Rough sets based reasoning and pattern mining for a two-stage information filtering system

This paper presents a novel two-stage information filtering model which combines the merits of term-based and pattern- based approaches to effectively filter sheer volume of information. In particular, the first filtering stage is supported by a novel rough analysis model which efficiently removes a large number of irrelevant documents, thereby addressing the overload problem. The second filtering stage is empowered by a semantically rich pattern taxonomy mining model which effectively fetches incoming documents according to the specific information needs of a user, thereby addressing the mismatch problem. The experiments have been conducted to compare the proposed two-stage filtering (T-SM) model with other possible "term-based + pattern-based" or "term-based + term-based" IF models. The results based on the RCV1 corpus show that the T-SM model significantly outperforms other types of "two-stage" IF models.

Estoppel in the face of consumer protection in land transactions- judicial reasoning or judicial intuition

Nationally, there is much legislation regulating land sale transactions, particularly in relation to seller disclosure of information. The statutes require strict compliance by a seller failing which, in general, a buyer can terminate the contract. In a number of instances, when buyers have sought to exercise these rights, sellers have alleged that buyers have either expressly or by conduct waived their rights to rely upon these statutes. This article examines the nature of these rights in this context, whether they are capable of waiver and, if so, what words or conduct might be sufficient to amount to waiver. The analysis finds that the law is in a very unsatisfactory state, that the operation of those rules that can be identified as having relevance are unevenly applied and concludes that sellers have, in the main, been unsuccessful in defeating buyers' statutory rights as a result of an alleged waiver by those buyers.

Young children’s beliefs about including others in their play: Social and moral reasoning about inclusion and exclusion

Previous research has emphasised the importance of active citizenship in the early years for the development of a tolerant and cohesive Australian society. This paper presents findings related to young children’s beliefs about exclusion based on gender and race. The findings draw from a larger study exploring the development of children’s moral and social values and teachers’ beliefs and practices related to teaching for moral development, in the early years of school in Australia. This current study examined reasoning about exclusion in early childhood with children aged 5-8 years. One hundred children from seven schools (Preparatory to Grade 3) answered questions relating to two scenarios in which the children had to make a decision about whether to include others of different gender or race in their play. The majority of children believed that others should be included in their play, regardless of their gender or race. When asked to explain, the children primarily gave reasons related to moral concern and fairness. Children were then asked whether they would continue to include or exclude if their friends (social consensus) or teachers (authority) suggested otherwise. The majority of children maintained their beliefs when beliefs to the contrary were voiced by their peers and teachers. The implications of these responses are discussed.

Using ‘think aloud’ as a strategy for learning clinical reasoning in high fidelity case-based simulation for undergraduate nursing students

