Digital tablets as a tool for blended learning in power engineering education

Digital tablets have been identified as a tool for enabling blended learning and supporting online teaching and learning. A small scale trial was undertaken to assess the effectiveness of this technology when applied to power engineering education. Critical findings and experiences gained from this trial, including potential benefits, presentation techniques and the resulting student feedback are presented in this paper.

Engaging creativity through an action learning and action research process to develop an Indigenous art exhibition

In most art exhibitions, the creative part of the exhibition is assumed to be the artworks on display. But for the Capricornia Arts Mob’s first collective art exhibition in Rockhampton during NAIDOC Week in 2012, the process of developing the exhibition became the focus of creative action learning and action research. In working together to produce a multi-media exhibition, we learned about the collaborative processes and time required to develop a combined exhibition. We applied Indigenous ways of working – including yarning, cultural respect, cultural protocols, mentoring young people, providing a culturally safe working environment and sharing both time and food – to develop our first collective art exhibition. We developed a process that allowed us to ask deep questions, engage in a joint journey of learning, and develop our collective story. This paper explores the processes that the Capricornia Arts Mob used to develop the exhibition for NAIDOC 2012.

Dictionary learning and sparse coding on Grassmann manifolds : an extrinsic solution

Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of linear subspaces, which form Riemannian structures known as Grassmann manifolds. To this end, we propose to embed Grassmann manifolds into the space of symmetric matrices by an isometric mapping, which enables us to devise a closed-form solution for updating a Grassmann dictionary, atom by atom. Furthermore, to handle non-linearity in data, we propose a kernelised version of the dictionary learning algorithm. Experiments on several classification tasks (face recognition, action recognition, dynamic texture classification) show that the proposed approach achieves considerable improvements in discrimination accuracy, in comparison to state-of-the-art methods such as kernelised Affine Hull Method and graph-embedding Grassmann discriminant analysis.

Emotional climate and high quality learning experiences in science teacher education

The role of emotion during learning encounters in science teacher education is under-researched and under-theorized. In this case study we explore the emotional climates, that is, the collective states of emotional arousal, of a preservice secondary science education class to illuminate practice for producing and reproducing high quality learning experiences for preservice science teachers. Theories related to the sociology of emotions informed our analyses from data sources such as preservice teachers’ perceptions of the emotional climate of their class, emotional facial expressions, classroom conversations, and cogenerative dialogue. The major outcome from our analyses was that even though preservice teachers reported high positive emotional climate during the professor’s science demonstrations, they also valued the professor’s in the moment reflections on her teaching that were associated with low emotional climate ratings. We co-relate emotional climate data and preservice teachers’ comments during cogenerative dialogue to expand our understanding of high quality experiences and emotional climate in science teacher education. Our study also contributes refinements to research perspectives on emotional climate.

Designing for collaborative learning spaces : an academic staff development pilot program

To prepare for the delivery of new Bachelor of Science units in collaborative learning spaces, academic and professional staff at Queensland University of Technology piloted an academic development program over the period of a semester. The program was informed by Rogers’ theory of innovation and diffusion (2003) and structured according to Wilson’s framework for faculty development (2007). Through a series of workshops and group mentoring activities, the program modelled inquiry-based learning in a collaborative learning space, and the participants designed and practiced the delivery of teaching activities. This paper provides a preliminary evaluation of the effectiveness of the pilot based on survey responses from participants, notes from the development team who coordinated the program and audience feedback from the final showcase session. The design and structure of the program is discussed as well as possible future directions.

Post-quantum key exchange for the TLS protocol from the ring learning with errors problem

Lattice-based cryptographic primitives are believed to offer resilience against attacks by quantum computers. We demonstrate the practicality of post-quantum key exchange by constructing cipher suites for the Transport Layer Security (TLS) protocol that provide key exchange based on the ring learning with errors (R-LWE) problem, we accompany these cipher suites with a rigorous proof of security. Our approach ties lattice-based key exchange together with traditional authentication using RSA or elliptic curve digital signatures: the post-quantum key exchange provides forward secrecy against future quantum attackers, while authentication can be provided using RSA keys that are issued by today's commercial certificate authorities, smoothing the path to adoption. Our cryptographically secure implementation, aimed at the 128-bit security level, reveals that the performance price when switching from non-quantum-safe key exchange is not too high. With our R-LWE cipher suites integrated into the Open SSL library and using the Apache web server on a 2-core desktop computer, we could serve 506 RLWE-ECDSA-AES128-GCM-SHA256 HTTPS connections per second for a 10 KiB payload. Compared to elliptic curve Diffie-Hellman, this means an 8 KiB increased handshake size and a reduction in throughput of only 21%. This demonstrates that provably secure post-quantum key-exchange can already be considered practical.

Improving deep convultional neural networks with unsupervised feature learning

The latest generation of Deep Convolutional Neural Networks (DCNN) have dramatically advanced challenging computer vision tasks, especially in object detection and object classification, achieving state-of-the-art performance in several computer vision tasks including text recognition, sign recognition, face recognition and scene understanding. The depth of these supervised networks has enabled learning deeper and hierarchical representation of features. In parallel, unsupervised deep learning such as Convolutional Deep Belief Network (CDBN) has also achieved state-of-the-art in many computer vision tasks. However, there is very limited research on jointly exploiting the strength of these two approaches. In this paper, we investigate the learning capability of both methods. We compare the output of individual layers and show that many learnt filters and outputs of the corresponding level layer are almost similar for both approaches. Stacking the DCNN on top of unsupervised layers or replacing layers in the DCNN with the corresponding learnt layers in the CDBN can improve the recognition/classification accuracy and training computational expense. We demonstrate the validity of the proposal on ImageNet dataset.

Enterprise education: Learning through personal experience

This paper outlines the development of a reflective process through which student feelings are brought to the surface to advance their learning outcomes. A key notion in relation to the capacity of student development is the ability of students to alter their collective habits of thought and in turn the nature of the learning environment. The paper examines student reflection in the context of students' heightened awareness of self and their potential influence on their environment. The notion of 'surfacing feelings' is used to describe the outcome of individual and group reflection through which several parties become aware of the active reflections of individual students, thereby increasing the potential depth of overall reflection. Finally, the author considers the transferability of the ideas discussed to other educational contexts.