Learning in and beyond small business advisory programmes

The purpose of this paper is to analyse how participants learn in small business advisory programmes and to explore the impact of these learning programmes on the development of reflective learning dispositions in participants. The research involves two case studies of small business advisory programmes in Queensland, a state of Australia. One involves training in the use of GPS/GIS technology amongst rural SMEs and the other seeks to develop improved management and operational capabilities in regional and metropolitan manufacturing SMEs. Face to face semi-structured interviews were conducted throughout rural, regional and metropolitan Queensland with participants, trainers and senior executives in the administering organisations that ran the programmes. Learning in these programmes occurs through a combination of interaction with others and the adoption of practice-based and learner-centred processes. The impact of the programmes on participants includes the development of reflective learning dispositions, improved confidence in learning and appreciation of the value of new knowledge to their business. The research suggests that small business training programmes have the potential to affect the development of critical reflective learning dispositions in participants which is of fundamental importance to the development of a learning or knowledge economy.

Australian Learning and Teaching Council, Learning and Teaching Academic Standards Statement for Architecture

The development of the Learning and Teaching Academic Standards Statement for Architecture (the Statement) centred on requirements for the Master of Architecture and proceeded alongside similar developments in the building and construction discipline under the guidance and support of the Australian Deans of Built Environment and Design (ADBED). Through their representation of Australian architecture programs, ADBED have provided high-level leadership for the Learning and Teaching Academic Standards Project in Architecture (LTAS Architecture). The threshold learning outcomes (TLOs), the description of the nature and extent of the discipline, and accompanying notes were developed through wide consultation with the discipline and profession nationally. They have been considered and debated by ADBED on a number of occasions and have, in their fi nal form, been strongly endorsed by the Deans. ADBED formed the core of the Architecture Reference Group (chaired by an ADBED member) that drew together representatives of every peak organisation for the profession and discipline in Australia. The views of the architectural education community and profession have been provided both through individual submissions and the voices of a number of peak bodies. Over two hundred individuals from the practising profession, the academic workforce and the student cohort have worked together to build consensus about the capabilities expected of a graduate of an Australian Master of Architecture degree. It was critical from the outset that the Statement should embrace the wisdom of the greater ‘tribe’, should ensure that graduates of the Australian Master of Architecture were eligible for professional registration and, at the same time, should allow for scope and diversity in the shape of Australian architectural education. A consultation strategy adopted by the Discipline Scholar involved meetings and workshops in Perth, Melbourne, Sydney, Canberra and Brisbane. Stakeholders from all jurisdictions and most universities participated in the early phases of consultation through a series of workshops that concluded late in October 2010. The Draft Architecture Standards Statement was formed from these early meetings and consultation in respect of that document continued through early 2011. This publication represents the outcomes of work to establish an agreed standards statement for the Master of Architecture. Significant further work remains to ensure the alignment of professional accreditation and recognition procedures with emerging regulatory frameworks cascading from the establishment of the Tertiary Education Quality and Standards Agency (TEQSA). The Australian architecture community hopes that mechanisms can be found to integrate TEQSA’s quality assurance purpose with well-established and understood systems of professional accreditation to ensure the good standing of Australian architectural education into the future. The work to build renewed and integrated quality assurance processes and to foster the interests of this project will continue, for at least the next eighteen months, under the auspices of Australian Learning and Teaching Council (ALTC)-funded Architecture Discipline Network (ADN), led by ADBED and Queensland University of Technology. The Discipline Scholar gratefully acknowledges the generous contributions given by those in stakeholder communities to the formulation of the Statement. Professional and academic colleagues have travelled and gathered to shape the Standards Statement. Debate has been vigorous and spirited and the Statement is rich with the purpose, critical thinking and good judgement of the Australian architectural education community. The commitments made to the processes that have produced this Statement reflect a deep and abiding interest by the constituency in architectural education. This commitment bodes well for the vibrancy and productivity of the emergent Architecture Discipline Network (ADN). Endorsement, in writing, was received from the Australian Institute of Architects National Education Committee (AIA NEC): The National Education Committee (NEC) of the Australian Institute of Architects thank you for your work thus far in developing the Learning and Teaching Academic Standards for Architecture In particular, we acknowledge your close consultation with the NEC on the project along with a comprehensive cross-section of the professional and academic communities in architecture. The TLOs with the nuanced levels of capacities – to identify, develop, explain, demonstrate etc – are described at an appropriate level to be understood as minimum expectations for a Master of Architecture graduate. The Architects Accreditation Council of Australia (AACA) has noted: There is a clear correlation between the current processes for accreditation and what may be the procedures in the future following the current review. The requirement of the outcomes as outlined in the draft paper to demonstrate capability is an appropriate way of expressing the measure of whether the learning outcomes have been achieved. The measure of capability as described in the outcome statements is enhanced with explanatory descriptions in the accompanying notes.

