Confluent Learning: Using a Design Approach to Develop Cognitive Abilities and Enhance Affective Capacities Through Change Management Curriculum

Purpose The aim of the study is to explore the role of confluent learning in supporting the development of change management knowledge, skills and attitudes and to inform the creation of a conceptual model based upon a priori and a posteriori knowledge gained from literature and the research. Design/methodology/approach The research adopts qualitative approach based on reflective inquiry methodology. There are two primary data sources, interviews with learners and the researchers’ reflective journals on learners’ opinions. Findings The confluent learning approach helped to stimulate affective states (e.g. interest and appreciation) to further reinforce cognitive gains (e.g. retention of knowledge) as a number of higher order thinking skills were further developed. The instructional design premised upon confluent learning enabled learners to further appreciate the complexities of change management. Research implications/ limitations The confluent learning approach offers another explanation to how learning takes place, contingent upon the use of a problem solving framework, instructional design and active learning in developing inter- and trans-disciplinary competencies. Practical implications This study not only explains how effective learning takes place but is also instructive to learning and teaching, and human resource development (HRD) professionals in curriculum design and the potential benefits of confluent learning. Social implications The adoption of a confluent learning approach helps to re-naturalise learning that appeals to learners affect. Originality/value This research is one of the few studies that provide an in-depth exploration of the use of confluent learning and how this approach co-develops cognitive abilities and affective capacity in the creation of a conceptual model.

Mapping Learning and Game Mechanics for Serious Games Analysis in Engineering Education

In a world where students are increasing digitally tethered to powerful, ‘always on’ mobile devices, new models of engagement and approaches to teaching and learning are required from educators. Serious Games (SG) have proved to have instructional potential but there is still a lack of methodologies and tools not only for their design but also to support game analysis and assessment. This paper explores the use of SG to increase student engagement and retention. The development phase of the Circuit Warz game is presented to demonstrate how electronic engineering education can be radically reimagined to create immersive, highly engaging learning experiences that are problem-centered and pedagogically sound. The Learning Mechanics–Game Mechanics (LM-GM) framework for SG game analysis is introduced and its practical use in an educational game design scenario is shown as a case study.

Integration of learning and practice as part of the educational system development in Eritrea. "School Management" - a distance learning program by technical university of Kaiserslautern

The distance learning program "School Management" supports decision makers at the school and ministerial levels in the shaping of formal and informal learning processes at different levels in schools and curricula in Eritrea. This paper examines how the distance learning program is interconnected to educational system development. (DIPF/Orig.)

Creating Common Ground: Architecture For Tactical Learning and Creative Convergence

Certain environments can inhibit learning and stifle enthusiasm, while others enhance learning or stimulate curiosity. Furthermore, in a world where technological change is accelerating we could ask how might architecture connect resource abundant and resource scarce innovation environments? Innovation environments developed out of necessity within urban villages and those developed with high intention and expectation within more institutionalized settings share a framework of opportunity for addressing change through learning and education. This thesis investigates formal and informal learning environments and how architecture can stimulate curiosity, enrich learning, create common ground, and expand access to education. The reason for this thesis exploration is to better understand how architects might design inclusive environments that bring people together to build sustainable infrastructure encouraging innovation and adaptation to change for years to come. The context of this thesis is largely based on Colin McFarlane’s theory that the “city is an assemblage for learning” The socio-spatial perspective in urbanism, considers how built infrastructure and society interact. Through the urban realm, inhabitants learn to negotiate people, space, politics, and resources affecting their daily lives. The city is therefore a dynamic field of emergent possibility. This thesis uses the city as a lens through which the boundaries between informal and formal logics as well as the public and private might be blurred. Through analytical processes I have examined the environmental devices and assemblage of factors that consistently provide conditions through which learning may thrive. These parameters that make a creative space significant can help suggest the design of common ground environments through which innovation is catalyzed.

