Encouraging Diversity in Computer Science among Young People: Using a Games Design Intervention based on an Integrated Pedagogical Framework

This research to practice full paper presents the results from using a games design intervention to encourage diversity in the uptake of computer science by young people, explore stereotypes with them and increase their awareness of careers in the sector. The intervention is based on an integrated pedagogical framework appropriate for use with primary age school children (age 7 - 11 years). Despite the increasing use of technology, the percentage of young people taking up a computer science education-career path remains stubbornly low in the UK and across a number of other countries, particularly for females and those from lower socio-economic backgrounds. Previous research suggests that games can be used to generate interest and engage young people with computer science. Other studies advocate targeting young people at an earlier age (7 years or below) and sustaining engagement throughout their education to widen participation in a particular sector. In this intervention, young people designed and developed individual games through a three stage process: design and story development; game building; testing and evaluation. This research adopts elements from two pedagogical learning theories Direct Instruction and Cognitive Constructivism to create an integrated pedagogical framework to support the game creation process and enable effective learning. This provides an approach that can cater for a range of participants' abilities along the novice-expert spectrum and provide an engaging and age appropriate educational experience.The intervention was completed in two cycles: cycle 1 consisted of a series of workshop sessions with 20 young people aged 9-10 years over a period of 5 weeks; and cycle 2 was a single session with 19 young people aged 7-11 years. A quasi-experimental approach was adopted for evaluating the intervention using the following instruments; pre and post questionnaires, planning sheets, the games created by the participants and a set of already developed engagement factors. Results show an increase from 5% to 25% in participants' aspiration towards a computer science career. 45% of the young people also knew more careers in the game industry post-intervention. Girls chose a variety of diversity in their lead characters while boys chose mainly male human lead characters in the games that they designed. Participants' evaluation of each other's games using the engagement factors showed girls were more interested in receiving feedback than boys. This paper highlights the effectiveness of combining different learning approaches to provide an age appropriate intervention. It also presents evidence on the positive effect of using games in the classroom to explore stereotypes, and learn about, and encourage career choices in computer science

Varieties of Exploratory Experimentation in Nanotoxicology

There has been relatively little effort to provide a systematic overview of different forms of exploratory experimentation (EE). The present paper examines the growing subdiscipline of nanotoxicology and suggests that it illustrates at least four ways that researchers can engage in EE: searching for regularities; developing new techniques, simulation models, and instrumentation; collecting and analyzing large swaths of data using new experimental strategies (e.g., computer-based simulation and “high-throughput” instrumentation); and structuring an entire disciplinary field around exploratory research agendas. In order to distinguish these and other activities more effectively, the paper proposes a taxonomy that includes three dimensions along which types of EE vary: (1) the aim of the experimental activity, (2) the role of theory in the activity, and (3) the methods or strategies employed for varying experimental parameters

Remote laboratories in teaching and learning – issues impinging on widespread adoption in science and engineering education

This paper discusses the major issues that impinge on the widespread adoption of remote controlled laboratories in science and engineering education. This discussion largely emerges from the work of the PEARL project and is illustrated with examples and evaluation data from the project. Firstly the rationale for wanting to offer students remote experiments is outlined. The paper deliberately avoids discussion of technical implementation issues of remote experiments but instead focuses on issues that impinge on the specification and design of such facilities. This includes pedagogic, usability and accessibility issues. It compares remote experiments to software simulations. It also considers remote experiments in the wider context for educational institutions and outlines issues that will affect their decisions as to whether to adopt this approach. In conclusion it argues that there are significant challenges to be met if remote laboratories are to achieve a widespread presence in education but expresses the hope that this delineation of the issues is a contribution towards meeting these challenges

Auditory Spectrum-Based Pitched Instrument Onset Detection

In this paper, a method for onset detection of music signals using auditory spectra is proposed. The auditory spectrogram provides a time-frequency representation that employs a sound processing model resembling the human auditory system. Recent work on onset detection employs DFT-based features describing spectral energy and phase differences, as well as pitch-based features. These features are often combined for maximizing detection performance. Here, the spectral flux and phase slope features are derived in the auditory framework and a novel fundamental frequency estimation algorithm based on auditory spectra is introduced. An onset detection algorithm is proposed, which processes and combines the aforementioned features at the decision level. Experiments are conducted on a dataset covering 11 pitched instrument types, consisting of 1829 onsets in total. Results indicate that auditory representations outperform various state-of-the-art approaches, with the onset detection algorithm reaching an F-measure of 82.6%

Measuring cognitive load and cognition: metrics for technology-enhanced learning

This critical and reflective literature review examines international research published over the last decade to summarise the different kinds of measures that have been used to explore cognitive load and critiques the strengths and limitations of those focussed on the development of direct empirical approaches. Over the last 40 years, cognitive load theory has become established as one of the most successful and influential theoretical explanations of cognitive processing during learning. Despite this success, attempts to obtain direct objective measures of the theory's central theoretical construct – cognitive load – have proved elusive. This obstacle represents the most significant outstanding challenge for successfully embedding the theoretical and experimental work on cognitive load in empirical data from authentic learning situations. Progress to date on the theoretical and practical approaches to cognitive load are discussed along with the influences of individual differences on cognitive load in order to assess the prospects for the development and application of direct empirical measures of cognitive load especially in technology-rich contexts

The bi-objective travelling salesman problem with profits and its connection to computer networks.

This is an interdisciplinary work in Computer Science and Operational Research. As it is well known, these two very important research fields are strictly connected. Among other aspects, one of the main areas where this interplay is strongly evident is Networking. As far as most recent decades have seen a constant growing of every kind of network computer connections, the need for advanced algorithms that help in optimizing the network performances became extremely relevant. Classical Optimization-based approaches have been deeply studied and applied since long time. However, the technology evolution asks for more flexible and advanced algorithmic approaches to model increasingly complex network configurations. In this thesis we study an extension of the well known Traveling Salesman Problem (TSP): the Traveling Salesman Problem with Profits (TSPP). In this generalization, a profit is associated with each vertex and it is not necessary to visit all vertices. The goal is to determine a route through a subset of nodes that simultaneously minimizes the travel cost and maximizes the collected profit. The TSPP models the problem of sending a piece of information through a network where, in addition to the sending costs, it is also important to consider what “profit” this information can get during its routing. Because of its formulation, the right way to tackled the TSPP is by Multiobjective Optimization algorithms. Within this context, the aim of this work is to study new ways to solve the problem in both the exact and the approximated settings, giving all feasible instruments that can help to solve it, and to provide experimental insights into feasible networking instances

Straddling the intersection

Music technology straddles the intersection between art and science and presents those who choose to work within its sphere with many practical challenges as well as creative possibilities. The paper focuses on four main areas: secondary education, higher education, practice and research and finally collaboration. The paper emphasises the importance of collaboration in tackling the challenges of interdisciplinarity and in influencing future technological developments