A Bayesian Model for Learning Using Flashcards

Report published in the Proceedings of the National Conference on "Education and Research in the Information Society", Plovdiv, May, 2015

Predicting answering behaviour in online question answering communities

The value of Question Answering (Q&A) communities is dependent on members of the community finding the questions they are most willing and able to answer. This can be difficult in communities with a high volume of questions. Much previous has work attempted to address this problem by recommending questions similar to those already answered. However, this approach disregards the question selection behaviour of the answers and how it is affected by factors such as question recency and reputation. In this paper, we identify the parameters that correlate with such a behaviour by analysing the users' answering patterns in a Q&A community. We then generate a model to predict which question a user is most likely to answer next. We train Learning to Rank (LTR) models to predict question selections using various user, question and thread feature sets. We show that answering behaviour can be predicted with a high level of success, and highlight the particular features that inuence users' question selections.

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.

The effectiveness of workplace coaching:A meta-analysis of learning and performance outcomes; scale development; theoretical model of individual differences and longitudinal study

The extant literature on workplace coaching is characterised by a lack of theoretical and empirical understanding regarding the effectiveness of coaching as a learning and development tool; the types of outcomes one can expect from coaching; the tools that can be used to measure coaching outcomes; the underlying processes that explain why and how coaching works and the factors that may impact on coaching effectiveness. This thesis sought to address these substantial gaps in the literature with three linked studies. Firstly, a meta-analysis of workplace coaching effectiveness (k = 17), synthesizing the existing research was presented. A framework of coaching outcomes was developed and utilised to code the studies. Analysis indicated that coaching had positive effects on all outcomes. Next, the framework of outcomes was utilised as the deductive start-point to the development of the scale measuring perceived coaching effectiveness. Utilising a multi-stage approach (n = 201), the analysis indicated that perceived coaching effectiveness may be organised into a six factor structure: career clarity; team performance; work well-being; performance; planning and organizing and personal effectiveness and adaptability. The final study was a longitudinal field experiment to test a theoretical model of individual differences and coaching effectiveness developed in this thesis. An organizational sample of 84 employees each participated in a coaching intervention, completed self-report surveys, and had their job performance rated by peers, direct reports and supervisors (a total of 352 employees provided data on participant performance). The results demonstrate that compared to a control group, the coaching intervention generated a number of positive outcomes. The analysis indicated that coachees’ enthusiasm, intellect and orderliness influenced the impact of coaching on outcomes. Mediation analysis suggested that mastery goal orientation, performance goal orientation and approach motivation in the form of behavioural activation system (BAS) drive, were significant mediators between personality and outcomes. Overall, the findings of this thesis make an original contribution to the understanding of the types of outcomes that can be expected from coaching, and the magnitude of impact coaching has on outcomes. The thesis also provides a tool for reliably measuring coaching effectiveness and a theoretical model to understand the influence of coachee individual differences on coaching outcomes.

Anisotropic opinion dynamics

We consider the process of opinion formation in a society of interacting agents, where there is a set B of socially accepted rules. In this scenario, we observed that agents, represented by simple feed-forward, adaptive neural networks, may have a conservative attitude (mostly in agreement with B) or liberal attitude (mostly in agreement with neighboring agents) depending on how much their opinions are influenced by their peers. The topology of the network representing the interaction of the society's members is determined by a graph, where the agents' properties are defined over the vertexes and the interagent interactions are defined over the bonds. The adaptability of the agents allows us to model the formation of opinions as an online learning process, where agents learn continuously as new information becomes available to the whole society (online learning). Through the application of statistical mechanics techniques we deduced a set of differential equations describing the dynamics of the system. We observed that by slowly varying the average peer influence in such a way that the agents attitude changes from conservative to liberal and back, the average social opinion develops a hysteresis cycle. Such hysteretic behavior disappears when the variance of the social influence distribution is large enough. In all the cases studied, the change from conservative to liberal behavior is characterized by the emergence of conservative clusters, i.e., a closed knitted set of society members that follow a leader who agrees with the social status quo when the rule B is challenged.

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.

Learning user and product distributed representations using a sequence model for sentiment analysis

In product reviews, it is observed that the distribution of polarity ratings over reviews written by different users or evaluated based on different products are often skewed in the real world. As such, incorporating user and product information would be helpful for the task of sentiment classification of reviews. However, existing approaches ignored the temporal nature of reviews posted by the same user or evaluated on the same product. We argue that the temporal relations of reviews might be potentially useful for learning user and product embedding and thus propose employing a sequence model to embed these temporal relations into user and product representations so as to improve the performance of document-level sentiment analysis. Specifically, we first learn a distributed representation of each review by a one-dimensional convolutional neural network. Then, taking these representations as pretrained vectors, we use a recurrent neural network with gated recurrent units to learn distributed representations of users and products. Finally, we feed the user, product and review representations into a machine learning classifier for sentiment classification. Our approach has been evaluated on three large-scale review datasets from the IMDB and Yelp. Experimental results show that: (1) sequence modeling for the purposes of distributed user and product representation learning can improve the performance of document-level sentiment classification; (2) the proposed approach achieves state-of-The-Art results on these benchmark datasets.

