The effects of word prediction and text-to-speech technologies on the narrative writing skills of students with specific learning disabilities

This study investigated the effects of word prediction and text-to-speech on the narrative composition writing skills of 6, fifth-grade Hispanic boys with specific learning disabilities (SLD). A multiple baseline design across subjects was used to explore the efficacy of word prediction and text-to-speech alone and in combination on four dependent variables: writing fluency (words per minute), syntax (T-units), spelling accuracy, and overall organization (holistic scoring rubric). Data were collected and analyzed during baseline, assistive technology interventions, and at 2-, 4-, and 6-week maintenance probes. ^ Participants were equally divided into Cohorts A and B, and two separate but related studies were conducted. Throughout all phases of the study, participants wrote narrative compositions for 15-minute sessions. During baseline, participants used word processing only. During the assistive technology intervention condition, Cohort A participants used word prediction followed by word prediction with text-to-speech. Concurrently, Cohort B participants used text-to-speech followed by text-to-speech with word prediction. ^ The results of this study indicate that word prediction alone or in combination with text-to-speech has a positive effect on the narrative writing compositions of students with SLD. Overall, participants in Cohorts A and B wrote more words, more T-units, and spelled more words correctly. A sign test indicated that these perceived effects were not likely due to chance. Additionally, the quality of writing improved as measured by holistic rubric scores. When participants in Cohort B used text-to-speech alone, with the exception of spelling accuracy, inconsequential results were observed on all dependent variables. ^ This study demonstrated that word prediction alone or in combination assists students with SLD to write longer, improved-quality, narrative compositions. These results suggest that word prediction or word prediction with text-to-speech be considered as a writing support to facilitate the production of a first draft of a narrative composition. However, caution should be given to the use of text-to-speech alone as its effectiveness has not been established. Recommendations for future research include investigating the use of these technologies in other phases of the writing process, with other student populations, and with other writing styles. Further, these technologies should be investigated while integrated into classroom composition instruction. ^

The Impact of Quality Teachers on Student Achievement

Various research studies reveal that factors, such as teachers’ cognitive ability, subject matter knowledge, knowledge of teaching and learning, licensure, and teaching behaviors in the classroom, are related to teacher quality and increased student achievement. Through a literature review these five major themes emerged that support the research that quality teachers do matter.

Learning from Exemplary Service Providers

Twelve exemplary service providers from the most highly-acclaimed resorts discussed and demonstrated how they deliver award-winning service. Three emergent themes offer insights to improve service quality: emotional generosity, exemplary communication, and effective interactions of culture, tradition and control. These themes support current literature on human resource development and service quality.

Hazard mitigation element quality in coastal comprehensive plans in a state with strong requirements for hazard mitigation plan elements

This dissertation examines the quality of hazard mitigation elements in a coastal, hazard prone state. I answer two questions. First, in a state with a strong mandate for hazard mitigation elements in comprehensive plans, does plan quality differ among county governments? Second, if such variation exists, what drives this variation? My research focuses primarily on Florida's 35 coastal counties, which are all at risk for hurricane and flood hazards, and all fall under Florida's mandate to have a comprehensive plan that includes a hazard mitigation element. Research methods included document review to rate the hazard mitigation elements of all 35 coastal county plans and subsequent analysis against demographic and hazard history factors. Following this, I conducted an electronic, nationwide survey of planning professionals and academics, informed by interviews of planning leaders in Florida counties. I found that hazard mitigation element quality varied widely among the 35 Florida coastal counties, but were close to a normal distribution. No plans were of exceptionally high quality. Overall, historical hazard effects did not correlate with hazard mitigation element quality, but some demographic variables that are associated with urban populations did. The variance in hazard mitigation element quality indicates that while state law may mandate, and even prescribe, hazard mitigation in local comprehensive plans, not all plans will result in equal, or even adequate, protection for people. Furthermore, the mixed correlations with demographic variables representing social and disaster vulnerability shows that, at least at the county level, vulnerability to hazards does not have a strong effect on hazard mitigation element quality. From a theory perspective, my research is significant because it compares assumptions about vulnerability based on hazard history and demographics to plan quality. The only vulnerability-related variables that appeared to correlate, and at that mildly so, with hazard mitigation element quality, were those typically representing more urban areas. In terms of the theory of Neo-Institutionalism and theories related to learning organizations, my research shows that planning departments appear to have set norms and rules of operating that preclude both significant public involvement and learning from prior hazard events.

