Interactive sensory objects for and by people with learning disabilities

This project engages people with learning disabilities as co-researchers and co-designers in the development of multisensory interactive artworks, with the aim of making museums or heritage sites more interesting, meaningful, and fun. This article describes our explorations, within this context, of a range of technologies including squishy circuits, littleBits, and easy-build websites, and presents examples of objects created by the co-researchers such as “sensory boxes” and interactive buckets, baskets, and boots. Public engagement is an important part of the project and includes an annual public event and seminar day, a blog rich with photos and videos of the workshops, and an activities book to give people ideas for creating their own sensory explorations of museums and heritage sites.

littleBits go LARGE: making electronics more accessible to people with learning disabilities

The “littleBits go LARGE" project extends littleBits electronic modules, an existing product that is aimed at simplifying electronics for a wide range of audiences. In this project we augment the littleBits modules to make them more accessible to people with learning disabilities. We will demonstrate how we have made the modules easier to handle and manipulate physically, and how we are augmenting the design of the modules to make their functions more obvious and understandable.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

Joint multiple dictionary learning for tensor sparse coding

Traditional dictionary learning algorithms are used for finding a sparse representation on high dimensional data by transforming samples into a one-dimensional (1D) vector. This 1D model loses the inherent spatial structure property of data. An alternative solution is to employ Tensor Decomposition for dictionary learning on their original structural form —a tensor— by learning multiple dictionaries along each mode and the corresponding sparse representation in respect to the Kronecker product of these dictionaries. To learn tensor dictionaries along each mode, all the existing methods update each dictionary iteratively in an alternating manner. Because atoms from each mode dictionary jointly make contributions to the sparsity of tensor, existing works ignore atoms correlations between different mode dictionaries by treating each mode dictionary independently. In this paper, we propose a joint multiple dictionary learning method for tensor sparse coding, which explores atom correlations for sparse representation and updates multiple atoms from each mode dictionary simultaneously. In this algorithm, the Frequent-Pattern Tree (FP-tree) mining algorithm is employed to exploit frequent atom patterns in the sparse representation. Inspired by the idea of K-SVD, we develop a new dictionary update method that jointly updates elements in each pattern. Experimental results demonstrate our method outperforms other tensor based dictionary learning algorithms.

Beneath a learning management system: understanding the human information interaction in information systems

Studies on learning management systems have largely been technical in nature with an emphasis on the evaluation of the human computer interaction (HCI) processes in using the LMS. This paper reports a study that evaluates the information interaction processes on an eLearning course used in teaching an applied Statistics course. The eLearning course is used as a synonym for information systems. The study explores issues of missing context in stored information in information systems. Using the semiotic framework as a guide, the researchers evaluated an existing eLearning course with the view to proposing a model for designing improved eLearning courses for future eLearning programmes. In this exploratory study, a survey questionnaire is used to collect data from 160 participants on an eLearning course in Statistics in Applied Climatology. The views of the participants are analysed with a focus on only the human information interaction issues. Using the semiotic framework as a guide, syntactic, semantic, pragmatic and social context gaps or problems were identified. The information interactions problems identified include ambiguous instructions, inadequate information, lack of sound, interface design problems among others. These problems affected the quality of new knowledge created by the participants. The researchers thus highlighted the challenges of missing information context when data is stored in an information system. The study concludes by proposing a human information interaction model for improving the information interaction quality issues in the design of eLearning course on learning management platforms and those other information systems.

Becoming a written word: eye movements reveal order of acquisition effects following incidental exposure to new words during silent reading

We know that from mid-childhood onwards most new words are learned implicitly via reading; however, most word learning studies have taught novel items explicitly. We examined incidental word learning during reading by focusing on the well-documented finding that words which are acquired early in life are processed more quickly than those acquired later. Novel words were embedded in meaningful sentences and were presented to adult readers early (day 1) or later (day 2) during a five-day exposure phase. At test adults read the novel words in semantically neutral sentences. Participants’ eye movements were monitored throughout exposure and test. Adults also completed a surprise memory test in which they had to match each novel word with its definition. Results showed a decrease in reading times for all novel words over exposure, and significantly longer total reading times at test for early than late novel words. Early-presented novel words were also remembered better in the offline test. Our results show that order of presentation influences processing time early in the course of acquiring a new word, consistent with partial and incremental growth in knowledge occurring as a function of an individual’s experience with each word.

