Work integrated learning : an industry partners’ perspective

In recent years the Australian tertiary education sector may be said to be undergoing a vocational transformation. Vocationalism, that is, an emphasis on learning directed at work related outcomes is increasingly shaping the nature of tertiary education. This paper reports some findings to date of a project that seeks to identify the key issues faced by students, industry and university partners engaged in the provision of WIL within an undergraduate program offered by the Creative Industries faculty of a major metropolitan university. Here, those findings are focussed on some of the motivations and concerns of the industry partners who make their workplaces available for student internships. Businesses are not universities and do not perceive of themselves as primarily learning institutions. However, their perspectives of work integrated learning and their contributions to it need to understand more fully at practical and conceptual levels of learning provision. This paper and the findings presented here suggest that the diversity of industry partner motivations and concerns contributing to WIL provision requires that universities understand and appreciate those partners as contributors with them to a culture of learning provision and support. These industry partner contribution need to be understood as valuing work as learning, not work as something that needs to be integrated with learning to make that learning more authentic and thereby more vocational.

Investigating the process of teaching and learning principles through practice : a case study on collegiate action by media practitioners and teachers, designing a skills-based learning program

This paper in the journalism education field reports on the construction of a new subject as part of a postgraduate coursework degree. The subject, or unit1 will offer both Journalism students and other students an introductory experience of creating media, using common ‘new media’ tools, with exercises that will model the learning of communication principles through practice. It has been named ‘Fundamental Media Skills for the Workplace’. The conceptualisation and teaching of it will be characteristic of the Journalism academic discipline that uses the ‘inside perspective’—understanding mass media by observing from within. Proposers for the unit within the Journalism discipline have sought to extend the common teaching approach, based on training to produce start-ready recruits for media jobs, backed by a study of contexts, e.g. journalistic ethics, or media audiences. In this proposal, students would then examine the process to elicit additional knowledge about their learning. The paper draws on literature of journalism and its pedagogy, and on communication generally. It also documents a ‘community of practice’ exercise conducted among practitioners as teachers for the subject, developing exercises and models of media work. A preliminary conclusion from that exercise is that it has taken a step towards enhancing skills-based learning for media work, as a portal to more generalised knowledge.

An investigation of the effect of individual cognitive preferences on learning through computer-based instruction

This paper reports a study investigating the effect of individual cognitive styles on learning through computer-based instruction. The study adopted a quasi-experimental design involving four groups which were presented with instructional material that either matched or mismatched with their preferred cognitive styles. Cognitive styles were measured by cognitive style assessment software (Riding, 1991). The instructional material was designed to cater for the four cognitive styles identified by Riding. Students' learning outcomes were measured by the time taken to perform test tasks and the number of marks scored. The results indicate no significant difference between the matched and mismatched groups on both time taken and scores on test tasks. However, there was significant difference between the four cognitive styles on test score. The Wholist/Verbaliser group performed better then all other groups. There was no significant difference between the other groups. An analysis of the performance on test task by each cognitive style showed significant difference between the groups on recall, labelling and explanation. Difference between the cognitive style groups did not reach significance level for problem-solving tasks. The findings of the study indicate a potential for cognitive style to influence learning outcomes measured by performance on test tasks.

Cognitive load and assembly tasks : effect of instructional formats on learning assembly procedures

The study investigated the effect on learning of four different instructional formats used to teach assembly procedures. Cognitive load and spatial information processing theories were used to generate the instructional material. The first group received a physical model to study, the second an isometric drawing, the third an isometric drawing plus a model and the fourth an orthographic drawing. Forty secondary school students were presented with the four different instructional formats and subsequently tested on an assembly task. The findings indicated that there may be evidence to argue that the model format which only required encoding of an already constructed three dimensional representation, caused less extraneous cognitive load compared to the isometric and the orthographic formats. No significant difference was found between the model and the isometric-plus-model formats on all measures because 80% of the students in the isometric-plus-model format chose to use the model format only. The model format also did not differ significantly from other groups in total time taken to complete the assembly, in number of correctly assembled pieces and in time spent on studying the tasks. However, the model group had significantly more correctly completed models and required fewer extra looks than the other groups.

