Elements of Better Assessment for the Improvement of Learning

Building a community of shared practice at the classroom level calls for clarity about the important assessment capabilities and dispositions of teachers, especially when teachers are expected to take a direct focus on learning. In this chapter, we present new ways of thinking about teachers’ assessment literacies, offering a formulation of better assessment for the improvement of learning, including three elements, namely (i) assessment criteria and standards; (ii) the teacher’s professional judgment; and (iii) social moderation. The potential of the first element lies in teachers’ classroom practices that deliberately embed assessment criteria and standards in pedagogy in productive ways. The second element involves the engagement of teachers and students in judgment practice, that develops the understanding that judgment involves more than the application of explicit or stated criteria. More fundamental is the matter of how teachers bring to bear stated features of quality and other intellectual and experiential resources in arriving at judgment. That is to say, they range across and orient to explicit (stated), tacit (unstated) and meta-criteria in judgment making. These insights have direct relevance to teachers’ efforts to develop students’ own evaluative experience, especially as this involves students working with stated features of quality for self-assessment and peer-assessment purposes. Further, practices for social moderation are discussed, giving examples of good practice in moderation, how teachers experience moderation and the potential benefits of various types.

The power of naming : the multifaceted value of learning students’ names

The modern day Australian law school is expected to educate and engage law students. Ideally law school will instil a sense of passion (or at least appreciation) for the law, promote a positive professional identity, foster a sense of community, and provide general support to law students. Collectively, the Australian legal academy is struggling with these goals. Significant numbers of students feel isolated, disconnected and unengaged throughout their tertiary legal education. Teaching students from increasingly diverse backgrounds, who spend less time on campus and less face-to-face time in class, many law academics feel ill-equipped to respond to the challenge of engaging law students in time and cost efficient ways. Intentionally learning and using student names has potential to humanise the law school experience, build community, and positively impact upon the wellbeing of students and staff.

Comparing different approach and avoidance models of learning and personality in the prediction of work, university, and leadership outcomes

Jackson (2005) developed a hybrid model of personality and learning, known as the learning styles profiler (LSP) which was designed to span biological, socio-cognitive, and experiential research foci of personality and learning research. The hybrid model argues that functional and dysfunctional learning outcomes can be best understood in terms of how cognitions and experiences control, discipline, and re-express the biologically based scale of sensation-seeking. In two studies with part-time workers undertaking tertiary education (N equals 137 and 58), established models of approach and avoidance from each of the three different research foci were compared with Jackson's hybrid model in their predictiveness of leadership, work, and university outcomes using self-report and supervisor ratings. Results showed that the hybrid model was generally optimal and, as hypothesized, that goal orientation was a mediator of sensation-seeking on outcomes (work performance, university performance, leader behaviours, and counterproductive work behaviour). Our studies suggest that the hybrid model has considerable promise as a predictor of work and educational outcomes as well as dysfunctional outcomes.

The experience of learning in “The Cube” : Queensland University of Technology’s giant interactive multimedia environment

In this paper we report findings of the first phase of an investigation, which explored the experience of learning amongst high-level managers, project leaders and visitors in QUT’s “Cube”. “The Cube” is a giant, interactive, multi-media display; an award-winning configuration that hosts several interactive projects. The research team worked with three groups of participants to understand the relationship between a) the learning experiences that were intended in the establishment phase; b) the learning experiences that were enacted through the design and implementation of specific projects; and c) the lived experiences of learning of visitors interacting with the system. We adopted phenomenography as a research approach, to understand variation in people’s understandings and lived experiences of learning in this environment. The project was conducted within the first twelve months of The Cube being open to visitors.

Conceptions of learning held by Aboriginal students in a tertiary program in Indigenous primary health care

This paper is a description of a pilot investigation into conceptions of learning held by a sample of 10 Aboriginal students in a Bachelors degree courses. Results from this study suggest that this group of students view and approach learning in much the same way as other university students. They mostly hold quantitative conceptions of learning and use repetitive strategies which are potentially at odds with the objectives and procedures of the problems based program in which they are studying.

On the operationalisation of conceptions of learning in higher education and their association with students’ knowledge and experiences of their learning

Conceptions of learning, as well as other associated aspects of prior knowledge, are theoretically important factors in influencing the manner in which the content and context of learning are engaged. The present study reports on: (a) the operationalisation of some of these factors aimed at isolating sources of explanatory variation that can be used for modelling purposes; and (b) a conservative exploration of the discriminatory power of, and exhibited patterns of association between, such sources of variation as have been isolated. Based on a conservative analytical approach, the results of the present study do not support a single clearly defined empirical model of conceptions of learning and associated constructs. Instead, there is consistent evidence that underlying empirical structures appear to be sensitive to the response context and other factors.

From policy borrowing to implementation : an illuminative evaluation of learning and teaching in higher education in Australia (2002 to 2008)

This study documents and theorises the consequences of the 2003 Australian Government Reform Package focussed on learning and teaching in Higher Education during the period 2002 to 2008. This is achieved through the perspective of program evaluation and the methodology of illuminative evaluation. The findings suggest that the three national initiatives of that time, Learning and Teaching Performance Fund (LTPF), Australian Learning and Teaching Council (ALTC), and Australian Universities Quality Agency (AUQA), were successful in repositioning learning and teaching as a core activity in universities. However, there were unintended consequences brought about by international policy borrowing, when the short-lived nature of LTPF suggests a legacy of quality compliance rather than one of quality enrichment.

