Development of adult education

I. INTRODUCTORY - Early efforts to establish Adult education - philanthropy - great educationalists of the Nineteenth Century. pp 1 - 36. • II. THE INFLUENCE OF THE MECHANICS' INSTITUTIONS. pp.37 - 56. • III. THE CONTINUATION SCHOOL SYSTEM - rise of technical schools - establishment of Department of Education. pp.57 - 82. • IV. UNIVERSITY EXTENSION. pp.83 - 105. • V. WORKERS' EDUCATIONAL ASSOCIATION. pp.106 - 135. • VI. RECENT DEVELOPMENTS - W.E.A. work Continued - education within factories - Birmingham University and Trade Unions - Misfits in industry. pp.136 - 154. • VII. ADULT EDUCATION ABROAD - European Countries - America - The Colonies - Australia - Conclusion. pp.155 - 177.In conclusion one might add that although there yet remains a great deal to he done in the educational world, yet education alone and unaided can never bring about the longed-for reforms which many enthusiasts would claim. Education alone can never raise to a high level the standard of living of certain classes. We no longer believe with Socrates that knowledge is virtue. Indeed education alone can never affect to any great degree those who are apathetic, who do not spontaneously take advantage of what it offers. All that can be done in the realm of adult education is to provide a means to betterment mentally, morally, and physically for those who will of their own accord accept of it. Education can never be thrust upon adults. It must be provided in response to a spontaneous demand. In that respect therefore, adult education depends upon primary and secondary education. If they are unsuccessful adult education is almost an impossibility. Again, if education is to achieve anything very much it must co-operate with other arts and sciences which have to deal with human beings. "At present the educational campaign to direct our energies to better advantage is carried on by various field services, which, working without any knowledge of the general purpose and scope of other operations, are marked by much confusion of intention and enormous waste of energy. The responsibility for this disadvantage must lie in the patch-work character of most of our schemes of educational reform, social improvement and betterment of living conditions. Real progress towards such betterment demands a biological point of view, and intensive co-operation in the numerous departments of research. The word life should be associated with words suggesting the commonest phases of human behaviour - home, school, college, social and political life,the life of the courts, prisons, reformatories, and of individual persons and groups, such as the life of a community, nation and race

Ab initio calculations of stationary points on the benzene-Ar and p-difluorobenzene-Ar potential energy surfaces: barriers to bound orbiting states

The potential energy surfaces of the van der Waals complexes benzene–Ar and p-difluorobenzene– Ar have been investigated at the second-order Møller–Plesset (MP2) level of theory with the aug-cc-pVDZ basis set. Calculations were performed with unconstrained geometry optimization for all stationary points. This study has been performed to elucidate the nature of a conflict between experimental results from dispersed fluorescence and velocity map imaging (VMI). The inconsistency is that spectra for levels of p-difluorobenzene–Ar and –Kr below the dissociation thresholds determined by VMI show bands where free p-difluorobenzene emits, suggesting that dissociation is occurring. We proposed that the bands observed in the dispersed fluorescence spectra are due to emission from states in which the rare gas atom orbits the aromatic chromophore; these states are populated by intramolecular vibrational redistribution from the initially excited level [S. M. Bellm, R. J. Moulds, and W. D. Lawrance, J. Chem. Phys. 115, 10709 (2001)]. To test this proposition, stationary points have been located on both the benzene–Ar and p-difluorobenzene–Ar potential energy surfaces (PESs) to determine the barriers to this orbiting motion. Comparison with previous single point CCSD(T) calculations of the benzene–Ar PES has been used to determine the amount by which the barriers are overestimated at the MP2 level. As there is little difference in the comparable regions of the benzene–Ar and p-difluorobenzene–Ar PESs, the overestimation is expected to be similar for p-difluorobenzene–Ar. Allowing for this overestimation gives the barrier to movement of the Ar atom around the pDFB ring via the valley between the H atoms as [less than or equal to] 204 cm⁻¹ in So (including zero point energy). From the estimated change upon electronic excitation, the corresponding barrier in S1 is estimated to be [less than or equal to] 225 cm⁻¹. This barrier is less than the 240 cm⁻¹ energy of 30², the vibrational level for which the anomalous "free p-difluorobenzene" bands were observed in dispersed fluorescence from p-difluorobenzene–Ar, supporting our hypothesis for the origin of these bands.Rebecca J. Moulds, Mark A. Buntine and Warren D. Lawranc

