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Learning Approach (learning + approach)
Kinds of Learning Approach Selected AbstractsReconsidering Regulation and Governance Theory: A Learning ApproachLAW & POLICY, Issue 2 2009JOHN S. F. WRIGHT Theories and frameworks for regulation of particular industries or types of behavior have grown in richness in recent years. This article identifies three perspectives within contemporary regulatory theory: "normative,""descriptive," and "poststructuralist" perspectives. We ask whether contemporary models of regulatory governance arrangements adequately capture and explain the characteristics and operation of existing regulatory spaces. We outline three key models linked to these perspectives (responsive regulation, smart regulation, and nodal governance) and discuss their relevance with specific reference to one complex case study, the gambling industry in a federal polity, Australia, where the regulatory arrangements are quite diverse. We argue that regulatory theory needs to remain flexible if it is to inform an understanding of concrete regulatory challenges, thereby assisting analysts and practitioners to assess current and potential approaches for improved regulatory governance arrangements. Accordingly, we build a case for considering a learning perspective on regulation and governance theory linked to pragmatism. [source] Teaching Instructional Design: An Action Learning ApproachPERFORMANCE IMPROVEMENT QUARTERLY, Issue 2 2001Brenda Bannan-Ritland ABSTRACT Many theorists and practitioners are calling for more authentically based teaching approaches in the preparation of instructional designers and performance technologists to address the complexity of the field's practice. Although many innovative methods have been incorporated into the study of instructional design and development and human performance technology, including case studies and applied experiences with collaborative groups, among others, the majority of teaching approaches are limited to the time constraints and format of the traditional university classroom setting. This paper discusses an alternative teaching approach that incorporates action learning principles along with authentic project-based methods into the full-time study of instructional design. The paper reviews action learning principles and highlights the commonalties between these principles and the application of the practice and teaching of the instructional design process in an authentic manner. Finally, the implementation of action learning principles within a graduate program in instructional technology is described. Action learning principles may be applied to many content areas; however, the highly complementary nature of this specific methodology to the teaching and practice of instructional design may have the potential to improve greatly our preparation of professionals in the complex work environments characteristic of this and related disciplines. As a valuable component of performance technology skills, training in instructional design methods based on an action learning approach may have broad implications for both the preparation of instructional designers and performance technologists. [source] Local identification of prototypes for genetic learning of accurate TSK fuzzy rule-based systemsINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 9 2007R. Alcalá This work presents the use of local fuzzy prototypes as a new idea to obtain accurate local semantics-based Takagi,Sugeno,Kang (TSK) rules. This allow us to start from prototypes considering the interaction between input and output variables and taking into account the fuzzy nature of the TSK rules. To do so, a two-stage evolutionary algorithm based on MOGUL (a methodology to obtain Genetic Fuzzy Rule-Based Systems under the Iterative Rule Learning approach) has been developed to consider the interaction between input and output variables. The first stage performs a local identification of prototypes to obtain a set of initial local semantics-based TSK rules, following the Iterative Rule Learning approach and based on an evolutionary generation process within MOGUL (taking as a base some initial linguistic fuzzy partitions). Because this generation method induces competition among the fuzzy rules, a postprocessing stage to improve the global system performance is needed. Two different processes are considered at this stage, a genetic niching-based selection process to remove redundant rules and a genetic tuning process to refine the fuzzy model parameters. The proposal has been tested with two real-world problems, achieving good results. © 2007 Wiley Periodicals, Inc. Int J Int Syst 22: 909,941, 2007. [source] Learning-based 3D face detection using geometric contextCOMPUTER ANIMATION AND VIRTUAL WORLDS (PREV: JNL OF VISUALISATION & COMPUTER ANIMATION), Issue 4-5 2007Yanwen Guo Abstract In computer graphics community, face model is one of the most useful entities. The automatic detection of 3D face model has special significance to computer graphics, vision, and human-computer interaction. However, few methods have been dedicated to this task. This paper proposes a machine learning approach for fully automatic 3D face detection. To exploit the facial features, we introduce geometric context, a novel shape descriptor which can compactly encode the distribution of local