Evaluating the quality of learning in Computer Supported Co-operative Learning

Can learning quality be maintained in the face of increasing class size by the use of Computer Supported Co-operative Learning (CSCL) technologies? In particular, can Computer-Mediated Communication promote critical thinking in addition to surface information transfer? We compared face-to-face seminars with asynchronous computer conferencing in the same Information Management class. From Garrison's theory of critical thinking and Henri's critical reasoning skills, we developed two ways of evaluating critical thinking: a student questionnaire and a content analysis technique. We found evidence for critical thinking in both situations, with some subtle differences in learning style. This paper provides an overview of this work.

An experiment in group learning technology: evaluating critical thinking in face-to-face and computer-supported seminars

Can learning quality be maintained in the face of increasing class size by the use of Computer Supported Co-operative Learning (CSCL) technologies? In particular, can Computer-Mediated Communication promote critical thinking in addition to surface information transfer? We compared face-to-face seminars with asynchronous computer conferencing in the same Information Management class. From Garrison's theory of critical thinking and Henri's critical reasoning skills, we developed two ways of evaluating critical thinking: a student questionnaire and a content analysis technique. We found evidence for critical thinking in both situations, with some subtle differences in learning style. This paper provides an overview of this work.

A new Jacobian matrix for optimal learning of single-layer neural networks

This paper investigates the learning of a wide class of single-hidden-layer feedforward neural networks (SLFNs) with two sets of adjustable parameters, i.e., the nonlinear parameters in the hidden nodes and the linear output weights. The main objective is to both speed up the convergence of second-order learning algorithms such as Levenberg-Marquardt (LM), as well as to improve the network performance. This is achieved here by reducing the dimension of the solution space and by introducing a new Jacobian matrix. Unlike conventional supervised learning methods which optimize these two sets of parameters simultaneously, the linear output weights are first converted into dependent parameters, thereby removing the need for their explicit computation. Consequently, the neural network (NN) learning is performed over a solution space of reduced dimension. A new Jacobian matrix is then proposed for use with the popular second-order learning methods in order to achieve a more accurate approximation of the cost function. The efficacy of the proposed method is shown through an analysis of the computational complexity and by presenting simulation results from four different examples.

Social categorizations, social comparisons and stigma: Presentations of self in people with learning difficulties

Self-categorization theory stresses the importance of the context in which the metacontrast principle is proposed to operate. This study is concerned with how 'the pool of psychologically relevant stimuli' (Turner, Hogg, Oakes, Reicher & Wetherell, 1987, p. 47) comprising the context is determined. Data from interviews with 33 people with learning difficulties were used to show how a positive sense of self might be constructed by members of a stigmatized social category through the social worlds that they describe, and therefore the social comparisons and categorizations that are made possible. Participants made downward comparisons which focused on people with learning difficulties who were less able or who displayed challenging behaviour, and with people who did not have learning difficulties but who, according to the participants, behaved badly, such as beggars, drunks and thieves. By selection of dimensions and comparison others, a positive sense of self and a particular set of social categorizations were presented. It is suggested that when using self-categorization theory to study real-world social categories, more attention needs to be paid to the involvement of the perceiver in determining which stimuli are psychologically relevant since this is a crucial determinant of category salience.

Learning Not to Curse: Swearing, Testimony, and Truth in Olaudah Equiano’s The Interesting Narrative

This article addresses swearing and testimony in Olaudah Equiano’s The Interesting Narrative (1789) by reading the work in the context of a broader contemporary discourse concerning profane swearing and cursing. Acts of profane enunciation inform a number of key episodes in Equiano’s life, and bear particular significance for his spiritual development and abolitionist witnessing. Within the Narrative, swearing is cast as a failure of piety, civility, and humanity, and shown to be actively avenged by a retributive deity. In Britain, profane swearing was also thought to undermine the validity of legal testimony; while, in the British West Indies, slaves were denied recourse to such testimony against their oppressors. By disavowing profane swearing and cursing, the essay argues, Equiano sought to assert both the validity of his oath and the truth of his testimony against the iniquities of the British slave trade.

A heterosynaptic learning rule for neural networks

In this article we intoduce a novel stochastic Hebb-like learning rule for neural networks that is neurobiologically motivated. This learning rule combines features of unsupervised (Hebbian) and supervised (reinforcement) learning and is stochastic with respect to the selection of the time points when a synapse is modified. Moreover, the learning rule does not only affect the synapse between pre- and postsynaptic neuron, which is called homosynaptic plasticity, but effects also further remote synapses of the pre-and postsynaptic neuron. This more complex form of synaptic plasticity has recently come under investigations in neurobiology and is called heterosynaptic plasticity. We demonstrate that this learning rule is useful in training neural networks by learning parity functions including the exclusive-or (XOR) mapping in a multilayer feed-forward network. We find, that our stochastic learning rule works well, even in the presence of noise. Importantly, the mean leaxning time increases with the number of patterns to be learned polynomially, indicating efficient learning.

Using location-aware technology for learning Geography in a real digital space outside the classroom

The use of new mobile technologies is still in its infancy in many secondary schools and there is limited evidence of the educational and pedagogical benefits on pupils’ learning in the formal school context. This qualitative study focuses on the use of handheld devices to teach a topic in geography to an examination class. Action research combined with pupil observations and focus group interviews are used to capture the pupils’ experiences of using mediascapes. Activity Theory is used as a lens to structure the analysis of the data and to report on the cognitive and affective impact of m-learning on pupils’ academic performance in the topic. Increased attainment and the development of wider skills for lifelong learning were identified in the study. The adaptability of the majority of pupils to the technology resulted in increased levels of willingness to learn in this novel context.