A study of learners' perceived value and satisfaction for implied effectiveness of online learning systems

Online learning systems (OLS) have become center stage for corporations and educational institutions as a competitive tool in the knowledge economy. The satisfaction construct has received extensive coverage in information systems literature as an indicator of effectiveness but has been criticized for lack of validity; yet, the value construct has been largely ignored, although it has a long history in psychology, sociology, and behavioral science. The purpose of this dissertation is to investigate the value and satisfaction constructs in the context of OLS, and their perceived by learners relationship for implied effectiveness of OLS. ^ First, a qualitative phase is employed to gather OLS values from learners' focus groups, followed by a pilot phase to refine a proposed instrument, and a main phase to validate the survey. Responses were received from 75 students in four focus groups, 141 in the pilot, and 207 the main survey. Extensive data cleaning and exploratory factor analysis were done to identify factors of learners' perceived value and satisfaction of OLS. Then, Value-Satisfaction grids and the Learners' Value Index of Satisfaction (LeVIS) were developed as benchmarking tools of OLS. Moreover, Multicriteria Decision Analysis (MCDA) techniques were employed to impute value from satisfaction scores in order to reduce survey response time. ^ The results provided four satisfaction and four value factors with high reliability (Cronbach's α). Moreover, value and satisfaction were found to have low linear and nonlinear correlations, indicating that they are two distinct uncorrelated constructs. This is consistent with the literature. Value-Satisfaction grids and the LeVIS index indicated relatively high effectiveness for technology and support characteristics, relatively low effectiveness for professor's characteristics, while course and learner characteristics indicated average effectiveness. ^ The main contributions of this study include identifying, defining, and articulating the relationship between value and satisfaction constructs as assessment of users' implied IS effectiveness, as well as assessing the accuracy of MCDA procedures to predict value scores, thus reducing by half the survey questionnaire size. ^

Theological reflection at work: A phenomenological study of learning processes

Using the learning descriptions of graduates of a graduate ministry program, the mechanisms of interactions between the knowledge facets in learning processes were explored and described. The intent of the study was to explore how explicit, implicit, and emancipatory knowledge facets interacted in the learning processes at or about work. The study provided empirical research on Yang's (2003) holistic learning theory. ^ A phenomenological research design was used to explore the essence of knowledge facet interactions. I achieved epoche through the disclosure of assumptions and a written self-experience to bracket biases. A criterion based, stratified sampling strategy was used to identify participants. The sample was stratified by graduation date. The sample consisted of 11 participants and was composed primarily of married (n = 9), white, non-Hispanic (n = 10), females (n = 9), who were Roman Catholic (n = 9). Professionally, the majority of the group were teachers or professors (n = 5). ^ A semi-structured interview guide with scheduled and unscheduled probes was used. Each approximately 1-hour long interview was digitally recorded and transcribed. The transcripts were coded using a priori codes from holistic learning theory and one emergent code. The coded data were analyzed by identifying patterns, similarities, and differences under each code and then between codes. Steps to increase the trustworthiness of the study included member checks, coding checks, and thick descriptions of the data. ^ Five themes were discovered including (a) the difficulty in describing interactions between knowledge facets; (b) actual mechanisms of interactions between knowledge facets; (c) knowledge facets initiating learning and dominating learning processes; (d) the dangers of one-dimensional learning or using only one knowledge facet to learn; and (e) the role of community in learning. The interpretation confirmed, extended, and challenged holistic learning theory. Mechanisms of interaction included knowledge facets expressing, informing, changing, and guiding one another. Implications included the need for a more complex model of learning and the value of seeing spirituality in the learning process. The study raised questions for future research including exploring learning processes with people from non-Christian faith traditions or other academic disciplines and the role of spiritual identity in learning. ^

Development and validation of an instrument to predict online student success using faculty perceptions

