Something to talk about: Content and Language Integrated Learning in Modern Languages in British Higher Education. A case study of German at Aston University

This thesis investigates Content and Language Integrated Learning (CLIL) in German undergraduate programmes in the UK. At its core is a study of how one German department integrates the teaching of language and content in its undergraduate programmes and how instructors and students experience this approach. This micro-context is embedded in the wider macro-context of UK Higher Education and subject to outside forces - be they political, economic, socio-cultural - whose effects will manifest in more or less obvious ways. Data was collected via an online survey of Heads of German at British universities to determine the status quo of CLIL in UK Higher Education and to investigate how certain institutional parameters determine the introduction of CLIL in Higher Education. This project employs a mixed-method case study approach and is based on student questionnaires and semi-structured interview with German teaching staff. The study brings to light a number of significant aspects. For example, contrary to popular belief, content provision in the L2 is rather common at British universities, which is currently not reflected in the research. Student data indicates that German students perceive clear advantages in the university’s approach to CLIL. They consider German-taught content classes challenging yet beneficial for their language development. Staff interviews have yielded intriguing information about perceived advantages and disadvantages of CLIL, about its implications for classroom practice, and about instructors’ attitude towards teacher training, which echo findings from similar investigations in European contexts. Finally, the results of the macro-analysis and the case study are compared and contrasted with findings from European research on ICLHE/CLIL to determine differences and similarities with the British context, a set of recommendations is made regarding CLIL practice at the case study institution, and some implications these indings may have for the future of CLIL in British higher education are discussed.

Nursing faculty intention to use service learning as pedagogy in higher education

The purpose of this study was to identify the factors that motivate nursing faculty to use service learning. The study was based on the theory of planned behavior (TPB), which implies that the target behavior of intention to use service learning in higher education is influenced by the predictor variables of behavior beliefs (attitude), normative beliefs (peer influence), and control beliefs (confidence and resources). External variables were also considered (years of teaching experience, tenure status, and the type of curriculum). ^ Group interviews and a pilot test were conducted to create the instrument for the study, and Cronbach alpha were calculated for survey item reliability. The participants were full time undergraduate nursing faculty members ( n = 160) in the Southeastern United States who taught in universities with accredited nurse education programs. Demographic data as well as scores on scaled survey responses were used to evaluate the intention of nursing faculty to use service learning in their classes. ^ Pearson product moment correlation coefficient and path analysis were applied to the data. The correlation findings indicated that there were statistically significant relationships between behavior beliefs, normative beliefs, and control beliefs and nursing faculty intention to use service learning. The path analysis also indicated that behavior beliefs and normative beliefs were significant, while control beliefs were not a strong influence on intention to use service learning. Normative beliefs showed the strongest direct influence. The use of a community based curriculum also had a positive influence on intention, and faculty with tenure status were more likely to have positive behavior beliefs (attitude) towards service learning. Finally, as teaching experience increased, positive attitudes towards the intention to use service learning decreased. Seventy-nine percent of the variation in the intention to use service learning was explained by the theory of planned behavior, the type of curriculum, teaching experience, and tenure status. These results will assist nursing administration and faculty to design strategies to facilitate the implementation of service learning pedagogy, as well as a community based curriculum which will help meet the 21st century goals set forth from the American Association of Colleges of Nursing. ^

Group presence in virtual worlds: Supporting collaborative e-learning

Even though e-learning endeavors have significantly proliferated in recent years, current e-learning technologies provide poor support for group-oriented learning. The now popular virtual world's technologies offer a possible solution. Virtual worlds provide the users with a 3D - computer generated shared space in which they can meet and interact through their virtual representations. Virtual worlds are very successful in developing high levels of engagement, presence and group presence in the users. These elements are also desired in educational settings since they are expected to enhance performance. The goal of this research is to test the hypothesis that a virtual world learning environment provides better support for group-oriented collaborative e-learning than other learning environments, because it facilitates the emergence of group presence. To achieve this, a quasi-experimental study was conducted and data was gathered through the use of various survey instruments and a set of collaborative tasks assigned to the participants. Data was gathered on the dependent variables: Engagement, Group Presence, Individual Presence, Perceived Individual Presence, Perceived Group Presence and Performance. The data was analyzed using the statistical procedures of Factor Analysis, Path Analysis, Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA). The study provides support for the hypothesis. The results also show that virtual world learning environments are better than other learning environments in supporting the development of all the dependent variables. It also shows that while only Individual Presence has a significant direct effect on Performance; it is highly correlated with both Engagement and Group Presence. This suggests that these are also important in regards to performance. Developers of e-learning endeavors and educators should incorporate virtual world technologies in their efforts in order to take advantage of the benefit they provide for e-learning group collaboration.

