A learning approach for performance evaluation of local network

In this paper, a novel approach is developed to evaluate the overall performance of a local area network as well as to monitor some possible intrusion detections. The data is obtained via system utility 'ping' and huge data is analyzed via statistical methods. Finally, an overall performance index is defined and simulation experiments in three months proved the effectiveness of the proposed performance index. A software package is developed based on these ideas.

Designing and implementing a blended learning approach to executive SCM education:a case study from Ireland

The National Institute for Transport and Logistics (NITL) is Ireland’s centre of excellence for supply chain management (SCM). As part of its mission to promote the development of supply chain expertise in Irish business, it designs and delivers executive modular learning programmes. In 2004, as part of a drive to create more flexible learning opportunities for course participants, NITL designed and implemented an eLearning programme, which involved converting traditionally tutored modules to online modules. This paper describes the rationale behind this initiative and the significance of technology as an enabling tool for executive education, as well as detailing the design and implementation processes for the pilot module. The paper concludes with a critique of the expected and actual benefits realised, as well as future development considerations.

Using cognitive load theory to interpret student difficulties with a problem-based learning approach to engineering education:a case study

This article reports on an investigationwith first year undergraduate ProductDesign and Management students within a School of Engineering and Applied Science. The students at the time of this investigation had studied fundamental engineering science and mathematics for one semester. The students were given an open ended, ill-formed problem which involved designing a simple bridge to cross a river.They were given a talk on problemsolving and given a rubric to follow, if they chose to do so.They were not given any formulae or procedures needed in order to resolve the problem. In theory, they possessed the knowledge to ask the right questions in order tomake assumptions but, in practice, it turned out they were unable to link their a priori knowledge to resolve this problem. They were able to solve simple beam problems when given closed questions. The results show they were unable to visualize a simple bridge as an augmented beam problem and ask pertinent questions and hence formulate appropriate assumptions in order to offer resolutions.

An organizational learning approach to expatriate cross-cultural adjustment, organizational commitment, and job satisfaction

The purpose of this study was to investigate the relationship between organizational learning and expatriation in overseas subsidiaries as well as in organizations as a whole. In doing so, two issues were addressed--(i) the use of expatriation as firms internationalize, and (ii) the significance of various factors to expatriate success as firms gain international experience. The sample of companies for this study was drawn from U.S. Fortune 500 multinational corporations (MNCs) in two sets of related industries--computers/electronics and petroleum/chemicals. Based on the learning that takes place within organizations as they increase their involvement overseas, a positive relationship was expected between international experience and expatriation when internationalization was low, and a negative relationship was expected when internationalization was high. Results indicate a significant positive relationship between country experience and the proportion of expatriates in that subsidiary when subsidiaries were relatively young, and a negative relationship, however not significant, for more mature subsidiaries. The relationship between overall firm degree of internationalization (DOI) and the proportion of expatriates in the firm as a whole was negative regardless of stage of internationalization, but this relationship was significant only for highly internationalized firms. It was further suspected that individual, environmental, and family-related characteristics would have a significant effect on the success of expatriates whose firms were low on internationalization, and that organizational characteristics would play a significant role in highly internationalized firms. Support for these hypotheses was received with respect to certain outcomes and some determinants of success. The preponderance of support was found for those addressing the effects of both environmental and family-related characteristics on the cross-cultural adjustment of expatriates in firms with little international experience. Considerable support was also found for those hypotheses addressing the impact of organizational characteristics on the job satisfaction levels of expatriates assigned to mature subsidiaries. The relevant literatures on organizational learning and expatriation are reviewed, and a model is developed underlying the logic of the hypotheses. Research methods are then described in full detail, results are reported, and implications for theory and for management are discussed. ^

Employee Orientation: An Organizational and Experiential Learning Approach

Employee orientation problems for a resort chain were studied and addressed through action research. The implemented solution leveraged experiential learning to foster employee initiative and problem solving to instill a culture of learning, improve customer satisfaction and increase employee retention. Business results were achieved but learner/ management reaction was mixed.

