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.

Quo Vadis? Reliable and Practical Rule Extraction from Neural Networks

Rule extraction from neural network algorithms have been investigated for two decades and there have been significant applications. Despite this level of success, rule extraction from neural network methods are generally not part of data mining tools, and a significant commercial breakthrough may still be some time away. This paper briefly reviews the state-of-the-art and points to some of the obstacles, namely a lack of evaluation techniques in experiments and larger benchmark data sets. A significant new development is the view that rule extraction from neural networks is an interactive process which actively involves the user. This leads to the application of assessment and evaluation techniques from information retrieval which may lead to a range of new methods.

Female genital mutilation : legal, attitudinal and practical reform

Female genital mutilation (FGM) is a cultural practice common in many Islamic societies. It involves the deliberate, non-therapeutic physical modification of young girls’ genitalia. FGM can take several forms, ranging from less damaging incisions to actual removal of genitalia and narrowing or even closing of the vagina. While often thought to be required by religion, FGM both predates and has no basis in the Koran. Rather, it is a cultural tradition, motivated by a patriarchal social desire to control female bodies to ensure virginity at marriage (preserving family honour), and to prevent infidelity by limiting sexual desire. In the USA and Australia in 2010, peak medical bodies considered endorsing the medical administration of a ‘lesser’ form of FGM. The basis for this was pragmatic: it would be preferable to satisfy patients’ desire for FGM in medically-controlled conditions, rather than have these patients seek it, possibly in more severe forms, under less safe conditions. While arguments favouring medically-administered FGM were soon overcome, the prospect of endorsing FGM illuminated the issue in these two Western countries and beyond. This paper will review the nature of FGM, its physical and psychological health consequences, and Australian laws prohibiting FGM. Then, it will scan recent developments in Africa, where FGM has been made illegal by a growing number of nations and by the Protocol to the African Charter on Human and Peoples’ Rights 2003 (the Maputo Protocol), but is still proving difficult to eradicate. Finally, based on arguments derived from theories of rights, health evidence, and the historical and religious contexts, this paper will ask whether an absolute human right against FGM can be developed.

Practical decision support system evaluation for consultant selection

The widespread development of Decision Support System (DSS) in construction indicate that the evaluation of software become more important than before. However, it is identified that most research in construction discipline did not attempt to assess its usability. Therefore, little is known about the approach on how to properly evaluate a DSS for specific problem. In this paper, we present a practical framework that can be guidance for DSS evaluation. It focuses on how to evaluate software that is dedicatedly designed for consultant selection problem. The framework features two main components i.e. Sub-system Validation and Face Validation. Two case studies of consultant selection at Malaysian Department of Irrigation and Drainage were integrated in this framework. Some inter-disciplinary area such as Software Engineering, Human Computer Interaction (HCI) and Construction Project Management underpinned the discussion of the paper. It is anticipated that this work can foster better DSS development and quality decision making that accurately meet the client’s expectation and needs

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.

How do the learning outcomes of students compare in units with different levels of practical work? A comparative study about the relation between Problem-­Based Learning and assessment approaches

The literature supporting the notion that active, student-centered learning is superior to passive, teacher-centered instruction is encyclopedic (Bonwell & Eison, 1991; Bruning, Schraw, & Ronning, 1999; Haile, 1997a, 1997b, 1998; Johnson, Johnson, & Smith, 1999). Previous action research demonstrated that introducing a learning activity in class improved the learning outcomes of students (Mejias, 2010). People acquire knowledge and skills through practice and reflection, not by watching and listening to others telling them how to do something. In this context, this project aims to find more insights about the level of interactivity in the curriculum a class should have and its alignment with assessment so the intended learning outcomes (ILOs) are achieved. In this project, interactivity is implemented in the form of problem- based learning (PBL). I present the argument that a more continuous formative feedback when implemented with the correct amount of PBL stimulates student engagement bringing enormous benefits to student learning. Different levels of practical work (PBL) were implemented together with two different assessment approaches in two subjects. The outcomes were measured using qualitative and quantitative data to evaluate the levels of student engagement and satisfaction in the terms of ILOs.

A practical approach for identifying expected solution performance and robustness in operations research applications

A practical approach for identifying solution robustness is proposed for situations where parameters are uncertain. The approach is based upon the interpretation of a probability density function (pdf) and the definition of three parameters that describe how significant changes in the performance of a solution are deemed to be. The pdf is constructed by interpreting the results of simulations. A minimum number of simulations are achieved by updating the mean, variance, skewness and kurtosis of the sample using computationally efficient recursive equations. When these criterions have converged then no further simulations are needed. A case study involving several no-intermediate storage flow shop scheduling problems demonstrates the effectiveness of the approach.

