Early childhood educators in the United States and worldwide face the growing challenge of “schoolification,” - the imposition of conventional academic content from later grade levels into their classrooms (e.g., Ring & O’Sullivan, 2018). The science of learning offers a different approach with evidence to support more active, engaging, and inclusive educational environments for all students (e.g., Darling-Hammond et al., 2020, Hirsh-Pasek et al., 2020, Nasir et al., 2021). The Active Playful Learning framework is one promising model that combines principles of how children learn through play, and particularly adult-initiated, child-directed guided play (e.g., Weisberg et al., 2013), with the “6 Cs,” a set of skills for success in the classroom and beyond. A preliminary, mixed methods evaluation of an intervention to promote guided play in kindergarten classrooms through instructional coaching was conducted by Nesbitt et al. (under review) across New Hampshire. This study builds on the prior research, first by attempting to replicate the positive effects of the intervention for teachers and students, as provided by teacher reports. It then advances beyond the previous study to determine if teacher and student behaviors shaped by guided play and the playful learning principles are detectable through independent classroom observations. Lastly, it incorporates a preliminary comparison between intervention and business as usual control classrooms. Results support a replication of the previous teacher reports. Other results are mixed, but they indicate significant behavior changes consistent with adoption of playful learning, even if not yet guided play. This study represents a considerable advance in our implementation and evaluation of Active Playful Learning for educators and students. / Psychology

No description available.

Citizen Cyberscience Projects (CCPs) are projects mediated through the Internet, in which teams of scientists recruit members of the public (volunteers) to assist in scientific research, typically through the processing of large quantities of data. This thesis presents qualitative ethnographic case studies of the communities that have formed around two such projects, climateprediction.net and Galaxy Zoo. By considering these social actors in the broader contexts in which they are situated (historical, institutional, social, scientific), I discuss the co-shaping of the interests of these actors, the nature of the relationships amongst these actors, and the infrastructure of the projects and the purposes and nature of the scientific work performed. The thesis focusses on two relationships in particular. The first is that between scientists and volunteers, finding that, although scientists in both projects are concerned with treating volunteers with respect, there are nevertheless considerable differences between the projects. These are related to a number of interconnecting factors, including the particular contexts in which each project is embedded, the nature of the scientific work that volunteers are asked to undertake, the possibilities and challenges for the future development of the projects as perceived by the scientists, and the tools at the disposal of the respective teams of scientists for mediating relationships with volunteers. The second is amongst the volunteers themselves. This thesis argues that volunteers are heterogeneous, from disparate backgrounds, and that they sustain their involvement in CCPs for very different purposes. In particular, they seek to pursue these through the way they negotiate and construct their relationships with other volunteers, drawing on particular features of the project to do so. This thesis contributes to two fields. The first is to Citizen Cyberscience itself, with a view to improving the running of such projects. Some social studies have already been conducted of CCPs to this end, and this thesis both extends the analysis of some of these pre-existing studies and also problematizes aspects of CCPs that these studies had not considered. I discuss the significance of my findings for those involved in setting up and running a CCP, and present some recommendations for practice. The second field is Science and Technology Studies, in particular studies of public engagement with scientific and technological decision- and knowledge-making processes. The modes of engagement found in CCPs differ in key ways from those that have already been documented in the existing literature (in particular, different power relationships) and thus offer new ways of understanding how the public might be engaged successfully in such processes.

Literature has shown the importance of lifelong learning in the training of today's workforce and the crucial role of Higher Education in preparing graduates for lifelong learning. The aim of the current study is to establish the profile of Medical Radiation Science (MRS) practitioners as lifelong learners and to examine the implications of these findings for MRS undergraduate programs in Australia. The study builds on Candy et. al.'s 1994 report, Developing Lifelong Learners through Undergraduate Education, by drawing on the report's profile of lifelong learners and the features of the undergraduate program that promote lifelong learning. This present study used both quantitative and qualitative approaches, including collating the stakeholders' views on lifelong learning via surveys, one-to-one interviews and focus group discussion.Findings from this study indicate that all stakeholders (MRS practitioners, Heads of MRS Departments, students and teaching staff) viewed lifelong learning to be relevant to the profession and are important attributes for MRS practitioners to attain. However, attributes that were directly related to clinical competencies were more highly valued than attributes which were perceived to be associated with learning competencies. For each of the 25 attributes surveyed, the actual level of attainment fell below the nominated level of importance. Furthermore, the workplace culture was found to be non-supportive of lifelong learning. All MRS courses in Australia promote lifelong learning as one of their course objectives. There is a general trend towards adopting teaching approaches that promote lifelong learning, while assessment methods that promote and evaluate lifelong learning attributes were lagging behind.These findings have implications for both the MRS workplace and the MRS undergraduate courses in Australia. There needs to be greater ++ / dialogue and collaboration between the MRS employers and the universities to address the gap identified in the attributes. A conceptual model integrating lifelong learning in the context of MRS has been introduced to circumnavigate the predicament felt by most respondents that clinical competency must take precedence over all other attributes. Selection criteria by employers for graduates who are entering the workplace for the first time serve as the vital link between the workplace and the universities. By incorporating lifelong learning attributes as an essential part of the selection criteria, students would come to see the relevance of lifelong learning in their undergraduate training. A learning portfolio can be used as a means of demonstrating that the appropriate learning has taken place. There needs to be a closer link between teaching and assessment by aligning the teaching of lifelong learning objectives and activities with the assessment methods. To this end, it is important that teaching staff must be provided with the appropriate professional support to cultivate lifelong learning attributes and to equip them with the appropriate facilitation skills, before the lecturers can be expected to adopt lifelong learning approaches. This research provides a snapshot of lifelong learning in the MRS profession and should assist in the implementation of lifelong learning strategies that would direct the future of the profession.

