639 resultados para online learning


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We aim to design strategies for sequential decision making that adjust to the difficulty of the learning problem. We study this question both in the setting of prediction with expert advice, and for more general combinatorial decision tasks. We are not satisfied with just guaranteeing minimax regret rates, but we want our algorithms to perform significantly better on easy data. Two popular ways to formalize such adaptivity are second-order regret bounds and quantile bounds. The underlying notions of 'easy data', which may be paraphrased as "the learning problem has small variance" and "multiple decisions are useful", are synergetic. But even though there are sophisticated algorithms that exploit one of the two, no existing algorithm is able to adapt to both. In this paper we outline a new method for obtaining such adaptive algorithms, based on a potential function that aggregates a range of learning rates (which are essential tuning parameters). By choosing the right prior we construct efficient algorithms and show that they reap both benefits by proving the first bounds that are both second-order and incorporate quantiles.

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A significant challenge for the implementation of the Australian Curriculum: The Arts is the professional development of primary school teachers in all parts of the country. During 2012, the Sydney Symphony Orchestra (SSO) conducted a remote music professional development workshop as part of the Sydney Opera House’s Digital Education Program for teachers in New South Wales using the Department of Education’s Connected Classroom system which allows live synchronous interaction between facilitators and participants in multiple sites. In this article, we analyse observational and videotape data collected during this live professional development event to consider the opportunities and challenges presented by this type of professional learning experience in the arts. In particular, consideration is given to the impact of a remote musical interaction on embodied learning and aesthetic experience. We draw on actor-network theory to consider the ways in which a remote professional development experience differs to one in which all participants are present in the same space. Finally, we conclude that although there are significant differences in the type of learning that occurs in a remote music interaction, the online space provides a legitimate and potentially transforming experience for primary school teachers.

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Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

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Images of Research is the annual competition and exhibition from the University of Strathclyde, which is designed to broaden the appeal of the university's research outputs to the general public. This year, to bring the research to life Chris Thomson, subject specialist - online learning and the digital student experience, Jisc, helped to support the participants in using digital storytelling. Rachel Clark, project coordinator at the university, talks about the thinking behind the exhibition.

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This paper presents an incremental learning solution for Linear Discriminant Analysis (LDA) and its applications to object recognition problems. We apply the sufficient spanning set approximation in three steps i.e. update for the total scatter matrix, between-class scatter matrix and the projected data matrix, which leads an online solution which closely agrees with the batch solution in accuracy while significantly reducing the computational complexity. The algorithm yields an efficient solution to incremental LDA even when the number of classes as well as the set size is large. The incremental LDA method has been also shown useful for semi-supervised online learning. Label propagation is done by integrating the incremental LDA into an EM framework. The method has been demonstrated in the task of merging large datasets which were collected during MPEG standardization for face image retrieval, face authentication using the BANCA dataset, and object categorisation using the Caltech101 dataset. © 2010 Springer Science+Business Media, LLC.

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研究多移动机器人的运动规划问题.针对机器人模型未知或不精确以及环境的动态变化,提出一种自学习模糊控制器(FLC)来进行准确的速度跟踪.首先通过神经网络的学习训练构造FLC,再由再励学习算法来在线调节FLC的输出,以校正机器人运动状态,实现安全协调避撞

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Research in traditional education shows chronotype, sleep duration and sleep quality to be related to learning performance. Research in adult students participating in distance education (DE) is scarce. This study aims to provide knowledge on these relationships in this educational setting. In an observational longitudinal study, chronotype, sleep duration (i.e., for work and free days separately) and sleep quality of 894 students were analyzed in a multiple regression analyses. Students provided information on sleep-relatedmeasures and important covariates at the start of their study and study progress was evaluated after 14 months (i.e., the number of successfully completed modules). In linewith previous research, chronotype did not predict study progress. Further, sleep duration did not predict study progress, neither as a linear nor as a polynomial term. Third, sleep quality did not predict study progress. Concluding, these results are in linewith previous research that DE provides a solution to the asynchrony problem. Findings regarding sleep duration and sleep quality are new and unexpected, asking for attention and further research. Despite the study's observational nature, findings suggest that students participating in DE may benefit from this type of education as the asynchrony problem appears not to apply here, as students can choose their own study schedule.