Distance learning is growing and transforming educational institutions. The increasing use of distance learning by higher education institutions and particularly community colleges coupled with the higher level of student attrition in online courses than in traditional classrooms suggests that increased attention should be paid to factors that affect online student course completion. The purpose of the study was to develop and validate an instrument to predict community college online student course completion based on faculty perceptions, yielding a prediction model of online course completion rates. Social Presence and Media Richness theories were used to develop a theoretically-driven measure of online course completion. This research study involved surveying 311 community college faculty who taught at least one online course in the past 2 years. Email addresses of participating faculty were provided by two south Florida community colleges. Each participant was contacted through email, and a link to an Internet survey was given. The survey response rate was 63% (192 out of 303 available questionnaires). Data were analyzed through factor analysis, alpha reliability, and multiple regression. The exploratory factor analysis using principal component analysis with varimax rotation yielded a four-factor solution that accounted for 48.8% of the variance. Consistent with Social Presence theory, the factors with their percent of variance in parentheses were: immediacy (21.2%), technological immediacy (11.0%), online communication and interactivity (10.3%), and intimacy (6.3%). Internal consistency of the four factors was calculated using Cronbach's alpha (1951) with reliability coefficients ranging between .680 and .828. Multiple regression analysis yielded a model that significantly predicted 11% of the variance of the dependent variable, the percentage of student who completed the online course. As indicated in the literature (Johnson & Keil, 2002; Newberry, 2002), Media Richness theory appears to be closely related to Social Presence theory. However, elements from this theory did not emerge in the factor analysis.

Learning Behind Bars: Exploring Prison Educators’ Facilitation of Inmates’ Self-directed Learning through Garrison’s Model

Formal education programs in prisons have had success in reducing recidivism, but the introduction of informal learning can have additional benefits and longer lasting effects. This paper addresses recidivism and its effects on inmates and society at large and how prison educators can facilitate self-directed learning in prisons through Garrison’s model.

Adults Learning Math Online: A Surprising Harmony

Adults returning to school face challenges including overcoming math anxiety. Many choose online courses as they balance life and work schedules. Online math courses therefore can be restructured to prevent math anxiety by catering to individual learning styles, providing tools that aid concept attainment, and using problem-based learning strategies.

The relationship between faculty perceptions and implementation of elements of transactional distance theory and online web-based course completion rates

The purpose of this study was to explore the relationship between faculty perceptions, selected demographics, implementation of elements of transactional distance theory and online web-based course completion rates. This theory posits that the high transactional distance of online courses makes it difficult for students to complete these courses successfully; too often this is associated with low completion rates. Faculty members play an indispensable role in course design, whether online or face-to-face. They also influence course delivery format from design through implementation and ultimately to how students will experience the course. This study used transactional distance theory as the conceptual framework to examine the relationship between teaching and learning strategies used by faculty members to help students complete online courses. Faculty members' sex, number of years teaching online at the college, and their online course completion rates were considered. A researcher-developed survey was used to collect data from 348 faculty members who teach online at two prominent colleges in the southeastern part of United States. An exploratory factor analysis resulted in six factors related to transactional distance theory. The factors accounted for slightly over 65% of the variance of transactional distance scores as measured by the survey instrument. Results provided support for Moore's (1993) theory of transactional distance. Female faculty members scored higher in all the factors of transactional distance theory when compared to men. Faculty number of years teaching online at the college level correlated significantly with all the elements of transactional distance theory. Regression analysis was used to determine that two of the factors, instructor interface and instructor-learner interaction, accounted for 12% of the variance in student online course completion rates. In conclusion, of the six factors found, the two with the highest percentage scores were instructor interface and instructor-learner interaction. This finding, while in alignment with the literature concerning the dialogue element of transactional distance theory, brings a special interest to the importance of instructor interface as a factor. Surprisingly, based on the reviewed literature on transactional distance theory, faculty perceptions concerning learner-learner interaction was not an important factor and there was no learner-content interaction factor.

Two -way direction of influence in mother-infant interaction as denoted by concurrent reciprocal learning processes

This series of 5 single-subject studies used the operant conditioning paradigm to investigate, within the two-way influence process, how (a) contingent infant attention can reinforce maternal verbal behaviors during a period of mother-infant interaction and under subsequent experimental manipulation. Differential reinforcement was used to determine if it is possible that an infant attending to the mother (denoted by head-turns towards the image of the mother plus eye contact) increases (reinforces) the mother's verbal response (to a cue from the infant) upon which the infant behavior is contingent. There was also (b) an evaluation during the contrived parent-infant interaction for concurrent operant learning of infant vocal behavior via contingent verbal responding (reinforcement) implemented by the mother. Further, it was noted (c) whether or not the mother reported being aware that her responses were influenced by the infant's behavior. Findings showed: the operant conditioning of the maternal verbal behaviors were reinforced by contingent infant attention; and the operant conditioning of infant vocalizations was reinforced by contingent maternal verbal behaviors. No parent reported (1) being aware of the increase in their verbal response reinforced during operant conditioning of parental behavior nor a decrease in those responses during the DRA reversal phase, or (2) noticing a contingency between infant's and mother's response. By binomial 1-tail tests, the verbal-behavior patterns of the 5 mothers were conditioned by infant reinforcement (p < 0.02) and, concurrently, the vocal-response patterns of the 5 infants were conditioned by maternal reinforcement (p < 0.02). A program of systematic empirical research on the determinants of concurrent conditioning within mother-child interaction may provide a way to evaluate the differential effectiveness of interventions aimed at improving parent-child interactions. The work conducted in the present study is one step in this direction. ^