geometry and can be evaluated efficiently by using a new volume encoding form, named integral volume. Geometric contexts over 3D face offer the rich and discriminative representation of facial shapes and hence are quite suitable to classification. We adopt an AdaBoost learning algorithm to select the most effective geometric context-based classifiers and to combine them into a strong classifier. Given an arbitrary 3D model, our method first identifies the symmetric parts as candidates with a new reflective symmetry detection algorithm. Then uses the learned classifier to judge whether the face part exists. Experiments are performed on a large set of 3D face and non-face models and the results demonstrate high performance of our method. Copyright © 2007 John Wiley & Sons, Ltd. [source] Sparse points matching by combining 3D mesh saliency with statistical descriptorsCOMPUTER GRAPHICS FORUM, Issue 2 2008U. Castellani Abstract This paper proposes new methodology for the detection and matching of salient points over several views of an object. The process is composed by three main phases. In the first step, detection is carried out by adopting a new perceptually-inspired 3D saliency measure. Such measure allows the detection of few sparse salient points that characterize distinctive portions of the surface. In the second step, a statistical learning approach is considered to describe salient points across different views. Each salient point is modelled by a Hidden Markov Model (HMM), which is trained in an unsupervised way by using contextual 3D neighborhood information, thus providing a robust and invariant point signature. Finally, in the third step, matching among points of different views is performed by evaluating a pairwise similarity measure among HMMs. An extensive and comparative experimental session has been carried out, considering real objects acquired by a 3D scanner from different points of view, where objects come from standard 3D databases. Results are promising, as the detection of salient points is reliable, and the matching is robust and accurate. [source] Learning with an active e-course in the Knowledge Grid environmentCONCURRENCY AND COMPUTATION: PRACTICE & EXPERIENCE, Issue 3 2006Hai Zhuge Abstract An active e-course is an open, self-representable and self-organizable media mechanism. Its kernel idea is to organize learning materials in a concept space rather than in a page space. The tailored content and flexible structure of the e-courses can be dynamically formed to cater for different learners with different backgrounds, capabilities and expectations, at different times and venues. The active e-course can also assess learners' learning performances and give appropriate suggestions to guide them in further learning. An authoring tool for constructing course ontology and a system prototype have been developed to support an active e-course, enabling a learner-centred, highly interactive and adaptive learning approach. The results of an empirical study show that the system can help enhance the effectiveness and efficiency of learning. Copyright © 2005 John Wiley & Sons, Ltd. [source] Evolving modular networks with genetic algorithms: application to nonlinear time seriesEXPERT SYSTEMS, Issue 4 2004A.S. Cofiño Abstract: A key problem of modular neural networks is finding the optimal aggregation of the different subtasks (or modules) of the problem at hand. Functional networks provide a partial solution to this problem, since the inter-module topology is obtained from domain knowledge (functional relationships and symmetries). However, the learning process may be too restrictive in some situations, since the resulting modules (functional units) are assumed to be linear combinations of selected families of functions. In this paper, we present a non-parametric learning approach for functional networks using feedforward neural networks for approximating the functional modules of the resulting architecture; we also introduce a genetic algorithm for finding the optimal intra-module topology (the appropriate balance of neurons for the different modules according to the complexity of their respective tasks). Some benchmark examples from nonlinear time-series prediction are used to illustrate the performance of the algorithm for finding optimal modular network architectures for specific problems. [source] Active versus passive teaching styles: An empirical study of student learning outcomesHUMAN RESOURCE DEVELOPMENT QUARTERLY, Issue 4 2009Norbert Michel This study compares the impact of an active teaching approach and a traditional (or passive) teaching style on student cognitive outcomes. Across two sections of an introductory business course, one class was taught in an active or "nontraditional" manner, with a variety of active learning exercises. The second class was taught in a passive or "traditional" manner, emphasizing daily lectures. Although the active learning approach does not appear to have improved overall mastery of the subject, we did find evidence that active learning can lead to improved cognitive outcomes in class-specific materials. The discussion emphasizes the role of delivery style on learning outcomes. [source] Learning invariants to illumination changes typical of indoor environments: Application to image color correctionINTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, Issue 3 