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In this article, we address the importance and relevance that social networks exhibit in their use as an educational resource.  This relevance relies in the possibility of implementing new learning resources or increasing the level of the participant's connectivity, as well as developing learning communities.  Also, the risk entailed from their use is discussed, especially for the students that have a low technological education or those having excessive confidence on the media.  It is important to highlight that the educational use of social networks is not a simple extension or translation of the student's habitual, recreational use, but that it implies an important change in the roles given to teachers as well as learners; from accommodative learning environments that only encourage memorization to other environments that demand an active, reflective, collaborative and proactive attitude, that require the development/acquisition of technological as well as social abilities, aptitudes and values.  It is also important to highlight that a correct implementation and adequate use will not only foment formal learning, but also informal and non-formal learning.

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Adult learners are a discrete population with specific needs and characteristics. The context of this project is a Career Services office in a Faculty of Education at a Local University [pseudonym]. The office serves a population of students from various programs within the Faculty, with the majority of students enrolled in the Bachelor of Education program. As a result of the current job market for teachers in Ontario and Canada, it is important to be able to communicate effectively with students to support them in their job searches. The purpose of this project was to identify the needs and characteristics of adult learners, and to identify ways that the current Career Services curriculum could be improved to better support adult learners. In order to engage this population of students, it is important to ensure that the content of the course addresses and meets their needs. To provide a more personalized learning environment, online resources were considered to allow students to participate more, providing a more convenient and suitable method of delivery for our intended audience, and a sample website was created to host the online resources. In addition, the entire Career Services curriculum was formalized by producing a curriculum document to outline the goals and outcomes of the program to ensure that the content will facilitate the achievement of those goals. What resulted is a hybrid, online and in-person program for Career Services, and a more robust curriculum that considers the needs of our adult learners.

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Background: Clinical supervision takes place once the newly qualified nurse is employed in clinical practice. However, often the variety and diversity of nursing jobs can result in a hit and miss delivery of supervision training. By introducing training uniformly at undergraduate stage a more seamless transition may occur (McColgan K, Rice C. 2012).

There is an increased interest in higher education in the use of online learning resources for students. As part completion of a DNP an App. for training students in clinical supervision was developed.

Aim: The creation of a clinical supervision training App. for use in undergraduate nursing.

Objectives:
•To develop a teaching tool that is up to date, current and easily accessible to students.
•To introduce supervision training for undergraduate nursing students
•To motivate the undergraduate nursing student to identify examples from their clinical experience to encourage change and promote professional development.

Approach:
Stage 1
In 2010/11 informal inquiries with senior nurses regarding the introduction of supervision training in undergraduate nursing
Stage 2
A review of UK supervision training.
Stage 3
Template production of teaching tool.
Stage 4
Collaboration with a computer technician to transfer multimedia outputs onto an App.
Stage 5
App. piloted with lecturers (n=4) and post registration students (n=20).
Stage 6
Minor alterations made to App. design template
Stage 7
App. included in an experimental study looking at online learning versus blended learning June 2013 (n=61, n=63)

Conclusion: A collaborative approach to the development of any educational programme is essential to ensure the success of the final teaching product (McCutcheon 2013). The end result is that this App. could be:
•Made available to nurses in the UK.
•Adapted to suit other healthcare professionals and students.
•Used as a prototype for other healthcare related subjects.

McColgan K., Rice C. (2012) An online training resource for clinical supervision. Nursing Standard, 26(24) 35-39.
McCutcheon K. (2013) Development of a multi-media book for clinical supervision training in an undergraduate nursing programme. Journal of Nursing Education and Practice, 3(5) 31-38.

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In this paper, we propose a novel visual tracking framework, based on a decision-theoretic online learning algorithm namely NormalHedge. To make NormalHedge more robust against noise, we propose an adaptive NormalHedge algorithm, which exploits the historic information of each expert to perform more accurate prediction than the standard NormalHedge. Technically, we use a set of weighted experts to predict the state of the target to be tracked over time. The weight of each expert is online learned by pushing the cumulative regret of the learner towards that of the expert. Our simulation experiments demonstrate the effectiveness of the proposed adaptive NormalHedge, compared to the standard NormalHedge method. Furthermore, the experimental results of several challenging video sequences show that the proposed tracking method outperforms several state-of-the-art methods.