AIMS This paper reports on the implementation of a research project that trials an educational strategy implemented over six months of an undergraduate third year nursing curriculum. This project aims to explore the effectiveness of ‘think aloud’ as a strategy for learning clinical reasoning for students in simulated clinical settings. BACKGROUND Nurses are required to apply and utilise critical thinking skills to enable clinical reasoning and problem solving in the clinical setting [1]. Nursing students are expected to develop and display clinical reasoning skills in practice, but may struggle articulating reasons behind decisions about patient care. For students learning to manage complex clinical situations, teaching approaches are required that make these instinctive cognitive processes explicit and clear [2-5]. In line with professional expectations, nursing students in third year at Queensland University of Technology (QUT) are expected to display clinical reasoning skills in practice. This can be a complex proposition for students in practice situations, particularly as the degree of uncertainty or decision complexity increases [6-7]. The ‘think aloud’ approach is an innovative learning/teaching method which can create an environment suitable for developing clinical reasoning skills in students [4, 8]. This project aims to use the ‘think aloud’ strategy within a simulation context to provide a safe learning environment in which third year students are assisted to uncover cognitive approaches that best assist them to make effective patient care decisions, and improve their confidence, clinical reasoning and active critical reflection on their practice. MEHODS In semester 2 2011 at QUT, third year nursing students will undertake high fidelity simulation, some for the first time commencing in September of 2011. There will be two cohorts for strategy implementation (group 1= use think aloud as a strategy within the simulation, group 2= not given a specific strategy outside of nursing assessment frameworks) in relation to problem solving patient needs. Students will be briefed about the scenario, given a nursing handover, placed into a simulation group and an observer group, and the facilitator/teacher will run the simulation from a control room, and not have contact (as a ‘teacher’) with students during the simulation. Then debriefing will occur as a whole group outside of the simulation room where the session can be reviewed on screen. The think aloud strategy will be described to students in their pre-simulation briefing and allow for clarification of this strategy at this time. All other aspects of the simulations remain the same, (resources, suggested nursing assessment frameworks, simulation session duration, size of simulation teams, preparatory materials). RESULTS Methodology of the project and the challenges of implementation will be the focus of this presentation. This will include ethical considerations in designing the project, recruitment of students and implementation of a voluntary research project within a busy educational curriculum which in third year targets 669 students over two campuses. CONCLUSIONS In an environment of increasingly constrained clinical placement opportunities, exploration of alternate strategies to improve critical thinking skills and develop clinical reasoning and problem solving for nursing students is imperative in preparing nurses to respond to changing patient needs. References 1. Lasater, K., High-fidelity simulation and the development of clinical judgement: students' experiences. Journal of Nursing Education, 2007. 46(6): p. 269-276. 2. Lapkin, S., et al., Effectiveness of patient simulation manikins in teaching clinical reasoning skills to undergraduate nursing students: a systematic review. Clinical Simulation in Nursing, 2010. 6(6): p. e207-22. 3. Kaddoura, M.P.C.M.S.N.R.N., New Graduate Nurses' Perceptions of the Effects of Clinical Simulation on Their Critical Thinking, Learning, and Confidence. The Journal of Continuing Education in Nursing, 2010. 41(11): p. 506. 4. Banning, M., The think aloud approach as an educational tool to develop and assess clinical reasoning in undergraduate students. Nurse Education Today, 2008. 28: p. 8-14. 5. Porter-O'Grady, T., Profound change:21st century nursing. Nursing Outlook, 2001. 49(4): p. 182-186. 6. Andersson, A.K., M. Omberg, and M. Svedlund, Triage in the emergency department-a qualitative study of the factors which nurses consider when making decisions. Nursing in Critical Care, 2006. 11(3): p. 136-145. 7. O'Neill, E.S., N.M. Dluhy, and C. Chin, Modelling novice clinical reasoning for a computerized decision support system. Journal of Advanced Nursing, 2005. 49(1): p. 68-77. 8. Lee, J.E. and N. Ryan-Wenger, The "Think Aloud" seminar for teaching clinical reasoning: a case study of a child with pharyngitis. J Pediatr Health Care, 1997. 11(3): p. 101-10.

Swapping as the "Hello World" of relational reasoning : replications, reflections and extensions

At the previous conference in this series, Corney, Lister and Teague presented research results showing relationships between code writing, code tracing and code explaining, from as early as week 3 of semester. We concluded that the problems some students face in learning to program start very early in the semester. In this paper we report on our replication of that experiment, at two institutions, where one is the same as the original institution. In some cases, we did not find the same relationship between explaining code and writing code, but we believe this was because our teachers discussed the code in lectures between the two tests. Apart from that exception, our replication results at both institutions are consistent with our original study.

Some empirical results for neo-Piagetian reasoning in novice programmers and the relationship to code explanation questions

Recent research on novice programmers has suggested that they pass through neo-Piagetian stages: sensorimotor, preoperational, and concrete operational stages, before eventually reaching programming competence at the formal operational stage. This paper presents empirical results in support of this neo-Piagetian perspective. The major novel contributions of this paper are empirical results for some exam questions aimed at testing novices for the concrete operational abilities to reason with quantities that are conserved, processes that are reversible, and properties that hold under transitive inference. While the questions we used had been proposed earlier by Lister, he did not present any data for how students performed on these questions. Our empirical results demonstrate that many students struggle to answer these problems, despite the apparent simplicity of these problems. We then compare student performance on these questions with their performance on six explain in plain English questions.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.

A qualitative think aloud study of the early Neo-Piagetian stages of reasoning in novice programmers

Recent research indicates that some of the difficulties faced by novice programmers are manifested very early in their learning. In this paper, we present data from think aloud studies that demonstrate the nature of those difficulties. In the think alouds, novices were required to complete short programming tasks which involved either hand executing ("tracing") a short piece of code, or writing a single sentence describing the purpose of the code. We interpret our think aloud data within a neo-Piagetian framework, demonstrating that some novices reason at the sensorimotor and preoperational stages, not at the higher concrete operational stage at which most instruction is implicitly targeted.

Using ‘think aloud’ as a strategy for improving clinical reasoning in high fidelity case-based simulation for undergraduate nursing students.

