealed reasonably acceptable results in terms of its usability and learning abilities are concerned

Supporting organisational learning: an overview of the ENRICH approach

Traditional training separates learning from the work context in which the newly acquired knowledge is to be applied. This requires the worker themselves to apply imparted theoretical knowledge to knowledge in practice, a process that is grossly inefficient. The ENRICH approach builds on organisational learning theory to intertwine working and learning. The ENRICH methodology incorporates theories of learning at the individual, group and organisational level. Individual level learning is supported through the provision of semantically related resources to support problem reframing and to challenge assumptions. Group learning is supported through the evolution of domain concepts through work documents and representations linked to formal models of group knowledge, and the development of group practices and perspectives through enhanced sharing and collaboration. Organisational learning is supported through exposure to customs and conventions of other groups through shared best practices and knowledge models. The approach is being investigated in a range of industrial settings and applications

Attitude polarization

Psychological evidence suggests that people’s learning behavior is often prone to a “myside bias” or “irrational belief persistence” in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such a bias may result in diverging posterior beliefs and attitude polarization even if agents receive identical information. Such patterns cannot be explained by the standard model of rational Bayesian learning that implies convergent beliefs. As our key contribution, we therefore develop formal models of Bayesian learning with psychological bias as alternatives to rational Bayesian learning. We derive condi- tions under which beliefs may diverge in the learning process and thus conform with the psychological evidence. Key to our approach is the assumption of ambiguous beliefs that are formalized as non-additive probability measures arising in Choquet expected utility theory. As a specific feature of our approach, our models of Bayesian learning with psychological bias reduce to rational Bayesian learning in the absence of ambiguity.

Attitude polarization

Psychological evidence suggests that people’s learning behavior is often prone to a “myside bias”or “irrational belief persistence”in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such a bias may result in diverging posterior beliefs and attitude polarization even if agents receive identical information. Such patterns cannot be explained by the standard model of rational Bayesian learning that implies convergent beliefs. As our key contribution, we therefore develop formal models of Bayesian learning with psychological bias as alternatives to rational Bayesian learning. We derive conditions under which beliefs may diverge in the learning process and thus conform with the psychological evidence. Key to our approach is the assumption of ambiguous beliefs that are formalized as non-additive probability measures arising in Choquet expected utility theory. As a speci…c feature of our approach, our models of Bayesian learning with psychological bias reduce to rational Bayesian learning in the absence of ambiguity.

On attitude polarization under Bayesian learning with non-additive beliefs

Ample psychological evidence suggests that people’s learning behavior is often prone to a "myside bias" or "irrational belief persistence" in contrast to learning behavior exclusively based on objective data. In the context of Bayesian learning such a bias may result in diverging posterior beliefs and attitude polarization even if agents receive identical information. Such patterns cannot be explained by the standard model of rational Bayesian learning that implies convergent beliefs. As our key contribution, we therefore develop formal models of Bayesian learning with psychological bias as alternatives to rational Bayesian learning. We derive conditions under which beliefs may diverge in the learning process despite the fact that all agents observe the same - arbitrarily large - sample, which is drawn from an "objective" i.i.d. process. Furthermore, one of our learning scenarios results in attitude polarization even in the case of common priors. Key to our approach is the assumption of ambiguous beliefs that are formalized as non-additive probability measures arising in Choquet expected utility theory. As a specific feature of our approach, our models of Bayesian learning with psychological bias reduce to rational Bayesian learning in the absence of ambiguity.Non-additive Probability Measures, Choquet Expected Utility Theory, Bayesian Learning, Bounded Rationality

Learning to Become Youth. An Action Theory Approach

Youth is a historical construction and an answer to a specific challenge of individualisation in biography. And, as a historical and social construction, youth has to be learned. This article focuses on youth development from an action or activity theory perspective and as a learning process. It demonstrates how different youth problems and forms of youth differentiation follow forms of youth learning. Moreover, it shows how late modern development creates the demand for a new non-formal learning perspective to secure the development of new forms of competence. Based on Danish research concerning peer learning as a non-formal learning context, some perspectives of peer-learning competence are discussed