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The efficiency of large group teaching (lectures) has long been called into question with much research high lighting low levels of student participation, and poor attention spans leading to a lack of engagement with learning which inhibits deep learning. Small group teaching and Enquiry Based Learning (EBL) are methods of teaching that can help promote deep learning. There is also a growing need and demand for Technology Enhanced Learning to suit changing lifestyles. The Labtutor® System, is one such piece of software that is designed to incorporate EBL and small group teaching quality into the large group setting.

This study provides a descriptive survey of adult nursing student’s perceptions of the Labtutor system following its use in two Life Science modules within an undergraduate nursing programme. A convenience sample of first year adult nursing students (n= 115) were identified to complete a 32 item questionnaire (appendix three).
Participants reported overall that they enjoyed using the system and found it beneficial to their learning specifically:
(a) Increased engagement with material in online learning as a result of using the system.
(b) Increased participation and levels of interactivity in the lecture as a result of using the system.
(c) Increased enhancement of learning as a result of using the system and
(d) Usefulness of the formative assessment facilitated by using the system.

The study concludes that Labtutor® system and other such methods of Technology Enhanced Learning packages if used correctly can enhance learning.

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Introduction
The use of video capture of lectures in Higher Education is not a recent occurrence with web based learning technologies including digital recording of live lectures becoming increasing commonly offered by universities throughout the world (Holliman and Scanlon, 2004). However in the past decade the increase in technical infrastructural provision including the availability of high speed broadband has increased the potential and use of videoed lecture capture. This had led to a variety of lecture capture formats including pod casting, live streaming or delayed broadcasting of whole or part of lectures.
Additionally in the past five years there has been a significant increase in the popularity of online learning, specifically via Massive Open Online Courses (MOOCs) (Vardi, 2014). One of the key aspects of MOOCs is the simulated recording of lecture like activities. There has been and continues to be much debate on the consequences of the popularity of MOOCs, especially in relation to its potential uses within established University programmes.
There have been a number of studies dedicated to the effects of videoing lectures.
The clustered areas of research in video lecture capture have the following main themes:
• Staff perceptions including attendance, performance of students and staff workload
• Reinforcement versus replacement of lectures
• Improved flexibility of learning
• Facilitating engaging and effective learning experiences
• Student usage, perception and satisfaction
• Facilitating students learning at their own pace
Most of the body of the research has concentrated on student and faculty perceptions, including academic achievement, student attendance and engagement (Johnston et al, 2012).
Generally the research has been positive in review of the benefits of lecture capture for both students and faculty. This perception coupled with technical infrastructure improvements and student demand may well mean that the use of video lecture capture will continue to increase in frequency in the next number of years in tertiary education. However there is a relatively limited amount of research in the effects of lecture capture specifically in the area of computer programming with Watkins 2007 being one of few studies . Video delivery of programming solutions is particularly useful for enabling a lecturer to illustrate the complex decision making processes and iterative nature of the actual code development process (Watkins et al 2007). As such research in this area would appear to be particularly appropriate to help inform debate and future decisions made by policy makers.
Research questions and objectives
The purpose of the research was to investigate how a series of lecture captures (in which the audio of lectures and video of on-screen projected content were recorded) impacted on the delivery and learning of a programme of study in an MSc Software Development course in Queen’s University, Belfast, Northern Ireland. The MSc is conversion programme, intended to take graduates from non-computing primary degrees and upskill them in this area. The research specifically targeted the Java programming module within the course. It also analyses and reports on the empirical data from attendances and various video viewing statistics. In addition, qualitative data was collected from staff and student feedback to help contextualise the quantitative results.
Methodology, Methods and Research Instruments Used
The study was conducted with a cohort of 85 post graduate students taking a compulsory module in Java programming in the first semester of a one year MSc in Software Development. A pre-course survey of students found that 58% preferred to have available videos of “key moments” of lectures rather than whole lectures. A large scale study carried out by Guo concluded that “shorter videos are much more engaging” (Guo 2013). Of concern was the potential for low audience retention for videos of whole lectures.
The lecturers recorded snippets of the lecture directly before or after the actual physical delivery of the lecture, in a quiet environment and then upload the video directly to a closed YouTube channel. These snippets generally concentrated on significant parts of the theory followed by theory related coding demonstration activities and were faithful in replication of the face to face lecture. Generally each lecture was supported by two to three videos of durations ranging from 20 – 30 minutes.
Attendance
The MSc programme has several attendance based modules of which Java Programming was one element. In order to assess the consequence on attendance for the Programming module a control was established. The control used was a Database module which is taken by the same students and runs in the same semester.
Access engagement
The videos were hosted on a closed YouTube channel made available only to the students in the class. The channel had enabled analytics which reported on the following areas for all and for each individual video; views (hits), audience retention, viewing devices / operating systems used and minutes watched.
Student attitudes
Three surveys were taken in regard to investigating student attitudes towards the videoing of lectures. The first was before the start of the programming module, then at the mid-point and subsequently after the programme was complete.
The questions in the first survey were targeted at eliciting student attitudes towards lecture capture before they had experienced it in the programme. The midpoint survey gathered data in relation to how the students were individually using the system up to that point. This included feedback on how many videos an individual had watched, viewing duration, primary reasons for watching and the result on attendance, in addition to probing for comments or suggestions. The final survey on course completion contained questions similar to the midpoint survey but in summative view of the whole video programme.
Conclusions and Outcomes
The study confirmed findings of other such investigations illustrating that there is little or no effect on attendance at lectures. The use of the videos appears to help promote continual learning but they are particularly accessed by students at assessment periods. Students respond positively to the ability to access lectures digitally, as a means of reinforcing learning experiences rather than replacing them. Feedback from students was overwhelmingly positive indicating that the videos benefited their learning. Also there are significant benefits to part recording of lectures rather than recording whole lectures. The behaviour viewing trends analytics suggest that despite the increase in the popularity of online learning via MOOCs and the promotion of video learning on mobile devices in fact in this study the vast majority of students accessed the online videos at home on laptops or desktops However, in part, this is likely due to the nature of the taught subject, that being programming.
The research involved prerecording the lecture in smaller timed units and then uploading for distribution to counteract existing quality issues with recording entire live lectures. However the advancement and consequential improvement in quality of in situ lecture capture equipment may well help negate the need to record elsewhere. The research has also highlighted an area of potentially very significant use for performance analysis and improvement that could have major implications for the quality of teaching. A study of the analytics of the viewings of the videos could well provide a quick response formative feedback mechanism for the lecturer. If a videoed lecture either recorded live or later is a true reflection of the face to face lecture an analysis of the viewing patterns for the video may well reveal trends that correspond with the live delivery.