Interactive learning in UK construction practice: examining the role of BIM process standards

From a construction innovation systems perspective, firms acquire knowledge from suppliers, clients, universities and institutional environment. Building information modelling (BIM) involves these firms using new process standards. To understand the implications on interactive learning using BIM process standards, a case study is conducted with the UK operations of a multinational construction firm. Data is drawn from: a) two workshops involving the firm and a wider industry group, b) observations of practice in the BIM core team and in three ongoing projects, c) 12 semi-structured interviews; and d) secondary publications. The firm uses a set of BIM process standards (IFC, PAS 1192, Uniclass, COBie) in its construction activities. It is also involved in a pilot to implement the COBie standard, supported by technical and management standards for BIM, such as Uniclass and PAS1192. Analyses suggest that such BIM process standards unconsciously shapes the firm's internal and external interactive learning processes. Internally standards allow engineers to learn from each through visualising 3D information and talking around designs with operatives to address problems during construction. Externally, the firm participates in trial and pilot projects involving other construction firms, government agencies, universities and suppliers to learn about the standard and access knowledge to solve its specific design problems. Through its BIM manager, the firm provides feedback to standards developers and information technology suppliers. The research contributes by articulating how BIM process standards unconsciously change interactive learning processes in construction practice. Further research could investigate these findings in the wider UK construction innovation system.

Experiential learning from entrepreneurial failure

This paper examines the phenomenon of 'entrepreneurial failure' from a UK regionally-based qualitative study, being that of explanations for failure provided by entrepreneurial CEOs. This paper contends that there are valuable lessons to be learned, from explanations provided of failure, that may reduce the very high recorded mortality rates of entrepreneurial businesses, in particular that of nascent entrepreneurs. Our intention is to make nascent entrepreneurs and their advisors more aware of the consequences of the likely personal risks they will be assuming, especially before they embark on their new business ventures. This paper focuses strongly on entrepreneurial 'personality characteristics' which can detrimentally influence the quality of decision-making. We provide data of some 'experiential learning from failure' from our case studies, that were compiled from interviews with the former directors, following their completion of the questionnaire survey. We describe 'failed entrepreneurs' who have successfully restarted their businesses as 'phoenix' entrepreneurs.

New occupancy

The chapter is part of a book which has contributors from interior architecture education across the world. New Occupancy refers to the re use of existing structures in educational environments and how they can be successfully adapted and reinvented to accommodate new client requirements and also create exciting stimulating learning environments.

Interactive sensory objects for and by people with learning disabilities

This project engages people with learning disabilities to participate as co-researchers and explore museum interpretation through multisensory workshops using microcontrollers and sensors to enable alternative interactive visitor experiences in museums and heritage sites. This article describes how the project brings together artists, engineers, and experts in multimedia advocacy, as well as people with learning disabilities in the co-design of interactive multisensory objects that replicate or respond to objects of cultural significance in our national collections. Through a series of staged multi-sensory art and electronics workshops, people with learning disabilities explore how the different senses could be utilised to augment existing artefacts or create entirely new ones. The co-researchers employ multimedia advocacy tools to reflect on and to communicate their experiences and findings.

Using problem-based learning in a chemistry practical class for pharmacy students and engaging them with feedback

Objective: To introduce a new approach to problem based learning (PBL) used in the context of medicinal chemistry practical class teaching pharmacy students. Design: The described chemistry practical is based on independent studies by small groups of undergraduate students (4-5), who design their own practical work taking relevant professional standards into account. Students are carefully guided by feedback and acquire a set of skills important to their future profession as healthcare professionals. This model has been tailored to the application of PBL in a chemistry practical class setting for a large student cohort (150 students). Assessment: The achievement of learning outcomes is based on the submission of relevant documentation including a certificate of analysis, in addition to peer assessment. Some of the learning outcomes are also assessed in the final written examination at the end of the academic year. Conclusion: The described design of a novel PBL chemistry laboratory course for pharmacy students has been found to be successful. Self-reflective learning and engagement with feedback were encouraged, and students enjoyed the challenging learning experience. Skills that are highly essential for the students’ future careers as healthcare professionals are promoted.

Interactive sensory objects for and by people with learning disabilities

This project engages people with learning disabilities to participate as co-researchers and explore museum interpretation through multisensory workshops using microcontrollers and sensors to enable alternative interactive visitor experiences in museums and heritage sites. This article describes how the project brings together artists, engineers, and experts in multimedia advocacy, as well as people with learning disabilities in the co-design of interactive multisensory objects that replicate or respond to objects of cultural significance in our national collections. Through a series of staged multi-sensory art and electronics workshops, people with learning disabilities explore how the different senses could be utilised to augment existing artefacts or create entirely new ones. The co-researchers employ multimedia advocacy tools to reflect on and to communicate their experiences and findings.