Plucked strings are an exciting sound generation model for technical and timbral exploration. Mechatronic chordophones take advantage of this model and have been the focus of extensive research and exploration in musical robotics, often used as stand-alone instruments or as part of sound art installations. However, no existing chordophone designs have utilised the expressive potential of plucked strings to their full extent.In this paper, we introduce an expressive mechatronic mono-chord that serves as a prototyping platform for the construction of a polystring chordophone. This new chordophone has been developed to offer enhanced dynamic range, fast picking speeds, fast pitch shifter displacement, and additional expressive techniques compared to existing systems.

A reward mechanism is critical for a Reinforcement Learning agent to learn action policies from rewards. The reward mechanism establishes a policy by estimating contributions of constituents of the policy to a reward. Traditionally, rewards from an environment have two categories: long-term rewards for guiding the policy learning process, and short-term rewards for optimisation. However, long-term, positive rewards are scarce at the initial learning phase in multistep problems such that existing reward mechanisms lack sufficient stimulus to learn policies effectively. This paper proposes XCSCR, an Accuracy-based Learning Classifier System (XCS) algorithm with a combined reward (CR) method, to guide the search for global optimal policies in multistep maze problems. The XCSCR discriminates long-term and short-term rewards through four novel rewardassignment mechanisms: 1) A short-term reward mechanism encourages exploration of the RL agent searching for policies based on short-term rewards. 2) An imprinting mechanism amends the negative impact of indiscriminate rewards between exploration and exploitation. 3) A learning-rate switching mechanism emphasises the impact of long-term positive rewards in the policy searching process. 4) A learning step-threshold mechanism creates an optimisation pressure for policies. Experiments were conducted in three maze environments as this enabled the effects of XCSCR on policies to interpreted easily. Results show that the XCSCR enables learning the optimum path-finding policies quicker and more often than previous XCS algorithms. The XCSCR's improvements for the policy search will facilitate realworld applications, e.g. robotic applications.

This paper reports on the development of team and individual project based learning in our two core first-year engineering courses (Engineering Technology ENGR101 & Engineering Modelling and Design ENGR110) as an innovative and successful alternative to traditional lecture and laboratory learning. Both courses are central to the first-year programme, and student experience, and are taken by all engineering majors in our Bachelor of Engineering (BE). Improvements to these courses have shown a marked increase in student success crucial for our relatively open entry programme.

This paper reports on the findings from 15 pastoral care interviews as part of a broader research project aimed at investigating the relatively low completion rate of first-year Bachelor of Engineering (BE) students. A Foucauldian Discourse Analysis (FDA) was chosen to examine the text for issues beyond the student's academic ability or performance. In particular, we examine the interview text in relation to Foucauldian concepts of governmentality and biopower in an attempt to reflect on the power-relations within the first year teaching and learning environment.

The continuous automatic calibration of musical robots is an important step toward enabling them to create accurate, reliable, and expressive performances. Several attempts have been made to achieve this using external laptops, single-board computers and off-the-shelf hardware, but these solutions have various drawbacks that preclude their use in many musical robotics contexts. This paper presents a new, custom-built embedded DSP system that is capable of up to 32 channels of high quality audio input and output, created to carry out musical information retrieval tasks on the sonic output of musical robots in real time while they are performing. The results of these analyses are continuously fed to musical robot control hardware in order to inform their performance. The design and construction of the circuit board is described, the Musical Information Retrieval (MIR)-based algorithms carried out by the board are outlined, the system's performance in representative applications are evaluated, and its various implications to the field of musical robotics and beyond are discussed. By integrating this system into new musical robots, the result is instruments that are able to `listen' to the audible results of their own actuations in real time, and continuously calibrate their actions to best represent the intentions of the programmed musical composition or live input.

This full-paper relates to research on the effectiveness of GPA thresholding as a predictor of eventual grade performance in engineering study. Rather than rely on High School grades as a predictor of eventual success in tertiary (ICT-related) engineering, we have adopted a more open-entry model, but require a high performance from the students over their compulsory first year courses in order to progress in engineering study. In this paper we examine whether this is a satisfactory predictor of eventual student success (based on grade performance), or is it that issues such as High-School to University transition unduly negatively influence these grades and lead to a decision not to allow an otherwise capable student to progress. To examine this, we compare student GPAs and graduation rates between a four year Bachelor of Engineering and a three year Bachelor of Science degree which share similar courses. The hypothesis to test is whether students who have been excluded from continuing with Engineering study are in fact capable of passing the advanced level technical courses.