Knowledge creation in dynamic learning environments

Researchers have extensively discussed using knowledge management to achieve sustainable competitive advantages; however, the successful implementation of knowledge management programs in organizations remains challenging. Problems with knowledge management arise primarily from issues related to inter-subjective creation of meaning by diverse individuals in a dynamic learning environment. ^ The first part of this dissertation examined the concepts of shared interpretive resources referring to background assumptions, shared language, and symbolic resources upon which individuals draw in their interactions in the community. The discussion adopted an interpretive research approach to underscore how community members develop shared interpretive resources over time. The second part examined how learners' behaviors influence knowledge acquisition in the community, emphasizing the associations between learners' learning approaches and learning contexts. An empirical survey of learners provided significant evidence to demonstrate the influences of learners' learning approaches. The third part examined an instructor's strategy—namely, advance organizer—to enhance learners' knowledge assimilation process. Advance organizer is an instructor strategy that refers to a set of inclusive concepts that introduce and sum up new material, and refers to a method of bridging and linking old information with something new. In this part, I underscore the concepts of advance organizer, and the implementations of advance organizer in one learning environment. A study was conducted in one higher educational environment to show the implementation of advance organizer. Additionally, an advance organizer instrument was developed and tested, and results from learners' feedback were analyzed. The significant empirical evidence showed the association between learners' learning outcomes and the implementation of advance organizer strategy. ^

An incremental multilinear system for human face learning and recognition

This dissertation establishes a novel system for human face learning and recognition based on incremental multilinear Principal Component Analysis (PCA). Most of the existing face recognition systems need training data during the learning process. The system as proposed in this dissertation utilizes an unsupervised or weakly supervised learning approach, in which the learning phase requires a minimal amount of training data. It also overcomes the inability of traditional systems to adapt to the testing phase as the decision process for the newly acquired images continues to rely on that same old training data set. Consequently when a new training set is to be used, the traditional approach will require that the entire eigensystem will have to be generated again. However, as a means to speed up this computational process, the proposed method uses the eigensystem generated from the old training set together with the new images to generate more effectively the new eigensystem in a so-called incremental learning process. In the empirical evaluation phase, there are two key factors that are essential in evaluating the performance of the proposed method: (1) recognition accuracy and (2) computational complexity. In order to establish the most suitable algorithm for this research, a comparative analysis of the best performing methods has been carried out first. The results of the comparative analysis advocated for the initial utilization of the multilinear PCA in our research. As for the consideration of the issue of computational complexity for the subspace update procedure, a novel incremental algorithm, which combines the traditional sequential Karhunen-Loeve (SKL) algorithm with the newly developed incremental modified fast PCA algorithm, was established. In order to utilize the multilinear PCA in the incremental process, a new unfolding method was developed to affix the newly added data at the end of the previous data. The results of the incremental process based on these two methods were obtained to bear out these new theoretical improvements. Some object tracking results using video images are also provided as another challenging task to prove the soundness of this incremental multilinear learning method.