Datasets, features, learning, and models in visual recognition

Visual recognition is a fundamental research topic in computer vision. This dissertation explores datasets, features, learning, and models used for visual recognition. In order to train visual models and evaluate different recognition algorithms, this dissertation develops an approach to collect object image datasets on web pages using an analysis of text around the image and of image appearance. This method exploits established online knowledge resources (Wikipedia pages for text; Flickr and Caltech data sets for images). The resources provide rich text and object appearance information. This dissertation describes results on two datasets. The first is Berg’s collection of 10 animal categories; on this dataset, we significantly outperform previous approaches. On an additional set of 5 categories, experimental results show the effectiveness of the method. Images are represented as features for visual recognition. This dissertation introduces a text-based image feature and demonstrates that it consistently improves performance on hard object classification problems. The feature is built using an auxiliary dataset of images annotated with tags, downloaded from the Internet. Image tags are noisy. The method obtains the text features of an unannotated image from the tags of its k-nearest neighbors in this auxiliary collection. A visual classifier presented with an object viewed under novel circumstances (say, a new viewing direction) must rely on its visual examples. This text feature may not change, because the auxiliary dataset likely contains a similar picture. While the tags associated with images are noisy, they are more stable when appearance changes. The performance of this feature is tested using PASCAL VOC 2006 and 2007 datasets. This feature performs well; it consistently improves the performance of visual object classifiers, and is particularly effective when the training dataset is small. With more and more collected training data, computational cost becomes a bottleneck, especially when training sophisticated classifiers such as kernelized SVM. This dissertation proposes a fast training algorithm called Stochastic Intersection Kernel Machine (SIKMA). This proposed training method will be useful for many vision problems, as it can produce a kernel classifier that is more accurate than a linear classifier, and can be trained on tens of thousands of examples in two minutes. It processes training examples one by one in a sequence, so memory cost is no longer the bottleneck to process large scale datasets. This dissertation applies this approach to train classifiers of Flickr groups with many group training examples. The resulting Flickr group prediction scores can be used to measure image similarity between two images. Experimental results on the Corel dataset and a PASCAL VOC dataset show the learned Flickr features perform better on image matching, retrieval, and classification than conventional visual features. Visual models are usually trained to best separate positive and negative training examples. However, when recognizing a large number of object categories, there may not be enough training examples for most objects, due to the intrinsic long-tailed distribution of objects in the real world. This dissertation proposes an approach to use comparative object similarity. The key insight is that, given a set of object categories which are similar and a set of categories which are dissimilar, a good object model should respond more strongly to examples from similar categories than to examples from dissimilar categories. This dissertation develops a regularized kernel machine algorithm to use this category dependent similarity regularization. Experiments on hundreds of categories show that our method can make significant improvement for categories with few or even no positive examples.

Towards an understanding of Pakistani undergraduates’ current attitudes towards learning and speaking English

The English language has an important place in Pakistan and in its education system, not least because of the global status of English and its role in employment. Realising the need to enhance language learning outcomes, especially at the tertiary level, the Higher Education Commission (HEC) of Pakistan has put in place some important measures to improve the quality of English language teaching practice through its English Language Teaching Reforms (ELTR) project. However, there is a complex linguistic, educational and ethnic diversity in Pakistan and that diversity, alongside the historical and current role of English in the country, makes any language teaching reform particularly challenging. I argue, in this thesis, that reform to date has largely ignored the issues of learner readiness to learn and learner perceptions of the use of English. I argue that studying learner attitudes is important if we are to understand how learners perceive the practice of learning and the use of English in their lives. This study focuses on the attitudes of undergraduate learners of English as a foreign language at two universities in the provinces of Sindh and Balochistan in Pakistan. These provinces have experienced long struggles and movements related to linguistic and ethnic rights and both educate students from all of the districts of their respective provinces. Drawing on debates around linguistic imperialism, economic necessity, and linguistic and educational diversity, I focus on learners’ perceptions about learning and speaking English, asking what their attitudes are towards learning and speaking English with particular reference to socio-psychological factors at a given time and context, including perceived threats to their culture, religion, and mother tongue. I ask how they make choices about learning and speaking English in different domains of language use and question their motivation to learn and speak English. Additionally, I explore issues of anxiety with reference to their use of English. Following a predominantly qualitative mixed methods research approach, the study employs two research tools: an adapted Likert Scale questionnaire completed by 300 students and semi-structured interviews with 20 participants from the two universities. The data were analysed through descriptive statistics and qualitative content analysis, with each set of data synthesised for interpretation. The findings suggest that, compared with the past, the majority of participants hold positive attitudes towards learning and speaking English regardless of their ethnic or linguistic backgrounds. Most of these undergraduate students do not perceive the use of English as a threat to their culture, mother tongue or religious values but, instead, they have a pragmatic and, at the same time, aspirational attitude to the learning and use of English. I present these results and conclude this thesis with reference to ways in which this small-scale study contributes to a better understanding of learner attitudes and perceptions. Acknowledging the limitations of this study, I suggest ways in which the study, enhanced and extended by further research, might have implications for practice, theory and policy in English language teaching and learning in Pakistan.

