What is the learning in games-based learning?

This chapter explores the nature of “learning” in games-based learning and the cognitive and motivational processes that might underpin that learning by drawing on psychological theories and perspectives. Firstly, changing conceptions of learning over the last few decades are reviewed. This is described in relation to the changes in formal learning theories and connections made between learning theory and GBL. Secondly, the chapter reviews empirical research on the learning outcomes that have been identified for GBL, with specific focus on cognitive benefits, school attainment, collaborative working, and the motivational and engaging appeal of games. Finally, an overview of the dominant theoretical perspectives/findings mostly associated with GBL is presented in an attempt to broaden understanding of the potential for GBL in the classroom.

Engaging the Senses: Object-based learning in higher education

The use of museum collections as a path to learning for university students is fast becoming a new pedagogy for higher education. Despite a strong tradition of using lectures as a way of delivering the curriculum, the positive benefits of ‘active’ and ‘experiential learning’ are being recognised in universities at both a strategic level and in daily teaching practice. As museum artefacts, specimens and art works are used to evoke, provoke, and challenge students’ engagement with their subject, so transformational learning can take place. This unique book presents the first comprehensive exploration of ‘object-based learning’ as a pedagogy for higher education in a broad context. An international group of authors offer a spectrum of approaches at work in higher education today. They explore contemporary principles and practice of object-based learning in higher education, demonstrating the value of using collections in this context and considering the relationship between academic discipline and object-based learning as a teaching strategy.

A Proposed Framework for Simulation Based Learning of Inheritance

Different types of serious games have been used in elucidating computer science areas such as computer games, mobile games, Lego-based games, virtual worlds and webbased games. Different evaluation techniques have been conducted like questionnaires, interviews, discussions and tests. Simulation have been widely used in computer science as a motivational and interactive learning tool. This paper aims to evaluate the possibility of successful implementation of simulation in computer programming modules. A framework is proposed to measure the impact of serious games on enhancing students understanding of key computer science concepts. Experiments will be held on the EEECS of Queen’s University Belfast students to test the framework and attain results.

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.

How Prepared are UK Medical Graduates for Practice? Final report from a programme of research commissioned by the General Medical Council

This programme of research aimed to understand the extent to which current UK medical graduates are prepared for practice. Commissioned by the General Medical Council, we conducted: (1) A Rapid Review of the literature between 2009 and 2013; (2) narrative interviews with a range of stakeholders; and (3) longitudinal audio-diaries with Foundation Year 1 doctors. The Rapid Review (RR) resulted in data from 81 manuscripts being extracted and mapped against a coding framework (including outcomes from Tomorrow's Doctors (2009) (TD09)). A narrative synthesis of the data was undertaken. Narrative interviews were conducted with 185 participants from 8 stakeholder groups: F1 trainees, newly registered trainee doctors, clinical educators, undergraduate and postgraduate deans and foundation programme directors, other healthcare professionals, employers, policy and government and patient and public representatives. Longitudinal audio-diaries were recorded by 26 F1 trainees over 4 months. The data were analysed thematically and mapped against TD09. Together these data shed light onto how preparedness for practice is conceptualised, measured, how prepared UK medical graduates are for practice, the effectiveness of transition interventions and the currently debated issue of bringing full registration forward to align with medical students’ graduation. Preparedness for practice was conceptualised as both a long- and short-term venture that included personal readiness as well as knowledge, skills and attitudes. It has mainly been researched using self-report measures of generalised incidents that have been shown to be problematic. In terms of transition interventions: assistantships were found to be valuable and efficacious for proactive students as team members, shadowing is effective when undertaken close to employment/setting of F1 post and induction is generally effective but of inconsistent quality. The August transition was highlighted in our interview and audio-diary data where F1s felt unprepared, particularly for the step-change in responsibility, workload, degree of multitasking and understanding where to go for help. Evidence of preparedness for specific tasks, skills and knowledge was contradictory: trainees are well prepared for some practical procedures but not others, reasonably well prepared for history taking and full physical examinations, but mostly unprepared for adopting an holistic understanding of the patient, involving patients in their care, safe and legal prescribing, diagnosing and managing complex clinical conditions and providing immediate care in medical emergencies. Evidence for preparedness for interactional and interpersonal aspects of practice was inconsistent with some studies in the RR suggesting graduates were prepared for team working and communicating with colleagues and patients, but other studies contradicting this. Interview and audio-diary data highlights concerns around F1s preparedness for communicating with angry or upset patients and relatives, breaking bad news, communicating with the wider team (including interprofessionally) and handover communication. There was some evidence in the RR to suggest that graduates were unprepared for dealing with error and safety incidents and lack an understanding of how the clinical environment works. Interview and audio-diary data backs this up, adding that F1s are also unprepared for understanding financial aspects of healthcare. In terms of being personally prepared, RR, interview and audio diary evidence is mixed around graduates’ preparedness for identifying their own limitations, but all data points to graduates’ difficulties in the domain of time management. In terms of personal and situational demographic factors, the RR found that gender did not typically predict perceptions of preparedness, but graduates from more recent cohorts, graduate entry students, graduates from problem based learning courses, UK educated graduates and graduates with an integrated degree reported feeling better prepared. The longitudinal audio-diaries provided insights into the preparedness journey for F1s. There seems to be a general development in the direction of trainees feeling more confident and competent as they gain more experience. However, these developments were not necessarily linear as challenging circumstances (e.g. new specialty, new colleagues, lack of staffing) sometimes made them feel unprepared for situations where they had previously indicated preparedness.

