Learning design twofold strategies for teacher-led inquiry andstudent active learning

This workshop paper states that fostering active student participation both in face-to-face lectures / seminars and outside the classroom (personal and group study at home, the library, etc.) requires a certain level of teacher-led inquiry. The paper presents a set of strategies drawn from real practice in higher education with teacher-led inquiry ingredients that promote active learning. Thesepractices highlight the role of the syllabus, the importance of iterative learning designs, explicit teacher-led inquiry, and the implications of the context, sustainability and practitioners’ creativity. The strategies discussed in this paper can serve as input to the workshop as real cases that need to be represented in design and supported in enactment (with and without technologies).

Incorporating features of distribution and progression for automatic Makam classification

Automatic classification of makams from symbolic data is a rarely studied topic. In this paper, first a review of an n-gram based approach is presented using various representations of the symbolic data. While a high degree of precision can be obtained, confusion happens mainly for makams using (almost) the same scale and pitch hierarchy but differ in overall melodic progression, seyir. To further improve the system, first n-gram based classification is tested for various sections of the piece to take into account a feature of the seyir that melodic progression starts in a certain region of the scale. In a second test, a hierarchical classification structure is designed which uses n-grams and seyir features in different levels to further improve the system.

CLFP intrinsic constraints-based group management of blended learning situations

When applying a Collaborative Learning Flow Pattern (CLFP) to structure sequences of activities in real contexts, one of the tasks is to organize groups of students according to the constraints imposed by the pattern. Sometimes,unexpected events occurring at runtime force this pre-defined distribution to be changed. In such situations, an adjustment of the group structures to be adapted to the new context is needed. If the collaborative pattern is complex, this group redefinitionmight be difficult and time consuming to be carried out in real time. In this context, technology can help on notifying the teacher which incompatibilitiesbetween the actual context and the constraints imposed by the pattern. This chapter presents a flexible solution for supporting teachers in the group organization profiting from the intrinsic constraints defined by a CLFPs codified in IMS Learning Design. A prototype of a web-based tool for the TAPPS and Jigsaw CLFPs and the preliminary results of a controlled user study are alsopresented as a first step towards flexible technological systems to support grouping tasks in this context.

The influence of learning on evolution: a mathematical framework.

The Baldwin effect can be observed if phenotypic learning influences the evolutionary fitness of individuals, which can in turn accelerate or decelerate evolutionary change. Evidence for both learning-induced acceleration and deceleration can be found in the literature. Although the results for both outcomes were supported by specific mathematical or simulation models, no general predictions have been achieved so far. Here we propose a general framework to predict whether evolution benefits from learning or not. It is formulated in terms of the gain function, which quantifies the proportional change of fitness due to learning depending on the genotype value. With an inductive proof we show that a positive gain-function derivative implies that learning accelerates evolution, and a negative one implies deceleration under the condition that the population is distributed on a monotonic part of the fitness landscape. We show that the gain-function framework explains the results of several specific simulation models. We also use the gain-function framework to shed some light on the results of a recent biological experiment with fruit flies.

Bicarbonate de sodium pour ralentir la progression de la maladie rénale chronique [Sodium bicarbonate to slow the progression of chronic kidney disease].

Metabolic acidosis is a prevalent complication in moderate and late stages of chronic kidney disease (CKD). It is established that the correction of metabolic acidosis may improve metabolic bone disorders and protein degradation in the skeletal muscle, two characteristic complications of patients with advanced CKD. In the last 18 months, three randomized controlled trials have drawn the attention on a novel indication to correct metabolic acidosis in these patients, i.e., halting CKD progression. These data show that sodium bicarbonate, a cheap and easily manageable treatment, may delay the progression of CKD and the need of a renal replacement therapy such as dialysis or kidney transplantation.

Clinical Learning Environment and Supervision. Development and Validation of the CLES Evaluation Scale

