Learning styles, personalisation and adaptable e-learning

Common Learning Management Systems (for example Moodle [1] and Blackboard [2]) are limited in the amount of personalisation that they can offer the learner. They are used widely and do offer a number of tools for instructors to enable them to create and manage courses, however, they do not allow for the learner to have a unique personalised learning experience. The e-Learning platform iLearn offers personalisation for the learner in a number of ways and one way is to offer the specific learning material to the learner based on the learner's learning style. Learning styles and how we learn is a vast research area. Brusilovsky and Millan [3] state that learning styles are typically defined as the way people prefer to learn. Examples of commonly used learning styles are Kolb Learning Styles Theory [4], Felder and Silverman Index of Learning Styles [5], VARK [6] and Honey and Mumford Index of Learning Styles [7] and many research projects (SMILE [8], INSPIRE [9], iWeaver [10] amonst others) attempt to incorporate these learning styles into adaptive e-Learning systems. This paper describes how learning styles are currently being used within the area of adaptive e-Learning. The paper then gives an overview of the iLearn project and also how iLearn is using the VARK learning style to enhance the platform's personalisation and adaptability for the learner. This research also describes the system's design and how the learning style is incorporated into the system design and semantic framework within the learner's profile.

Exploration of the student experience of e-learning: beginning to bridge the learning divide

Introduction This proposal aims, through debate within symposium to explore the student experience of e-learning. The team facilitating the discussion will draw upon their experience of an HEA funded pathfinder project, the main aim of which was to collect learner stories about their experience of using technology in their everyday learning activities at the University of Greenwich across a range of programmes, levels, locations and student groups. Method The project design responded to the growing body of student voice literature and then utilised and built upon the JISC-funded studies that focussed on understanding the learner perspectives on the role of technology in learning, namely: • the LEX study which investigated a broad spectrum of technology use by eliciting rich data about learners’ feelings, beliefs and intentions towards e-learning (Creanor et al, 2006); • the LXP studies which explored disciplinary differences in uses of technology by university students through a variety of methodologies (Conole et al, 2006). Results The symposium will be organised as a round table discussion that will be structured into three sections: • Designing an online survey tool, and the results of our survey. • Exploring student stories. • What can learned from the project and taking the findings back to enhance learning. To stimulate discussion each section will start by asking the participants to discuss and debate a particular question, this will be followed by an interactive presentation by the respective member of the project team who will share the findings of the project and invite contributions to the resulting discussion from personal perspectives. The questions are: • What is effective learning within a context of digital technology? • What are the myths and truths about the identity of today's learners? • What practical changes need to happen in order to see real change? Conclusion The final section of the symposium will invite contributions from the participants in order to collate the views and perspectives of all the participants in order to focus the discussion on the following: • The issues that have arisen as a result of the round table debates. • New speculative approaches to enhancing the student experience. • A controversial stand to the future of Higher Education teaching and learning and the role and integration of technology within that education. The symposium will provide an opportunity to explore the predictive value of Student Experience of E-Learning Laboratory (SEEL) project.

Learning Bayesian networks from data: An information-theory based approach

This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop efficient algorithms that can effectively learn Bayesian networks, requiring only polynomial numbers of conditional independence (CI) tests in typical cases. We provide precise conditions that specify when these algorithms are guaranteed to be correct as well as empirical evidence (from real world applications and simulation tests) that demonstrates that these systems work efficiently and reliably in practice.

A case study in group learning and supervision

Student units or the group-based field education and supervision of social work students offer many advantages as an efficient field placement model as well as opportunities for students to learn from each other through sharing knowledge, working collaboratively, hearing different perspectives and discussing issues. Despite the enormous potential of student units, they are a largely uncharted territory. There is a scarcity of literature on the topic and very few guidelines as to the provision of student units. The term student unit covers a broad range of student group learning opportunities and activities. This study explores this model of social work field education and its implications for student field work learning in a group context. The discussion is based on a review of the experiences, opinions and impressions of participants of an actual university based social work student unit.

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.

Robust visual tracking based on online learning sparse representation

Handling appearance variations is a very challenging problem for visual tracking. Existing methods usually solve this problem by relying on an effective appearance model with two features: (1) being capable of discriminating the tracked target from its background, (2) being robust to the target's appearance variations during tracking. Instead of integrating the two requirements into the appearance model, in this paper, we propose a tracking method that deals with these problems separately based on sparse representation in a particle filter framework. Each target candidate defined by a particle is linearly represented by the target and background templates with an additive representation error. Discriminating the target from its background is achieved by activating the target templates or the background templates in the linear system in a competitive manner. The target's appearance variations are directly modeled as the representation error. An online algorithm is used to learn the basis functions that sparsely span the representation error. The linear system is solved via ℓ1 minimization. The candidate with the smallest reconstruction error using the target templates is selected as the tracking result. We test the proposed approach using four sequences with heavy occlusions, large pose variations, drastic illumination changes and low foreground-background contrast. The proposed approach shows excellent performance in comparison with two latest state-of-the-art trackers.

