Evaluating interviews which search for the truth with suspects: but are investigators’ self-assessments of their own skills truthful ones?

Self-evaluation of one’s own performance has been found in prior research to be an enabler of professional development. The task of evaluation is also a core component of a model of the investigative interviewing of victims, witnesses and suspects, being increasingly used throughout the world. However, it remains the case that there has been little research as to how practitioners approach the task itself. The present study examined the topic through the lens of observing how effectively 30 real-life investigators in the UK undertook evaluation of their interviews, representing almost the entire investigative frontline workforce of a small law enforcement agency in this country. Using an established scale of measurement, both investigators’ and an expert’s ratings of the same sample of interviews were compared across a range of tasks and behaviours. It was found that in almost all the assessed behaviours, requiring of the investigators to provide a self-rating, their scores tended to significantly outstrip those applied to the sample by the expert. Reasons are explored for the investigators’ overstated assessments. Implications for practice are then discussed.N/

Reducing the Cost of Technical and Vocational Education

Teaching/Communication/Extension/Profession,

Cardiorespiratory requirements of the 6-min walk test in patients with left ventricular systolic disfunction and no major structural heart disease

The six-minute walk test (6-MWT) is widely used to assess functional status in patients with chronic heart failure (CHF). The aims of the present study were: (1) to compare metabolic gas exchange during the 6-MWT in older patients with left ventricular systolic dysfunction (LVSD) and in breathless patients with no major structural heart disease (MSHD); (2) to determine the exercise intensity of the 6-MWT relative to peak oxygen uptake; (3) to establish the accuracy and reproducibility of the Metamax 3B ergospirometer during an incremental workload. Twenty four older patients with LVSD (19 male; age 76 ± 5 years; BMI 27 ± 4), and 18 patients with no MSHD (12 male; age 75 ± 8 years; BMI 27 ± 4) attended on consecutive days at the same time. Patients completed a 6-MWT with metabolic gas exchange measurements using the Metamax 3B portable ergospirometer, and an incremental cycle ergometry test using both the Metamax 3B and Oxycon Pro metabolic cart. Patients returned and performed a second 6-MWT and an incremental treadmill test, metabolic gas exchange was measured with the Metamax 3B. In patients with LVSD, the 6-MWT was performed at a higher fraction of maximal exercise capacity (p = 0.02). The 6-MWT was performed below the anaerobic threshold in patients with LVSD (83 %) and in patients with no MSHD (61 %). The Metamax 3B showed satisfactory to high accuracy at 10 W and 20 W in patients with LVSD (r = 0.77 - 0.97, p < 0.05), and no MSHD (r = 0.76 - 0.94, p < 0.05). Metabolic gas exchange variables measured during the 6-MWT showed satisfactory to high day-to-day reproducibility in patients with LVSD (ICC = 0.75 - 0.98), but a higher variability was evident in participants with no MSHD (ICC = 0.62 - 0.97). The Metamax 3B portable ergospirometer is an accurate and reproducible device during submaximal, fixed rate exercise in older patients with LVSD and no MSHD. In elderly patients with LVSD and no MSHD, the 6-MWT should not be considered a maximal test of exercise capacity but rather a test of submaximal exercise performance. Our study demonstrates that the 6-MWT takes place at a higher proportion of peak oxygen uptake in patients with LVSD compared to those with no MSHD, and may be one reason why fatigue is a more prominent symptom in these patients

Evidencing the value of inquiry based, constructionist learning for student coders

For the last decade, there has been growing interest in the STEAM approach (essentially combining methods and practices in arts, humanities and social sciences into STEM teaching and research) with its potential to deliver better research and education, and to enable us to produce students who can work more effectively in the current and developing marketplace. However, despite this interest, there seems to be little quantitative evidence of the true power of STEAM learning, especially describing how it compares and performs with respect to more established approaches. To address this, we present a comparative, quantitative study of two distinct approaches to teaching programming, one based on STEAM (with an open ended inquirydriven, inductive approach), the other based on a more traditional, non-STEAM approach (where constrained problems are set and solved deductively). Our key results evidence how students exhibit different styles of programming in different types of lessons and, crucially, that students who tend to exhibit more of the style of programming observed in our STEAM lessons also tend to achieve higher grades. We present our claims through a range of visualisations and statistical validations which clearly show the significance of the results, despite the small scale of the study. We believe that this work provides clear evidence for the advantages of STEAM over non-STEAM, and provides a strong theoretical and technological framework for future, larger studies

Examining Student Coding Behaviours in Creative Computing Lessons using Abstract Syntax Trees and Vocabulary Analysis