A holistic blended design studio model : a basis for exploring and expanding learning opportunities

While the studio environment has been promoted as an ideal educational setting for project-based disciplines, few qualitative studies have been undertaken in a comprehensive way (Bose, 2007). This study responds to this need by adopting Grounded Theory methodology in a qualitative comparative approach. The research aims to explore the limitations and benefits of a face-to-face (f2f) design studio as well as a virtual design studio (VDS) as experienced by architecture students and educators at an Australian university in order to find the optimal combination for a blended environment to maximize learning. The main outcome is a holistic multidimensional blended model being sufficiently flexible to adapt to various setting, in the process, facilitating constructivist learning through self-determination, self-management, and personalization of the learning environment.

Enhancing foreign language learning through listening strategy delivered in L1: an experimental study

Listening used in language teaching refers to a complex process that allows us to understand spoken language. The current study, conducted in Iran with an experimental design, investigated the effectiveness of teaching listening strategies delivered in L1 (Persian) and its effect on listening comprehension in L2. Five listening strategies: Guessing, making inferences, identifying topics, repetition, and note-taking were taught over 14 weeks during a semester. Sixty lower intermediate female participants came from two EFL classrooms in an English language institute. The experimental class (n = 30) who listened to their classroom activities performed better (t value = 10.083) than the control class using a methodology that led learners through five listening strategies in Persian. The same teacher taught the students in the control class (n = 30), who listened to the same classroom listening activities without any of the above listening strategies. A pre and post listening test made by a group of experts in the language institute assessed the effect of teaching listening strategies delivered in L1. Results gathered on the post intervention listening test revealed that listening strategies delivered in L1 led to a statistically significant improvement in their discrete listening scores compared with the control group.

Learning domain-specific sentiment lexicons for predicting product sales

Generic sentiment lexicons have been widely used for sentiment analysis these days. However, manually constructing sentiment lexicons is very time-consuming and it may not be feasible for certain application domains where annotation expertise is not available. One contribution of this paper is the development of a statistical learning based computational method for the automatic construction of domain-specific sentiment lexicons to enhance cross-domain sentiment analysis. Our initial experiments show that the proposed methodology can automatically generate domain-specific sentiment lexicons which contribute to improve the effectiveness of opinion retrieval at the document level. Another contribution of our work is that we show the feasibility of applying the sentiment metric derived based on the automatically constructed sentiment lexicons to predict product sales of certain product categories. Our research contributes to the development of more effective sentiment analysis system to extract business intelligence from numerous opinionated expressions posted to the Web

Teaching and assessing critical thinking : the interaction of student approaches to learning and teaching approaches

This study explored the relationship among student approaches to learning and teaching methods on critical thinking in two business units. Key findings included differences in critical thinking scores between student approaches to learning and some evidence of an interaction between student approaches to learning and critical thinking teach method (immersion vs. infusion). Possible explanations for the results are examined and implications for developing critical thinking skills across a degree discussed. What is apparent is that as Universities move towards program-wide level assessment of critical thinking, further work is required in terms of the design of critical thinking teaching interventions and assessment at the unit, school, and degree level. The session will discuss the challenges in developing critical thinking programs in individual units and at the Faculty level.

A comparison of methods for classifying clinical samples based on proteomics data : a case study for statistical and machine learning approaches

The discovery of protein variation is an important strategy in disease diagnosis within the biological sciences. The current benchmark for elucidating information from multiple biological variables is the so called “omics” disciplines of the biological sciences. Such variability is uncovered by implementation of multivariable data mining techniques which come under two primary categories, machine learning strategies and statistical based approaches. Typically proteomic studies can produce hundreds or thousands of variables, p, per observation, n, depending on the analytical platform or method employed to generate the data. Many classification methods are limited by an n≪p constraint, and as such, require pre-treatment to reduce the dimensionality prior to classification. Recently machine learning techniques have gained popularity in the field for their ability to successfully classify unknown samples. One limitation of such methods is the lack of a functional model allowing meaningful interpretation of results in terms of the features used for classification. This is a problem that might be solved using a statistical model-based approach where not only is the importance of the individual protein explicit, they are combined into a readily interpretable classification rule without relying on a black box approach. Here we incorporate statistical dimension reduction techniques Partial Least Squares (PLS) and Principal Components Analysis (PCA) followed by both statistical and machine learning classification methods, and compared them to a popular machine learning technique, Support Vector Machines (SVM). Both PLS and SVM demonstrate strong utility for proteomic classification problems.