A defeasible reasoning model of inductive concept learning from examples and communication

This paper introduces a logical model of inductive generalization, and specifically of the machine learning task of inductive concept learning (ICL). We argue that some inductive processes, like ICL, can be seen as a form of defeasible reasoning. We define a consequence relation characterizing which hypotheses can be induced from given sets of examples, and study its properties, showing they correspond to a rather well-behaved non-monotonic logic. We will also show that with the addition of a preference relation on inductive theories we can characterize the inductive bias of ICL algorithms. The second part of the paper shows how this logical characterization of inductive generalization can be integrated with another form of non-monotonic reasoning (argumentation), to define a model of multiagent ICL. This integration allows two or more agents to learn, in a consistent way, both from induction and from arguments used in the communication between them. We show that the inductive theories achieved by multiagent induction plus argumentation are sound, i.e. they are precisely the same as the inductive theories built by a single agent with all data. © 2012 Elsevier B.V.

Using a Systematic Approach To Develop a Chemistry Course Introducing Students to Instrumental Analysis

A systematic approach to develop the teaching of instrumental analytical chemistry is discussed, as well as a conceptual framework for organizing and executing lectures and a laboratory course. Three main components are used in this course: theoretical knowledge developed in the classroom, simulations via a virtual laboratory, and practical training via experimentation. Problem-based learning and cooperative-learning methods are applied in both the classroom and laboratory aspects of the course. In addition, some reflections and best practices are presented on how to encourage students to learn actively. Overall, a student-centered environment is proposed that aims to cultivate students' practical abilities and individual talents.

The detection of repetitions in noise before and after perceptual learning.

In noise repetition-detection tasks, listeners have to distinguish trials of continuously running noise from trials in which noise tokens are repeated in a cyclic manner. Recently, it has been shown that using the exact same noise token across several trials (“reference noise”) facilitates the detection of repetitions for this token [Agus et al. (2010). Neuron 66, 610–618]. This was attributed to perceptual learning. Here, the nature of the learning was investigated. In experiment 1, reference noise tokens were embedded in trials with or without cyclic presentation. Naïve listeners reported repetitions in both cases, thus responding to the reference noise even in the absence of an actual repetition. Experiment 2, with the same listeners, showed a similar pattern of results even after the design of the experiment was made explicit, ruling out a misunderstanding of the task. Finally, in experiment 3, listeners reported repetitions in trials containing the reference noise, even before ever hearing it presented cyclically. The results show that listeners were able to learn and recognize noise tokens in the absence of an immediate repetition. Moreover, the learning mandatorily interfered with listeners' ability to detect repetitions. It is concluded that salient perceptual changes accompany the learning of noise.

Evaluation of the contribution of theatre attendance to medical undergraduate neuroscience teaching - a pilot study.

Introduction: Medical students often attend the neurosurgical theatre during their clinical neurosciences attachment. However, few studies have been performed to objectively assess the value of this theatre-based learning experience. The main aim of this study was to explore student perceptions on the contribution of neurosurgical theatre attendance to clinical neuroscience teaching.

Materials and Methods: Third-year medical students undergoing their 2-week clinical neurosciences rotation at the Royal Hospitals Belfast were invited to participate in this study. A multi-method strategy was employed using a survey questionnaire comprising of closed and open-ended questions followed by semi-structured interviews to gain a greater 'in-depth' analysis of the potential contribution of neurosurgical theatre attendance to neuroscience teaching.

Results: Based on the completed survey responses of 22 students, the overall experience of neurosurgical theatre-based learning was a positive one. 'In-depth' analysis from semi-structured interviews indicated that students felt that some aspects of their neurosurgical theatre attendance could be improved. Better preparation such as reading up on the case in hand and an introduction to simple theatre etiquette to put the student at ease (in particular, for students who had never attended theatre previously), would improve the learning experience. In addition, having an expectation of what students are expected to learn in theatre making it more learning outcomes-based would probably make it feel a more positive experience by the student.

Conclusions: The vast majority of students acknowledged the positive learning outcomes of neurosurgical theatre attendance and felt that it should be made a mandatory component of the curriculum.

Lifelong learning:Reflections of a junior doctor

Purpose - The aim of this paper is investigate the importance of lifelong learning in the area of medicine. Design/methodology/approach - The paper examines changes in methods of learning and challenges to educators today. Findings - The paper finds that today there is a pressure for the formalized accounting of education with a few high profile cases of negligent medical care which have perhaps created the belief that recording learning for all may catch errant doctors in the future. It is suggested that learning risks becoming an exercise in meeting demands, but inspiring the desire to learn is also crucial. Originality/value - The paper provides a useful opinion on lifelong learning for the medical profession. © Emerald Group Publishing Limited.

