Systematic Influences on Teaching Evaluations : The Case for Caution

The evaluation of teaching and learning has become an important activity in tertiary education institutions. Student surveys provide information about student perceptions and judgments of a particular subject. However, as is widely recognised, the appropriate interpretation of this data is problematic. There is a large literature, mainly for the US, on the use and usefulness of student subject evaluations. This literature has highlighted a number of ‘mitigating factors’ such as subject difficulty, discipline area, etc., that should be taken into account in interpreting the results of these questionnaires. In this paper we examine 8 years of QOT responses from an Economics Department in an Australian University which accounted for more than 79,000 student subject enrolments in 565 subjects. The purpose of this analysis is to establish how the information contained in these data can be used to interpret the responses. In particular, we determine to what extent other factors besides the instructor in charge of the subject have an impact on the raw average student evaluation scores. We find that the following characteristics of the students in these classes had an influence on the average QOT score: year level, enrolment size, the quantitative nature of the subject, the country of origin of the students, the proportion that are female, Honours status of the student, the differential in their mark from previous marks, quality of workbook, quality of textbook and the relative QOT score versus other subjects taught at the same time. However, a number of other factors proposed in the literature to be important influences were found not to be. These include the student’s fee paying status, whether they attended a public, private or catholic secondary school, which other faculty within the University they came from, and if the subject was taught in multiple sessions.

Approach to equilibrium of diffusion in a logarithmic potential

The late-time distribution function P(x,t) of a particle diffusing in a one-dimensional logarithmic potential is calculated for arbitrary initial conditions. We find a scaling solution with three surprising features: (i) the solution is given by two distinct scaling forms, corresponding to a diffusive (x ~ t^(1/2)) and a subdiffusive (x ~ t^{\gamma} with a given {\gamma} < 1/2) length scale, respectively, (ii) the overall scaling function is selected by the initial condition, and (iii) depending on the tail of the initial condition, the scaling exponent which characterizes the scaling function is found to exhibit a transition from a continuously varying to a fixed value.Comment: 4 pages, 3 figures; Published versio

An Efficient Data Structure for Dynamic Two-Dimensional Reconfiguration

In the presence of dynamic insertions and deletions into a partially reconfigurable FPGA, fragmentation is unavoidable. This poses the challenge of developing efficient approaches to dynamic defragmentation and reallocation. One key aspect is to develop efficient algorithms and data structures that exploit the two-dimensional geometry of a chip, instead of just one. We propose a new method for this task, based on the fractal structure of a quadtree, which allows dynamic segmentation of the chip area, along with dynamically adjusting the necessary communication infrastructure. We describe a number of algorithmic aspects, and present different solutions. We also provide a number of basic simulations that indicate that the theoretical worst-case bound may be pessimistic.Comment: 11 pages, 12 figures; full version of extended abstract that appeared in ARCS 201

Interaction of reed and acoustic resonator in clarinetlike systems

Sound emergence in clarinetlike instruments is investigated in terms of instability of the static regime. Various models of reed-bore coupling are considered, from the pioneering work of Wilson and Beavers ["Operating modes of the clarinet", J. Acoust. Soc. Am. 56, 653--658 (1974)] to more recent modeling including viscothermal bore losses and vena contracta at the reed inlet. The pressure threshold above which these models may oscillate as well as the frequency of oscillation at threshold are calculated. In addition to Wilson and Beavers' previous conclusions concerning the role of the reed damping in the selection of the register the instrument will play on, the influence of the reed motion induced flow is also emphasized, particularly its effect on playing frequencies, contributing to reduce discrepancies between Wilson and Beavers' experimental results and theory, despite discrepancies still remain concerning the pressure threshold. Finally, analytical approximations of the oscillating solution based on Fourier series expansion are obtained in the vicinity of the threshold of oscillation. This allows to emphasize the conditions which determine the nature of the bifurcation (direct or inverse) through which the note may emerge, with therefore important consequences on the musical playing performances

The Physicist's Guide to the Orchestra

An experimental study of strings, woodwinds (organ pipe, flute, clarinet, saxophone and recorder), and the voice was undertaken to illustrate the basic principles of sound production in music instruments. The setup used is simple and consists of common laboratory equipment. Although the canonical examples (standing wave on a string, in an open and closed pipe) are easily reproduced, they fail to explain the majority of the measurements. The reasons for these deviations are outlined and discussed.Comment: 11 pages, 10 figures (jpg files). Submitted to European Journal of Physic