Evaluation of Video Presentation to Deliver Surgical Anatomy Teaching

Title Evaluation of Video Presentation to Deliver Surgical Anatomy Teaching

Authors Walsh I.K., Boohan M., Dorman A.

Objectives To evaluate the efficacy of newly introduced video presentation to deliver Surgical Anatomy teaching to undergraduate medical students.

Design and Setting Qualitative and quantitative study using questionnaires and focus groups, employing students undertaking the perioperative medicine module of the phase 4 undergraduate medical curriculum at Queen’s University Belfast.

Outcome Measures To determine:
(1) if video presentation is effective in delivering surgical anatomy teaching,
(2) student’s learning preferences regarding this teaching method.
Results The questionnaire response rate was 89% (216 of 244 students; female: male ratio 1.25) and 42 students participated in 6 focus groups. Mean questionnaire responses indicated a favourable opinion on quality assurance items, with a mixed response to video presentation as a learning method. 71% of students preferred to receive a lecture in person, rather than via video presentation. There were no statistically significant differences between genders regarding learning preferences in general and regarding video versus live presentation in particular. Exploratory factor analysis demonstrated that favourable responses to video presentation were strongly associated with perceived audiovisual quality and learning preferences (Cronbach’s alpha coefficient 0.77), with 72% of students considering video presentation worthwhile. Positive perception of overall quality was strongly associated with learning preferences as well as more generic quality assurance issues (80% students; alpha coefficient 0.83).
The results were supported by triangulation of the above quantitative data with qualitative data generated by the focus groups. Students further articulated the view that video presentation may be more appropriate and effective in a mixed method setting.

Reference Basu Roy R, McMahon GT. Video-based cases disrupt deep critical thinking in problem-based learning. Med Educ 2012 Apr;46(4):426-435.

Learning and organization in the knowledge-based information economy: Initial findings from a participatory action research case study

This paper reports on an ongoing, multiphase, project-based action learning and research project. In particular, it summarizes some aspects of the learning climate and outcomes for a case study company In the software industry, Using a participatory action research approach, the learning company framework developed by Pedler et al, (1997) is used to initiate critical reflection in the company at three levels: managing director, senior management team and technical and professional staff. As such, this is one of the first systematic attempts to apply this framework to the entire organization and to a company in the knowledge-based learning economy. Two sets of issues are of general concern to the company: internal issues surrounding the company's reward and recognition policies and practices and the provision of accounting and control information in a business relevant way to all levels of staff; and external issues concerning the extent to which the company and its members actively learn from other companies and effectively capture, disseminate and use information accessed by staff in boundary-spanning roles. The paper concludes with some illustrations of changes being introduced by the company as a result of the feedback on and discussion of these issues.