The learning environment has been the focus of considerable educational research over a long period of time. The study reported in this thesis utilises the perceptions of 208 junior science students from a North Queensland state secondary school to inform classroom environment improvement plans developed and implemented by their teachers' in an attempt to improve the cognitive and attitudinal outcomes of the students. The five stage process on which the study is based combines theory and practice in providing the participating teachers with a structured means of bringing about change in their classrooms. Students' perceptions of actual and preferred teacher interpersonal behaviour and the laboratory learning environment are measured using the QTI and SLEI respectively. Particular aspects of teacher interpersonal behaviour and the laboratory learning environment are targeted for change through the classroom environment improvement plans. The study identified which aspects of the learning environment had changed after a period of intervention. It also identified associations between students' perceptions of aspects of their laboratory learning environment and attitudinal outcomes as well as associations between teacher interpersonal behaviours and attitudinal outcomes. While no direct associations were found between aspects of the laboratory learning environment or teacher interpersonal behaviours and cognitive outcomes, students' cognitive outcomes did improve over the duration of the study thus supporting a previously established link between student attitudes and cognitive outcomes.

The purpose of this study was to investigate scientific epistemological beliefs, perceptions of constructivist learning environment, attitude towards science, prior knowledge and gender as determinants of students&rsquo / approaches to learning. This study was carried out in 2005-2006 Spring Semester. One thousand, one hundred and fifty two eighth grade students from seven public schools in &Ccedil / ankaya, a district of Ankara participated in this study. Epistemological Beliefs Questionnaire, Constructivist Learning Environment Scale, Learning Approaches Questionnaire and Attitude towards Science Scale were administered to students in order to determine their scientific epistemological beliefs, their perceptions of constructivist learning environments, approaches to learning and attitudes towards science respectively. Descriptive statistics were used in order to explore the general characteristics of the sample. Paired samples t-test was used in order to evaluate the mean difference iv between the scales of the actual and preferred learning environments. Pearson Correlation Analyses and Multiple Regression Analyses were conducted to see the relationships among the variables and the variables that contribute to students&rsquo / meaningful and rote learning approaches. Results of the paired samples t-test showed that the actual learning environments of the students did not adapt their preferences. In fact, students preferred more constructivist learning environments where they have more opportunity to relate science with the real world, communicate in the classroom, take role in the decision making process of what will go on in the lesson to be more beneficial for them, question what is going on in the lesson freely and experience the formulation of scientific knowledge. Pearson correlation analyses, however, showed that students who had meaningful learning orientations had tentative views of scientific epistemological beliefs, positive attitudes towards science, high prior knowledge and perceived their learning environments as constructivist. On the other hand, students who had rote learning approaches had fixed views of scientific epistemological beliefs, positive attitudes towards science and low prior knowledge. In addition, the rote learners perceived their environments as constructivist in all scales except shared control scale. Multiple Regression Analyses by using actual learning environment showed that attitude towards science is the best predictor of both meaningful and rote learning approaches.

Thesis (Ph. D.)--Brandeis University, 2009. / "UMI:3369218." MICROFILM COPY ALSO AVAILABLE IN THE UNIVERSITY ARCHIVES. Includes bibliographical references.

The dominant discourse surrounding academic research libraries today is one of change and scholarship in the humanities has seen a similar revolution in practice. Yet, most of the documented changes in either have been ascribed to the availability of online journal materials. Despite the accessibility of millions of rare, digitized primary resources freely available on the web, little has been done to understand the impact of these materials on either the practice of scholarship or on libraries. The research described in this proposal is an investigation into digitization projects involving rare and closely guarded materials and the effects of these projects on humanities scholarship. This thesis uses both qualitative and quantitative measures to: Assess the impact of digitized primary resources on the work of humanities scholars; To construct a model based on the findings that explains current use of digitized primary sources; and, To discuss the implications of these findings for academic research libraries. The research questions are answered through a detailed analysis of the role of digitization in the field of Tibetan and Himalayan studies. The author presents detailed evidence of how digitization is changing the inputs, practice, and outputs of scholarship in this field, as well as the characteristics of digitization that have led to these changes. Importantly, these findings separate out the success of individual projects from the success of digitization across the field as a whole. Support for community and innovation as well as the presence of critical mass across the field are stressed as the three most significant factors. Finally, the implications of these findings are assessed within a newly proposed model of academic libraries. This “scholar-centric” model is intended to provide both a theoretical framework for the research findings as well as a normative provocation for structuring future research and discussions about the role of academic libraries and their presence online.

