The (new ?) basics of a teacher professional learning community

This paper argues for the need to further theorise the concept of teacher professional learning communities and provides empirical evidence to support this case. The paper presents findings from an ongoing research project, which investigates the nature of teacher professional learning communities. The study reveals that actual communities do not conform to a normailized articulation of features, as outlined in much of the literature on this topic. Consequently, it represents an attempt to engage in the difficult but necessary task of simultaneously fashioning theory from practice, whilst interpreting theory, in practice. The study proposes that current functionalist understandings of teacher professional learning communities are based upon a literature base which is insufficiently nuanced to capture the complexity inherent within these bodies. A broader base of a more critical sociological literature is also drawn upon to better understand actual, "lived" teacher communities, which are somewhat difficult to describe. In part, such communities exhibit features of functionalist conceptions but they are also organic entities which may be quite unpredictable in their outcomes and cannot be reduced to specific features; they each have their own specific "logic of practice" (Bourdieu, 1990) which influences their activities, in their particular field. The argument proposed here is that in one particular community, this complexity may be represented by the many purposes which the community served, arguably often unbeknown to its members, which fashioned the actual community. This paper tries to add to the existing theoretical base of literature, at the same time as providing evidence to support this theorisation.

Consumer responses to really new products: examining the impacts of learning strategies and presentation formats on product comprehension and attitude formation

Mental simulations and analogies have been identified as powerful learning tools for RNPs. Furthermore, visuals in advertising have recently been conceptualized as meaningful sources of information as opposed to peripheral cues and thus may help consumers learn about RNPs. The study of visual attention may also contribute to understanding the links between conceptual and perceptual analyses when learning for a RNP. Two conceptual models are developed. the first model consists of causal relationships between the attributes of advertising stimuli for RNPs and consumer responses, as well as mediating influences. The second model focuses on the role of visual attention in product comprehension as a response to advertising stimuli. Two experiments are conducted: a Web-Experiment and an eye-tracking experiment. The first experiment (858 subjects) examines the effect of learning strategies (mental simulation vs. analogy vs. no analogy/no mental simulation) and presentation formats (words vs. pictures) on individual responses. The mediating role of emotions is assessed. The second experiment investigates the effect of learning strategies and presentation formats on product comprehension, along with the role of attention (17 subjects). The findings from experiment 1 indicate that learning strategies and presentation formats can either enhance or undermine the effect of advertising stimuli on individual responses. Moreover, the nature of the product (i.e. hedonic vs. utilitarian vs. hybrid) should be considered when designing communications for RNPs. The mediating role of emotions is verified. Experiment 2 suggests that an increase in attention to the message may either reflect enhanced comprehension or confusion.

New lecturers' beliefs about learning, teaching and assessment in higher education:the role of the PGCLTHE programme

This study was carried out with new lecturers on a two year Post Graduate Certificate in Learning and Teaching in Higher Education programme in a UK university. The aim was to establish their beliefs about how studying on the programme aligned with their teaching and learning philosophy and what, if anything, had changed or constrained those beliefs. Ten lecturers took part in an in-depth semi-structured interview. Content analysis of the transcripts suggested positive reactions to the programme but lecturers’ new insights were sometimes constrained by departments and university bureaucracy, particularly in the area of assessment. The conflicting roles of research and teaching were also a major issue facing these new professionals.

Development of a learning resource manual for nurses new to thoracic surgery

Background: Patients with lung and esophageal cancer often have surgery as a means of treatment. In Newfoundland and Labrador, patients with lung and esophageal issues are cared for on Six East, the General/Thoracic Surgery unit at St. Clare’s Mercy Hospital. These patients frequently require chest tubes, which are managed and assessed by Registered Nurses (RNs) on the unit. For nurses new to thoracic surgery, fulfilling their new role and caring for chest tube systems can be daunting. Purpose: The purpose of this practicum project was to develop a learning resource manual for nurses who are new to thoracic surgery. Via self-directed learning, the manual can increase the knowledge and self-efficacy of nurses who are caring for thoracic surgery clients and assessing chest tube systems. Methods: An informal needs assessment, integrated literature review, and several consultations via in-person interviews were conducted. Results: Based on the findings from these methodologies, Knowles’ Adult Learning Theory, and Benner’s Novice to Expert Model, a learning resource manual was created. The manual was divided into chapters covering various aspects of patient and chest tube system care and assessment. Conclusion: For the purpose of this practicum project, no evaluation was conducted. However, a plan for future evaluation of the learning resource manual has been developed to determine if the manual assisted with increasing the knowledge and self-efficacy of nurses new to thoracic surgery. “Test Your Knowledge” questions were included at the end of each chapter in the manual as well as case study scenarios to allow for participant self-evaluation.

New Advancements of Scalable Statistical Methods for Learning Latent Structures in Big Data

Constant technology advances have caused data explosion in recent years. Accord- ingly modern statistical and machine learning methods must be adapted to deal with complex and heterogeneous data types. This phenomenon is particularly true for an- alyzing biological data. For example DNA sequence data can be viewed as categorical variables with each nucleotide taking four different categories. The gene expression data, depending on the quantitative technology, could be continuous numbers or counts. With the advancement of high-throughput technology, the abundance of such data becomes unprecedentedly rich. Therefore efficient statistical approaches are crucial in this big data era.

Previous statistical methods for big data often aim to find low dimensional struc- tures in the observed data. For example in a factor analysis model a latent Gaussian distributed multivariate vector is assumed. With this assumption a factor model produces a low rank estimation of the covariance of the observed variables. Another example is the latent Dirichlet allocation model for documents. The mixture pro- portions of topics, represented by a Dirichlet distributed variable, is assumed. This dissertation proposes several novel extensions to the previous statistical methods that are developed to address challenges in big data. Those novel methods are applied in multiple real world applications including construction of condition specific gene co-expression networks, estimating shared topics among newsgroups, analysis of pro- moter sequences, analysis of political-economics risk data and estimating population structure from genotype data.