2007B. Bascle Abstract This paper presents a new approach for automatic image color correction, based on statistical learning. The method both parameterizes color independently of illumination and corrects color for changes of illumination. This is useful in many image processing applications, such as image segmentation or background subtraction. The motivation for using a learning approach is to deal with changes of lighting typical of indoor environments such as home and office. The method is based on learning color invariants using a modified multi-layer perceptron (MLP). The MLP is odd-layered. The middle layer includes two neurons which estimate two color invariants and one input neuron which takes in the luminance desired in output of the MLP. The advantage of the modified MLP over a classical MLP is better performance and the estimation of invariants to illumination. The trained modified MLP can be applied using look-up tables, yielding very fast processing. Results illustrate the approach and compare it with other color correction approaches from the literature. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 132,142, 2007 [source] An evolutionary learning approach for adaptive negotiation agentsINTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, Issue 1 2006Raymond Y.K. Lau Developing effective and efficient negotiation mechanisms for real-world applications such as e-business is challenging because negotiations in such a context are characterized by combinatorially complex negotiation spaces, tough deadlines, very limited information about the opponents, and volatile negotiator preferences. Accordingly, practical negotiation systems should be empowered by effective learning mechanisms to acquire dynamic domain knowledge from the possibly changing negotiation contexts. This article illustrates our adaptive negotiation agents, which are underpinned by robust evolutionary learning mechanisms to deal with complex and dynamic negotiation contexts. Our experimental results show that GA-based adaptive negotiation agents outperform a theoretically optimal negotiation mechanism that guarantees Pareto optimal. Our research work opens the door to the development of practical negotiation systems for real-world applications. © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 41,72, 2006. [source] Intelligent control of DC motor driven mechanical systems: a robust learning control approachINTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL, Issue 1 2003Tae-Yong Kuc Abstract A robust learning controller is presented for DC motor driven mechanical systems with friction. The proposed controller takes advantage of both robust and learning control approaches to learn and compensate periodic and non-periodic uncertain dynamics. In the learning controller, a set of learning rules is implemented in which three types of learnings occur: one is direct learning of desired inverse dynamics input and the other two learning of unknown linear parameters and nonlinear bounding functions in the models of system dynamics and friction. The global asymptotic stability of learning control system is shown by using the Lyapunov stability theory. Experimental data demonstrate the effectiveness of developed learning approach to tracking of DC motor driven mechanical systems. Copyright © 2002 John Wiley & Sons, Ltd. [source] A distance learning approach to teaching management science and statisticsINTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH, Issue 2 2003John Lawrence Although there is no universal approach for offering distance learning courses over the Internet, nonetheless distance learning has emerged as a formidable way to offer instruction for many types of courses. One approach that has been successfully used for teaching introductory statistics and management science/operations research courses in a College of Business is discussed. [source] Social learning, sexual and physical abuse, and adult crimeAGGRESSIVE BEHAVIOR, Issue 6 2009Richard B. Felson Abstract This research examines the relationship between childhood physical and sexual abuse and the types of crimes committed by male adult offenders. We use the method of discriminant prediction to determine whether independent and dependent variables are related in ways that theories predict. Our analyses of data from the Survey of Inmates in State and Federal Correctional Facilities suggest that offenders model specific behaviors to which they have been exposed. Male offenders who were sexually abused as a child are more likely to commit sexual offenses, particularly sexual offenses against children, than nonsexual offenses. Offenders who were physically abused are more likely to engage in violent offenses than nonviolent offenses. Further analyses show that sexual offenders, and to a lesser extent violent offenders, are likely to specialize in those offenses. Our results are consistent with a social learning approach. They address a heretofore neglected issue: what exactly do children model when they are mistreated. Aggr. Behav. 