Creative computing is an approach to computing education which emphasises the creation of interactive audiovisual software and an art-school influenced pedagogy. Given this emphasis on Dewey’s "learning by doing”, we set out to investigate the processes students use to develop their programs. We refer to these processes as the students’ ‘coding behaviour’, and we expect that understanding it will provide us with valuable information about how students learn in our creative computing classes. As existing metrics were not sufficient, we introduce a new set of quantitative metrics to describe coding behaviours. The metrics consider factors such as students’ vocabulary use and development, how fast and how much they alter the functionality of code over time and how they iterate on their code through text insert and delete operations. Many of our lessons involve providing students with demonstrator code which they use as a base for the development of their programs, so we use demo code as an entry point to our dataset. We look at programs students have written through developing the demo code in a dataset of over 16,000 programs. We clustered the demo code using the set of descriptive metrics. This lead to a set of clusters containing programs which are associated with distinct coding behaviours. Four was the ideal number of clusters for cluster density and separation. We found that the clusters had distinct behaviour patterns, that they were associated with different instructors and that they contained demo programs with different lengths

Collaborative Coding Interfaces on the Web

The recent developments in Web technologies, including full‐stack reactive application frameworks, peer‐to‐peer communication and client‐side audiovisual APIs have introduced the possibility of creative collaboration in a number of contexts. Such technologies have the potential to transform the way Internet users interact with code. This paper introduces a theoretical and technical methodology for developing collaborative coding interfaces as web applications, tackling the issues of interactive rendering, user‐platform interaction and collaboration. A number of existing interactive programming environments are reviewed, followed by a technical description and evaluation of C odeCircle, a collaborative coding web platform developed at Goldsmiths, University of London

Rapid Prototyping of New Instruments with CodeCircle

Our research examines the use of CodeCircle, an online, collaborative HTML, CSS, and JavaScript editor, as a rapid prototyping environment for musically expressive instruments. In CodeCircle, we use two primary libraries: MaxiLib and RapidLib. MaxiLib is a synthesis and sample processing library which interfaces with the Web Audio API for sound generation in the browser. RapidLib is a product of the Rapid-Mix project, and allows users to implement interactive machine learning, using “programming by demonstration” to design new expressive interactions

Write once run anywhere revisited: machine learning and audio tools in the browser with C++ and emscripten

A methodology for deploying interactive machine learning and audio tools written in C++ across a wide variety of platforms, including web browsers, is described. The work flow involves development of the code base in C++, making use of all the facilities available to C++ programmers, then transpiling to asm.js bytecode, using Emscripten to allow use of the libraries in web browsers. Audio capabilities are provided via the C++ Maximilian library that is transpiled and connected to the Web Audio API, via the ScriptProcessorNode. Machine learning is provided via the RapidLib library which implements neural networks, k-NN and Dynamic Time Warping for regression and classification tasks. An online, browser-based IDE is the final part of the system, making the toolkit available for education and rapid prototyping purposes, without requiring software other than a web browser. Two example use cases are described: rapid prototyping of novel, electronic instruments and education. Finally, an evaluation of the performance of the libraries is presented, showing that they perform acceptably well in the web browser, compared to the native counterparts but there is room for improvement here. The system is being used by thousands of students in our on-campus and online courses

Contemporary Machine Learning for Audio and Music Generation on the Web: Current Challenges and Potential Solutions

We evaluate specific Web-based technologies that can be used to implement complex contemporary Machine Learning systems for Computer Music research, in particular for the problem of audio signal generation. As a result of greater investment from large corporations including Google and Facebook in areas such as the development of Web-based, accelerated, cross-platform Machine Learning libraries, alongside greater interest and engagement from the academic community in exploring such approaches, Machine Learning is becoming much more prevalent on the Web. This could have great potential impact for Computer Music research, acting to democratise access to complex, accelerated Machine Learning technologies through increased usability and flexibility, in tandem with clear documentation and examples. However, some problems remain in relation to the creation of more complete Machine Learning pipe-lines for Music and Sound generation. We discuss some key potential challenges in this area, and attempt to evaluate some relevant solutions for developing more accessible Computer Music Machine Learning systems

Laser Welding of a Stent

We consider the problem of modelling the manufacture of a cylindrical Stent, in which layers of a plastic material are welded together by a Laser beam. We firstly set up the equations for this system and solve them by using a Finite Element method. We then look at various scalings which allow the equations to be simplified. The resulting equations are then solved analytically to obtain approximate solutions to the radial temperature profile and the averaged axial temperature profile