An interview study of community college student perspectives on service -learning

Over the past two decades, the community college in the United States has boasted a leadership role in the movement to make education community-based and performance-oriented. This has led to an intensification in attempts to search for more innovative means to make education more experiential and relevant to students' lived experiences. ^ One such innovative program that holds promise to meet this challenge is service-learning. This paradigm attempts to relate the academic education in the classroom to community-based problems, which fits in neatly with the community-based characteristics of the community college. It promises to link ideas developed in the classroom and their practical application within the community through guided reflection. It is designed to enhance and enrich student learning of course material by combining citizenship, academic subjects, skills, and values. ^ Though many studies have been carried out in regard to the outcomes of service-learning through quantitative means, relatively few qualitative studies are available, and those available have primarily studied traditional students at four-year residential colleges or universities. Therefore, there is an urgent need to study non-traditional students' perspectives at the community college level. ^ The purpose of this study was to describe and explain the perspectives of five students at Broward Community College, Central Campus, Ft. Lauderdale, Florida. The following exploratory questions guided this study: (1) What elements constitute these students' perspectives? (2) What variables influence their perspectives? (3) What beliefs do these students hold about their service-learning experience which support or are contrary to their perspectives? ^ This ethnographic interview study was conducted over a period of twelve months and consisted of three interviews for each of the five participants. The analysis of the data was conducted following the stringent principles of ethnographic research which included constant comparative analysis. The interviews were tape recorded with the participants' permission, transcribed verbatim, and organized into categories for in-depth understanding. Furthermore, these categories were developed from the data collected and an organizational scheme for understanding and interpreting of these perspectives emerged. The researcher, as well, kept a reflective journal of the research process as part of the data set. ^ The results of this study show the need for a better grasp of the concepts of service-learning on the part of all involved with its implementation. In spite of this, all of the participants displayed gains to a greater or lesser degree in personal growth, academic skills, and citizenship skills. ^

The effect of active student responding in computer -assisted instruction on social -studies learning by students with learning disabilities

The purpose of this study was to compare the effects of three student response conditions during computer-assisted instruction on the acquisition and maintenance of social-studies facts. Two of the conditions required active student responding (ASR), whereas the other required an on-task (OT) response. Participants were five fifth-grade students, with learning disabilities enrolled in a private school. An alternating treatments design with a best treatments phase was used to compare the effects of the response procedures on three major dependent measures: same-day tests, next-day tests, and maintenance tests. ^ Each week for six weeks, participants were provided daily one-to-one instruction on sets of 21 unknown social-studies facts using a hypermedia computer program, with a new set of facts being practiced each week. Each set of 21 facts was divided randomly into three conditions: Clicking-ASR, Repeating-ASR, and Listening-OT. Hypermedia lesson began weekly with the concept introduction lesson, followed by practice and testing. Practice and testing occurred four days per week, per set. During Clicking-ASR, student practice involved the selection of a social-studies response by clicking on an item with the mouse on the hypermedia card. Repeating-ASR instruction required students to orally repeat the social-studies facts when prompted by the computer. During Listening-OT, students listened to the social-studies facts being read by the computer. During weeks seven and eight, instruction occurred with seven unknown facts using only the best treatment. ^ Test results show that all for all 5 students, the Repeating-ASR practice procedure resulted in more social-studies facts stated correctly on same-day tests, next-day tests, and one-and two-week maintenance tests. Clicking-ASR was the next most effective procedure. During the seventh and eighth week of instruction when only the best practice condition was implemented, Repeating-ASR produced higher scores than all conditions (including Repeating-ASR) during the first six weeks of the study. ^ The results lend further support to the growing body of literature that demonstrates the positive relation between ASR and student achievement. Much of the ASR literature has focused on the effects of increased ASR during teacher-led or peer-mediated instruction. This study adds a dimension to that research in that it demonstrated the importance of ASR during computer-assisted instruction and further suggests that the type of ASR used during computer-assisted instruction may influence learning. Future research is needed to investigate the effectiveness of other types of ASR during computer-assisted instruction and to identify other fundamental characteristics of an effective computer-assisted instruction. ^