35:489,501, 2009. © 2009 Wiley-Liss, Inc. [source] Statistical Discrimination of Liquid Gasoline Samples from CaseworkJOURNAL OF FORENSIC SCIENCES, Issue 5 2008Nicholas D. K. Petraco Ph.D. Abstract:, The intention of this study was to differentiate liquid gasoline samples from casework by utilizing multivariate pattern recognition procedures on data from gas chromatography-mass spectrometry. A supervised learning approach was undertaken to achieve this goal employing the methods of principal component analysis (PCA), canonical variate analysis (CVA), orthogonal canonical variate analysis (OCVA), and linear discriminant analysis. The study revealed that the variability in the sample population was sufficient enough to distinguish all the samples from one another knowing their groups a priori. CVA was able to differentiate all samples in the population using only three dimensions, while OCVA required four dimensions. PCA required 10 dimensions of data in order to predict the correct groupings. These results were all cross-validated using the "jackknife" method to confirm the classification functions and compute estimates of error rates. The results of this initial study have helped to develop procedures for the application of multivariate analysis to fire debris casework. [source] Finding nuggets in documents: A machine learning approachJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 6 2006Yi-fang Brook Wu Document keyphrases provide a concise summary of a document's content, offering semantic metadata summarizing a document. They can be used in many applications related to knowledge management and text mining, such as automatic text summarization, development of search engines, document clustering, document classification, thesaurus construction, and browsing interfaces. Because only a small portion of documents have keyphrases assigned by authors, and it is time-consuming and costly to manually assign keyphrases to documents, it is necessary to develop an algorithm to automatically generate keyphrases for documents. This paper describes a Keyphrase Identification Program (KIP), which extracts document keyphrases by using prior positive samples of human identified phrases to assign weights to the candidate keyphrases. The logic of our algorithm is: The more keywords a candidate keyphrase contains and the more significant these keywords are, the more likely this candidate phrase is a keyphrase. KIP's learning function can enrich the glossary database by automatically adding new identified keyphrases to the database. KIP's personalization feature will let the user build a glossary database specifically suitable for the area of his/her interest. The evaluation results show that KIP's performance is better than the systems we compared to and that the learning function is effective. [source] Forecasting murder within a population of probationers and parolees: a high stakes application of statistical learningJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES A (STATISTICS IN SOCIETY), Issue 1 2009Richard Berk Summary., Forecasts of future dangerousness are often used to inform the sentencing decisions of convicted offenders. For individuals who are sentenced to probation or paroled to community supervision, such forecasts affect the conditions under which they are to be supervised. The statistical criterion for these forecasts is commonly called recidivism, which is defined as a charge or conviction for any new offence, no matter how minor. Only rarely do such forecasts make distinctions on the basis of the seriousness of offences. Yet seriousness may be central to public concerns, and judges are increasingly required by law and sentencing guidelines to make assessments of seriousness. At the very least, information about seriousness is essential for allocating scarce resources for community supervision of convicted offenders. The paper focuses only on murderous conduct by individuals on probation or parole. Using data on a population of over 60000 cases from Philadelphia's Adult Probation and Parole Department, we forecast whether each offender will be charged with a homicide or attempted homicide within 2 years of beginning community supervision. We use a statistical learning approach that makes no assumptions about how predictors are related to the outcome. We also build in the costs of false negative and false positive charges and use half of the data to build the forecasting model, and the other half of the data to evaluate the quality of the forecasts. Forecasts that are based on this approach offer the possibility of concentrating rehabilitation, treatment and surveillance resources on a small subset of convicted offenders who may be in greatest need, and who pose the greatest risk to society. [source] Integrating local and scientific knowledge for adaptation to land degradation: Kalahari rangeland management optionsLAND DEGRADATION AND DEVELOPMENT, Issue 3 2007M. S. Reed Abstract Despite numerous assessments of the sensitivity and resilience of drylands to degradation, there has been little research into the way affected communities innovate and adapt in response to land degradation. This paper shows how local and scientific knowledge can be combined to identify rangeland management strategies to reduce or adapt to land degradation. To achieve this, we have developed and applied a four-stage social learning approach based on stakeholder participation in three degradation ,hotspots' in communal rangelands of the Kalahari, Botswana. This approach aims to collate, evaluate and apply both scientific and local knowledge on rangeland degradation and management options. First, current practice and possible management options were