Factors associated with social work student satisfaction with field placements in child welfare by Diane Elias Alperin.

This study was conducted during the 1994-1995 academic year. Seven social work education programs in the state of Florida, all accredited by the Council on Social Work Education, participated in this study. Graduate and undergraduate social work students in child welfare field placements, and their field instructors, were surveyed during the Spring 1995 semester to assess their satisfaction with field placements ii this area and the relationship of this satisfaction to employment interests and field placement recommendations. The majority of social work students responding to this survey were generally satisfied with several aspects of their field placements--the learning, field work program, field instructor, child welfare agency, and overall field experience. The field instructors were generally more satisfied than the students, but only statistically different from the students in the areas of satisfaction with the field work program and the child welfare agency. Multiple regression analysis revealed that learning assignment opportunities, field instructor relationship characteristics, placement preference, and pre-placement interview contributed to the prediction of student satisfaction. Student satisfaction in field placement was significantly related to the acceptance of employment, if offered, and the recommendation of the field placement to other students. Logistic regression analysis revealed that satisfaction with the child welfare agency was the greatest contributor to the prediction of acceptance of employment, and satisfaction with the field work program was the greatest contributor to the prediction of field placement recommendation.

Risk-taking propensity of faculty, administrators and academic departament heads at large, urban, multicampus community college

This research was undertaken to explore dimensions of the risk construct, identify factors related to risk-taking in education, and study risk propensity among employees at a community college. Risk-taking propensity (RTP) was measured by the 12-item BCDQ, which consisted of personal and professional risk-related situations balanced for the money, reputation, and satisfaction dimensions of the risk construct. Scoring ranged from 1.00 (most cautious) to 6.00 (most risky). Surveys including the BCDQ and seven demographic questions relating to age, gender, professional status, length of service, academic discipline, highest degree, and campus location were sent to faculty, administrators, and academic department heads. A total of 325 surveys were returned, resulting in a 66.7% response rate. Subjects were relatively homogeneous for age, length of service, and highest degree. Subjects were also homogeneous for risk-taking propensity: no substantive differences in RTP scores were noted within and among demographic groups, with the possible exception of academic discipline. The mean RTP score for all subjects was 3.77, for faculty was 3.76, for administrators was 3.83, and for department heads was 3.64. The relationship between propensity to take personal risks and propensity to take professional risks was tested by computing Pearson r correlation coefficients. The relationships for the total sample, faculty, and administrator groups were statistically significant, but of limited practical significance. Subjects were placed into risk categories by dividing the response scale into thirds. A 3 X 3 factorial ANOVA revealed no interaction effects between professional status and risk category with regard to RTP score. A discriminant analysis showed that a seven-factor model was not effective in predicting risk category. The homogeneity of the study sample and the effect of a risk encouraging environment were discussed in the context of the community college. Since very little data on risk-taking in education is available, risk propensity data from this study could serve as a basis for comparison to future research. Results could be used by institutions to plan professional development activities, designed to increase risk-taking and encourage active acceptance of change.

Development and validation of an attitudinal-profiling tool for patients with asthma

Peer reviewed

Radiotherapy Treatment Assessment using DCE-MRI

Abstract

The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.

This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.

I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.

Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.

II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.

The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.

In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.

El "Análisis de Correspondencias Múltiples" como herramienta metodológica de síntesis teórica y empírica : Su aporte al estudio del locus universitario privado argentino (1955-1983)

El Análisis de Correspondencias Múltiples (ACM), recurso metodológico utilizado por Bourdieu y su equipo en un nivel avanzado de síntesis teórico-empírica, constituye una herramienta fundamental para la construcción analítica de espacios relacionales. Permite posicionar relacionalmente unidades de análisis en función de un conjunto determinado de variables y plasmar la multiplicidad resultante tanto gráfica como analíticamente. Comenzando por una reflexión general sobre las potencialidades de la herramienta, este artículo analiza la configuración del espacio universitario privado en Argentina (1955-1983) a partir del ACM, que permitió determinar las relaciones de homología y principios de diferenciación existentes entre las instituciones que lo componen.

Sedentary behavior and not physical activity predicts study progress in distance education`

For the official publication, see: http://dx.doi.org/10.1016/j.lindif.2016.06.021

Mindfulness and Spirituality as determinants of Existential Loneliness in the Dutch

