8 resultados para B-Learning
Resumo:
It is important for young people to be able to read science-related media reports with discernment. ‘Getting Newswise’ was a research project designed to enable science and English teachers, working collaboratively, to equip pupils through the curriculum with critical reading skills appropriate for science news. Phase one of the study found that science and English teachers respond differently to science news articles and eight categories of critical response were identified. These findings informed phase two, in which classroom activities were devised whereby pupils examined, evaluated and responded to science-related news reports. Science-English collaboration had positive outcomes for pupil understanding
Resumo:
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.
Resumo:
Many have called for medical students to learn how to manage complexity in healthcare. This study examines the nuances of students' challenges in coping with a complex simulation learning activity, using concepts from complexity theory, and suggests strategies to help them better understand and manage complexity.Wearing video glasses, participants took part in a simulation ward-based exercise that incorporated characteristics of complexity. Video footage was used to elicit interviews, which were transcribed. Using complexity theory as a theoretical lens, an iterative approach was taken to identify the challenges that participants faced and possible coping strategies using both interview transcripts and video footage.Students' challenges in coping with clinical complexity included being: a) unprepared for 'diving in', b) caught in an escalating system, c) captured by the patient, and d) unable to assert boundaries of acceptable practice.Many characteristics of complexity can be recreated in a ward-based simulation learning activity, affording learners an embodied and immersive experience of these complexity challenges. Possible strategies for managing complexity themes include: a) taking time to size up the system, b) attuning to what emerges, c) reducing complexity, d) boundary practices, and e) working with uncertainty. This study signals pedagogical opportunities for recognizing and dealing with complexity.
Resumo:
This study examines whether virtual reality (VR) is more superior to paper-based instructions in increasing the speed at which individuals learn a new assembly task. Specifically, the work seeks to quantify any learning benefits when individuals have been given the opportunity and compares the performance of two groups using virtual and hardcopy media types to pre-learn the task. A build experiment based on multiple builds of an aircraft panel showed that a group of people who pre-learned the assembly task using a VR environment completed their builds faster (average build time 29.5% lower). The VR group also made fewer references to instructional materials (average number of references 38% lower) and made fewer errors than a group using more traditional, hard copy instructions. These outcomes were more pronounced during build one with differences in build time and number of references showing limited statistical differences.
Resumo:
Gun related violence is a complex issue and accounts for a large proportion of violent incidents. In the research reported in this paper, we set out to investigate the pro-gun and anti-gun sentiments expressed on a social media platform, namely Twitter, in response to the 2012 Sandy Hook Elementary School shooting in Connecticut, USA. Machine learning techniques are applied to classify a data corpus of over 700,000 tweets. The sentiments are captured using a public sentiment score that considers the volume of tweets as well as population. A web-based interactive tool is developed to visualise the sentiments and is available at this http://www.gunsontwitter.com. The key findings from this research are: (i) There are elevated rates of both pro-gun and anti-gun sentiments on the day of the shooting. Surprisingly, the pro-gun sentiment remains high for a number of days following the event but the anti-gun sentiment quickly falls to pre-event levels. (ii) There is a different public response from each state, with the highest pro-gun sentiment not coming from those with highest gun ownership levels but rather from California, Texas and New York.
Resumo:
Introduction: Foundation doctors are expected to assess and interpret plain x-ray studies of the chest/abdomen before a definitive report is issued by senior staff. The Royal College of Radiologists have published guidelines (RCR curriculum) on the scope of plain film findings medical students should be familiar with.1 Studies have shown that the x-ray interpretation without feedback does not significantly improve diagnostic ability. 2 Queen’s University, Belfast Trust Radiology and Experior Medical developed an online system to assess individual student ability to interpret X-ray findings. Over a series of assessments each student’s profile is built up, identifying strengths and weakness. The system can then create bespoke individual assessments re-evaluating previously identified weak areas and quantifying interpretative skill improvement. Aim: To determine how readily an online system is adopted by senior medical students, investigating if increasing exposure to x-ray interpretation combined with cyclical formative feedback enhances performance. Methods: The system was offered to all 270 final year medical students as an online resource. The system comprised a series of 20 weekly 30 minute assessments, containing normal and abnormal x-rays within the RCR curriculum. After each assessment students were given formative feedback, including their own result, annotated answers, peer group comparison and a breakdown of areas of strength and weakness. Focus groups of 4-5 students addressed student perspectives of the system, including ease of use, image resolution, system performance across different operating platforms, perceived value of formative feedback loops, breakdown of performance and the value of bespoke personalised assessments. Research Ethics Approval was granted for the study. Data analysis was via two-sided one-sample t-test; initial minimal recruitment was estimated as 60 students, to detect a mean 10% change in performance, with a standard deviation of 20%. Results and Discussion: Over 80% (n = XXX/270) of the student cohort engaged with the study. Student baseline average was 39%, increasing to 62% by the exit test. The steadily sustained improvement (57% relative performance in interpretative diagnostic accuracy) was despite increasing test difficulty. Student feedback via focus groups was universally positive throughout the examined domains. Conclusion: The online resource proved to be valuable, with high levels of student engagement, improving performance despite increasingly difficulty testing and positive learner experience with the system. References: 1. Undergraduate Radiology Curriculum, The Royal College of Ra, April 2012. Ref No. BFCR(12)4 The Royal College of Radiologists, April 2012 2. I Satia, S Bashagha, A Bibi, R Ahmed, S Mellor, F Zaman. Assessing the accuracy and certainty in interpretating chest x-rays in the medical division. Clin Med August 2013 Vol.13 no. 4 349-352
Resumo:
Traditional heuristic approaches to the Examination Timetabling Problem normally utilize a stochastic method during Optimization for the selection of the next examination to be considered for timetabling within the neighbourhood search process. This paper presents a technique whereby the stochastic method has been augmented with information from a weighted list gathered during the initial adaptive construction phase, with the purpose of intelligently directing examination selection. In addition, a Reinforcement Learning technique has been adapted to identify the most effective portions of the weighted list in terms of facilitating the greatest potential for overall solution improvement. The technique is tested against the 2007 International Timetabling Competition datasets with solutions generated within a time frame specified by the competition organizers. The results generated are better than those of the competition winner in seven of the twelve examinations, while being competitive for the remaining five examinations. This paper also shows experimentally how using reinforcement learning has improved upon our previous technique.