Quality of student involvement and college contribution toward development of traditional and nontraditional undergraduate students

Nontraditional students differ from traditional students on characteristics such as age, employment status, marital status, and parental status. The quality of a student's experience is important as it relates to his or her transformation and is a reflection of the quality of the college. Using theory of involvement as a framework, the purpose of this study was to test if there were differences between traditional and nontraditional undergraduate students in their ratings of quality of college involvement (academic, co-curricular, student interactions, and faculty interactions) and perceptions of college contribution toward development (intellectual, personal, social, and career). A two part survey was distributed to a random cluster sample of sophomore and higher level undergraduate classes equaling 400 undergraduate students. Results of a 2 X 4 repeated measures ANOVA indicated that traditional students rated quality for co-curricular involvement and student involvement significantly higher than nontraditional students. Both traditional and nontraditional students had similar ratings of college contribution toward development. There were different patterns of correlations between involvement and development. Traditional students' ratings of academic and student involvement were more highly correlated with development than were the ratings of nontraditional students. However, nontraditional students' ratings of academic and faculty involvement were more highly correlated with development. When testing for differences in correlations between quality of involvement and college contribution toward development, the largest observed differences were quality of student involvement and college contribution toward personal and social development. Although not significantly different, traditional students had stronger correlations between those factors than did the nontraditional students. This research demonstrates the importance of using social role when defining student type. It contributes to involvement theory by explaining how traditional and nontraditional students differ in their ratings of quality of involvement. Further, it identifies different patterns of correlations between ratings of quality of involvement and college contribution toward development for the two types of students. While traditional students may need a more rounded college experience that includes more social and co-curricular experiences, nontraditional students use the classroom as their stage for learning.

Inclusive pedagogy : from learning to action. Supporting each individual in the context of 'everybody'

Peer reviewed

Inclusive pedagogy : from learning to action. Supporting each individual in the context of 'everybody'

Peer reviewed

The state of the nations:current and future developments in technology enhanced learning

Right across Europe technology is playing a vital part in enhancing learning for an increasingly diverse population of learners. Learning is increasingly flexible, social and mobile and supported by high quality multi-media resources. Institutional VLEs are seeing a shift towards open source products and these core systems are supplemented by a range of social and collaborative learning tools based on web 2.0 technologies. Learners undertaking field studies and those in the workplace are coming to expect that these off-campus experiences will also be technology-rich whether supported by institutional or user-owned devices. As well as keeping European businesses competitive, learning is seen as a means of increasing social mobility and supporting an agenda of social justice. For a number of years the EUNIS E-Learning Task Force (ELTF) has conducted snapshot surveys of e-learning across member institutions, collected case studies of good practice in e-learning see (Hayes, et al., 2009) in references, supported a group looking at the future of e-learning, and showcased the best of innovation in its e-learning Award. Now for the first time the ELTF membership has come together to undertake an analysis of developments in the member states and to assess what this might mean for the future. The group applied the techniques of World Café conversation and Scenario Thinking to develop its thoughts. The analysis is unashamedly qualitative and draws on expertise from leading universities across eight of the EUNIS member states. What emerges is interesting in terms of the common trends in developments in all of the nations and similarities in hopes and concerns about the future development of learning.

