Outliers Resistant Learning Algorithm for Radial-basis-fuzzy-wavelet-neural Network in Stomach Acute Injury Diagnosis Tasks

In this paper an outliers resistant learning algorithm for the radial-basis-fuzzy-wavelet-neural network based on R. Welsh criterion is proposed. Suggested learning algorithm under consideration allows the signals processing in presence of significant noise level and outliers. The robust learning algorithm efficiency is investigated and confirmed by the number of experiments including medical applications.

KFTKGA: Knowledge Flow Tracer and Growth Analyzer for Community Learning

The advances in building learning technology now have to emphasize on the aspect of the individual learning besides the popular focus on the technology per se. Unlike the common research where a great deal has been on finding ways to build, manage, classify, categorize and search knowledge on the server, there is an interest in our work to look at the knowledge development at the individual’s learning. We build the technology that resides behind the knowledge sharing platform where learning and sharing activities of an individual take place. The system that we built, KFTGA (Knowledge Flow Tracer and Growth Analyzer), demonstrates the capability of identifying the topics and subjects that an individual is engaged with during the knowledge sharing session and measuring the knowledge growth of the individual learning on a specific subject on a given time space.

TQM in e-Learning: a Self-assessment Model and Questionnaire

Organizations are seeking new, integrated systems that enable rapid changes through early identification of opportunities and problems, tracking of progress against plans, flexible allocation of resources to achieve goals, and consistent operations. Total Quality Management (TQM) is an overall business strategy. It means that all activities of the company will be focused on satisfying all stakeholders of the company. TQM can be realised by using the EFQM model. The EFQM model is a tool that organizations may use as a framework for self-evaluation that enables an organization to identify its strengths and areas for improvement and the extent to which its operations and results are in line with the characteristics of an excellent organization. We focus on a training organisation or to the learning department of an organization. So we are limiting the EFQM model to the training /learning activities. We can apply EFQM perfect on the level of an activity (business line) of a company. We selected the main criteria for which the learner can play the role of assessor. So only three main criteria left: the enabling resources, the enabling processes and the (learning) results for the learner. We limited the last one to “learning results” based on the Kirkpatrick model.

Quality Estimation of e-Learning Systems

Existing approaches to quality estimation of e-learning systems are analyzed. The “layered” approach for quality estimation of e-learning systems enhanced with learning process modeling and simulation is presented. The method of quality estimation using learning process modeling and quality criteria are suggested. The learning process model based on extended colored stochastic Petri net is described. The method has been implemented in the automated system of quality estimation of e-learning systems named “QuAdS”. Results of approbation of the developed method and quality criteria are shown. We argue that using learning process modeling for quality estimation simplifies identifying lacks of an e-learning system for an expert.

Using the e-Class Open Platform for e-Learning Support at the TEI of Larissa, Greece

In the current paper we firstly give a short introduction on e-learning platforms and review the case of the e-class open e-learning platform being used by the Greek tertiary education sector. Our analysis includes strategic selection issues and outcomes in general and operational and adoption issues in the case of the Technological Educational Institute (TEI) of Larissa, Greece. The methodology is being based on qualitative analysis of interviews with key actors using the platform, and statistical analysis of quantitative data related to adoption and usage in the relevant populations. The author has been a key actor in all stages and describes his insights as an early adopter, diffuser and innovative user. We try to explain the issues under consideration using existing past research outcomes and we also arrive to some conclusions and points for further research.

Educational Games for Learning Programming Languages

A concept of educational game for learning programming languages is presented. The idea of learning programming languages and improving programming skills through programming game characters’ behavior is described. The learning course description rules for using in games are suggested. The concept is implemented in a game for learning C# programming language. A common game architecture is modified for using in the educational game. The game engine is built on the base of the graphical engine Ogre3D and extended with game logic. The game has been developed as an industry level commercial product and is planned for sale to educational institutions.

e-Learning, e-Practising and e-Tutoring: an Integrated Approach

In this paper is described a didactic methodology combining current e-learning methods and the support of Intelligent Agents technologies. The aim is to favor the synthesis among theoretical approach and based practical approach using the so-called Intelligent Agent, software that exploits the Artificial Intelligence and that operates as tutor, facilitating the consumers in the training operations. The paper illustrates how such new Intelligent Agent algorithm (IA) is used in the training of employees working in the transportation sector, thanks to the experience gained with the PARMENIDE project - Promoting Advanced Resources and Methodologies for New Teaching and Learning Solutions in Digital Education.