De nos jours, avec l'expansion d'Internet, l'abondance et la diversité des données accessibles qui en résulte, de nombreuses applications requièrent l'utilisation de méthodes d'apprentissage automatique supervisé capables de prendre en considération différentes sources d'informations. Par exemple, pour des applications relevant de l'indexation sémantique de documents multimédia, il s'agit de pouvoir efficacement tirer bénéfice d'informations liées à la couleur, au texte, à la texture ou au son des documents à traiter. La plupart des méthodes existantes proposent de combiner ces informations multimodales, soit en fusionnant directement les descriptions, soit en combinant des similarités ou des classifieurs, avec pour objectif de construire un modèle de classification automatique plus fiable pour la tâche visée. Ces aspects multimodaux induisent généralement deux types de difficultés. D'une part, il faut être capable d'utiliser au mieux toute l'information a priori disponible sur les objets à combiner. D'autre part, les données sur lesquelles le modèle doit être appliqué ne suivent nécessairement pas la même distribution de probabilité que les données utilisées lors de la phase d'apprentissage. Dans ce contexte, il faut être à même d'adapter le modèle à de nouvelles données, ce qui relève de l'adaptation de domaine. Dans cette thèse, nous proposons plusieurs contributions fondées théoriquement et répondant à ces problématiques. Une première série de contributions s'intéresse à l'apprentissage de votes de majorité pondérés sur un ensemble de votants dans le cadre de la classification supervisée. Ces contributions s'inscrivent dans le contexte de la théorie PAC-Bayésienne permettant d'étudier les capacités en généralisation de tels votes de majorité en supposant un a priori sur la pertinence des votants. Notre première contribution vise à étendre un algorithme récent, MinCq, minimisant une borne sur l'erreur du vote de majorité en classification binaire. Cette extension permet de prendre en compte une connaissance a priori sur les performances des votants à combiner sous la forme d'une distribution alignée. Nous illustrons son intérêt dans une optique de combinaison de classifieurs de type plus proches voisins, puis dans une perspective de fusion de classifieurs pour l'indexation sémantique de documents multimédia. Nous proposons ensuite une contribution théorique pour des problèmes de classification multiclasse. Cette approche repose sur une analyse PAC-Bayésienne originale en considérant la norme opérateur de la matrice de confusion comme mesure de risque. Notre seconde série de contributions concerne la problématique de l'adaptation de domaine. Dans cette situation, nous présentons notre troisième apport visant à combiner des similarités permettant d'inférer un espace de représentation de manière à rapprocher les distributions des données d'apprentissage et des données à traiter. Cette contribution se base sur la théorie des fonctions de similarités (epsilon,gamma,tau)-bonnes et se justifie par la minimisation d'une borne classique en adaptation de domaine. Pour notre quatrième et dernière contribution, nous proposons la première analyse PAC-Bayésienne appropriée à l'adaptation de domaine. Cette analyse se base sur une mesure consistante de divergence entre distributions permettant de dériver une borne en généralisation pour l'apprentissage de votes de majorité en classification binaire. Elle nous permet également de proposer un algorithme adapté aux classifieurs linéaires capable de minimiser cette borne de manière directe.

La sélection de sous-ensembles de molécules diverses est un enjeu très important de la recherche pharmaceutique. En effet, de la qualité de cette sélection, dépendra la découverte efficace d'un médicament. De nombreuses méthodes existent pour répondre à cette demande. Certaines sont basées sur la création de groupes de molécules, d'autres sur le principe de dissimilarité inter-moléculaire. Nous proposons dans ce travail, une nouvelle technique à la croisée de ces méthodes, qui permet d'obtenir des sous-ensembles à la fois divers dans l'espace et représentatifs de l'ensemble initial duquel ils sont extraits. Pour créer cette méthode de sélection, nous avons tout d'abord défini et formalisé mathématiquement un critère de diversité, puis nous nous sommes appuyés sur des heuristiques connues en apprentissage artificiel pour concevoir l'algorithme. Celui-ci a été comparé à d'autres types de sélections de diversité couramment utilisées en chémoinformatique telles que les k-medoïds, Maximum-Dissimilarity, Sphere-Exclusion. La formalisation du critère de diversité nous a enfin permis de proposer un nouveau critère d'évaluation de la qualité des sélections. La méthode et le critère présentés dans ce travail donnent des échantillons divers et représentatifs d'un espace chimique.