ethanporcaro/eric-fulltext-meta huggingface dataset:
Determining the Effectiveness of a Massive Open Online Course in Data Science for Health
Author: Alturkistani, Abrar
Date: 2018-07-00
Type: Speeches/Meeting Papers
Subjects: Large Group Instruction,Online Courses,Educational Technology,Technology Uses in Education,Foreign Countries,Higher Education,Professional Continuing Education,Data Collection,Data Analysis,Program Effectiveness,Student Attitudes,Student Behavior,College Students,Allied Health Personnel

Massive Open Online Courses (MOOCs) are widely used to deliver specialized education and training in different fields. Determining the effectiveness of these courses is an integral part of delivering comprehensive, high-quality learning. This study is an evaluation of a MOOC offered by Imperial College London in collaboration with Health iQ called, Data Science Essentials: Real World Evidence. The paper analyzes the reported learning outcomes, attitudes and behaviours of students after completing the MOOC. The study used mixed-methods, drawing from a Kirkpatrick evaluation-using data from semi-structured interviews transcribed and analyzed through Braun and Clark's method for thematic coding. 191 learners joined the MOOC. Two participants who completed at least 75% of the course were interviewed for the course evaluation. The findings of the analysis suggest that the course attracted target learners and learners found its application and engagement methods effective. Learners found the training provided by the MOOC to be helpful and with the potential to be applied in their work environment in the future and identified some work-related barriers that prevent knowledge application. Networking during and post-MOOC was identified as an area that needs improvement and development in the future. Findings derived from this evaluation support the fact that generally, MOOCs can improve learning and knowledge attainment in practical skills-based knowledge. One implication of this study is to inform factors that engage learners in the design and implementation of MOOC. The findings have shown that factors that affect the learners' engagement are the availability of lecture videos, self-assessment tools and high networking and communication between learners. In terms of knowledge application, support and availability of the right resources are essential because learners are not able to apply learning in their workplace if the workplace lacked the right resources and support. Developers of MOOCs for continuing professional development should take into consideration work-related barriers when designing their MOOCs. [For the complete proceedings, see ED590269.]
Influence of Virtual Simulator on the Change of Views on Behaviour in Traffic Case Study
Author: Vasiljevic, Jovica
Date: 2018-07-00
Type: Speeches/Meeting Papers
Subjects: Computer Simulation,Educational Technology,Technology Uses in Education,Video Technology,Drills (Practice),Traffic Safety,Risk Management,Attitude Change,Restraints (Vehicle Safety),Young Adults,Student Attitudes

Many studies have been conducted focusing on the use of virtual simulators in training in various scenarios, ranging from life and threats to situations in recreational activities. This study follows the direction of the discussion on the use of some virtual simulators that can be successfully exploited in the activities of training of drivers with the task of perception of reality and understanding of risk and threats with the goal to enable the change of attitude regarding the behaviour in traffic. In that sense, the virtual reality simulator can be used for the change of attitude on a concrete case of non-usage of safety belt and improper speed in driving. This application was created using 5D video materials in order to efficiently use the training simulators. Therefore in our project the individuals are put in a virtual world in which they can practice and improve their driving skillset with the acceptance of new and real attitudes on the risk and threats that those imply. Used in the work was an questionnaire method, with three levels of experimental simulation being applied, lasting 10 minutes each. After the conducted simulation, the questionnaire was repeated. After that, a comparative analysis has been carried out before and after, with the goal to establish the influence of virtual simulators on the change of attitudes on behaviour in traffic. [For the complete proceedings, see ED590269.]
Listening and Learning? Privileging the Student Voice in E-Learning Discourses of Withdrawal: A Qualitative Analysis
Author: Glover, Hayley
Date: 2018-07-00
Type: Speeches/Meeting Papers
Subjects: Foreign Countries,Electronic Learning,Educational Technology,Student Participation,Withdrawal (Education),Student Attitudes,College Freshmen,Academic Persistence,School Holding Power,Distance Education,Stress Variables