Self-Learning Fuzzy Spiking Neural Network as a Nonlinear Pulse-Position Threshold Detection Dynamic System Based on Second-Order Critically Damped Response Units

Architecture and learning algorithm of self-learning spiking neural network in fuzzy clustering task are outlined. Fuzzy receptive neurons for pulse-position transformation of input data are considered. It is proposed to treat a spiking neural network in terms of classical automatic control theory apparatus based on the Laplace transform. It is shown that synapse functioning can be easily modeled by a second order damped response unit. Spiking neuron soma is presented as a threshold detection unit. Thus, the proposed fuzzy spiking neural network is an analog-digital nonlinear pulse-position dynamic system. It is demonstrated how fuzzy probabilistic and possibilistic clustering approaches can be implemented on the base of the presented spiking neural network.

The Cascade Neo-Fuzzy Architecture and its Online Learning Algorithm

In the paper learning algorithm for adjusting weight coefficients of the Cascade Neo-Fuzzy Neural Network (CNFNN) in sequential mode is introduced. Concerned architecture has the similar structure with the Cascade-Correlation Learning Architecture proposed by S.E. Fahlman and C. Lebiere, but differs from it in type of artificial neurons. CNFNN consists of neo-fuzzy neurons, which can be adjusted using high-speed linear learning procedures. Proposed CNFNN is characterized by high learning rate, low size of learning sample and its operations can be described by fuzzy linguistic “if-then” rules providing “transparency” of received results, as compared with conventional neural networks. Using of online learning algorithm allows to process input data sequentially in real time mode.

Students' recollections of participating in a first year residential learning community experience

The purpose of this qualitative study was to gain an understanding of what participation in a first year residential learning community meant to students 2–3 years after their involvement in the program. Various theories including environmental, student involvement, psychosocial and intellectual, were used as a framework for this case study. Each of the ten participants was a junior or senior level student at the time of the study, but had previously participated in a first year residential learning community at Florida International University. The researcher held two semi-structured interviews with each participant, and collected data sheets from each. ^ The narrative data produced from the interviews were transcribed, coded and analyzed to gain insights into the experiences and perspectives of the participants. Member checking was used after the interview process. A peer reviewer offered feedback during the data analysis. The resulting data was coded into categories, with a final selection of four themes and 15 sub-themes, which captured the essence of the participants' experiences. The four major themes included: (a) community, (b) involvement, (c) identity, and (d) academics. The community theme is used to describe how students perceived the environment to be. The involvement theme is used to describe the students' participation in campus life and their interaction with other members of the university community. The identity theme is used to describe the students' process of development, and the personal growth they underwent as a result of their experiences. The academics theme refers to the intellectual development of students and their interaction around academic issues. ^ The results of this study showed that the participants valued greatly their involvement in the First Year Residents Succeeding Together program (FYRST) and can articulate how it helped them succeed as students. In describing their experience, they most recall the sense of community that existed, the personal growth they experienced, the academic development process they went through, and their involvement, both with other people and with activities in their community. Recommendations are provided for practice and research, including several related to enhancing the academic culture, integrating faculty, utilizing peer influence and providing further opportunities to create a seamless learning environment. ^

Making and Evaluating Strategy: Learning from the Military

Use of military analogy is rampant and considered an acceptable part of business vernacular. However, analogies only illustrate, and bad analogies make bad strategy. There are important lessons to be learned from military strategy, though. This article identifies "the ten principles of strategy" that corporate strategists could utilize in testing their strategic theories, concepts, and plans.

The impact of a Classroom Performance System on learning gains in a biology course for science majors

This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as "Clickers", improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.