Existential loneliness is a concept that is largely ignored in the psychological research tradition, although from a philosophical perspective it is deeply connected to inherent human longings of connection and meaning. This research investigated the relationship between existential loneliness and two variables that are theoretically closely related to the concepts of connection and meaning, namely mindfulness (connection to oneself and others) and spiritual well-being (connection to a larger whole). This was done in a sample of n = 180 individuals (61.7% female; mean age 41.72, SD = 12.16) of the Dutch population. A multiple regression analysis was conducted. It can be concluded that there is a negative relationship between mindfulness and existential loneliness, as well as between spiritual well-being and existential loneliness. This means that people with a higher level of mindfulness and/or a higher level of spiritual well-being experience a lower level of existential loneliness. At the same time, people with a lower level of mindfulness and/or spiritual well-being experience a lower level of existential loneliness. There are some limitations to this study, for example the use of a non-random sampling method, a limited sample group, a scale that has not been widely tested, and a potential bias towards the higher educated. However, these limitations are inherent to exploratory research and does not diminish the main strength of this thesis, namely that it has provided more insight into an important and prevalent societal phenomenon, that had not been extensively researched previously, that has so far only been addressed in more philosophical instead of scientific debates, and linked almost exclusively to negative concepts, such as terminal illness. This research provides a first understanding of two positive determinants of existential loneliness, which could potentially be used to help make sense of this inherently humane condition, as well as to actively cope with the potential (adverse) effects of it.

Discrimination of honey of different floral origins by a combination of various chemical parameters

Abstract Honey is a high value food commodity with recognized nutraceutical properties. A primary driver of the value of honey is its floral origin. The feasibility of applying multivariate data analysis to various chemical parameters for the discrimination of honeys was explored. This approach was applied to four authentic honeys with different floral origins (rata, kamahi, clover and manuka) obtained from producers in New Zealand. Results from elemental profiling, stable isotope analysis, metabolomics (UPLC-QToF MS), and NIR, FT-IR, and Raman spectroscopic fingerprinting were analyzed. Orthogonal partial least square discriminant analysis (OPLS-DA) was used to determine which technique or combination of techniques provided the best classification and prediction abilities. Good prediction values were achieved using metabolite data (for all four honeys, Q² = 0.52; for manuka and clover, Q² = 0.76) and the trace element/isotopic data (for manuka and clover, Q² = 0.65), while the other chemical parameters showed promise when combined (for manuka and clover, Q² = 0.43).

Posterior Probability Modeling and Image Classification for Archaeological Site Prospection: Building a Survey Efficacy Model for Identifying Neolithic Felsite Workshops in the Shetland Islands

The application of custom classification techniques and posterior probability modeling (PPM) using Worldview-2 multispectral imagery to archaeological field survey is presented in this paper. Research is focused on the identification of Neolithic felsite stone tool workshops in the North Mavine region of the Shetland Islands in Northern Scotland. Sample data from known workshops surveyed using differential GPS are used alongside known non-sites to train a linear discriminant analysis (LDA) classifier based on a combination of datasets including Worldview-2 bands, band difference ratios (BDR) and topographical derivatives. Principal components analysis is further used to test and reduce dimensionality caused by redundant datasets. Probability models were generated by LDA using principal components and tested with sites identified through geological field survey. Testing shows the prospective ability of this technique and significance between 0.05 and 0.01, and gain statistics between 0.90 and 0.94, higher than those obtained using maximum likelihood and random forest classifiers. Results suggest that this approach is best suited to relatively homogenous site types, and performs better with correlated data sources. Finally, by combining posterior probability models and least-cost analysis, a survey least-cost efficacy model is generated showing the utility of such approaches to archaeological field survey.

Statistical modelling of the rheological and mucoadhesive properties of aqueous poly(methylvinylether-co-maleic acid) networks: Redefining biomedical applications and the relationship between viscoelasticity and mucoadhesion

Poly(methylvinylether-co-maleic acid) (PMVE/MA) is commonly used as a component of pharmaceutical platforms, principally to enhance interactions with biological substrates (mucoadhesion). However, the limited knowledge on the rheological properties of this polymer and their relationships with mucoadhesion has negated the biomedical use of this polymer as a mono-component platform. This study presents a comprehensive study of the rheological properties of aqueous PMVE/MA platforms and defines their relationships with mucoadhesion using multiple regression analysis. Using dilute solution viscometry the intrinsic viscosities of un-neutralised PMVE/MA and PMVE/MA neutralised using NaOH or TEA were 22.32 ± 0.89 dL g-1, 274.80 ± 1.94 dL g-1 and 416.49 ± 2.21 dL g-1 illustrating greater polymer chain expansion following neutralisation using Triethylamine (TEA). PMVE/MA platforms exhibited shear-thinning properties. Increasing polymer concentration increased the consistencies, zero shear rate (ZSR) viscosities (determined from flow rheometry), storage and loss moduli, dynamic viscosities (defined using oscillatory analysis) and mucoadhesive properties, yet decreased the loss tangents of the neutralised polymer platforms. TEA neutralised systems possessed significantly and substantially greater consistencies, ZSR and dynamic viscosities, storage and loss moduli, mucoadhesion and lower loss tangents than their NaOH counterparts. Multiple regression analysis enabled identification of the dominant role of polymer viscoelasticity on mucoadhesion (r > 0.98). The mucoadhesive properties of PMVE/MA platforms were considerable and were greater than those of other platforms that have successfully been shown to enhance in vivo retention when applied to the oral cavity, indicating a positive role for PMVE/MA mono-component platforms for pharmaceutical and biomedical applications.