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This work presents a new general purpose classifier named Averaged Extended Tree Augmented Naive Bayes (AETAN), which is based on combining the advantageous characteristics of Extended Tree Augmented Naive Bayes (ETAN) and Averaged One-Dependence Estimator (AODE) classifiers. We describe the main properties of the approach and algorithms for learning it, along with an analysis of its computational time complexity. Empirical results with numerous data sets indicate that the new approach is superior to ETAN and AODE in terms of both zero-one classification accuracy and log loss. It also compares favourably against weighted AODE and hidden Naive Bayes. The learning phase of the new approach is slower than that of its competitors, while the time complexity for the testing phase is similar. Such characteristics suggest that the new classifier is ideal in scenarios where online learning is not required.

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Online chatbots (also known as pedagogical agents or virtual assistants) are becoming embedded into the fabric of technology, both in educational and commercial settings. Yet understanding of these technologies is inchoate and often untheorised, influenced by individuals’ willingness to trust technologies, aesthetic appearance of the chatbot and technical literacy, among other factors. This paper draws upon data from two research studies that evaluated students’ experiences of using pedagogical agents in education using responsive evaluation. The findings suggest that emotional connections with pedagogical agents were intrinsic to the user’s sense of trust and therefore likely to affect levels of truthfulness and engagement. They also indicate that the topic of the pedagogical agent-student interaction is key to the student’s experience. The implications of these studies are that truthfulness, personalisation and emotional engagement are all vital components in using pedagogical agents to enhance online learning.