Work, Professional Development And Teaching Commitment: Deconstructing Meanings

The paper we present is part of the research project "The professional identity of teacher studies", that we are development for last 3 years. The third phase of this research put the focus on the experience of job placement of novel teachers, graduated no more than 5 years. We work with focal groups and professional experience and teacher education accounts of teachers implied in this research. Also, for any teachers, we do biographical interviews to deepen on processes of construction of professional identity. In this paper we present the Ana Belen History, a female teacher of pre-school education with an experience of 4 years in school, working in a urban school with students in risk of exclusion. This school have a educative project, commitment with the neighbourhood, joint with the community and other social groups. Ana Belen story, from professional perspective, is linked with the social politic and educational commitment of this school. Our interest is focused in the comprehension of professional identity that Ana Belen has gone forging along her personal story and how her education and job placement has contributed for it. Also we are interested in knowing how early professional experiences have influenced in her professional development as teacher. Specifically we ask ourselves about what influence have for her professional identity, that her career starts in this particular school. In consequence, this paper leads us to question the current teacher education model. In particular we are interested on the kind of professional experience that have place and, so, the kinds of commitments that enables. We understand that frameworks in which professional education and experience have place are relevant to enable more or less transformer understandings about teaching. From conceptual perspective this paper adopts a socio-critical point of view (Gergen, 1985; Kincheloe, 2001; Wenger, 1988, etc.). We understand that teaching has to be analysing according work contexts and personal stories of teachers, because we face processes historical and collective building. Teaching is the result of action of their actors, over time, and in specific stage. So, with this research we intend to break with the old gap between pre and in-service education. We think that both of them are part of the same process and are formed according similar logical; although scenes change. We understand that they are part of a continuous process in which is giving sense to different and complex settings where teaching profession is built, but they are not differenced and independent stages. The teacher work, so, is subject to particular conditions, generated from such different fields as institutional, corporative, cultural, social, political, moral, etc. It displays a kaleidoscopic view on space, time, context, ... These are the axis in which the teaching is formed, from the complexity and heterogeneity. How this complexity is articulated results in different ways to face the teacher work, according different personal and professional stories. The teacher acts with subjects in instituted contexts from relationships he has with them, which gives a situated and contingent character. But, these contexts are strongly structured and ruled according centralized and generalized positions; which is, at the very least, paradoxical. Possibly, from our point of view, same of the crisis of teaching have to explain from this paradoxical perspective and the conflict, which characterize this job (Rivas, Leite y Cortés, 2011)

Practical assessment on the run – iPads as an effective mobile and paperless tool in physical education and teaching

This paper investigates the use of iPads in the assessment of predominantly second year Bachelor of Education (Primary/Early Childhood) pre-service teachers undertaking a physical education and health unit. Within this unit, practical assessment tasks are graded by tutors in a variety of indoor and outdoor settings. The main barriers for the lecturer or tutor for effective assessment in these contexts include limited time to assess and the provision of explicit feedback for large numbers of students, complex assessment procedures, overwhelming record-keeping and assessing students without distracting from the performance being presented. The purpose of this pilot study was to investigate whether incorporating mobile technologies such as iPads to access online rubrics within the Blackboard environment would enhance and simplify the assessment process. Results from the findings indicate that using iPads to access online rubrics was successful in streamlining the assessment process because it provided pre-service teachers with immediate and explicit feedback. In addition, tutors experienced a reduction in the amount of time required for the same workload by allowing quicker forms of feedback via the iPad dictation function. These outcomes have future implications and potential for mobile paperless assessment in other disciplines such as health, environmental science and engineering.