identified from the literature. Second, a series of semi-structured interviews with rangeland users identified local knowledge of strategies to reduce and adapt to land degradation. Third, these options were discussed and evaluated with rangeland stakeholders in focus groups held across each study region. Finally, the outputs from these focus groups were used to produce rangeland assessment guides for each region that provided management options agreed to be locally relevant by both researchers and local stakeholders. The study found that the majority of strategies reported in the literature were not suitable for use by pastoralists in the Kalahari. However, many of the strategies suggested by stakeholders could only be applied effectively under common property regimes, giving impetus to the growing literature encouraging institutional reform to strengthen common property management regimes. The research stimulated a social learning process that combined knowledge from local stakeholders (both pastoralists and extension workers) with the scientific knowledge of researchers to provide a range of management options that could help land managers reduce or adapt to land degradation. By combining participatory research with insights from scientific literature in this way, more relevant results were provided than either approach could have achieved alone. Copyright © 2007 John Wiley & Sons, Ltd. [source] Effectiveness of basic clinical skills training programmes: a cross-sectional comparison of four medical schoolsMEDICAL EDUCATION, Issue 2 2001Roy Remmen Objective Training in physical diagnostic skills is an important part of undergraduate medical education. The objective of this study was to study the outcome of skills training at four medical schools. Context At the time of the study, three schools had a traditional lecture-based curriculum and one school had a problem-based learning curriculum with a longitudinal skills training programme. All schools offer extended exposure to clerkships. Method A cross-sectional study in four medical schools was performed, using a written test of skills that has good correlation with actual student performance. The scores attained from four student groups were compared within and between the four medical schools. A total of 859 volunteer students from the later four years at each medical school participated in the study. Results The mean scores in the traditional medical schools increased with the start of skill training and the hands-on experience offered during the clerkships. Students from the school with the longitudinal skills training programme and the problem-based learning approach had significantly higher mean scores at the start of the clerkships, and maintained their lead in the subsequent clinical years. Conclusions Longitudinal skills training seems to offer the students a superior preparation for clerkships as well as influencing the students' learning abilities during the clerkships. The effect of the problem-based learning approach, also related to the innovative philosophy of the curriculum, could not be accounted for. [source] Teaching Instructional Design: An Action Learning ApproachPERFORMANCE IMPROVEMENT QUARTERLY, Issue 2 2001Brenda Bannan-Ritland ABSTRACT Many theorists and practitioners are calling for more authentically based teaching approaches in the preparation of instructional designers and performance technologists to address the complexity of the field's practice. Although many innovative methods have been incorporated into the study of instructional design and development and human performance technology, including case studies and applied experiences with collaborative groups, among others, the majority of teaching approaches are limited to the time constraints and format of the traditional university classroom setting. This paper discusses an alternative teaching approach that incorporates action learning principles along with authentic project-based methods into the full-time study of instructional design. The paper reviews action learning principles and highlights the commonalties between these principles and the application of the practice and teaching of the instructional design process in an authentic manner. Finally, the implementation of action learning principles within a graduate program in instructional technology is described. Action learning principles may be applied to many content areas; however, the highly complementary nature of this specific methodology to the teaching and practice of instructional design may have the potential to improve greatly our preparation of professionals in the complex work environments characteristic of this and related disciplines. As a valuable component of performance technology skills, training in instructional design methods based on an action learning approach may have broad implications for both the preparation of instructional designers and performance technologists. [source] Mastery learning and assessment: Implications for students and teachers in an era of high-stakes testingPSYCHOLOGY IN THE SCHOOLS, Issue 3 2008Barry J. Zimmerman Federal efforts to improve American students' achievement through high-stakes testing have led to significant concerns about the fairness and effectiveness of standardized tests. We attribute these concerns to the use of summative tests to assess academic progress without