An interview study of community college student perspectives on service-learning

Over the past two decades, the community college in the United States has boasted a leadership role in the movement to make education community-based and performance-oriented. This has led to an intensification in attempts to search for more innovative means to make education more experiential and relevant to students' lived experiences. One such innovative program that holds promise to meet this challenge is service- learning. This paradigm attempts to relate the academic education in the classroom to community-based problems, which fits in neatly with the community-based characteristics of the community college. It promises to link ideas developed in the classroom and their practical application within the community through guided reflection. It is designed to enhance and enrich student learning of course material by combining citizenship, academic subjects, skills, and values. Though many studies have been carried out in regard to the outcomes of service-learning through quantitative means, relatively few qualitative studies are available, and those available have primarily studied traditional students at four-year residential colleges or universities. Therefore, there is an urgent need to study non-traditional students' perspectives at the community college level. The purpose of this study was to describe and explain the perspectives of five students at Broward Community College, Central Campus, Ft. Lauderdale, Florida. The following exploratory questions guided this study: 1. What elements constitute these students' perspectives? 2. What variables influence their perspectives? 3. What beliefs do these students hold about their service-learning experience which support or are contrary to their perspectives? This ethnographic interview study was conducted over a period of twelve months and consisted of three interviews for each of the five participants. The analysis of the data was conducted following the stringent principles of ethnographic research which included constant comparative analysis. The interviews were tape recorded with the participants' permission, transcribed verbatim, and organized into categories for in-depth understanding. Furthermore, these categories were developed from the data collected and an organizational scheme for understanding and interpreting of these perspectives emerged. The researcher, as well, kept a reflective journal of the research process as part of the data set. The results of this study show the need for a better grasp of the concepts of service-learning on the part of all involved with its implementation. In spite of this, all of the participants displayed gains to a greater or lesser degree in personal growth, academic skills, and citizenship skills.

Nursing faculty intention to use service learning as pedagogy in higher education

The purpose of this study was to identify the factors that motivate nursing faculty to use service learning. The study was based on the theory of planned behavior (TPB), which implies that the target behavior of intention to use service learning in higher education is influenced by the predictor variables of behavior beliefs (attitude), normative beliefs (peer influence), and control beliefs (confidence and resources). External variables were also considered (years of teaching experience, tenure status, and the type of curriculum). Group interviews and a pilot test were conducted to create the instrument for the study, and Cronbach alpha were calculated for survey item reliability. The participants were full time undergraduate nursing faculty members (n=-160) in the Southeastern United States who taught in universities with accredited nurse education programs. Demographic data as well as scores on scaled survey responses were used to evaluate the intention of nursing faculty to use service learning in their classes. Pearson product moment correlation coefficient and path analysis were applied to the data. The correlation findings indicated that there were statistically significant relationships between behavior beliefs, normative beliefs, and control beliefs and nursing faculty intention to use service learning. The path analysis also indicated that behavior beliefs and normative beliefs were significant, while control beliefs were not a strong influence on intention to use service learning. Normative beliefs showed the strongest direct influence. The use of a community based curriculum also had a positive influence on intention, and faculty with tenure status were more likely to have positive behavior beliefs (attitude) towards service learning. Finally, as teaching experience increased, positive attitudes towards the intention to use service learning decreased. Seventy-nine percent of the variation in the intention to use service learning was explained by the theory of planned behavior, the type of curriculum, teaching experience, and tenure status. These results will assist nursing administration and faculty to design strategies to facilitate the implementation of service learning pedagogy, as well as a community based curriculum which will help meet the 21st century goals set forth from the American Association of Colleges of Nursing.

Laboratory focussed learning of core electronic engineering concepts in the first year of an honours degree programme

In common with most universities teaching electronic engineering in the UK, Aston University has seen a shift in the profile of its incoming students in recent years. The educational background of students has moved away from traditional Alevel maths and science and if anything this variation is set to increase with the introduction of engineering diplomas. Another major change to the circumstances of undergraduate students relates to the introduction of tuition fees in 1998 which has resulted in an increased likelihood of them working during term time. This may have resulted in students tending to concentrate on elements of the course that directly provide marks contributing to the degree classification. In the light of these factors a root and branch rethink of the electronic engineering degree programme structures at Aston was required. The factors taken into account during the course revision were:. Changes to the qualifications of incoming students. Changes to the background and experience of incoming students. Increase in overseas students, some with very limited practical experience. Student focus on work directly leading to marks. Modular compartmentalisation of knowledge. The need for provision of continuous feedback on performance We discuss these issues with specific reference to a 40 credit first year electronic engineering course and detail the new course structure and evaluate the effectiveness of the changes. The new approach appears to have been successful both educationally and with regards to student satisfaction. The first cohort of students from the new course will graduate in 2010 and results from student surveys relating particularly to project and design work will be presented at the conference. © 2009 K Sugden, D J Webb and R P Reeves.

