Effective Teaching and Learning of Science in the Outdoors: A Blended Model

This paper reports on an innovative Continuing Professional Development (CPD) programme which addressed transition issues and issues with conducting outdoor work and attitudes towards science through ‘Shared Learning' days between elementary and middle school transition classes. Teachers supported each other to overcome issues with conducting outdoor work and contributed their expertise from their educational stage. The project utilised a blended CPD approach of workshops, coteaching and in-class support and was based upon a wealth earlier successful CPD programmes to result in a sound theoretical framework.
The outcomes were measured using a thorough mixed-methods approach. This paper will report on the achieved outcomes with effective outdoor learning as the vehicle to overcome identified issues and key challenges for policy development.

Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification

In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.