An Investigation of the Features and Effectiveness of the Full-Day Early Learning Kindergarten Program in Ontario

This dissertation includes two studies. Study 1 is a qualitative case study that describes enactment of the main components of a high fidelity Full-Day Early Learning Kindergarten (FDELK) classroom, specifically play-based learning and teacher-ECE collaboration. Study 2 is a quantitative analysis that investigates how effectively the FDELK program promotes school readiness skills, namely self-regulation, literacy, and numeracy, in Kindergarteners. To describe the main components of an FDELK classroom in Study 1, a sub-sample of four high fidelity case study schools were selected from a larger case study sample. Interview data from these schools’ administrators, educators, parents, and community stakeholders were used to describe how the main components of the FDELK program enabled educators to meet the individual needs of students and promote students’ SR development. In Study 2, hierarchical regression analyses of 32,207 students’ self-regulation, literacy, and numeracy outcomes using 2012 Ontario Early Development Instrument (EDI) data revealed essentially no benefit for students participating in the FDELK program when compared to peers in Half-Day or Alternate-Day Kindergarten programs. Being older and female predicted more positive SR and literacy outcomes. Age and gender accounted for limited variance in numeracy outcomes. Results from both studies suggest that the Ontario Ministry of Education should take steps to improve the quality of the FDELK program by incorporating evidence-based guidelines and goals for play, reducing Kindergarten class sizes to more effectively scaffold learning, and revising curriculum expectations to include a greater focus on SR, literacy, and numeracy skills.

Unraveling networked learning initiatives: an analytic framework

Networked learning happens naturally within the social systems of which we are all part. However, in certain circumstances individuals may want to actively take initiative to initiate interaction with others they are not yet regularly in exchange with. This may be the case when external influences and societal changes require innovation of existing practices. This paper proposes a framework with relevant dimensions providing insight into precipitated characteristics of designed as well as ‘fostered or grown’ networked learning initiatives. Networked learning initiatives are characterized as “goal-directed, interest-, or needs based activities of a group of (at least three) individuals that initiate interaction across the boundaries of their regular social systems”. The proposed framework is based on two existing research traditions, namely 'networked learning' and 'learning networks', comparing, integrating and building upon knowledge from both perspectives. We uncover some interesting differences between definitions, but also similarities in the way they describe what ‘networked’ means and how learning is conceptualized. We think it is productive to combine both research perspectives, since they both study the process of learning in networks extensively, albeit from different points of view, and their combination can provide valuable insights in networked learning initiatives. We uncover important features of networked learning initiatives, characterize actors and connections of which they are comprised and conditions which facilitate and support them. The resulting framework could be used both for analytic purposes and (partly) as a design framework. In this framework it is acknowledged that not all successful networks have the same characteristics: there is no standard ‘constellation’ of people, roles, rules, tools and artefacts, although there are indications that some network structures work better than others. Interactions of individuals can only be designed and fostered till a certain degree: the type of network and its ‘growth’ (e.g. in terms of the quantity of people involved, or the quality and relevance of co-created concepts, ideas, artefacts and solutions to its ‘inhabitants’) is in the hand of the people involved. Therefore, the framework consists of dimensions on a sliding scale. It introduces a structured and analytic way to look at the precipitation of networked learning initiatives: learning networks. Successive research on the application of this framework and feedback from the networked learning community is needed to further validate it’s usability and value to both research as well as practice.