Cognitive load and mental rotation : structuring orthographic projection for learning and problem solving

Cognitive load theory was used to generate a series of three experiments to investigate the effects of various worked example formats on learning orthographic projection. Experiments 1 and 2 investigated the benefits of presenting problems, conventional worked examples incorporating the final 2-D and 3-D representations only, and modified worked examples with several intermediate stages of rotation between the 2-D and 3-D representations. Modified worked examples proved superior to conventional worked examples without intermediate stages while conventional worked examples were, in turn, superior to problems. Experiment 3 investigated the consequences of varying the number and location of intermediate stages in the rotation trajectory and found three stages to be superior to one. A single intermediate stage was superior when nearer the 2-D than the 3-D end of the trajectory. It was concluded that (a) orthographic projection is learned best using worked examples with several intermediate stages and that (b) a linear relation between angle of rotation and problem difficulty did not hold for orthographic projection material. Cognitive load theory could be used to suggest the ideal location of the intermediate stages.

Computer assisted instruction and individual cognitive style preferences in learning : does it matter?

This paper reports the findings of a pilot study aimed at improving learning outcomes from Computer Assisted Instruction (CAI). The study involved second year nursing students at the Queensland University of Technology. Students were assessed for their preferred cognitive style and presented with either matched or mismatched instructional material. The instructional material was developed in accordance with four cognitive styles (Riding & Cheema, 1991). The findings indicate groups that received instructional material which matched their preferred cognitive style, possibly, performed better than groups that received mismatched instructional material. The matched group was particularly better in the explanation and problem solving tasks.

Restructuring instructional material in vocational education to enhance learning

This paper reviews research findings regarding the design of instructional material and its effectiveness in facilitating learning. Firstly, a discussion of memory processes engaged in when learning from different types of instructional material is presented. Secondly, referring to empirical research, the implications of the above discussion for vocational education instruction, and in particular, for engineering graphics, CNC programming and learning to use equipment from manuals are presented.

Acknowledging social justice and equity through good practice for monitoring student learning engagement in FYE

As higher education institutions respond to government targets to widen participation, their student populations will become increasingly diverse, and the issues around student success and retention will be more closely scrutinised. The concept of student engagement is a key factor in student achievement and retention and Australasian institutions have a range of initiatives aimed at monitoring and intervening with students who are at risk of disengaging. Within the widening participation agenda, it is absolutely critical that these initiatives are designed to enable success for all students, particularly those for whom social and cultural disadvantage have been a barrier. Consequently, for the sector, initiatives of this type must be consistent with the concept of social justice and a set of principles would provide this foundation. This session will provide an opportunity for participants to examine a draft set of principles and to discuss their potential value for the participants’ institutional contexts.

Scaffolding large units for small group collaborative learning : a case study.

Undergraduates working in teams can be a problematic endeavour, sometimes exacerbated for the student by poor prior experiences, a predisposition to an individual orientation of assessment, and simply the busyness that now typifies the life of a student. But effort in pedagogical design is worthwhile where team work is often a prerequisite in terms of graduate capabilities, robust learning, increased motivation, and indeed in terms of equipping individuals for emergent knowledge-age work practice, often epitomised by collaborative effort in both blended and virtual contexts. Through an iterative approach, based extensively on the established literature, we have developed a successful scaffold which is workable with a large cohort group (n >800), such that it affords students the lived experience of being a part of a learning network. Individuals within teams work together, to develop individual components that are subsequently aggregated and reified to an overall team knowledge artefact. We describe our case and propose a pedagogical model of scaffolding based on three perspectives: conceptual, rule-based and community-driven. This model provides designers with guidelines for producing and refining assessment tasks for team-based learning.

Privacy v IP Litigation : preliminary third party discovery on the Internet

The enforcement of Intellectual Property rights poses one of the greatest current threats to the privacy of individuals online. Recent trends have shown that the balance between privacy and intellectual property enforcement has been shifted in favour of intellectual property owners. This article discusses the ways in which the scope of preliminary discovery and Anton Piller orders have been overly expanded in actions where large amounts of electronic information is available, especially against online intermediaries (service providers and content hosts). The victim in these cases is usually the end user whose privacy has been infringed without a right of reply and sometimes without notice. This article proposes some ways in which the delicate balance can be restored, and considers some safeguards for user privacy. These safeguards include restructuring the threshold tests for discovery, limiting the scope of information disclosed, distinguishing identity discovery from information discovery, and distinguishing information preservation from preliminary discovery.