Speaker-independent emotion recognition exploiting a psychologically-inspired binary cascade classification schema

In this paper, a psychologically-inspired binary cascade classification schema is proposed for speech emotion recognition. Performance is enhanced because commonly confused pairs of emotions are distinguishable from one another. Extracted features are related to statistics of pitch, formants, and energy contours, as well as spectrum, cepstrum, perceptual and temporal features, autocorrelation, MPEG-7 descriptors, Fujisakis model parameters, voice quality, jitter, and shimmer. Selected features are fed as input to K nearest neighborhood classifier and to support vector machines. Two kernels are tested for the latter: Linear and Gaussian radial basis function. The recently proposed speaker-independent experimental protocol is tested on the Berlin emotional speech database for each gender separately. The best emotion recognition accuracy, achieved by support vector machines with linear kernel, equals 87.7%, outperforming state-of-the-art approaches. Statistical analysis is first carried out with respect to the classifiers error rates and then to evaluate the information expressed by the classifiers confusion matrices. © Springer Science+Business Media, LLC 2011

Agronomic performance and transcriptional analysis of carotenoid biosynthesis in fruits of transgenic HighCaro and control tomato lines under field conditions

Genetic manipulation of carotenoid biosynthesis in higher plants has been the objective of a number of biotechnology programs, e.g. the Golden Rice Program. However, tomato (Solanumlycopersicum L.), which naturally accumulates lycopene in fruits, has attracted the attention of many groups who have manipulated it to increase or diversify carotenoid accumulation. One of the most significant achievements was “HighCaro (HC),” a transgenic tomato plant constitutively expressing the tomato lycopene beta-cyclase (tLcy-b), that produces orange fruits due to the complete conversion of lycopene to β-carotene. In this article we report the results of a field trial conducted in Metaponto (Italy) on HC and on two control genotypes to evaluate the stability of the transgenic trait and their yield performances. Transcriptional regulation of eight genes involved in carotenogenesis was assayed by quantitative real-time PCR (qRT-PCR) analysis on fruits collected at four distinct development stages. Statistical analysis results demonstrated that in field conditions the transgene maintained its ability to induce the conversion of lycopene to β-carotene. Moreover, agronomic performances and fruit quality in the transgenic line were not impaired by this metabolic disturbance. Results of qRT-PCR analysis suggested that transcription of PSY-1, PDS and ZDS genes were developmentally regulated in both genotypes. Unexpectedly, Lcy-b expression in transgenic fruits was also developmentally regulated, despite the fact that the gene was driven by a constitutive promoter. Our data provide evidence that in photosynthetic cells a strict and aspecific mechanism controls the level of transcripts until the onset of chromoplasts differentiation, at which point a gene-specific control on transcription takes place

Implementing EM and Viterbi algorithms for Hidden Markov Model in linear memory

<p>Abstract</p> <p>Background</p> <p>The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clustering. A linear memory procedure recently proposed by <it>Miklós, I. and Meyer, I.M. </it>describes a memory sparse version of the Baum-Welch algorithm with modifications to the original probabilistic table topologies to make memory use independent of sequence length (and linearly dependent on state number). The original description of the technique has some errors that we amend. We then compare the corrected implementation on a variety of data sets with conventional and checkpointing implementations.</p> <p>Results</p> <p>We provide a correct recurrence relation for the emission parameter estimate and extend it to parameter estimates of the Normal distribution. To accelerate estimation of the prior state probabilities, and decrease memory use, we reverse the originally proposed forward sweep. We describe different scaling strategies necessary in all real implementations of the algorithm to prevent underflow. In this paper we also describe our approach to a linear memory implementation of the Viterbi decoding algorithm (with linearity in the sequence length, while memory use is approximately independent of state number). We demonstrate the use of the linear memory implementation on an extended Duration Hidden Markov Model (DHMM) and on an HMM with a spike detection topology. Comparing the various implementations of the Baum-Welch procedure we find that the checkpointing algorithm produces the best overall tradeoff between memory use and speed. In cases where sequence length is very large (for Baum-Welch), or state number is very large (for Viterbi), the linear memory methods outlined may offer some utility.</p> <p>Conclusion</p> <p>Our performance-optimized Java implementations of Baum-Welch algorithm are available at <url>http://logos.cs.uno.edu/~achurban</url>. The described method and implementations will aid sequence alignment, gene structure prediction, HMM profile training, nanopore ionic flow blockades analysis and many other domains that require efficient HMM training with EM.</p