Recent research has found that many novice programmers often hold non-viable mental models of basic programming concepts such as assignment and object reference, which can limit their potential to develop programming skills. This paper proposes a constructivist-based teaching model that integrates cognitive conflict and program visualisation with the aim of supporting novice programmers in the formulation of appropriate mental models. The results of an initial empirical study produced three findings of note. Firstly, a teaching model based on either visualisation alone or cognitive conflict integrated with visualisation can help students develop viable models of value assignment. Secondly, there was evidence to suggest that cognitive conflict integrated with visualisation outperformed visualisation alone in helping students develop viable models of the more challenging concept of object reference assignment. And thirdly, there was evidence of an improvement in students' understanding of value and object reference assignment using the teaching model based on visualisation and cognitive conflict
The aim of this research is to use Social Cognitive Career Theory (SCCT) to identify and understand reasons why students choose to study Computer Science (CS) at university. SCCT focuses on students' prior experience, social support, self-efficacy and outcome expectation. The research is partly motivated by the desire to increase female participation rates in CS, particularly in the UK. Policymakers can use the factors that both females and males identify as influencing their choice of studying CS to enhance the experiences of all students prior to coming to university, but female students in particular. The study uses a semi-structured interview with 17 mixed gender subjects currently studying CS at three Scottish universities. The findings are that social support from family, teachers, friends and mentors is a particularly important factor in choosing to study CS, especially for female subjects. The career paths offered by a CS degree is another major factor, not just the potential jobs, but also the general value of a CS education and the potential to make useful contributions to society. School education appeared to have limited influence, though exposure to problem solving, programming, online self-learning and internships are positive influences. The stereotypical view of CS students as 'geeks' is outdated and unhelpful -it is more appropriate to see them as 'analytical' or 'over-achievers'. Subjects make many suggestions for improving the CS education provided at school, especially to make it more attractive to females, including: make it compulsory, teach it earlier, include more programming and problem solving, and increase the visibility of female exemplars and role models.
Recent research has found that many novice programmers often hold non-viable mental models of basic programming concepts which can limit their potential to develop appropriate programming skills. Previous work by the authors suggests that a teaching model that integrates cognitive conflict and program visualisation can help novices formulate appropriate mental models. This paper first outlines a 'concepts roadmap' that provides an ordered approach to learning programming concepts allowing students to build on fundamental base knowledge. It then reports the results of a series of studies investigating the use of the Jeliot visualisation tool as the visualisation component of the proposed learning model when applied to these concepts. The findings include: the ease with which Jeliot can be tailored to visualise a range of concepts using a variety of examples; the Jeliot visualisation of object reference was too complex for CS1 students; further evidence that CS1 students struggle to develop appropriate understanding of a range of key programming concepts; and, further evidence that an integrated cognitive conflict/visualisation strategy can help students develop an appropriate understanding of key programming concepts
Recent research has found that many novice programmers often hold non-viable mental models of basic programming concepts such as assignment and object reference, which can limit their potential to develop programming skills. This paper proposes a constructivist-based teaching model that integrates cognitive conflict and program visualisation with the aim of supporting novice programmers in the formulation of appropriate mental models. The results of an initial empirical study produced three findings of note. Firstly, a teaching model based on either visualisation alone or cognitive conflict integrated with visualisation can help students develop viable models of value assignment. Secondly, there was evidence to suggest that cognitive conflict integrated with visualisation outperformed visualisation alone in helping students develop viable models of the more challenging concept of object reference assignment. And thirdly, there was evidence of an improvement in students' understanding of value and object reference assignment using the teaching model based on visualisation and cognitive conflict.
Abstract. Growing user expectations of anywhere, anytime access to information require new types of data representations to be considered. While semi-structured data is a common exchange format, its verbose nature makes files of this type too large to be transferred quickly, especially where only a small part of that data is required by the user. There is consequently a need to develop new models of data storage to support the sharing of small segments of semi-structured data since existing XML compressors require the transfer of the entire compressed structure as a single unit. This paper examines the potential for bisimilarity-based partitioning (i.e. the grouping of items with similar structural patterns) to be combined with dictionary compression methods to produce a data storage model that remains directly accessible for query processing whilst facilitating the sharing of individual data segments. Study of the effects of differing types of bisimilarity upon the storage of data values identified the use of both forwards and backwards bisimilarity as the most promising basis for a dictionary-compressed structure. A query strategy is detailed that takes advantage of the compressed structure to reduce the number of data segments that must be accessed (and therefore transferred) to answer a query. A method to remove redundancy within the data dictionaries is also described and shown to have a positive effect on memory usage.
Abstract. Network modelling provides an increasingly popular conceptualisation in a wide range of domains, including the analysis of protein structure. Typical approaches to analysis model parameter values at nodes within the network. The spherical locality around a node provides a microenvironment that can be used to characterise an area of a network rather than a particular point within it. Microenvironments that centre on the nodes in a protein chain can be used to quantify parameters that are related to protein functionality. They also permit particular patterns of such parameters in node-centred microenvironments to be used to locate sites of particular interest. This paper evaluates an approach to index generation that seeks to rapidly construct microenvironment data. The results show that index generation performs best when the radius of microenvironments matches the granularity of the index. Results are presented to show that such microenvironments improve the utility of protein chain parameters in classifying the structural characteristics of nodes using both support vector machines and neural networks.
Special educational needs specialist Isla Ross explains how an established training model in Scotland is increasing school support for pupils with Down Syndrome.
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