Unraveling networked learning initiatives: an analytic framework

Networked learning happens naturally within the social systems of which we are all part. However, in certain circumstances individuals may want to actively take initiative to initiate interaction with others they are not yet regularly in exchange with. This may be the case when external influences and societal changes require innovation of existing practices. This paper proposes a framework with relevant dimensions providing insight into precipitated characteristics of designed as well as ‘fostered or grown’ networked learning initiatives. Networked learning initiatives are characterized as “goal-directed, interest-, or needs based activities of a group of (at least three) individuals that initiate interaction across the boundaries of their regular social systems”. The proposed framework is based on two existing research traditions, namely 'networked learning' and 'learning networks', comparing, integrating and building upon knowledge from both perspectives. We uncover some interesting differences between definitions, but also similarities in the way they describe what ‘networked’ means and how learning is conceptualized. We think it is productive to combine both research perspectives, since they both study the process of learning in networks extensively, albeit from different points of view, and their combination can provide valuable insights in networked learning initiatives. We uncover important features of networked learning initiatives, characterize actors and connections of which they are comprised and conditions which facilitate and support them. The resulting framework could be used both for analytic purposes and (partly) as a design framework. In this framework it is acknowledged that not all successful networks have the same characteristics: there is no standard ‘constellation’ of people, roles, rules, tools and artefacts, although there are indications that some network structures work better than others. Interactions of individuals can only be designed and fostered till a certain degree: the type of network and its ‘growth’ (e.g. in terms of the quantity of people involved, or the quality and relevance of co-created concepts, ideas, artefacts and solutions to its ‘inhabitants’) is in the hand of the people involved. Therefore, the framework consists of dimensions on a sliding scale. It introduces a structured and analytic way to look at the precipitation of networked learning initiatives: learning networks. Successive research on the application of this framework and feedback from the networked learning community is needed to further validate it’s usability and value to both research as well as practice.

Evaluation Framework EFI for Measuring the Impact of Learning, Education and Training

This article introduces the Evaluation Framework EFI for the Impact Measurement of learning, education and training: The Evaluation Framework for Impact Measurement was developed for specifying the evaluation phase and its objectives and tasks within the IDEAL Reference Model for the introduction and optimization of quality development within learning, education and training. First, a description of the Evaluation Framework for Impact Measurement will be provided, followed by a brief overview of the IDEAL Reference Model. Finally, an example for the implementation of the Evaluation Framework for Impact Measurement within the ARISTOTELE project is presented.

Extracting Patterns from Educational Traces via Clustering and Associated Quality Metrics

Clustering algorithms, pattern mining techniques and associated quality metrics emerged as reliable methods for modeling learners’ performance, comprehension and interaction in given educational scenarios. The specificity of available data such as missing values, extreme values or outliers, creates a challenge to extract significant user models from an educational perspective. In this paper we introduce a pattern detection mechanism with-in our data analytics tool based on k-means clustering and on SSE, silhouette, Dunn index and Xi-Beni index quality metrics. Experiments performed on a dataset obtained from our online e-learning platform show that the extracted interaction patterns were representative in classifying learners. Furthermore, the performed monitoring activities created a strong basis for generating automatic feedback to learners in terms of their course participation, while relying on their previous performance. In addition, our analysis introduces automatic triggers that highlight learners who will potentially fail the course, enabling tutors to take timely actions.

Efficient Learning of Bayesian Networks with Bounded Tree-width

Learning Bayesian networks with bounded tree-width has attracted much attention recently, because low tree-width allows exact inference to be performed efficiently. Some existing methods \cite{korhonen2exact, nie2014advances} tackle the problem by using $k$-trees to learn the optimal Bayesian network with tree-width up to $k$. Finding the best $k$-tree, however, is computationally intractable. In this paper, we propose a sampling method to efficiently find representative $k$-trees by introducing an informative score function to characterize the quality of a $k$-tree. To further improve the quality of the $k$-trees, we propose a probabilistic hill climbing approach that locally refines the sampled $k$-trees. The proposed algorithm can efficiently learn a quality Bayesian network with tree-width at most $k$. Experimental results demonstrate that our approach is more computationally efficient than the exact methods with comparable accuracy, and outperforms most existing approximate methods.

How using Technology Enhanced Learning could help modernise traditional large group teaching or Lecturing.

The efficiency of lecturing or large group teaching has been called into question for many years. An abundance of literature details the components of effective teaching which are not provided in the traditional lecture setting, with many alternative methods of teaching recommended. However, with continued constraints on resources large group teaching is here to stay and student’s expect and are familiar with this method.

Technology Enhanced Learning may be the way forward, to prevent educators from “throwing out the baby with the bath water”. TEL could help Educator’s especially in the area of life sciences which is often taught by lectures to engage and involve students in their learning, provide feedback and incorporate the “quality” of small group teaching, case studies and Enquiry Based Learning into the large group setting thus promoting effective and deep learning.