Learning higher-level features with convolutional restricted Boltzmann machines for sentiment analysis

In recent years, learning word vector representations has attracted much interest in Natural Language Processing. Word representations or embeddings learned using unsupervised methods help addressing the problem of traditional bag-of-word approaches which fail to capture contextual semantics. In this paper we go beyond the vector representations at the word level and propose a novel framework that learns higher-level feature representations of n-grams, phrases and sentences using a deep neural network built from stacked Convolutional Restricted Boltzmann Machines (CRBMs). These representations have been shown to map syntactically and semantically related n-grams to closeby locations in the hidden feature space. We have experimented to additionally incorporate these higher-level features into supervised classifier training for two sentiment analysis tasks: subjectivity classification and sentiment classification. Our results have demonstrated the success of our proposed framework with 4% improvement in accuracy observed for subjectivity classification and improved the results achieved for sentiment classification over models trained without our higher level features.

Knowledge Presentation and Reasoning with Loglinear Models

Our approach for knowledge presentation is based on the idea of expert system shell. At first we will build a graph shell of both possible dependencies and possible actions. Then, reasoning by means of Loglinear models, we will activate some nodes and some directed links. In this way a Bayesian network and networks presenting loglinear models are generated.

A Planning Model with Resources in e-Learning

This work proposes a model for planning of education based on resources and layers. Each learning material or concept is determined by certain characteristics: a layer and a list of resources and resource values. Models of studied subject domain, learner, information and verification unit, learning material, plan of education and education have been defined. The plan of education can be conventional, statical, author’s and dynamic. Algorithms for course generation, dynamic plan generation and carrying out education are presented. The proposed model for planning of education based on resources and layers has been included in the system PeU.

Distance Learning Education of Software Engineering: Principles and Experiences

Whether distance learning spells the end of traditional campuses, as some maintain, or whether distance learning instead represents a powerful addition to a growing array of delivery options for higher education, its impact on higher education is great and growing. Distance learning is creating alternative models of teaching and learning, new job descriptions for faculty, and new types of higher education providers. The advent of Distance and Distributed Learning has raised numerous questions about quality and quality assurance: ² How do established distance learning institutions ensure quality? ² What more needs to be done? ² How do quality assurance agencies view the distinction between on- and off-campus teaching and learning? This talk discusses these issues from the viewpoints of funding organisa- tion, quality assurance agencies and the learners.

Adaptive E-learning Content Design and Delivery Based on Learning Styles and Knowledge Level

ACM Computing Classification System (1998): K.3.1, K.3.2.

Supervised learning of graph structure

Graph-based representations have been used with considerable success in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the methodology available for learning structural representations from sets of training examples is relatively limited. In this paper we take a simple yet effective Bayesian approach to attributed graph learning. We present a naïve node-observation model, where we make the important assumption that the observation of each node and each edge is independent of the others, then we propose an EM-like approach to learn a mixture of these models and a Minimum Message Length criterion for components selection. Moreover, in order to avoid the bias that could arise with a single estimation of the node correspondences, we decide to estimate the sampling probability over all the possible matches. Finally we show the utility of the proposed approach on popular computer vision tasks such as 2D and 3D shape recognition. © 2011 Springer-Verlag.

A Multi-View Learning Algorithm

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

How Students Study? An Analysis of Learning Strategies in Engineering and Technology Courses

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2014

Age differences in associative and strategic processes in human conditional learning

Research indicates associative and strategic deficits mediate age related deficits in memory, whereas simple associative processes are independent of strategic processing and strategic processes mediate resistance to interference. The present study showed age-related deficits in a contingency learning task, although older participants' resistance to interference was not disproportionately affected. Recognition memory predicted discrimination, whereas general cognitive ability predicted resistance to interference, suggesting differentiation between associative and strategic processes in learning and memory, and age declines in associative processes. Older participants' generalisation of associative strength from existing to novel stimulus-response associations was consistent with elemental learning theories, whereas configural models predicted younger participants' responses. This is consistent with associative deficits and reliance on item-level representations in memory during later life. © 2011 Psychology Press Ltd.

Using observation ageing to improve Markovian model learning in QoS engineering

Markovian models are widely used to analyse quality-of-service properties of both system designs and deployed systems. Thanks to the emergence of probabilistic model checkers, this analysis can be performed with high accuracy. However, its usefulness is heavily dependent on how well the model captures the actual behaviour of the analysed system. Our work addresses this problem for a class of Markovian models termed discrete-time Markov chains (DTMCs). We propose a new Bayesian technique for learning the state transition probabilities of DTMCs based on observations of the modelled system. Unlike existing approaches, our technique weighs observations based on their age, to account for the fact that older observations are less relevant than more recent ones. A case study from the area of bioinformatics workflows demonstrates the effectiveness of the technique in scenarios where the model parameters change over time.