Development of a work-based learning MSc course which incorporates the development and demonstration of professional engineering competence standards

UK engineering standards are regulated by the Engineering Council (EC) using a set of generic threshold competence standards which all professionally registered Chartered Engineers in the UK must demonstrate, underpinned by a separate academic qualification at Masters Level. As part of an EC-led national project for the development of work-based learning (WBL) courses leading to Chartered Engineer registration, Aston University has started an MSc Professional Engineering programme, a development of a model originally designed by Kingston University, and build around a set of generic modules which map onto the competence standards. The learning pedagogy of these modules conforms to a widely recognised experiential learning model, with refinements incorporated from a number of other learning models. In particular, the use of workplace mentoring to support the development of critical reflection and to overcome barriers to learning is being incorporated into the learning space. This discussion paper explains the work that was done in collaboration with the EC and a number of Professional Engineering Institutions, to design a course structure and curricular framework that optimises the engineering learning process for engineers already working across a wide range of industries, and to address issues of engineering sustainability. It also explains the thinking behind the work that has been started to provide an international version of the course, built around a set of globalised engineering competences. © 2010 W J Glew, E F Elsworth.

Learning from Geometry

Subspaces and manifolds are two powerful models for high dimensional signals. Subspaces model linear correlation and are a good fit to signals generated by physical systems, such as frontal images of human faces and multiple sources impinging at an antenna array. Manifolds model sources that are not linearly correlated, but where signals are determined by a small number of parameters. Examples are images of human faces under different poses or expressions, and handwritten digits with varying styles. However, there will always be some degree of model mismatch between the subspace or manifold model and the true statistics of the source. This dissertation exploits subspace and manifold models as prior information in various signal processing and machine learning tasks.

A near-low-rank Gaussian mixture model measures proximity to a union of linear or affine subspaces. This simple model can effectively capture the signal distribution when each class is near a subspace. This dissertation studies how the pairwise geometry between these subspaces affects classification performance. When model mismatch is vanishingly small, the probability of misclassification is determined by the product of the sines of the principal angles between subspaces. When the model mismatch is more significant, the probability of misclassification is determined by the sum of the squares of the sines of the principal angles. Reliability of classification is derived in terms of the distribution of signal energy across principal vectors. Larger principal angles lead to smaller classification error, motivating a linear transform that optimizes principal angles. This linear transformation, termed TRAIT, also preserves some specific features in each class, being complementary to a recently developed Low Rank Transform (LRT). Moreover, when the model mismatch is more significant, TRAIT shows superior performance compared to LRT.

The manifold model enforces a constraint on the freedom of data variation. Learning features that are robust to data variation is very important, especially when the size of the training set is small. A learning machine with large numbers of parameters, e.g., deep neural network, can well describe a very complicated data distribution. However, it is also more likely to be sensitive to small perturbations of the data, and to suffer from suffer from degraded performance when generalizing to unseen (test) data.

From the perspective of complexity of function classes, such a learning machine has a huge capacity (complexity), which tends to overfit. The manifold model provides us with a way of regularizing the learning machine, so as to reduce the generalization error, therefore mitigate overfiting. Two different overfiting-preventing approaches are proposed, one from the perspective of data variation, the other from capacity/complexity control. In the first approach, the learning machine is encouraged to make decisions that vary smoothly for data points in local neighborhoods on the manifold. In the second approach, a graph adjacency matrix is derived for the manifold, and the learned features are encouraged to be aligned with the principal components of this adjacency matrix. Experimental results on benchmark datasets are demonstrated, showing an obvious advantage of the proposed approaches when the training set is small.