In this full paper we describe an innovative practice regarding the design and introduction of compulsory, small-group, holistic tutorials into our core first year engineering courses. Instead of traditional tutorials which seek to reinforce lecture content or provide guided help with assignments or test revision, these tutorials specifically focus on connecting topics between all courses a student is currently taking. They also aim to clearly demonstrate the value of a cohesive body of knowledge, instead of rote-learning of facts from individual areas. Tutorials are accompanied by practical demonstrations, and collaborative, guided discussions. The inclusion of these tutorials, along with other minor changes to the course content, has shown marked improvements in students' grades, retention, student evaluations and, most importantly, a change in many students' perception of the value of a coherent body of knowledge separate to that necessary to perform well in assessments. Such tutorials appear to have positively affected the retention rate of engineering students in our degree programme.

The Information and Communications Technology (ICT) industry in New Zealand is growing rapidly. The traditional university courses are preparing an insufficient number of graduates to sustain the growth. Many of the traditional graduate students lack key soft skills that are important in team based software development. This paper reports on the development of a conversion Master of Software Development degree. The students are all graduates with little or no computer science degrees, are taught key programming skills, with a focus on agile development. The programme begins by focusing on individual programming skills through solving problems. Later industrial partners are engaged by providing industrial problems to agile teams of students. The industrial partners are active partners in the agile teams as product owners. By solving the problems, the students develop both technical and non-technical skills while utilizing the skills obtained from previous studies. The results from the first year of the programme are encouraging. A key result is that a high number of students found work in paid IT positions before graduating. The main issue of the first year was introducing too many topics at the same time, over-assessment, not enough communication and contact time, little opportunity for the students to make their own experiences, and learning by making mistakes. The programme has been changed for the next year/s cohort to introduce less topics at once, provide time and space for learning, and a redesign of scheduling assessments.

An investigation into the initially high attrition rates in our new Engineering programme uncovered a number of non-academic factors that led to poor rates of student engagement. Dealing with today's “millennials” has required us to focus on meeting student expectations to a greater extent than we ever expected. Indeed, once we began to understand the modern, technically motivated student, we overhauled our first year engineering offering, as our focus on the traditional delivery of “enabling” subjects (physics, mathematics, programming) was failing. The result has been a substantial increase in student satisfaction and in the number of students gaining a GPA that enables them to proceed in engineering study.

We investigate the ability of introductory physics and mathematics courses to provide a successful pathway into the Engineering program at Victoria University of Wellington. We find that an increasing number of students require these courses, however neither course appears to adequately prepare students for the completion of an engineering degree. The introductory physics course in particular, does not adequately prepare student to pass subsequent physics courses. We examine both the delivery and curricula of these courses against literature `best practice' models. Finally we make a series of recommended changes be made to either university entry requirements or to these courses to offer allow students a reasonable pathway into the BE(Hons) degree.

An opportunity arose to secure a share of a multimillion dollar initiative to train additional ICT Postgraduate students. However, local and national ICT industries did not want such students, with the greatest demand being for conventional 4 year Bachelor of Engineering or 3 year Bachelor of Science graduates. This paper outlines a strategy that developed a suite of programmes that passed nine quality assurance stages and won a competitive bid to be selected as one of three preferred suppliers. Further, the programmes so developed addressed industry needs, and were able to target both domestic and international students.

This paper outlines and discusses the use of Foucauldian Discourse Analysis (FDA), a qualitative approach to investigating discourse. FDA offers a theoretical method which reveals, from the discourse, the various power structures affecting engineering students in their first year. This method has been unexplored in the STEM educational research field, but has been used successfully in psychology, humanities and educational research.

This paper presents an emotion inspired adaptive path planning approach for autonomous robotic navigation. Ideally a robotic navigation system should adapt its path planning and behaviour to overcome a variety of obstacles within an environment, without the need for single location planning approaches. Emotional analogies are appealing as they enable general planning, but require hard coding of `emotions'. Humans have a bias on what is an emotion, e.g. fear, which can adversely affect performance. We aim to provide the robot with the generalising ability of emotion without the pre-specifying bias. Inspired by theories on `emotion', the system presented utilises a Learning Classifier System (LCS) to learn a `bow-tie' structure of emotional reinforcers to intermediary emotion categories to a behavioural modifier that adapts the robot's navigation behaviour. The emotional states are not pre-set and are judged post learning based on the learned behaviour. The bow-tie creates a simple compact set of rules to adapt a robot's behaviour to better navigate its environment. The emotion system was verified on a state-of-the-art navigation system to learn a variety of parameters that control the robot's behaviour. The results show two easy to understand learned emotional states; the first is considered to be a model `fear', which increases obstacle avoidance while lowering speed when pain is induced or novelty is high. The second emotion is considered to be `happiness', which increases speed and lowers wall avoidance when pain is not present. Compared to the default non-adapting navigation system, the emotional responses decreased the overall number of collisions and improved time to navigate.

We established an engineering degree utilising existing science and mathematics courses where possible in order to minimise the resource requirements. After 7 years of running this degree, research indicated dissatisfaction by some students regarding the science, and in particular, mathematics component of the programme. We also uncovered numerous non-academic issues that contributed to student disengagement from the degree. This paper outlines the evolution of an engineering degree from its inception to its current form. This evolution is informed by student surveys, focus groups, interviews, and best practice. The result has been a significant change to the foundation engineering course, the creation of new engineering courses, the appointment of a pastoral support agent, the growing of a student engineering culture and the redevelopment and re-emphasising of first year mathematics.