A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.

Design and Practice in Architectural Theory Education

Benefiting from design in theory learning is not common in architecture schools. The general practice is to design in studio and to theorise in lectures. In the undergraduate module History and Theory in Architecture II at Queen’s University Belfast, students attend interactive lectures, participate in reading group discussions, design TextObjects, and write essays. TextObjects contain textual, audio and/or graphic representations that highlight a single concept or a complex set of issues derived from readings. Students experiment with diverse media, such as filmmaking, photography, and graphic design, some of which they experience for the first time. Lectures and readings revolve around theories of architectural representation, media and communication, which are practiced through TextObjects. This is a new way to link theory and practice in architectural education. Through action research, this study analyses this innovative teaching method called TextObject, which brings design and practice into architectural theory education to stimulate students towards critical thinking. The pedagogical research of architectural theoretician Necdet Teymur (1992, 1996, 2002) underlies the study.

Peer assisted learning in health education.

There are many forms of Peer Assisted Learning (PAL). There are well-established theoretical models as to why PAL is proven to be effective across educational sectors. To maximise gains from PAL careful consideration needs to be given to the roles of peers. Evidence suggests that PAL projects with clearly defined roles for interaction result in strongest outcomes. Effect Sizes (ES) from meta-analyses of peer assisted learning indicate ES of between 0.25-0.50. Outcomes can be social and emotional as well as academic. PAL generally requires adaptation of existing resources and can be cost-effective to implement compared to other educational developments.

Learning fluid prescription skills: why is it so challenging?

IIt is well recognised that medical students and junior doctors find fluid prescription a challenging topic. This study was designed to gain a greater understanding of the experiences that medical students face related to learning about fluid prescribing. Methods: A qualitative approach, using focus groups, was employed in this research. Final-year medical students in academic year 2011-12 at Queen's University Belfast were invited to participate during their 'Assistantship' placement in March 2012. Discussions in focus groups, consisting of between six and eight students, were recorded and transcribed verbatim. The research team, consisting of three separate investigators, conducted thematic analysis independently. A final consensus regarding emerging themes was reached by discussion within the whole research team. Medical students and junior doctors find fluid prescription a challenging topic Results: Five prominent themes emerged: 'Teaching experience: a disruptive variation'; 'Curricular disconnections'; 'The driving test: Theory-practice transformation'; 'Role modelling: which standard to aspire to?'; and finally 'Reconciling the perceived risk'. Discussion: This re search provided insights into medical students' opinions of the teaching practices and learning experiences related to fluid prescribing. The learning of prescribing skills is complex andcontextual. In the development of such skills, medical students are often exposed to conflicting educational experiences that challenge the novicelearner in making judgements on best prescribing practice. This study adds to the body of evidence that fluid prescription is a difficult topic, and has generated a number of multifaceted and strategic recommendations to potentially improve fluid prescription teaching.

Simulation using novel equipment designed to explain spirometric abnormalities in respiratory disease enhances learning in higher cognitive domains

Simulation of disorders of respiratory mechanics shown by spirometry provides insight into the pathophysiology of disease but some clinically important disorders have not been simulated and none have been formally evaluated for education. We have designed simple mechanical devices which, along with existing simulators, enable all the main dysfunctions which have diagnostic value in spirometry to be simulated and clearly explained with visual and haptic feedback. We modelled the airways as Starling resistors by a clearly visible mechanical action to simulate intra- and extra-thoracic obstruction. A narrow tube was used to simulate fixed large airway obstruction and inelastic bands to simulate restriction. We hypothesized that using simulators whose action explains disease promotes learning especially in higher domain educational objectives. The main features of obstruction and restriction were correctly simulated. Simulation of variable extra-thoracic obstruction caused blunting and plateauing of inspiratory flow, and simulation of intra-thoracic obstruction caused limitation of expiratory flow with marked dynamic compression. Multiple choice tests were created with questions allocated to lower (remember and understand) or higher cognitive domains (apply, analyse and evaluate). In a cross-over design, overall mean scores increased after 1½ h simulation spirometry (43-68 %, effect size 1.06, P < 0.0001). In higher cognitive domains the mean score was lower before and increased further than lower domains (Δ 30 vs 20 %, higher vs lower effect size 0.22, P < 0.05). In conclusion, the devices successfully simulate various patterns of obstruction and restriction. Using these devices medical students achieved marked enhancement of learning especially in higher cognitive domains.

Enabling Others in Social Work: Reflexivity and the Theory of Social Domains

This paper sets out a framework to structure reflexivity in social work practice. Based on the thinking of the sociologist, Derek Layder, it comprises five domains that impact on the individual and social life, namely: (i) psycho-biography – referring to a person’s unique experience throughout the life-course; (ii) situated activity – highlighting the impact of every day social interaction; (iii) social settings – addressing the role of organizations in social life; (iv) culture – covering the influence of attitudes, beliefs, tastes and ideas on symbolic meaning; and (v) politico-economy – alluding to the ramifications of political and economic forces on people’s lives. It is contended that power circulates throughout each domain as an enabling and constraining force. The paper then outlines a process for using the reflexive framework in ‘enabling’ activities such as practice learning, supervision, mentoring and coaching. By applying the framework in these contexts, it is argued that social workers can reflect critically on their role and develop emancipatory forms of practice.