Theme Paper for Curriculum innovation and enhancement theme AIM: This paper reports on a research project that trialled an educational strategy implemented in an undergraduate nursing curriculum. The project aimed to explore the effectiveness of ‘think aloud’ as a strategy for improving clinical reasoning for students in simulated clinical settings. BACKGROUND: Nurses are required to apply and utilise critical thinking skills to enable clinical reasoning and problem solving in the clinical setting (Lasater, 2007). Nursing students are expected to develop and display clinical reasoning skills in practice, but may struggle articulating reasons behind decisions about patient care. The ‘think aloud’ approach is an innovative learning/teaching method which can create an environment suitable for developing clinical reasoning skills in students (Banning, 2008, Lee and Ryan-Wenger, 1997). This project used the ‘think aloud’ strategy within a simulation context to provide a safe learning environment in which third year students were assisted to uncover cognitive approaches to assist in making effective patient care decisions, and improve their confidence, clinical reasoning and active critical reflection about their practice. MEHODS: In semester 2 2011 at QUT, third year nursing students undertook high fidelity simulation (some for the first time), commencing in September of 2011. There were two cohorts for strategy implementation (group 1= used think aloud as a strategy within the simulation, group 2= no specific strategy outside of nursing assessment frameworks used by all students) in relation to problem solving patient needs. The think aloud strategy was described to students in their pre-simulation briefing and allowed time for clarification of this strategy. All other aspects of the simulations remained the same, (resources, suggested nursing assessment frameworks, simulation session duration, size of simulation teams, preparatory materials). Ethics approval has been obtained for this project. RESULTS: Results of a qualitative analysis (in progress- will be completed by March 2012) of student and facilitator reports on students’ ability to meet the learning objectives of solving patient problems using clinical reasoning and experience with the ‘think aloud’ method will be presented. A comparison of clinical reasoning learning outcomes between the two groups will determine the effect on clinical reasoning for students responding to patient problems. CONCLUSIONS: In an environment of increasingly constrained clinical placement opportunities, exploration of alternate strategies to improve critical thinking skills and develop clinical reasoning and problem solving for nursing students is imperative in preparing nurses to respond to changing patient needs.

Reasoning about component similarity in building product models from the construction perspective

Identifying the design features that impact construction is essential to developing cost effective and constructible designs. The similarity of building components is a critical design feature that affects method selection, productivity, and ultimately construction cost and schedule performance. However, there is limited understanding of what constitutes similarity in the design of building components and limited computer-based support to identify this feature in a building product model. This paper contributes a feature-based framework for representing and reasoning about component similarity that builds on ontological modelling, model-based reasoning and cluster analysis techniques. It describes the ontology we developed to characterize component similarity in terms of the component attributes, the direction, and the degree of variation. It also describes the generic reasoning process we formalized to identify component similarity in a standard product model based on practitioners' varied preferences. The generic reasoning process evaluates the geometric, topological, and symbolic similarities between components, creates groupings of similar components, and quantifies the degree of similarity. We implemented this reasoning process in a prototype cost estimating application, which creates and maintains cost estimates based on a building product model. Validation studies of the prototype system provide evidence that the framework is general and enables a more accurate and efficient cost estimating process.

Genome-scale phylogeny and the detection of systematic biases

Phylogenetic inference from sequences can be misled by both sampling (stochastic) error and systematic error (nonhistorical signals where reality differs from our simplified models). A recent study of eight yeast species using 106 concatenated genes from complete genomes showed that even small internal edges of a tree received 100% bootstrap support. This effective negation of stochastic error from large data sets is important, but longer sequences exacerbate the potential for biases (systematic error) to be positively misleading. Indeed, when we analyzed the same data set using minimum evolution optimality criteria, an alternative tree received 100% bootstrap support. We identified a compositional bias as responsible for this inconsistency and showed that it is reduced effectively by coding the nucleotides as purines and pyrimidines (RY-coding), reinforcing the original tree. Thus, a comprehensive exploration of potential systematic biases is still required, even though genome-scale data sets greatly reduce sampling error.

Students' perceptions of teacher biases : experimental economics in schools

We put forward a new experimental economics design with monetary incentives to estimate students’ perceptions of grading discrimination. We use this design in a large field experiment which involved 1,200 British students in grade 8 classrooms across 29 schools. In this design, students are given an endowment they can invest on a task where payoff depends on performance. The task is a written verbal test which is graded non anonymously by their teacher, in a random half of the classrooms, and graded anonymously by an external examiner in the other random half of the classrooms. We find significant evidence that students’ choices reflect perceptions of biases in teachers’ grading practices. Our results show systematic gender interaction effects: male students invest less with female teachers than with male teachers while female students invest more with male teachers than with female teachers. Interestingly, female students’ perceptions are not in line with actual discrimination: Teachers tend to give better grades to students of their own gender. Results do not suggest that ethnicity and socioeconomic status play a role. .