What Are the Effects of Teaching Evidence-Based Health Care (EBHC)? Overview of Systematic Reviews

Background

An evidence-based approach to health care is recognized internationally as a key competency for healthcare practitioners. This overview systematically evaluated and organized evidence from systematic reviews on teaching evidence-based health care (EBHC).

Methods/Findings

We searched for systematic reviews evaluating interventions for teaching EBHC to health professionals compared to no intervention or different strategies. Outcomes covered EBHC knowledge, skills, attitudes, practices and health outcomes. Comprehensive searches were conducted in April 2013. Two reviewers independently selected eligible reviews, extracted data and evaluated methodological quality. We included 16 systematic reviews, published between 1993 and 2013. There was considerable overlap across reviews. We found that 171 source studies included in the reviews related to 81 separate studies, of which 37 are in more than one review. Studies used various methodologies to evaluate educational interventions of varying content, format and duration in undergraduates, interns, residents and practicing health professionals. The evidence in the reviews showed that multifaceted, clinically integrated interventions, with assessment, led to improvements in knowledge, skills and attitudes. Interventions improved critical appraisal skills and integration of results into decisions, and improved knowledge, skills, attitudes and behaviour amongst practicing health professionals. Considering single interventions, EBHC knowledge and attitude were similar for lecture-based versus online teaching. Journal clubs appeared to increase clinical epidemiology and biostatistics knowledge and reading behavior, but not appraisal skills. EBHC courses improved appraisal skills and knowledge. Amongst practicing health professionals, interactive online courses with guided critical appraisal showed significant increase in knowledge and appraisal skills. A short workshop using problem-based approaches, compared to no intervention, increased knowledge but not appraisal skills.

Conclusions

EBHC teaching and learning strategies should focus on implementing multifaceted, clinically integrated approaches with assessment. Future rigorous research should evaluate minimum components for multifaceted interventions, assessment of medium to long-term outcomes, and implementation of these interventions.

Efficient Structure Learning of Bayesian Networks using Constraints

This paper addresses the problem of learning Bayesian network structures from data based on score functions that are decomposable. It describes properties that strongly reduce the time and memory costs of many known methods without losing global optimality guarantees. These properties are derived for different score criteria such as Minimum Description Length (or Bayesian Information Criterion), Akaike Information Criterion and Bayesian Dirichlet Criterion. Then a branch-and-bound algorithm is presented that integrates structural constraints with data in a way to guarantee global optimality. As an example, structural constraints are used to map the problem of structure learning in Dynamic Bayesian networks into a corresponding augmented Bayesian network. Finally, we show empirically the benefits of using the properties with state-of-the-art methods and with the new algorithm, which is able to handle larger data sets than before.

An Efficient LS-SVM-Based Method for Fuzzy System Construction

This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the LS-SVMs have their computational advantage over conventional SVMs in the model training process; however, the model sparseness is lost, which is the main drawback of LS-SVMs. This is an open problem for the LS-SVMs. To tackle the nonsparseness issue, a new regression alternative to the Lagrangian solution for the LS-SVM is first presented. A novel efficient learning mechanism is then proposed in this paper to extract a sparse set of support vectors for generating fuzzy IF-THEN rules. This novel mechanism works in a stepwise subset selection manner, including a forward expansion phase and a backward exclusion phase in each selection step. The implementation of the algorithm is computationally very efficient due to the introduction of a few key techniques to avoid the matrix inverse operations to accelerate the training process. The computational efficiency is also confirmed by detailed computational complexity analysis. As a result, the proposed approach is not only able to achieve the sparseness of the resultant LS-SVM-based fuzzy systems but significantly reduces the amount of computational effort in model training as well. Three experimental examples are presented to demonstrate the effectiveness and efficiency of the proposed learning mechanism and the sparseness of the obtained LS-SVM-based fuzzy systems, in comparison with other SVM-based learning techniques.