the benefits of an effective formative model of assessment and instruction, such as mastery learning. Historically, mastery learning models emerged as a reaction to the misuse of psychometric models of assessment for instructional purposes. Differences between these models are discussed along with a more recent form of mastery assessment, curriculum-based measurement. Apprehensions about the summative testing requirements of No Child Left Behind are considered along with efforts to make these tests fairer, such as the inclusion of a growth provision. Finally, we identified a mastery learning intervention program in mathematics in a high school that achieved national recognition, and we interviewed participating teachers and students. They reported the positive academic and motivational outcomes expected of a mastery learning approach and a few concerns about drawbacks associated with high-stakes testing. © 2008 Wiley Periodicals, Inc. [source] POLICY-LEARNING AND ENVIRONMENTAL POLICY INTEGRATION IN THE COMMON AGRICULTURAL POLICY, 1973,2003PUBLIC ADMINISTRATION, Issue 2 2010PETER H. FEINDT This article uses the Advocacy Coalition Framework (ACF) (Sabatier and Jenkins-Smith 1999; Weible and Sabatier 2007) and a refined version of the social learning approach of Peter Hall (1993) to assess and explain policy change in the Common (Agricultural) Policy (CAP) with a special view on Environmental Policy Integration (EPI). Three stages of EPI are discerned that move from central to vertical and later horizontal EPI, complementing an impact model of agriculture and the environment with a public goods model. Reform debates appear as prolonged and iterative battles over the institutionalization of new ideas which are finally incorporated into the existing policy framework. The policy network increasingly reflects cross-policy interdependencies and includes superior authorities, rendering the notion of a policy subsystem problematic. Contrary to the social learning model, the major (although not the most radical) change proponent dominates the policy community while superior authorities tend to intervene on behalf of the status quo. The argument is developed on the base of interviews with policy-makers in Brussels. [source] Practitioner Review: When parent training doesn't work: theory-driven clinical strategiesTHE JOURNAL OF CHILD PSYCHOLOGY AND PSYCHIATRY AND ALLIED DISCIPLINES, Issue 12 2009Stephen Scott Improving the parent,child relationship by using strategies based on social learning theory has become the cornerstone for the treatment of conduct problems in children. Over the past 40 years, interventions have expanded greatly from small, experimental procedures to substantial, systematic programmes that provide clear guidelines in detailed manuals on how practitioners should implement the standardised treatments. They are now widely disseminated and there is a great deal of empirical support that they are very effective for the majority of cases. However, evaluations of even the best of these evidence-based programmes show that a quarter to a third of families and their children do not benefit. What does the practitioner then do, when a standard social learning approach, diligently applied, doesn't work? We argue that under these circumstances, some of the major theories of child development, family functioning and individual psychology can help the skilled practitioner think his or her way through complex clinical situations. This paper describes a set of practical strategies that can then be flexibly applied, based on a systematic theoretical analysis. We hold that social learning theory remains the core of effective parent training interventions, but that ideas from attachment theory, structural family systems theory, cognitive-attribution theory, and shared empowerment/motivational interviewing can each, according to the nature of the difficulty, greatly enrich the practitioner's ability to help bring about change in families who are stuck. We summarise each of these models and present practical examples of when and how they may help the clinician plan treatment. [source] Continuing education meets the learning organization: The challenge of a systems approach to patient safetyTHE JOURNAL OF CONTINUING EDUCATION IN THE HEALTH PROFESSIONS, Issue 4 2000John M. Eisenberg MD Director Abstract Since the release of the report of the Institute of Medicine on medical errors and patient safety in November 1999, health policy makers and health care leaders in several nations have sought solutions that will improve the safety of health care. This attention to patient safety has highlighted the importance of a learning approach and a systems approach to quality measurement and improvement. Balanced with the need for public disclosure of performance, confidential reporting with feedback is one of the prime ways that nations such as the United States, Canada, the United Kingdom, and Australia have approached this challenge. In the United States, the Quality Interagency Coordination Task Force has convened federal agencies that are involved in health care quality improvement for a coordinated initiative. Based on an investment in a strong research foundation in health care quality measurement and improvement, there are eight key lessons for continuing education if it is to parlay the interest in patient safety into enhanced continuing