Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

The impact of mathematics teaching efficacy on teachers’ pedagogical practices

This study explores the pedagogical practices of 167 Year 4 and 160 Year 8 New Zealand mathematics teachers who have different levels of mathematics teaching efficacy. Using data from the National Monitoring Study of Student Achievement 2013, the teacher questionnaire items believed to be the indicators of mathematics teaching efficacy were selected, represented by six items such as “I feel confident about teaching maths”. Then, low, mid, and high efficacious teachers were identified and compared to see how they differed with respect to their teaching profile and the frequency they used effective pedagogies when teaching mathematics (italicised below) (Anthony & Walshaw, 2007). Twenty eight percent of Year 4 and 41% of Year 8 teachers had high mathematics teaching efficacy. Compared with the other teachers, teachers with high mathematics teaching efficacy were better able to provide an ethic of care in their classroom, they more frequently arranged their classrooms for learning to enable students to collaborate, and more frequently expected their students to communicate their thinking and debate ideas with others. They more frequently provided students with worthwhile mathematical tasks, they more frequently provided opportunities for their students to build on their own thinking, and to explore how new learning linked to or changed what they already knew. They more frequently expected their students to make mathematical connections by reflecting on their learning, to use multiple representations, and use ideas and skills from different curriculum areas

2012 Annual Research Symposium Abstract Book

2012 annual volume of abstracts for science research projects conducted by students at Trinity College

Ultra-high-speed imaging of bubbles interacting with cells and tissue

Ultrasound contrast microbubbles are exploited in molecular imaging, where bubbles are directed to target cells and where their high-scattering cross section to ultrasound allows for the detection of pathologies at a molecular level. In therapeutic applications vibrating bubbles close to cells may alter the permeability of cell membranes, and these systems are therefore highly interesting for drug and gene delivery applications using ultrasound. In a more extreme regime bubbles are driven through shock waves to sonoporate or kill cells through intense stresses or jets following inertial bubble collapse. Here, we elucidate some of the underlying mechanisms using the 25-Mfps camera Brandaris128, resolving the bubble dynamics and its interactions with cells. We quantify acoustic microstreaming around oscillating bubbles close to rigid walls and evaluate the shear stresses on nonadherent cells. In a study on the fluid dynamical interaction of cavitation bubbles with adherent cells, we find that the nonspherical collapse of bubbles is responsible for cell detachment. We also visualized the dynamics of vibrating microbubbles in contact with endothelial cells followed by fluorescent imaging of the transport of propidium iodide, used as a membrane integrity probe, into these cells showing a direct correlation between cell deformation and cell membrane permeability

The Multimodal Tutor: Adaptive Feedback from Multimodal Experiences

This doctoral thesis describes the journey of ideation, prototyping and empirical testing of the Multimodal Tutor, a system designed for providing digital feedback that supports psychomotor skills acquisition using learning and multimodal data capturing. The feedback is given in real-time with machine-driven assessment of the learner's task execution. The predictions are tailored by supervised machine learning models trained with human annotated samples. The main contributions of this thesis are: a literature survey on multimodal data for learning, a conceptual model (the Multimodal Learning Analytics Model), a technological framework (the Multimodal Pipeline), a data annotation tool (the Visual Inspection Tool) and a case study in Cardiopulmonary Resuscitation training (CPR Tutor). The CPR Tutor generates real-time, adaptive feedback using kinematic and myographic data and neural networks