The purpose of the study is: (1) to describe how nursing students' experienced their clinical learning environment and the supervision given by staff nurses working in hospital settings; and (2) to develop and test an evaluation scale of Clinical Learning Environment and Supervision (CLES). The study has been carried out in different phases. The pilot study (n=163) explored the association between the characteristics of a ward and its evaluation as a learning environment by students. The second version of research instrument (which was developed by the results of this pilot study) were tested by an expert panel (n=9 nurse teachers) and test-retest group formed by student nurses (n=38). After this evaluative phase, the CLES was formed as the basic research instrument for this study and it was tested with the Finnish main sample (n=416). In this phase, a concurrent validity instrument (Dunn & Burnett 1995) was used to confirm the validation process of CLES. The international comparative study was made by comparing the Finnish main sample with a British sample (n=142). The international comparative study was necessary for two reasons. In the instrument developing process, there is a need to test the new instrument in some other nursing culture. Other reason for comparative international study is the reflecting the impact of open employment markets in the European Union (EU) on the need to evaluate and to integrate EU health care educational systems. The results showed that the individualised supervision system is the most used supervision model and the supervisory relationship with personal mentor is the most meaningful single element of supervision evaluated by nursing students. The ward atmosphere and the management style of ward manager are the most important environmental factors of the clinical ward. The study integrates two theoretical elements - learning environment and supervision - in developing a preliminary theoretical model. The comparative international study showed that, Finnish students were more satisfied and evaluated their clinical placements and supervision with higher scores than students in the United Kingdom (UK). The difference between groups was statistical highly significant (p= 0.000). In the UK, clinical placements were longer but students met their nurse teachers less frequently than students in Finland. Arrangements for supervision were similar. This research process has produced the evaluation scale (CLES), which can be used in research and quality assessments of clinical learning environment and supervision in Finland and in the UK. CLES consists of 27 items and it is sub-divided into five sub-dimensions. Cronbach's alpha coefficient varied from high 0.94 to marginal 0.73. CLES is a compact evaluation scale and user-friendliness makes it suitable for continuing evaluation.

Does Reasoning Enhance Learning?

Utilizing the well-known Ultimatum Game, this note presents the following phenomenon. If we start with simple stimulus-response agents, learning through naive reinforcement, and then grant them some introspective capabilities, we get outcomes that are not closer but farther away from the fully introspective game-theoretic approach. The cause of this is the following: there is an asymmetry in the information that agents can deduce from their experience, and this leads to a bias in their learning process.

Absence of progression as assessed by response evaluation criteria in solid tumors predicts survival in advanced GI stromal tumors treated with imatinib mesylate: the intergroup EORTC-ISG-AGITG phase III trial.

PURPOSE: From February 2001 to February 2002, 946 patients with advanced GI stromal tumors (GISTs) treated with imatinib were included in a controlled EORTC/ISG/AGITG (European Organisation for Research and Treatment of Cancer/Italian Sarcoma Group/Australasian Gastro-Intestinal Trials Group) trial. This analysis investigates whether the response classification assessed by RECIST (Response Evaluation Criteria in Solid Tumors), predicts for time to progression (TTP) and overall survival (OS). PATIENTS AND METHODS: Per protocol, the first three disease assessments were done at 2, 4, and 6 months. For the purpose of the analysis (landmark method), disease response was subclassified in six categories: partial response (PR; > 30% size reduction), minor response (MR; 10% to 30% reduction), no change (NC) as either NC- (0% to 10% reduction) or NC+ (0% to 20% size increase), progressive disease (PD; > 20% increase/new lesions), and subjective PD (clinical progression). RESULTS: A total of 906 patients had measurable disease at entry. At all measurement time points, complete response (CR), PR, and MR resulted in similar TTP and OS; this was also true for NC- and NC+, and for PD and subjective PD. Patients were subsequently classified as responders (CR/PR/MR), NC (NC+/NC-), or PD. This three-class response categorization was found to be highly predictive of further progression or survival for the first two measurement points. After 6 months of imatinib, responders (CR/PR/MR) had the same survival prognosis as patients classified as NC. CONCLUSION: RECIST perfectly enables early discrimination between patients who benefited long term from imatinib and those who did not. After 6 months of imatinib, if the patient is not experiencing PD, the pattern of radiologic response by tumor size criteria has no prognostic value for further outcome. Imatinib needs to be continued as long as there is no progression according to RECIST.

Time Series Input Selection using Multiple Kernel Learning

In this paper we study the relevance of multiple kernel learning (MKL) for the automatic selection of time series inputs. Recently, MKL has gained great attention in the machine learning community due to its flexibility in modelling complex patterns and performing feature selection. In general, MKL constructs the kernel as a weighted linear combination of basis kernels, exploiting different sources of information. An efficient algorithm wrapping a Support Vector Regression model for optimizing the MKL weights, named SimpleMKL, is used for the analysis. In this sense, MKL performs feature selection by discarding inputs/kernels with low or null weights. The approach proposed is tested with simulated linear and nonlinear time series (AutoRegressive, Henon and Lorenz series).