The Development of Teaching Skills to Support Active Learning in University Science (ALIUS)

This paper describes an Australian Learning and Teaching Council funded project for which Learning Design is encompassed in the broadest sense. ALIUS (Active Learning In University Science) takes the design of learning back to the learning experiences created for students. ALIUS is not about designing a particular activity, or subject, or course, but rather the development of a method, or process, by which we have re-designed the way in which learning occurs in large university classrooms world wide

ASELL : the advancing science by enhancing learning in the laboratory project

Most science educators and researchers will agree that the laboratory experience ranks as a major factor that influences students’ attitudes to their science courses. Consequently, good laboratory programs should play a major role in influencing student learning and performance. The laboratory program can be pivotal in defining a student\u27s experience in the sciences, and if done poorly, can be a major contributing factor in causing disengagement from the subject area. The challenge remains to provide students with laboratory activities that are relevant, engaging and offer effective learning opportunities

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

PIDT: A Novel Decision Tree Algorithm Based on Parameterised Impurities and Statistical Pruning Approaches

In the process of constructing a decision tree, the criteria for selecting the splitting attributes influence the performance of the model produced by the decision tree algorithm. The most well-known criteria such as Shannon entropy and Gini index, suffer from the lack of adaptability to the datasets. This paper presents novel splitting attribute selection criteria based on some families of pa-rameterised impurities that we proposed here to be used in the construction of optimal decision trees. These criteria rely on families of strict concave functions that define the new generalised parameterised impurity measures which we ap-plied in devising and implementing our PIDT novel decision tree algorithm. This paper proposes also the S-condition based on statistical permutation tests, whose purpose is to ensure that the reduction in impurity, or gain, for the selected attrib-ute is statistically significant. We implemented the S-pruning procedure based on the S-condition, to prevent model overfitting. These methods were evaluated on a number of simulated and benchmark datasets. Experimental results suggest that by tuning the parameters of the impurity measures and by using our S-pruning method, we obtain better decision tree classifiers with the PIDT algorithm

The ACELL project: Student participation, professional development, and improving laboratory learning

The Australian Physical Chemistry Enhanced Laboratory Learning (APCELL) project (Barrie, Buntine, Jamie and Kable 2001a, 2001b, 2001c), and its all-of-chemistry successor, ACELL (Read, 2006a) are examples of contemporary efforts to meet the challenge of engaging students in laboratory activities which are both chemically and educationally sound. The project is collaborative; it overcomes many of the significant constraints imposed by the unavailability of time from individual teachers, by drawing on the resources and expertise of multiple institutions as well as chemical and pedagogical expertise. The project continues to produce a range of tangible outcomes, including chemistry education research publications, a database of freely available tested experiments, and pedagogical design tools (all available from http://acell.chem.usyd.edu.au/). Objective evidence is required to support the putative notion that the A(P)CELL concept is of benefit to educators as they design and evaluate laboratory programs; collection and evaluation of such empirical data is essential if views such as those of Hawkes (2004) are to be effectively challenged. In this paper we report on the views of staff and student delegates to the February 2006 ACELL Educational Workshop

Incorporating Social Context and Domain Knowledge for Entity Recognition

Recognizing entity instances in documents according to a knowl-edge base is a fundamental problem in many data mining applica-tions. The problem is extremely challenging for short documents in complex domains such as social media and biomedical domains. Large concept spaces and instance ambiguity are key issues that need to be addressed. Most of the documents are created in a social context by common authors via social interactions, such as reply and citations. Such social contexts are largely ignored in the instance-recognition liter-ature. How can users ’ interactions help entity instance recognition? How can the social context be modeled so as to resolve the ambi-guity of different instances? In this paper, we propose the SOCINST model to formalize the problem into a probabilistic model. Given a set of short document