Methods for integrating machine learning and constrained optimization

In the framework of industrial problems, the application of Constrained Optimization is known to have overall very good modeling capability and performance and stands as one of the most powerful, explored, and exploited tool to address prescriptive tasks. The number of applications is huge, ranging from logistics to transportation, packing, production, telecommunication, scheduling, and much more. The main reason behind this success is to be found in the remarkable effort put in the last decades by the OR community to develop realistic models and devise exact or approximate methods to solve the largest variety of constrained or combinatorial optimization problems, together with the spread of computational power and easily accessible OR software and resources. On the other hand, the technological advancements lead to a data wealth never seen before and increasingly push towards methods able to extract useful knowledge from them; among the data-driven methods, Machine Learning techniques appear to be one of the most promising, thanks to its successes in domains like Image Recognition, Natural Language Processes and playing games, but also the amount of research involved. The purpose of the present research is to study how Machine Learning and Constrained Optimization can be used together to achieve systems able to leverage the strengths of both methods: this would open the way to exploiting decades of research on resolution techniques for COPs and constructing models able to adapt and learn from available data. In the first part of this work, we survey the existing techniques and classify them according to the type, method, or scope of the integration; subsequently, we introduce a novel and general algorithm devised to inject knowledge into learning models through constraints, Moving Target. In the last part of the thesis, two applications stemming from real-world projects and done in collaboration with Optit will be presented.

Computational creativity: an interdisciplinary approach to sequential learning and creative generations

Creativity seems mysterious; when we experience a creative spark, it is difficult to explain how we got that idea, and we often recall notions like ``inspiration" and ``intuition" when we try to explain the phenomenon. The fact that we are clueless about how a creative idea manifests itself does not necessarily imply that a scientific explanation cannot exist. We are unaware of how we perform certain tasks, such as biking or language understanding, but we have more and more computational techniques that can replicate and hopefully explain such activities. We should understand that every creative act is a fruit of experience, society, and culture. Nothing comes from nothing. Novel ideas are never utterly new; they stem from representations that are already in mind. Creativity involves establishing new relations between pieces of information we had already: then, the greater the knowledge, the greater the possibility of finding uncommon connections, and the more the potential to be creative. In this vein, a beneficial approach to a better understanding of creativity must include computational or mechanistic accounts of such inner procedures and the formation of the knowledge that enables such connections. That is the aim of Computational Creativity: to develop computational systems for emulating and studying creativity. Hence, this dissertation focuses on these two related research areas: discussing computational mechanisms to generate creative artifacts and describing some implicit cognitive processes that can form the basis for creative thoughts.

Diagramas de Ellingham e de Van't Hoff: algumas considerações

The main subject of this article is to show the parallelism betwen the Ellingham and Van't Hoff diagrams. The first one is a graphic representation of the changes in the standard Gibbs free energy (deltarGtheta) as a function of T and was introduced by Ellingham in 1944, in order to study metallurgic processes involving oxides and sulphides. On the other hand, the Van't Hoff diagram is a representation of the function ln K versus (1/T). The equivalence between both diagrams is easily demonstrated, making simple mathematical manipulations. In order to show the parallelism between both diagrams, they are presented briefly and two examples are discussed. The comparison of the both diagrams surely will be helpful to students and teachers in their learning and teaching activities, and will certainly enrich important aspects of chemical thermodynamics.

Polar organic marker compounds in atmospheric aerosols during the LBA-SMOCC 2002 biomass burning experiment in Rondonia, Brazil: sources and source processes, time series, diel variations and size distributions

Measurements of polar organic marker compounds were performed on aerosols that were collected at a pasture site in the Amazon basin (Rondonia, Brazil) using a high-volume dichotomous sampler (HVDS) and a Micro-Orifice Uniform Deposit Impactor (MOUDI) within the framework of the 2002 LBA-SMOCC (Large-Scale Biosphere Atmosphere Experiment in Amazonia - Smoke Aerosols, Clouds, Rainfall, and Climate: Aerosols From Biomass Burning Perturb Global and Regional Climate) campaign. The campaign spanned the late dry season (biomass burning), a transition period, and the onset of the wet season (clean conditions). In the present study a more detailed discussion is presented compared to previous reports on the behavior of selected polar marker compounds, including levoglucosan, malic acid, isoprene secondary organic aerosol (SOA) tracers and tracers for fungal spores. The tracer data are discussed taking into account new insights that recently became available into their stability and/or aerosol formation processes. During all three periods, levoglucosan was the most dominant identified organic species in the PM(2.5) size fraction of the HVDS samples. In the dry period levoglucosan reached concentrations of up to 7.5 mu g m(-3) and exhibited diel variations with a nighttime prevalence. It was closely associated with the PM mass in the size-segregated samples and was mainly present in the fine mode, except during the wet period where it peaked in the coarse mode. Isoprene SOA tracers showed an average concentration of 250 ng m(-3) during the dry period versus 157 ng m(-3) during the transition period and 52 ng m(-3) during the wet period. Malic acid and the 2-methyltetrols exhibited a different size distribution pattern, which is consistent with different aerosol formation processes (i.e., gas-to-particle partitioning in the case of malic acid and heterogeneous formation from gas-phase precursors in the case of the 2-methyltetrols). The 2-methyltetrols were mainly associated with the fine mode during all periods, while malic acid was prevalent in the fine mode only during the dry and transition periods, and dominant in the coarse mode during the wet period. The sum of the fungal spore tracers arabitol, mannitol, and erythritol in the PM(2.5) fraction of the HVDS samples during the dry, transition, and wet periods was, on average, 54 ng m(-3), 34 ng m(-3), and 27 ng m(-3), respectively, and revealed minor day/night variation. The mass size distributions of arabitol and mannitol during all periods showed similar patterns and an association with the coarse mode, consistent with their primary origin. The results show that even under the heavy smoke conditions of the dry period a natural background with contributions from bioaerosols and isoprene SOA can be revealed. The enhancement in isoprene SOA in the dry season is mainly attributed to an increased acidity of the aerosols, increased NO(x) concentrations and a decreased wet deposition.