Learning Data-Driven Models of Non-Verbal Behaviors for Building Rapport Using an Intelligent Virtual Agent

There is a growing societal need to address the increasing prevalence of behavioral health issues, such as obesity, alcohol or drug use, and general lack of treatment adherence for a variety of health problems. The statistics, worldwide and in the USA, are daunting. Excessive alcohol use is the third leading preventable cause of death in the United States (with 79,000 deaths annually), and is responsible for a wide range of health and social problems. On the positive side though, these behavioral health issues (and associated possible diseases) can often be prevented with relatively simple lifestyle changes, such as losing weight with a diet and/or physical exercise, or learning how to reduce alcohol consumption. Medicine has therefore started to move toward finding ways of preventively promoting wellness, rather than solely treating already established illness. Evidence-based patient-centered Brief Motivational Interviewing (BMI) interven- tions have been found particularly effective in helping people find intrinsic motivation to change problem behaviors after short counseling sessions, and to maintain healthy lifestyles over the long-term. Lack of locally available personnel well-trained in BMI, however, often limits access to successful interventions for people in need. To fill this accessibility gap, Computer-Based Interventions (CBIs) have started to emerge. Success of the CBIs, however, critically relies on insuring engagement and retention of CBI users so that they remain motivated to use these systems and come back to use them over the long term as necessary. Because of their text-only interfaces, current CBIs can therefore only express limited empathy and rapport, which are the most important factors of health interventions. Fortunately, in the last decade, computer science research has progressed in the design of simulated human characters with anthropomorphic communicative abilities. Virtual characters interact using humans’ innate communication modalities, such as facial expressions, body language, speech, and natural language understanding. By advancing research in Artificial Intelligence (AI), we can improve the ability of artificial agents to help us solve CBI problems. To facilitate successful communication and social interaction between artificial agents and human partners, it is essential that aspects of human social behavior, especially empathy and rapport, be considered when designing human-computer interfaces. Hence, the goal of the present dissertation is to provide a computational model of rapport to enhance an artificial agent’s social behavior, and to provide an experimental tool for the psychological theories shaping the model. Parts of this thesis were already published in [LYL+12, AYL12, AL13, ALYR13, LAYR13, YALR13, ALY14].

Students' recollections of participating in a first year residential learning community experience

The purpose of this qualitative study was to gain an understanding of what participation in a first year residential learning community meant to students 2-3 years after their involvement in the program. Various theories including environmental, student involvement, psychosocial and intellectual, were used as a framework for this case study. Each of the ten participants was a junior or senior level student at the time of the study, but had previously participated in a first year residential learning community at Florida International University. The researcher held two semi-structured interviews with each participant, and collected data sheets from each. The narrative data produced from the interviews were transcribed, coded and analyzed to gain insights into the experiences and perspectives of the participants. Member checking was used after the interview process. A peer reviewer offered feedback during the data analysis. The resulting data was coded into categories, with a final selection of four themes and 15 sub-themes, which captured the essence of the participants' experiences. The four major themes included: (a) community, (b) involvement, (c) identity, and (d) academics. The community theme is used to describe how students perceived the environment to be. The involvement theme is used to describe the students' participation in campus life and their interaction with other members of the university community. The identity theme is used to describe the students' process of development, and the personal growth they underwent as a result of their experiences. The academics theme refers to the intellectual development of students and their interaction around academic issues. The results of this study showed that the participants valued greatly their involvement in the First Year Residents Succeeding Together program (FYRST) and can articulate how it helped them succeed as students. In describing their experience, they most recall the sense of community that existed, the personal growth they experienced, the academic development process they went through, and their involvement, both with other people and with activities in their community. Recommendations are provided for practice and research, including several related to enhancing the academic culture, integrating faculty, utilizing peer influence and providing further opportunities to create a seamless learning environment.

Do the Messages Matter? An Investigation of Classroom Messages and College Students’ Personal Theories about Education

Students hold a number of personal theories about education that influence motivation and achievement in the classroom: theories about their own abilities, knowledge, and the learning process. Therefore, college instructors have a great interest in helping to develop adaptive personal theories in their students. The current studies investigated whether specific messages that instructors send in college classroom might serve as a mechanism of personal theory development. Across 2 studies, 17 college instructors and 401 students completed surveys assessing their personal theories about education at the beginning and end of college courses. Students and instructors reported hearing and sending many messages in the classroom, including instructor help messages, conciliatory messages, uncertainty in the field messages, differential ability messages and generalized positive and negative feedback. Between-class and within-class differences in message reports were associated with students’ personal theories at the end of their courses, controlling for initial personal theories. Students’ initial personal theories were also related to the messages students reported hearing. The findings demonstrate the utility of assessing non-content messages in college classrooms as potential mechanisms for changing students’ personal theories in college. Implications for research and practice are discussed.