Practical physical activity measurement in youth : a review of contemporary approaches

Background: The accurate evaluation of physical activity levels amongst youth is critical for quantifying physical activity behaviors and evaluating the effect of physical activity interventions. The purpose of this review is to evaluate contemporary approaches to physical activity evaluation amongst youth. Data sources: The literature from a range of sources was reviewed and synthesized to provide an overview of contemporary approaches for measuring youth physical activity. Results: Five broad categories are described: self-report, instrumental movement detection, biological approaches, direct observation, and combined methods. Emerging technologies and priorities for future research are also identified. Conclusions: There will always be a trade-off between accuracy and available resources when choosing the best approach for measuring physical activity amongst youth. Unfortunately, cost and logistical challenges may prohibit the use of "gold standard" physical activity measurement approaches such as doubly labelled water. Other objective methods such as heart rate monitoring, accelerometry, pedometry, indirect calorimetry, or a combination of measures have the potential to better capture the duration and intensity of physical activity, while self-reported measures are useful for capturing the type and context of activity.

Practical client puzzles in the standard model

Client puzzles are cryptographic problems that are neither easy nor hard to solve. Most puzzles are based on either number theoretic or hash inversions problems. Hash-based puzzles are very efficient but so far have been shown secure only in the random oracle model; number theoretic puzzles, while secure in the standard model, tend to be inefficient. In this paper, we solve the problem of constucting cryptographic puzzles that are secure int he standard model and are very efficient. We present an efficient number theoretic puzzle that satisfies the puzzle security definition of Chen et al. (ASIACRYPT 2009). To prove the security of our puzzle, we introduce a new variant of the interval discrete logarithm assumption which may be of independent interest, and show this new problem to be hard under reasonable assumptions. Our experimental results show that, for 512-bit modulus, the solution verification time of our proposed puzzle can be up to 50x and 89x faster than the Karame-Capkum puzzle and the Rivest et al.'s time-lock puzzle respectively. In particular, the solution verification tiem of our puzzle is only 1.4x slower than that of Chen et al.'s efficient hash based puzzle.

Practical stability of approximating discrete-time filters with respect to model mismatch

This paper establishes practical stability results for an important range of approximate discrete-time filtering problems involving mismatch between the true system and the approximating filter model. Practical stability is established in the sense of an asymptotic bound on the amount of bias introduced by the model approximation. Our analysis applies to a wide range of estimation problems and justifies the common practice of approximating intractable infinite dimensional nonlinear filters by simpler computationally tractable filters.

Practical considerations for integrating alternate reality gaming into science education

In this article, I present my experience with integrating an alternate reality gaming (ARG) framework into a pre-service science teacher education course. My goal is to provide an account of my experiences that can inform other science education practitioners at the tertiary and secondary levels that wish to adopt a similar approach in their classes. A game was designed to engage pre-service teachers with issues surrounding the declining enrolments in science, technology, engineering and mathematics disciplines (i.e., the STEM crisis; Tytler, 2007) and ways of re-engaging learners with STEM subjects. The use of ARG in science education is highly innovative. Literature on the use of ARG for educational purposes is scarce so in the article I have drawn on a range of available literature on gaming and ARG to define what it is and to suggest how it can be included in school science classrooms.

A practical signal processing approach for condition monitoring of low speed machinery using Peak-Hold-Down-Sample algorithm

A simple and effective down-sample algorithm, Peak-Hold-Down-Sample (PHDS) algorithm is developed in this paper to enable a rapid and efficient data transfer in remote condition monitoring applications. The algorithm is particularly useful for high frequency Condition Monitoring (CM) techniques, and for low speed machine applications since the combination of the high sampling frequency and low rotating speed will generally lead to large unwieldy data size. The effectiveness of the algorithm was evaluated and tested on four sets of data in the study. One set of the data was extracted from the condition monitoring signal of a practical industry application. Another set of data was acquired from a low speed machine test rig in the laboratory. The other two sets of data were computer simulated bearing defect signals having either a single or multiple bearing defects. The results disclose that the PHDS algorithm can substantially reduce the size of data while preserving the critical bearing defect information for all the data sets used in this work even when a large down-sample ratio was used (i.e., 500 times down-sampled). In contrast, the down-sample process using existing normal down-sample technique in signal processing eliminates the useful and critical information such as bearing defect frequencies in a signal when the same down-sample ratio was employed. Noise and artificial frequency components were also induced by the normal down-sample technique, thus limits its usefulness for machine condition monitoring applications.