Factors influencing Saudi Arabian optometry candidates' career choices and institution of learning. Why do Saudi students choose to study optometry?

Optometry is a primary health-care profession (PHCP) and this study aimed to elucidate the factors influencing the choice of optometry as a career for Saudi students, the students' perceptions of optometry and the effect of gender. METHODS Two hundred and forty-seven students whose average age was 21.7 ± 1.5 (SD) years and who are currently enrolled in two colleges of optometry in Saudi Arabia--King Saud University (KSU) and Qassim University (QU)--completed self-administered questionnaires. The survey included questions concerning demography, career first choice, career perception and factors influencing career choices. RESULTS The response rate was 87.6 per cent and there were 161 male (64.9 per cent) students. Seventy-nine per cent of the participants were from KSU (males and females) and 20.6 per cent were from QU (only males). Seventy-three per cent come from Riyadh and 19 per cent are from Qassim province. Regarding the first choice for their careers, the females (92 per cent) were 0.4 times more likely (p = 0.012) to choose optometry than males (78.3 per cent). The males were significantly more likely to be influenced by the following factors: the Doctor of Optometry (OD) programs run at both universities, good salary and prospects (p < 0.05, for all). The women were significantly less likely to be influenced by another individual (p = 0.0004). Generally, more than two-thirds of the respondents viewed the desire to help others, professional prestige and the new OD programs as the three most influential factors in opting for a career in optometry. CONCLUSION Females were more likely to opt for a career in optometry and males were more likely to be influenced by the new OD programs, good salary and job prospects. Service provision to others in the community was a primary motivation to opt for a career in optometry among young Saudis.

Analyzing the impact of learning inputs on near-to-far terrain traversability estimation

With the increasing need to adapt to new environments, data-driven approaches have been developed to estimate terrain traversability by learning the rover’s response on the terrain based on experience. Multiple learning inputs are often used to adequately describe the various aspects of terrain traversability. In a complex learning framework, it can be difficult to identify the relevance of each learning input to the resulting estimate. This paper addresses the suitability of each learning input by systematically analyzing the impact of each input on the estimate. Sensitivity Analysis (SA) methods provide a means to measure the contribution of each learning input to the estimate variability. Using a variance-based SA method, we characterize how the prediction changes as one or more of the input changes, and also quantify the prediction uncertainty as attributed from each of the inputs in the framework of dependent inputs. We propose an approach built on Analysis of Variance (ANOVA) decomposition to examine the prediction made in a near-to-far learning framework based on multi-task GP regression. We demonstrate the approach by analyzing the impact of driving speed and terrain geometry on the prediction of the rover’s attitude and chassis configuration in a Marsanalogue terrain using our prototype rover Mawson.

Editorial for Journal of Learning Design, 6(3) - "Special issue: Legal education and curriculum renewal"

Welcome to this special edition of the Journal of Learning Design which focuses on legal education and curriculum renewal in law. At the outset ,we would like to thank the editors of the Journal, Margaret Lloyd and Nan Bahr for agreeing to host this special edition. The special edition is timely as legal education in Australia is enjoying a lively period of renewal.

Asymptotic behavior of a hierarchical system of learning automata

Learning automata arranged in a two-level hierarchy are considered. The automata operate in a stationary random environment and update their action probabilities according to the linear-reward- -penalty algorithm at each level. Unlike some hierarchical systems previously proposed, no information transfer exists from one level to another, and yet the hierarchy possesses good convergence properties. Using weak-convergence concepts it is shown that for large time and small values of parameters in the algorithm, the evolution of the optimal path probability can be represented by a diffusion whose parameters can be computed explicitly.

A hierarchical system of learning automata that can learn die globally optimal path

Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

A Hierarchical System of Learning Automata

A learning automaton operating in a random environment updates its action probabilities on the basis of the reactions of the environment, so that asymptotically it chooses the optimal action. When the number of actions is large the automaton becomes slow because there are too many updatings to be made at each instant. A hierarchical system of such automata with assured c-optimality is suggested to overcome that problem.The learning algorithm for the hierarchical system turns out to be a simple modification of the absolutely expedient algorithm known in the literature. The parameters of the algorithm at each level in the hierarchy depend only on the parameters and the action probabilities of the previous level. It follows that to minimize the number of updatings per cycle each automaton in the hierarchy need have only two or three actions.

A cooperative game of a pair of learning automata

A cooperative game played in a sequential manner by a pair of learning automata is investigated in this paper. The automata operate in an unknown random environment which gives a common pay-off to the automata. Necessary and sufficient conditions on the functions in the reinforcement scheme are given for absolute monotonicity which enables the expected pay-off to be monotonically increasing in any arbitrary environment. As each participating automaton operates with no information regarding the other partner, the results of the paper are relevant to decentralized control.