AR-based Technoself Enhanced Learning Approach to Improving Student Engagement

The emerging technologies have expanded a new dimension of self – ‘technoself’ driven by socio-technical innovations and taken an important step forward in pervasive learning. Technology Enhanced Learning (TEL) research has increasingly focused on emergent technologies such as Augmented Reality (AR) for augmented learning, mobile learning, and game-based learning in order to improve self-motivation and self-engagement of the learners in enriched multimodal learning environments. These researches take advantage of technological innovations in hardware and software across different platforms and devices including tablets, phoneblets and even game consoles and their increasing popularity for pervasive learning with the significant development of personalization processes which place the student at the center of the learning process. In particular, augmented reality (AR) research has matured to a level to facilitate augmented learning, which is defined as an on-demand learning technique where the learning environment adapts to the needs and inputs from learners. In this paper we firstly study the role of Technology Acceptance Model (TAM) which is one of the most influential theories applied in TEL on how learners come to accept and use a new technology. Then we present the design methodology of the technoself approach for pervasive learning and introduce technoself enhanced learning as a novel pedagogical model to improve student engagement by shaping personal learning focus and setting. Furthermore we describe the design and development of an AR-based interactive digital interpretation system for augmented learning and discuss key features. By incorporating mobiles, game simulation, voice recognition, and multimodal interaction through Augmented Reality, the learning contents can be geared toward learner's needs and learners can stimulate discovery and gain greater understanding. The system demonstrates that Augmented Reality can provide rich contextual learning environment and contents tailored for individuals. Augment learning via AR can bridge this gap between the theoretical learning and practical learning, and focus on how the real and virtual can be combined together to fulfill different learning objectives, requirements, and even environments. Finally, we validate and evaluate the AR-based technoself enhanced learning approach to enhancing the student motivation and engagement in the learning process through experimental learning practices. It shows that Augmented Reality is well aligned with constructive learning strategies, as learners can control their own learning and manipulate objects that are not real in augmented environment to derive and acquire understanding and knowledge in a broad diversity of learning practices including constructive activities and analytical activities.

Action-Emotion Style, Learning Approach and Coping Strategies, in Undergraduate University Students

Action-Emotion Style (AES) is an affective-motivational construct that describes the achievement motivation that is characteristic of students in their interaction with stressful situations. Using elements from the Type-A Behavior Pattern (TABP), characteristics of competitiveness and overwork occur in different combinations with emotions of impatience and hostility, leading to a classification containing five categories of action-emotion style (Type B, Impatient-hostile type, Medium type, Competitive-Overworking type and Type A). The objective of the present research is to establish how characteristics of action-emotion style relate to learning approach (deep and surface approaches) and to coping strategies (emotion-focused and problem-focused). The sample was composed of 225 students from the Psychology degree program. Pearson correlation analyses, ANOVAs and MANOVAs were used. Results showed that competitiveness-overwork characteristics have a significant positive association with the deep approach and with problem-focused strategies, while impatience-hostility is thus related to surface approach and emotion-focused strategies. The level of action-emotion style had a significant main effect. The results verified our hypotheses with reference to the relationships between action-emotion style, learning approaches and coping strategies.

Project-Based learning approach to foster strategic competences of adult students at Cafam Santa Lucia School

Tesis (Licenciado en Lenguas Castellana, Inglés y Francés).--Universidad de La Salle. Facultad de Ciencias de La Educación. Licenciatura en Lengua Castellana, Inglés y Francés, 2014

A machine learning approach to measure and monitor physical activity in children to help fight overweight and obesity

Physical Activity is important for maintaining healthy lifestyles. Recommendations for physical activity levels are issued by most governments as part of public health measures. As such, reliable measurement of physical activity for regulatory purposes is vital. This has lead research to explore standards for achieving this using wearable technology and artificial neural networks that produce classifications for specific physical activity events. Applied from a very early age, the ubiquitous capture of physical activity data using mobile and wearable technology may help us to understand how we can combat childhood obesity and the impact that this has in later life. A supervised machine learning approach is adopted in this paper that utilizes data obtained from accelerometer sensors worn by children in free-living environments. The paper presents a set of activities and features suitable for measuring physical activity and evaluates the use of a Multilayer Perceptron neural network to classify physical activities by activity type. A rigorous reproducible data science methodology is presented for subsequent use in physical activity research. Our results show that it was possible to obtain an overall accuracy of 96 % with 95 % for sensitivity, 99 % for specificity and a kappa value of 94 % when three and four feature combinations were used.

An ensemble learning approach for addressing the class imbalance problem in twitter spam detection

Being an important source for real-time information dissemination in recent years, Twitter is inevitably a prime target of spammers. It has been showed that the damage caused by Twitter spam can reach far beyond the social media platform itself. To mitigate the threat, a lot of recent studies use machine learning techniques to classify Twitter spam and report very satisfactory results. However, most of the studies overlook a fundamental issue that is widely seen in real-world Twitter data, i.e., the class imbalance problem. In this paper, we show that the unequal distribution between spam and non-spam classes in the data has a great impact on spam detection rate. To address the problem, we propose an ensemble learning approach, which involves three steps. In the first step, we adjust the class distribution in the imbalanced data set using various strategies, including random oversampling, random undersampling and fuzzy-based oversampling. In the next step, a classification model is built upon each of the redistributed data sets. In the final step, a majority voting scheme is introduced to combine all the classification models. Experimental results obtained using real-world Twitter data indicate that the proposed approach can significantly improve the spam detection rate in data sets with imbalanced class distribution.