Who is the corporate entrepreneur? Insights from opportunity discovery and Creation Theory

Recent research has begun to address and even compare nascent entrepreneurship and nascent corporate entrepreneurship. An opportunity based view holds great potential to integrate both streams of research, but also presents challenges in how we define corporate entrepreneurship. We extend (corporate) entrepreneurship literature to the opportunity identification phase by providing a framework to classify different types of corporate entrepreneurship. Through analysis of a large dataset on nascent (corporate) entrepreneurship (PSEDII) we show that these corporate entrepreneurs differ largely from each other in terms of human capital. Prior studies have indicated that independent and corporate entrepreneurs pursue different types of opportunities and utilize different strategies. Our findings from the opportunity identification phase challenge those differences and seem to indicate a difference between the opportunities corporate entrepreneurs identify versus the opportunities they exploit.

The role of digressive learning and uniqueness on performance : longitudinal evidence from young firms

The ability to differentiate from competitors through the selection of unique offerings is an important cornerstone of competitive performance. Developing unique products and services to offer in the marketplace is not only important for established firms, but also an important strategic choice for young firms (Baum and Haveman, 1997). Unlike large and established firms, young firms tend to have less access to adequate resources, well-developed sources of information, contact networks, and considerable experience and management know-how. That is, these firms differ significantly in their attributes and performance from larger and well-established firms (c.f. Miller and Chen, 1994). Although young firms are disadvantaged by the paucity of resources in putting together its unique product offering(s), they develop different pathways in advancing their assortment of capabilities that enables them to stay ahead of competitors.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Discovery & effective use of quality association rules in multi-level datasets

In today’s electronic world vast amounts of knowledge is stored within many datasets and databases. Often the default format of this data means that the knowledge within is not immediately accessible, but rather has to be mined and extracted. This requires automated tools and they need to be effective and efficient. Association rule mining is one approach to obtaining knowledge stored with datasets / databases which includes frequent patterns and association rules between the items / attributes of a dataset with varying levels of strength. However, this is also association rule mining’s downside; the number of rules that can be found is usually very big. In order to effectively use the association rules (and the knowledge within) the number of rules needs to be kept manageable, thus it is necessary to have a method to reduce the number of association rules. However, we do not want to lose knowledge through this process. Thus the idea of non-redundant association rule mining was born. A second issue with association rule mining is determining which ones are interesting. The standard approach has been to use support and confidence. But they have their limitations. Approaches which use information about the dataset’s structure to measure association rules are limited, but could yield useful association rules if tapped. Finally, while it is important to be able to get interesting association rules from a dataset in a manageable size, it is equally as important to be able to apply them in a practical way, where the knowledge they contain can be taken advantage of. Association rules show items / attributes that appear together frequently. Recommendation systems also look at patterns and items / attributes that occur together frequently in order to make a recommendation to a person. It should therefore be possible to bring the two together. In this thesis we look at these three issues and propose approaches to help. For discovering non-redundant rules we propose enhanced approaches to rule mining in multi-level datasets that will allow hierarchically redundant association rules to be identified and removed, without information loss. When it comes to discovering interesting association rules based on the dataset’s structure we propose three measures for use in multi-level datasets. Lastly, we propose and demonstrate an approach that allows for association rules to be practically and effectively used in a recommender system, while at the same time improving the recommender system’s performance. This especially becomes evident when looking at the user cold-start problem for a recommender system. In fact our proposal helps to solve this serious problem facing recommender systems.

Industry school partnerships : real world learning through the Gateway Schools Projects

In the last decade, a gradual but significant shift in education has taken place. Schools have transformed from hermetically sealed, impermeable bureaucracies to dynamic and flexible organisations characterised by openness to local communities and connectedness to global issues and cultures. They are also more responsive to the aspirations of students and parents. A central feature of what Christian Maroy (2009) has described as the post bureaucratic era of education has been the relationships formed between schools and other organisations through formalised partnerships. Partnerships have been a significant feature of schooling in Queensland since the 1980s when schools developed Vocational Education Programs (VET) providing alternative pathways from schooling to post school training or employment. However, partnerships that have emerged in recent times have been more structured in their organisation and more targeted in terms of the outcomes they aim to achieve. Examples here have included Queensland’s District Youth Achievement plans that linked schools, business, industry bodies, training organisations and community groups to improve transition outcomes, particularly for young people at risk in their transitions from school to post-school life.