Since the first offering of our Bachelor of Engineering degree (BE) at Victoria University of Wellington (VUW) in 2007 we have had consistently poor pass rates for first year students. At VUW we have collected survey information since 2010. While these surveys have provided excellent information they do not provide sufficient depth of information for us to fully understand the problems facing first year students. Since 2012 pastoral care interviews have greatly enhanced our understanding of the student experience. This paper discusses the findings of the surveys, the creation of our pastoral care system and findings from pastoral care interviews.

As a new provider of engineering, Victoria University of Wellington (VUW) faces a significant number of challenges in attracting and retaining quality students. As the primary funder of Universities, the New Zealand Government is providing conflicting funding directives, desiring an increase in student numbers, but penalizing poor course completion rates and banning funding on foundation or bridging courses. This paper details the development of a successful engineering programme, focusing on the modern “digital” aspects of engineering, in the face of these challenges.

The transition from High School to first year Engineering at University can be very difficult for many students. Victoria University of Wellington, New Zealand (VUW), developed an early warning system for student grade performance: Big Sister, and a system of Pastoral Care within the School of Engineering and Computer Science. This paper will discuss how Big Sister supports the identification of at risk students and how this system is integrated into the delivery of effective Pastoral Care. Importantly, this paper will also discuss the information gained from student interviews by the Pastoral Care staff member. In particular, we discuss the findings in relation to student self-efficacy and success and how this is being used to improve the first year teaching and learning environment.

The New Zealand Government is moving towards restricting access to tertiary education and implementing a managed entry scheme. It is therefore important to be able to predict whether a student has a reasonable likelihood of succeeding in tertiary engineering study. New Zealand secondary schools mostly operate on the National Certificate of Educational Achievement (NCEA) model whereby subjects are assessed on the basis of discrete individual modules. The paper compares the NCEA results to first year grades in tertiary engineering subjects obtained from most New Zealand providers of the BE degree to determine whether these NCEA grades can be used as a predictor of success or failure in tertiary engineering programmes. This is the first nation-wide survey of its kind and has yielded surprising results. For example, predicting success based on whether a student has not achieved is more insightful than basing on achievements, which is counter to the basis of many school league tables worldwide.

Victoria University of Wellington in partnership with the regional polytechnic, WelTec, undertook a major exercise to identify, and where possible, resolve, barriers to recruitment and retention in the “digital” engineering specializations. This paper focuses on the retention aspects of this research. Informed by student surveys, focus groups and secondary school academic achievement data, we identified contributing issues of academic preparation, student expectation and cultural influencers. In response we developed an engineering preparation course, a mathematics based diagnostic tool, Peer-Assisted learning support, engineering cultural activities, and redeveloped our core first year engineering course. Although in the early stages of delivery, these initiatives have been well received by the students. We are closely monitoring the results of these initiatives with the expectation that fewer students will abandon their studies and a greater portion of the marginal students will attain passing grades.

For artificial intelligence research to progress beyond the highly specialized task-dependent implementations achievable today, researchers may need to incorporate aspects of biological behavior that have not traditionally been associated with intelligence. Affective processes such as emotions may be crucial to the generalized intelligence possessed by humans and animals. A number of robots and autonomous agents have been created that can emulate human emotions, but the majority of this research focuses on the social domain. In contrast, we have developed a hybrid reactive/deliberative architecture that incorporates artificial emotions to improve the general adaptive performance of a mobile robot for a navigation task. Emotions are active on multiple architectural levels, modulating the robot's decisions and actions to suit the context of its situation. Reactive emotions interact with the robot's control system, altering its parameters in response to appraisals from short-term sensor data. Deliberative emotions are learned associations that bias path planning in response to eliciting objects or events. Quantitative results are presented that demonstrate situations in which each artificial emotion can be beneficial to performance.

Autonomous robots are presently unable to match the adaptive capabilities of even the simplest of animals. Affective processes such as emotions are highly effective facilitators of adaptive behavior in humans and animals. Thus, it can be argued that emotions can bestow robots with similar adaptive advantages. In particular, artificial emotions can improve a robot's performance by modulating actions, prioritizing goals and providing reinforcements for learning. A hierarchical robot architecture that incorporates reactive and deliberative emotions has been developed to test this hypothesis. Reactive emotions arise from predictions of emotion-eliciting events from short-term sensor data and internal representations. Deliberative emotions are modeled as learned associations between environmental states and previous emotion-eliciting events. Emotions interact with multiple architectural levels by modulating parameters controlling the robot's degree of bias towards various competing drives, such as goal-seeking, safety and exploration. The model has been implemented on a simulated mobile robot for a navigation task.