The making of professionals: Embedded civil society development in a transition country

The paper addresses the development of non-governmental organisations (NGOs) in transition settings. Caught in the balance of knowledge exchange and translation of ideas from abroad, organisations in turbulent setting legitimise their existence by learning through professional networks. By association, organisational actors gain acknowledgement by their sector by traversing the corridors of influence provided by international partnerships. What they learn is how to conduct themselves as agents of change in society, and how to deliver on stated missions and goals, therefore, legitimising their presence in a budding civil society at home. The paper presents a knowledge production and learning practices framework which indicates a presence of dual identity of NGOs - their “embeddedness” locally and internationally. Selected framework dimensions and qualitative case study themes are discussed with respect to the level of independence of organisational actors in the East from their partners in the West in a post-socialist context. A professional global civil society as organisations are increasingly managed in similar, professional ways (Anheier & Themudo 2002). Here knowledge “handling” and knowledge “translation” take place through partnership exchanges fostering capable and/or competitive change-inducing institutions (Czarniawska & Sevon 2005; Hwang & Suarez 2005). How professional identity presents itself in the third sector, as well as the sector’s claim to expertise, need further attention, adding to ongoing discussions on professions in institutional theory (Hwang & Powell 2005; Scott 2008; Noordegraaf 2011). A conceptual framework on the dynamic involved for the construction professional fields follows: • Multiple case analysis provides a taxonomy for understanding what is happening in knowledge transition, adaptation, and organisational learning capacity for NGOs with respect to their role in a networked civil society. With the model we can observe the types of knowledge produced and learning employed by organisations. • There are elements of professionalisation in third sector work organisational activity with respect to its accreditation, sources and routines of learning, knowledge claims, interaction with the statutory sector, recognition in cross-sector partnerships etc. • It signals that there is a dual embeddedness in the development of the sector at the core to the shaping the sector’s professional status. This is instrumental in the NGOs’ goal to gain influence as institutions, as they are only one part of a cross-sector mission to address complex societal problems The case study material highlights nuances of knowledge production and learning practices in partnerships, with dual embeddedness a main feature of the findings. This provides some clues to how professionalisation as expert-making takes shape in organisations: • Depending on the type of organisations’ purpose, over its course of development there is an increase in participation in multiple networks, as opposed to reliance on a single strategic partner for knowledge artefacts and practices; • Some types of organisations are better connected within international and national networks than others and there seem to be preferences for each depending on the area of work; • The level of interpretation or adaptation of the knowledge artefacts is related to an organisation’s embeddedness locally, in turn giving it more influence within the network of key institutions; An overreaching theme across taxonomy categories (Table 1)is “professionalisation” or developing organisational “expertise”, embodied at the individual, organisational, and sector levels. Questions relevant to the exercise of power arise: Is competence in managing a dual embeddedness signals the development of a dual identity in professionalisation? Is professionalisation in this sense a sign of organisations maturing into more capable partners to the arguably more experienced (Western) institutions, shifting the power balance? Or is becoming more professional a sign of domestication to the agenda of certain powerful stakeholders, who define the boundaries of the profession? Which dominant dynamics can be observed in a broadly-defined transition country civil society, where individual participation in the form of activism may be overtaking the traditional forms of organised development work, especially with the spread of social media?

Biomass, quality traits and methane production of extensive grassland: biodiversity effects and sensor approaches