Stochastic optimization makes it possible to track a slowly varying subspace underlying streaming data. By approximating local neighborhoods using affine subspaces, a slowly varying manifold can be efficiently tracked as well, even with corrupted and noisy data. The more the local neighborhoods, the better the approximation, but the higher the computational complexity. A multiscale approximation scheme is proposed, where the local approximating subspaces are organized in a tree structure. Splitting and merging of the tree nodes then allows efficient control of the number of neighbourhoods. Deviation (of each datum) from the learned model is estimated, yielding a series of statistics for anomaly detection. This framework extends the classical {\em changepoint detection} technique, which only works for one dimensional signals. Simulations and experiments highlight the robustness and efficacy of the proposed approach in detecting an abrupt change in an otherwise slowly varying low-dimensional manifold.

Personal learning artefacts: persistence, ownership and privacy

Traditional classrooms have been often regarded as closed spaces within which experimentation, discussion and exploration of ideas occur. Professors have been used to being able to express ideas frankly, and occasionally rashly while discussions are ephemeral and conventional student work is submitted, graded and often shredded. However, digital tools have transformed the nature of privacy. As we move towards the creation of life-long archives of our personal learning, we collect material created in various 'classrooms'. Some of these are public, and open, but others were created within 'circles of trust' with expectations of privacy and anonymity by learners. Taking the Creative Commons license as a starting point, this paper looks at what rights and expectations of privacy exist in learning environments? What methods might we use to define a 'privacy license' for learning? How should the privacy rights of learners be balanced with the need to encourage open learning and with the creation of eportfolios as evidence of learning? How might we define different learning spaces and the privacy rights associated with them? Which class activities are 'private' and closed to the class, which are open and what lies between? A limited set of set of metrics or zones is proposed, along the axes of private-public, anonymous-attributable and non-commercial-commercial to define learning spaces and the digital footprints created within them. The application of these not only to the artefacts which reflect learning, but to the learning spaces, and indeed to digital media more broadly are explored. The possibility that these might inform not only teaching practice but also grading rubrics in disciplines where public engagement is required will also be explored, along with the need for consideration by educational institutions of the data rights of students.

Learning and Exploiting Camera Geometry for Computer Vision

This work explores the use of statistical methods in describing and estimating camera poses, as well as the information feedback loop between camera pose and object detection. Surging development in robotics and computer vision has pushed the need for algorithms that infer, understand, and utilize information about the position and orientation of the sensor platforms when observing and/or interacting with their environment.

The first contribution of this thesis is the development of a set of statistical tools for representing and estimating the uncertainty in object poses. A distribution for representing the joint uncertainty over multiple object positions and orientations is described, called the mirrored normal-Bingham distribution. This distribution generalizes both the normal distribution in Euclidean space, and the Bingham distribution on the unit hypersphere. It is shown to inherit many of the convenient properties of these special cases: it is the maximum-entropy distribution with fixed second moment, and there is a generalized Laplace approximation whose result is the mirrored normal-Bingham distribution. This distribution and approximation method are demonstrated by deriving the analytical approximation to the wrapped-normal distribution. Further, it is shown how these tools can be used to represent the uncertainty in the result of a bundle adjustment problem.

Another application of these methods is illustrated as part of a novel camera pose estimation algorithm based on object detections. The autocalibration task is formulated as a bundle adjustment problem using prior distributions over the 3D points to enforce the objects' structure and their relationship with the scene geometry. This framework is very flexible and enables the use of off-the-shelf computational tools to solve specialized autocalibration problems. Its performance is evaluated using a pedestrian detector to provide head and foot location observations, and it proves much faster and potentially more accurate than existing methods.

Finally, the information feedback loop between object detection and camera pose estimation is closed by utilizing camera pose information to improve object detection in scenarios with significant perspective warping. Methods are presented that allow the inverse perspective mapping traditionally applied to images to be applied instead to features computed from those images. For the special case of HOG-like features, which are used by many modern object detection systems, these methods are shown to provide substantial performance benefits over unadapted detectors while achieving real-time frame rates, orders of magnitude faster than comparable image warping methods.

The statistical tools and algorithms presented here are especially promising for mobile cameras, providing the ability to autocalibrate and adapt to the camera pose in real time. In addition, these methods have wide-ranging potential applications in diverse areas of computer vision, robotics, and imaging.