education and quality improvement in learning health care systems. The themes for these lessons are (1) informatics for information, (2) guidelines as learning tools, (3) learning from opinion leaders, (4) learning from the patient, (5) decision support systems, (6) the team learning together, (7) learning organizations, and (8) just-in-time and point-of-care delivery. [source] Understanding fatty acid metabolism through an active learning approachBIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION, Issue 2 2010M. Fardilha Abstract A multi-method active learning approach (MALA) was implemented in the Medical Biochemistry teaching unit of the Biomedical Sciences degree at the University of Aveiro, using problem-based learning as the main learning approach. In this type of learning strategy, students are involved beyond the mere exercise of being taught by listening. Less emphasis is placed on transmitting information and the focus is shifted toward developing higher order thinking (analysis, synthesis, and evaluation). However, MALA should always involve clearly identified objectives and well-defined targets. Understanding fatty acid metabolism was one of the proposed goals of the Medical Biochemistry unit. To this end, students were challenged with a variety of learning strategies to develop skills associated with group conflict resolution, critical thinking, information access, and retrieval, as well as oral and written communication skills. Overall, students and learning facilitators were highly motivated by the diversity of learning activities, particularly due to the emphasis on correlating theoretical knowledge with human health and disease. As a quality control exercise, the students were asked to answer a questionnaire on their evaluation of the whole teaching/learning experience. Our initial analysis of the learning outcomes permits us to conclude that the approach undertaken yields results that surpass the traditional teaching methods. [source] Jumping off Arnstein's ladder: social learning as a new policy paradigm for climate change adaptationENVIRONMENTAL POLICY AND GOVERNANCE, Issue 6 2009Kevin Collins Abstract Participation of citizens, groups, organizations and businesses is now an essential element to tackle climate change effectively at international, European Union, national and local levels. However, beyond the general imperative to participate, major policy bodies offer little guidance on what this entails. We suggest that the dominance of Arnstein's ladder of citizen participation in policy discourses constrains the ways we think about, and critically the purposes we ascribe to, participation in a climate change context. We suggest an alternative framing of climate change, where no single group has clear access to understanding the issue and its resolution. Thus adaptation is fundamentally dependent on new forms of learning. Drawing on experiences of social learning approaches to natural resource managing, we explore how a commitment to social learning more accurately embodies the new kinds of role, relationship, practice and sense of purpose required to progress adaptive climate change agendas and practices. Copyright © 2009 John Wiley & Sons, Ltd and ERP Environment. [source] Using concept mapping principles in PowerPointEUROPEAN JOURNAL OF DENTAL EDUCATION, Issue 4 2007I. M. Kinchin Abstract:, The use of linear PowerPoint templates to support lectures may inadvertently encourage dental students to adopt a passive approach to learning and a narrow appreciation of the field of study. Such presentations may support short-term learning gains and validate assessment regimes that promote surface learning approaches at the expense of developing a wider appreciation of the field that is necessary for development of clinical expertise. Exploitation of concept mapping principles can provide a balance for the negative learning behaviour that is promoted by the unreflective use of PowerPoint. This increases the opportunities for students to access holistic knowledge structures that are indicators of expertise. We illustrate this using the example of partial denture design and show that undergraduates' grasp of learning and teaching issues is sufficiently sophisticated for them to appreciate the implications of varying the mode of presentation. Our findings indicate that students understand the strategic value of bullet-pointed presentations for short-term assessment goals and the benefits of deep learning mediated by concept mapping that may support longer term professional development. Students are aware of the tension between these competing agendas. [source] A comparison of changes in dental students' and medical students' approaches to learning during professional trainingEUROPEAN JOURNAL OF DENTAL EDUCATION, Issue 4 2001Robert Lindemann The purposes of this study were 1) to compare the learning approaches of dental students (DS) and medical students (MS) for the Class of 1998 at a single institution at admission and graduation and 2) to determine if their learning approaches changed over the course of their studies. An Approaches to Studying Inventory (ASI) was administered to DS and MS at two times: their first month in school and their last month in school. Means and standard deviations were calculated for three ASI orientations to studying: ,Meaning', ,Reproducing', and ,Achieving'. An