Assessing learning in Higher Education

Assessing Learning in Higher Education addresses what is probably the most time-consuming part of the work of staff in higher education, and something to the complexity of which many of the recent developments in higher education have added. Getting assessment ‘right’– that is, designing and implementing appropriate models and methods, can determine the future lives and careers of students. But, as Professor Phil Race comments in his excellent and thought-provoking foreword, students entering higher education often have little idea about how exactly assessment will work, and often find that the process is very different from anything they have previously encountered. Assessing Learning in Higher Education contains innovative approaches to assessment drawn from many different cultures and disciplines. The chapter authors argue the need for changing assessment and feedback processes so that they embrace online collaboration and discussion between students as well as between ‘students’ and ‘faculty’. The chapters demonstrate that at some points there is a need to be able to measure individual achievement, and to do this in ways that are valid, transparent, authentic – and above all fair. Assessment and feedback processes need to ensure that students are well prepared for this individual assessment, but also to take account of collaboration and interaction. The respective chapters of Assessing Learning in Higher Education all of which are complete in themselves, but with very useful links to ideas in other chapters, provide numerous illustrations of how this can be achieved.

Using structural equation modeling to assess two theoretical models that explain dropout

This study evaluated the relative fit of both Finn's (1989) Participation-Identification and Wehlage, Rutter, Smith, Lesko and Fernandez's (1989) School Membership models of high school completion to a sample of 4,597 eighth graders taken from the National Educational Longitudinal Study of 1988, (NELS:88), utilizing structural equation modeling techniques. This study found support for the importance of educational engagement as a factor in understanding academic achievement. The Participation-Identification model was particularly well fitting when applied to the sample of high school completers, dropouts (both overall and White dropouts) and African-American students. This study also confirmed the contribution of school environmental factors (i.e., size, diversity of economic and ethnic status among students) and family resources (i.e., availability of learning resources in the home and parent educational level) to students' educational engagement. Based on these findings, school social workers will need to be more attentive to utilizing macro-level interventions (i.e., community organization, interagency coordination) to achieve the organizational restructuring needed to address future challenges. The support found for the Participation-Identification model supports a shift in school social workers' attention from reactive attempts to improve the affective-interpersonal lives of students to proactive attention to their academic lives. The model concentrates school social work practices on the central mission of schools, which is educational engagement. School social workers guided by this model would be encouraged to seek changes in school policies and organization that would facilitate educational engagement. ^

A case study of adults in college who developed an experiential learning portfolio

This single-case study provides a description and explanation of selected adult students' perspectives on the impact that the development of an experiential learning portfolio had on their understanding of their professional and personal lives. The conceptual framework that undergirded the study included theoretical and empirical studies on adult learning, experiential learning, and the academic quality of nontraditional degree programs with a portfolio component. The study employed qualitative data collection techniques of individual interviews, document review, field notes, and researcher journal. A purposive sample of 8 adult students who completed portfolios as a component of their undergraduate degrees participated in the study. The 4 male and 4 female students who were interviewed represented 4 ethnic/racial groups and ranged in age from 32 to 55 years. Each student's portfolio was read prior to the interview to frame the semi-structured interview questions in light of written portfolio documents. ^ Students were interviewed twice over a 3-month period. The study lasted 8 months from data collection to final presentation of the findings. The data from interview transcriptions and student portfolios were analyzed, categorized, coded, and sorted into 4 major themes and 2 additional themes and submitted to interpretive analysis. ^ Participants' attitudes, perceptions, and opinions of their learning from the portfolio development experience were presented in the findings, which were illustrated through the use of excerpts from interview responses and individual portfolios. The participants displayed a positive reaction to the learning they acquired from the portfolio development process, regardless of their initial concerns about the challenges of creating a portfolio. Concerns were replaced by a greater recognition and understanding of their previous professional and personal accomplishments and their ability to reach future goals. Other key findings included (a) a better understanding of the role work played in their learning and development, (b) a deeper recognition of the impact of mentors and role models throughout their lives, (c) an increase in writing and organizational competencies, and (d) a sense of self-discovery and personal empowerment. ^

Effects of cooperative and individual integrated learning system on attitudes and achievement in mathematics

This study compares the effects of cooperative delivery (CD) and individual delivery (ID) of integrated learning system (ILS) instruction in mathematics on achievement, attitudes and behaviors in adult (16-21 yrs.) high school students (grades 9-13). The study was conducted in an urban adult high school in Miami-Dade County Public Schools using a pre-test/post-test design. Achievement was measured using the Test of Adult Basic Education (TABE) by CTB MC-Graw-Hill and Compass Learning. An attitudinal survey measured attitudes towards mathematics, the computer-related lessons, and attitudes toward group activities. Behavior was assessed using computer lab observations. ^ Two-way analyses of variance (ANOVA) were conducted on achievement (TABE and Compass) by group and time (pre and post). A one-way ANOVA was conducted on the overall attitude by group on the five components (i.e., content mathematics, delivery/computers, cooperative, partners, and self efficacy) and a one-way ANOVA was conducted on the on-task behavior by group. ^ The results of the study revealed that CD and ID students working on mathematics activities delivered by the ILS performed similarly on achievement tests of the TABE. The CD-ILS students had significantly better overall mathematics attitudes than the ID-ILS students and the ID-ILS group was on-task significantly more than the CD-ILS group. This study concludes that regularity and period of time over which the ILS is used may prove to be important variables although there were insufficient data to fully investigate the impact of models of use. Additionally, a minimum amount of time-on-system is necessary before gains can become apparent in innumeracy and increasing exposure to the system may have beneficial effects on learning. ^

When One Dimensional Models Fail: Complexifying Models of Knowledge Construction

One dimensional models of reflective practice do not incorporate spirituality and social responsibility. Theological reflection, a form of reflective practice, is contextualized by a vision of social responsibility and the use of spirituality. An alternative model of reflective practice is proposed for spirituality and socially responsive learning at work.