9 resultados para one-pass learning


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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

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In 2015 the Irish Mathematics Learning Support Network (IMLSN) commissioned a comprehensive audit of the extent and nature of mathematics learning support (MLS) provision on the island of Ireland. An online survey was sent to 32 institutions, including universities, institutes of technology, further education and teacher training colleges, and a 97% response rate was achieved. While the headline figure – 84% of institutions that responded to the survey provide MLS – sounds good, deeper analysis reveals that the true state of MLS is not so solid. For example, in 25% of institutions offering MLS, only five hours per week (at most) of physical MLS are available, while in 20% of institutions the service is provided by only one or two staff members. Furthermore, training of tutors is minimal or non-existent in at least half of the institutions offering MLS. The results provide an illuminating picture, however, identifying the true state of MLS in Ireland is beneficial only if it informs developments in the years ahead. This talk will present some of the findings of the survey in more depth along with conclusions and recommendations. Key among these is the need for institutions to recognise MLS as a vital element of mathematics teaching and learning strategy at third level and devote the necessary resources to facilitate the provision of a service which can grow and adapt to meet student requirements.

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Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.

Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.

Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.

Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.

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In this paper, we describe how the pathfinder algorithm converts relatedness ratings of concept pairs to concept maps; we also present how this algorithm has been used to develop the Concept Maps for Learning website (www.conceptmapsforlearning.com) based on the principles of effective formative assessment. The pathfinder networks, one of the network representation tools, claim to help more students memorize and recall the relations between concepts than spatial representation tools (such as Multi- Dimensional Scaling). Therefore, the pathfinder networks have been used in various studies on knowledge structures, including identifying students’ misconceptions. To accomplish this, each student’s knowledge map and the expert knowledge map are compared via the pathfinder software, and the differences between these maps are highlighted. After misconceptions are identified, the pathfinder software fails to provide any feedback on these misconceptions. To overcome this weakness, we have been developing a mobile-based concept mapping tool providing visual, textual and remedial feedback (ex. videos, website links and applets) on the concept relations. This information is then placed on the expert concept map, but not on the student’s concept map. Additionally, students are asked to note what they understand from given feedback, and given the opportunity to revise their knowledge maps after receiving various types of feedback.

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Our key contribution is a flexible, automated marking system that adds desirable functionality to existing E-Assessment systems. In our approach, any given E-Assessment system is relegated to a data-collection mechanism, whereas marking and the generation and distribution of personalised per-student feedback is handled separately by our own system. This allows content-rich Microsoft Word feedback documents to be generated and distributed to every student simultaneously according to a per-assessment schedule.

The feedback is adaptive in that it corresponds to the answers given by the student and provides guidance on where they may have gone wrong. It is not limited to simple multiple choice which are the most prescriptive question type offered by most E-Assessment Systems and as such most straightforward to mark consistently and provide individual per-alternative feedback strings. It is also better equipped to handle the use of mathematical symbols and images within the feedback documents which is more flexible than existing E-Assessment systems, which can only handle simple text strings.

As well as MCQs the system reliably and robustly handles Multiple Response, Text Matching and Numeric style questions in a more flexible manner than Questionmark: Perception and other E-Assessment Systems. It can also reliably handle multi-part questions where the response to an earlier question influences the answer to a later one and can adjust both scoring and feedback appropriately.

New question formats can be added at any time provided a corresponding marking method conforming to certain templates can also be programmed. Indeed, any question type for which a programmatic method of marking can be devised may be supported by our system. Furthermore, since the student’s response to each is question is marked programmatically, our system can be set to allow for minor deviations from the correct answer, and if appropriate award partial marks.

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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.

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Introduction
This paper reports to an exercise in evaluating poster group work and poster presentation and the extra learning and skill acquisition that this can provide to nursing students, through a creative and stimulating assessment method. Much had been written about the benefits of using posters as an assessment method, yet there appears to be a lack of research that captures the student experience.
Aim
This evaluative study sought to evaluate the student experience by using a triangulation approach to evaluation:
Methodology
All students from the February 2015 nursing intake, were eligible to take part (80 students) of which 71 participated (n=71). The poster group presentations took place at the end of their first phase of year one teaching and the evaluation took place at the end of their first year as undergraduate. Evaluation involved;
1. Quantitative data by questionnaires
2. Qualitative data from focus group discussions
Results
A number of key themes emerged from analysis of the data which captured the “added value” of learning from the process of poster assessment including:
 Professionalism: developing time keeping skills, presenting skills.
 Academic skills: developing literature search, critic and reporting
 Team building and collaboration
Overall 88% agreed that the process furnished them with additional skills and benefits above the actual production of the poster, with 97% agreeing that these additional skills are important skills for a nurse.
Conclusion
These results would suggest that the process of poster development and presentation furnish student nurses with many additional skills that they may not acquire through other types of assessment and are therefore beneficial. The structure of the assessment encourages a self-directed approach so students take control of the goals and purposes of learning. The sequential organization of the assessment guides students in the transition from dependent to self-directed learners.


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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