Energy policies around the world are mandating for a progressive increase in renewable energy production. Extensive grassland areas with low productivity and land use limitations have become target areas for sustainable energy production to avoid competition with food production on the limited available arable land resources and minimize further conversion of grassland into intensively managed energy cropping systems or abandonment. However, the high spatio-temporal variability in botanical composition and biochemical parameters is detrimental to reliable assessment of biomass yield and quality regarding anaerobic digestion. In an approach to assess the performance for predicting biomass using a multi-sensor combination including NIRS, ultra-sonic distance measurements and LAI-2000, biweekly sensor measurements were taken on a pure stand of reed canary grass (Phalaris aruninacea), a legume grass mixture and a diversity mixture with thirty-six species in an experimental extensive two cut management system. Different combinations of the sensor response values were used in multiple regression analysis to improve biomass predictions compared to exclusive sensors. Wavelength bands for sensor specific NDVI-type vegetation indices were selected from the hyperspectral data and evaluated for the biomass prediction as exclusive indices and in combination with LAI and ultra-sonic distance measurements. Ultrasonic sward height was the best to predict biomass in single sensor approaches (R² 0.73 – 0.76). The addition of LAI-2000 improved the prediction performance by up to 30% while NIRS barely improved the prediction performance. In an approach to evaluate broad based prediction of biochemical parameters relevant for anaerobic digestion using hyperspectral NIRS, spectroscopic measurements were taken on biomass from the Jena-Experiment plots in 2008 and 2009. Measurements were conducted on different conditions of the biomass including standing sward, hay and silage and different spectroscopic devices to simulate different preparation and measurement conditions along the process chain for biogas production. Best prediction results were acquired for all constituents at laboratory measurement conditions with dried and ground samples on a bench-top NIRS system (RPD > 3) with a coefficient of determination R2 < 0.9. The same biomass was further used in batch fermentation to analyse the impact of species richness and functional group composition on methane yields using whole crop digestion and pressfluid derived by the Integrated generation of solid Fuel and Biogas from Biomass (IFBB) procedure. Although species richness and functional group composition were largely insignificant, the presence of grasses and legumes in the mixtures were most determining factors influencing methane yields in whole crop digestion. High lignocellulose content and a high C/N ratio in grasses may have reduced the digestibility in the first cut material, excess nitrogen may have inhibited methane production in second cut legumes, while batch experiments proved superior specific methane yields of IFBB press fluids and showed that detrimental effects of the parent material were reduced by the technical treatment

Avskaffandet av revisionsplikten : Ränteeffekter på företag inom fastighetsbranschen efter avskaffandet av revisionsplikten

Bakgrund: År 2010 avskaffades revisionsplikten för mindre aktiebolag i Sverige. Anledningen till avskaffandet var att minska kostnaderna för mindre företag. Tidigare forskning har kommit fram till att företag som valt bort revisor får en högre kreditkostnad när de till exempel tar lån. Den tidigare forskningen menar att detta kan bero på att banker och andra kreditinstitut anser att oreviderade finansiella rapporter har en sämre kvalitet än reviderade rapporter vilket leder till en högre risk för kreditgivarna. Denna uppsats kommer att undersöka om det finns någon skillnad på låneräntan mellan företag som valt att ha kvar revisor och företag som valt bort revisor. Syfte: Syftet med denna uppsats är att undersöka, jämföra samt analysera låneräntan hos mindre aktiebolag inom fastighetsbranschen som inte är revisionspliktiga. Metod: Kvantitativ metod, multipel regressionsanalys. Resultat: Resultaten i denna studie visar på att företag med revisor har en lägre ränta i genomsnitt jämfört med företag utan revisor. Vi har även fått fram att revision har en negativ påverkan på företags ränta, men detta resultat är inte signifikant. Därför kan vi inte uttala oss om att revision har en negativ påverkan på företags ränta, trots att tidigare forskning har visat det. Slutsats: Företags val av revisor eller ej är inte det viktigaste för kreditgivare när det kommer till vilken ränta företagen skall få på sina lån. Det finns andra faktorer som har en större påverkan på räntan. I denna studie är det företags storlek samt andelen materiella tillgångar i förhållande till totala tillgångar som har den största negativa påverkan på företags ränta. Detta indikerar att banker och andra kreditinstitut ser dessa företag som en lägre risk.

Affect-Based Effects of Simulation Games on Learning

Empirical evidence has demonstrated the benefits of using simulation games in enhancing learning especially in terms of cognitive gains. This is to be expected as the dynamism and non-linearity of simulation games are more cognitively demanding. However, the other effects of simulation games, specifically in terms of learners’ emotions, have not been given much attention and are under-investigated. This study aims to demonstrate that simulation games stimulate positive emotions from learners that help to enhance learning. The study finds that the affect-based constructs of interest, engagement and appreciation are positively correlated to learning. A stepwise multiple regression analysis shows that a model involving interest and engagement are significantly associated with learning. The emotions of learners should be considered in the development of curriculum, and the delivery of learning and teaching as positive emotions enhances learning.

Imagens do terceiro setor: um estudo com pais e responsáveis financeiros das organizações educacionais

The present report is the result of an applied research in the educational entities of the third sector, aiming to demonstrate whether the financial influences the perception of users on the image of those entities. For both used the prospect of integrative marketing relationship adapting to and developing a set of indicators which bore the measurement of images from the model of Machado et al (2005) and Kotler and Fox (1994). The sample included a total of 187 parents and financial responsibility in 03 (three) institutions of education in Natal / RN. These data were processed by multivariate statistical analysis, factor analysis, linear regression, analysis of cluster and discriminant analysis. The factor analysis also identified 6 images perceived by users of services. Next were the relationships of cause and effect between the financial and images formed. In discriminant analysis, was identified two distinct groups of parents and guardians with financial perceptions similar and well defined. The result of the work shows that the differential level of financial participation of parents and guardians not influence the formation of the images formed from educational institutions of the third sector