A machine learning approach for recognising woody plants on railway trackbeds

The purpose of this work in progress study was to test the concept of recognising plants using images acquired by image sensors in a controlled noise-free environment. The presence of vegetation on railway trackbeds and embankments presents potential problems. Woody plants (e.g. Scots pine, Norway spruce and birch) often establish themselves on railway trackbeds. This may cause problems because legal herbicides are not effective in controlling them; this is particularly the case for conifers. Thus, if maintenance administrators knew the spatial position of plants along the railway system, it may be feasible to mechanically harvest them. Primary data were collected outdoors comprising around 700 leaves and conifer seedlings from 11 species. These were then photographed in a laboratory environment. In order to classify the species in the acquired image set, a machine learning approach known as Bag-of-Features (BoF) was chosen. Irrespective of the chosen type of feature extraction and classifier, the ability to classify a previously unseen plant correctly was greater than 85%. The maintenance planning of vegetation control could be improved if plants were recognised and localised. It may be feasible to mechanically harvest them (in particular, woody plants). In addition, listed endangered species growing on the trackbeds can be avoided. Both cases are likely to reduce the amount of herbicides, which often is in the interest of public opinion. Bearing in mind that natural objects like plants are often more heterogeneous within their own class rather than outside it, the results do indeed present a stable classification performance, which is a sound prerequisite in order to later take the next step to include a natural background. Where relevant, species can also be listed under the Endangered Species Act.

Social media as sensor for healthcare: A machine learning approach.

This thesis advances the area of applied machine learning, sentiment and psycholinguistic analysis in social media for health analytics. In particular, the thesis views social media as a gigantic form of 'sensor' to inform about mental health community and related topics.

Adopting an active learning approach to teaching in a research-intensive higher education context transformed staff teaching attitudes and behaviours

The conventional lecture has significant limitations in the higher education context, often leading to a passive learning experience for students. This paper reports a process of transforming teaching and learning with active learning strategies in a research-intensive educational context across a faculty of 45 academic staff and more than 1000 students. A phased approach was used, involving nine staff in a pilot phase during which a common vision and principles were developed. In short, our approach was to mandate a move away from didactic lectures to classes that involved students interacting with content, with each other and with instructors in order to attain domain-specific learning outcomes and generic skills. After refinement, an implementation phase commenced within all first-year subjects, involving 12 staff including three from the pilot group. The staff use of active learning methods in classes increased by sixfold and sevenfold in the pilot and implementation phases, respectively. An analysis of implementation phase exam questions indicated that staff increased their use of questions addressing higher order cognitive skills by 51%. Results of a staff survey indicated that this change in practice was caused by the involvement of staff in the active learning approach. Fifty-six percent of staff respondents indicated that they had maintained constructive alignment as they introduced active learning. After the pilot, only three out of nine staff agreed that they understood what makes for an effective active learning exercise. This rose to seven out of nine staff at the completion of the implementation phase. The development of a common approach with explicit vision and principles and the evaluation and refinement of active learning were effective elements of our transformational change management strategy. Future efforts will focus on ensuring that all staff have the time, skills and pedagogical understanding required to embed constructively aligned active learning within the approach.

A learning community approach to doctoral education in the social sciences

The paper reports on the findings of a community learning approach to doctoral education involving scholarly writing groups (SWGs) which was developed and implemented in the context of a higher degree research programme within the social sciences in an Australian university. The research evaluated the impact of the teaching intervention on students' perceptions of the community learning experience, their knowledge of scholarly writing and their attitudes towards writing. The findings are suggestive of the advantages of community approaches to learning in higher degree research education as a supplement to independent supervision. The SWGs were associated with improvements in both participants' knowledge of scholarly writing and their attitudes towards writing. However, a variety of characteristics of doctoral education are potential impediments to the creation of ongoing and regular interactions in learning communities such as SWGs. The paper concludes that a flexible approach to the recognition and enhancement of community approaches to learning is required to acknowledge the complex and diverse context of contemporary doctoral education.

An instrument to measure the approach to learning for assessment in economics

Economics education research studies conducted in the UK, USA and Australia to investigate the effects of learning inputs on academic performance have been dominated by the input-output model (Shanahan and Meyer, 2001). In the Student Experience of Learning framework, however, the link between learning inputs and outputs is mediated by students' learning approaches which in turn are influenced by their perceptions of the learning contexts (Evans, Kirby, & Fabrigar, 2003). Many learning inventories such as Biggs' Study Process Questionnaires and Entwistle and Ramsden' Approaches to Study Inventory have been designed to measure approaches to academic learning. However, there is a limitation to using generalised learning inventories in that they tend to aggregate different learning approaches utilised in different assessments. As a result, important relationships between learning approaches and learning outcomes that exist in specific assessment context(s) will be missed (Lizzio, Wilson, & Simons, 2002). This paper documents the construction of an assessment specific instrument to measure learning approaches in economics. The post-dictive validity of the instrument was evaluated by examining the association of learning approaches to students' perceived assessment demand in different assessment contexts.