additional domain referred to as ,Styles and Pathologies' identified learning problems. In comparison, DS and MS demonstrated a different pattern of learning approaches at matriculation; however, at graduation these differences were less apparent. Over time, DS reported a decreased use, and MS reported an increased use of the Reproducing orientation bringing them closer together. MS also demonstrated an increased use of the Achieving orientation. The Meaning orientation, which indicates a deep approach to learning, was equivalently used by both groups at entry and remained unaltered. [source] Genome-wide association analyses of expression phenotypesGENETIC EPIDEMIOLOGY, Issue S1 2007Gary K. Chen Abstract A number of issues arise when analyzing the large amount of data from high-throughput genotype and expression microarray experiments, including design and interpretation of genome-wide association studies of expression phenotypes. These issues were considered by contributions submitted to Group 1 of the Genetic Analysis Workshop 15 (GAW15), which focused on the association of quantitative expression data. These contributions evaluated diverse hypotheses, including those relevant to cancer and obesity research, and used various analytic techniques, many of which were derived from information theory. Several observations from these reports stand out. First, one needs to consider the genetic model of the trait of interest and carefully select which single nucleotide polymorphisms and individuals are included early in the design stage of a study. Second, by targeting specific pathways when analyzing genome-wide data, one can generate more interpretable results than agnostic approaches. Finally, for datasets with small sample sizes but a large number of features like the Genetic Analysis Workshop 15 dataset, machine learning approaches may be more practical than traditional parametric approaches. Genet Epidemiol 31 (Suppl. 1): S7,S11, 2007. © 2007 Wiley-Liss, Inc. [source] On the Application of Inductive Machine Learning Tools to Geographical AnalysisGEOGRAPHICAL ANALYSIS, Issue 2 2000Mark Gahegan Inductive machine learning tools, such as neural networks and decision trees, offer alternative methods for classification, clustering, and pattern recognition that can, in theory, extend to the complex or "deep" data sets that pervade geography. By contrast, traditional statistical approaches may fail, due to issues of scalability and flexibility. This paper discusses the role of inductive machine learning as it relates to geographical analysis. The discussion presented is not based on comparative results or on mathematical description, but instead focuses on the often subtle ways in which the various inductive learning approaches differ operationally, describing (1) the manner in which the feature space is partitioned or clustered, (2) the search mechanisms employed to identify good solutions, and (3) the different biases that each technique imposes. The consequences arising from these issues, when considering complex geographic feature spaces, are then described in detail. The overall aim is to provide a foundation upon which reliable inductive analysis methods can be constructed, instead of depending on piecemeal or haphazard experimentation with the various operational criteria that inductive learning tools call for. Often, it would appear that these criteria are not well understood by practitioners in the geographic sphere, which can lead to difficulties in configuration and operation, and ultimately to poor performance. [source] Cultivating problem-solving skills through problem-based approaches to professional developmentHUMAN RESOURCE DEVELOPMENT QUARTERLY, Issue 3 2002Margaret C. Lohman An extensive literature review was conducted of four problem-based approaches to professional development: (1) case study, (2) goal-based scenario, (3) problem-based learning, and (4) action learning. The review comparatively analyzed the training designs of these four approaches and found key differences in the nature of their case problems and training strategies. Specifically, the analysis found that case problems are ill structured in action learning and problem-based learning, are moderately structured in a goal-based scenario, and are fairly well structured in the case study approach. In addition, it was found that prototypical problems are used to a much greater extent in the problem-based learning and goal-based scenario approaches than they are in the other two approaches. Furthermore, the analysis found that the case study approach uses the most expert-oriented training strategy, the goal-based scenario approach uses a more learner-oriented strategy than the case study approach, and the problem-based learning and action learning approaches use strongly learner-oriented strategies. These design differences suggest that the case study and goal-based scenario approaches are more likely to result in single-loop learning and to foster the ability to solve well-structured problems, whereas the problem-based learning and action learning approaches are more likely to lead to double-loop learning and to promote the ability to solve ill-structured problems. Implications of these findings for the design and research of problem-based approaches to professional development are discussed. [source] | |||||||||||||||||||||||||||||||||||||||||||