Integrating elements of undergraduate curriculum learning

Integrating elements of undergraduate curriculum learning Rapidly advancing practice and recognition of nursing, midwifery and medicine as a vital interrelated workforce, implies a need for a variety of curricula opportunities. This project addresses the challenge for healthcare educators to widen student engagement and participation through inter-professional education by creating learning environments whereby student interactions foster the desire to develop situational awareness, independent learning and contribution to patient advocacy. Overall aim of this ‘Feeding and Nutrition in Infants and Children’ project is to provide opportunities for integrated learning to enable students to advance their knowledge and understanding of current best practice. This Inter-professional (IPE) student-lead workshop was initially implemented in 2006-07 in collaboration with the Centre for Excellence in IPE, within the curricula of medical and nursing programmes¹. Supported by the development of a student resource pack, this project is now being offered to Learning Disability nursing and Midwifery students since September 2014. Methods: Fourth year medical students, undertaking a ‘Child Healthcare module’, alongside nursing and /or midwifery students are divided into groups with three or four students from each profession. Each group focuses on a specific feeding problem that is scenario-based on a common real-life issue prior to the workshop and then present their findings / possible solutions to feeding problem. They are observed by both facilitators and peers, who provide constructive feedback on aspects of performance including patient safety, cultural awareness, communication, decision making skills, teamwork and an appreciation of the role of various professionals in managing feeding problems in infants and children. Results: Participants complete a Likert-scale questionnaire to ascertain their reactions to this integrated learning experience. Ongoing findings suggest that students evaluate this learning activity very positively and have stated that they value the opportunity to exercise their clinical judgement and decision making skills. Most recent comments: ‘appreciate working alongside other student’s / multidisciplinary team approach’ As a group students engage in this team problem-solving exercise, drawing upon their strengths and abilities to learn from each other. This project provides a crucial opportunity for learning and knowledge exchange for all those medical, midwifery and nursing students involved. Reference: 1. Purdy, J. & Stewart, M (2009) ‘Feeding and Nutrition in Infants and Children: An Interprofessional Approach’. The Clinical Teacher, vol 6, no.3. Authors: Dr. Angela Bell, Centre for Medical Education, Queen’s University Belfast. Doris Corkin, Senior Lecturer (education), Children’s Nursing, School of Nursing & Midwifery, Queen’s University Belfast. Carolyn Moorhead, Midwifery Lecturer, School of Nursing & Midwifery, Queen’s University Belfast. Ann Devlin, Lecturer (education), Learning Disability Nursing, School of Nursing & Midwifery, Queen’s University Belfast.

Improving parameter learning of Bayesian nets from incomplete data

This paper addresses the estimation of parameters of a Bayesian network from incomplete data. The task is usually tackled by running the Expectation-Maximization (EM) algorithm several times in order to obtain a high log-likelihood estimate. We argue that choosing the maximum log-likelihood estimate (as well as the maximum penalized log-likelihood and the maximum a posteriori estimate) has severe drawbacks, being affected both by overfitting and model uncertainty. Two ideas are discussed to overcome these issues: a maximum entropy approach and a Bayesian model averaging approach. Both ideas can be easily applied on top of EM, while the entropy idea can be also implemented in a more sophisticated way, through a dedicated non-linear solver. A vast set of experiments shows that these ideas produce significantly better estimates and inferences than the traditional and widely used maximum (penalized) log-likelihood and maximum a posteriori estimates. In particular, if EM is adopted as optimization engine, the model averaging approach is the best performing one; its performance is matched by the entropy approach when implemented using the non-linear solver. The results suggest that the applicability of these ideas is immediate (they are easy to implement and to integrate in currently available inference engines) and that they constitute a better way to learn Bayesian network parameters.

Learning Bounded Tree-Width Bayesian Networks via Sampling

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods [12, 14] tackle the problem by using k-trees to learn the optimal Bayesian network with tree-width up to k. In this paper, we propose a sampling method to efficiently find representative k-trees by introducing an Informative score function to characterize the quality of a k-tree. The proposed algorithm can efficiently learn a Bayesian network with tree-width at most k. Experiment results indicate that our approach is comparable with exact methods, but is much more computationally efficient.

Learning about probability from text and tables: Do color coding and labeling through an interactive-user interface help?

Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly assigned to learn about probabilistic reasoning from one of 4 computer-based lessons generated from a 2 (color coding/no color coding) by 2 (labeling/no labeling) between-subjects design. Learners added the labels or color coding at their own pace by clicking buttons in a computer-based lesson. Participants' eye movements were recorded while viewing the lesson. Labeling was beneficial for learning, but color coding was not. In addition, labeling, but not color coding, increased attention to important information in the table and time with the lesson. Both labeling and color coding increased looks between the text and corresponding information in the table. The findings provide support for the multimedia principle, and they suggest that providing labeling enhances learning about probabilistic reasoning from text and tables