Combined photocatalytic and fungal processes for the treatment of nitrocellulose industry wastewater

The objective of this work was to characterize the delignification effluent originating from the delignification industry and evaluate the combination of the fungus and photocatalytic process (TiO(2)/UV system) for the treatment of this effluent. The delignification effluent has proven harmful to the environment because it presents high color (3516 CU), total phenol (876 mg/L and TOC (1599 mg/L) and is also highly toxic even in a low concentration. The results of photocatalysis were 11%, 25% and 13% higher for reductions in color, total phenol and TOC, respectively. The combined treatments presented benefits when compared to the non-combined treatments. Fungus and photocatalysis in combination proved to be the best treatment, reducing the color, total phenol, toxicity (inhibition of Escherichia coli growth) and TOC by 94.2%, 92.6%, 4.9% and 62%, respectively. (C) 2008 Elsevier B.V. All rights reserved.

High gravity batch and continuous processes for beer production: Evaluation of fermentation performance and beer quality

This study deals with two innovative brewing processes, high gravity batch and complete continuous beer fermentation systems. The results show a significant influence of the variables such as concentration and temperature on the yield factor of the substrate into ethanol and consequently on the productivity of the high gravity batch process. The technological feasibility of continuous production of beer based on yeast immobilization on cheap alternative carriers was also demonstrated. The influence of process parameters on fermentation performance and quality of the obtained beers was studied by sensorial analysis. No significant difference in the degree of acceptance between the obtained products and some traditional market brands was found. (c) 2008 Institute of Chemistry, Slovak Academy of Sciences.

Feasibility of a Sequencing Reactor Operated in Batch and Fed-batch Mode Applied to Nitrification and Denitrification Processes

The objective of this work was to study the operational feasibility of nitrification and denitrification processes in a mechanically stirred sequencing batch reactor (SBR) operated in batch and fed-batch mode. The reactor was equipped with a draft-tube to improve mass transfer and contained dispersed (aerobic) and granulated (anaerobic) biomass. The following reactor variables were adjusted: aeration time during the nitrification step; dissolved oxygen concentration, feed time defining batch and fed-batch phases, concentration of external carbon source used as electron donor during the denitrification stage and volumetric ammonium nitrogen load in the influent. The reactor (5 L volume) was maintained at 30 +/- 1 degrees C and treated either 1.0 or 1.5 L wastewater in 8-h cycles. Ammonium nitrogen concentrations assessed were: 50 (condition 1) and 100 mgN-NH(4)(+).L(-1) (condition 2), resulting in 29 and 67 mgN-NH(4)(+).L-1-d(-1), respectively. A synthetic medium and ethanol were used as external carbon sources (ECS). Total nitrogen removal efficiencies were 94.4 and 95.9% when the reactor was operated under conditions 1 and 2, respectively. Low nitrite (0.2 and 0.3 mgN-NO(2)(-).L(-1), respectively) and nitrate (0.01 and 0.3 mgN-NO(3)(-).L(-1), respectively) concentrations were detected in the effluent and ammonium nitrogen removal efficiencies were 97.6% and 99.6% under conditions 1 and 2, respectively.