Along with the burgeoning expansion of online platforms for student learning in higher education have come complementary analytics tools to rate student engagement, learning, success and progression. As, in the UK, institutions embrace these tools as part of government-led attainment targets and awards (e.g. Teaching Excellence Framework), the 'quantitative rush' to measure and evaluate retention from the institutional perspective risks muffling the individual student voices that can be heard through qualitative approaches to their learning journeys. This is particularly relevant for introductory level students as they seek to navigate the unknown of their first year of higher education, and it is recognised that introductory students require the greatest levels of pastoral care to succeed. Enhancements to University CRM systems have created an opportunity for the preservation of narratives of withdrawal made by students as they engage with the university to defer, reduce or cancel their studies. This is particularly important in the distance learning sector, both because these dialogues have been less visible to the institution than through traditional campus support provision, and because part time students tend to have more complex lives. These narratives have permitted a criteria of authenticity and criticality to institutionally led discourses around withdrawal. They demonstrate the importance of considering the student experience, motivation and participation with the university, rather than the privileging of institutional frames of reference. Similarities and differences in perceptions around the meanings and values of their higher education experiences, and reasons for withdrawing have been developed thematically in this paper to better understand student motivation, and provide a useful triangulation to output from quantitative studies on retention. Key word findings from these introductory level students enrolled on Business and Law modules within a UK business school include the following: Dialogue on personal concerns, the time commitment to study successfully, and how stressors, both inside and outside of the study environment impact the student's ability to commit, or wish to commit to their courses. [For the complete proceedings, see ED590269.]
Semantic Web and Question Generation: An Overview of the State of the Art
Author: Papasalouros, Andreas
Date: 2018-07-00
Type: Speeches/Meeting Papers
Subjects: Computer Assisted Testing,Web 2.0 Technologies,Test Format,Multiple Choice Tests,Semantics,Web Based Instruction,Natural Language Processing,Test Items,Automation,Multimedia Materials

Automating the production of questions for assessment and self-assessment has become recently an active field of study. The use of Semantic Web technologies has certain advantages over other methods for question generation and thus is one of the most important lines of research for this problem. The aim of this paper is to provide an overview of the existing research of the subject of applying Semantic Web technologies for automatic question generation. The review provides a classification based on technological as well as on pedagogical aspects of the works presented. [For the complete proceedings, see ED590269.]
Assessing the Impact of Students&apos; Activities in E-Classes on Learning Outcomes: A Data Mining Approach
Author: Umek, Lan
Date: 2018-07-00
Type: Speeches/Meeting Papers
Subjects: Foreign Countries,College Freshmen,Electronic Learning,Learning Activities,Blended Learning,Grades (Scholastic),Tests,Prediction,Predictor Variables,Academic Achievement,Outcomes of Education,Integrated Learning Systems,Independent Study

In the paper, we present the results of a case study conducted at Faculty of Administration, University of Ljubljana among 1st year undergraduate students. We investigated the correlations between students' activities in the e-classroom and grades at the final exam. The sample included 92 participants who took part at the final exam in the course Basic Statistics. In the e-classroom, students learn new content for individual self-study is prepared and their knowledge is checked with quizzes. In the empirical study, we used data mining software Orange for two tasks of predictive modelling: The research question was: based on the student's performance on quizzes is it possible to predict if (1) a student will pass an exam, and (2) a student's grade at the exam will be good. The empirical results indicate very strong connection between students' performance on quizzes and their grade at final exam in the course. Moreover, the results pointed out which quizzes, in other words topics, are most important for passing an exam or obtaining better grade. [For the complete proceedings, see ED590269.]
Online vs. Classroom Students in an Undergraduate University Degree
Author: Scarabottolo, Nello
Date: 2018-07-00
Type: Speeches/Meeting Papers
Subjects: Online Courses,Educational Technology,Technology Uses in Education,Undergraduate Students,Conventional Instruction,Computer Security,Foreign Countries,Program Effectiveness

This paper compares the students enrolled to a three-year undergraduate, bachelor degree on Security of Computer Systems and Networks -- offered in traditional, classroom fashion as well as online at the University of Milan (Italy) -- in terms of results in exams of the various courses as well as in the final dissertation for obtaining the degree. This gives useful information about the effectiveness of e-learning vs. traditional learning in presence, and the possibility of using e-learning as a vehicle for extending the enrollment to already existing traditional university degrees. [For the complete proceedings, see ED590269.]
Implementation of Computer Games Elements into the Virtual Educational Environment
Author: Vereitina, Iryna
Date: 2018-07-00
Type: Speeches/Meeting Papers
Subjects: College Students,Educational Games,Educational Technology,Technology Uses in Education,Computer Games,Teaching Methods,Second Language Instruction

The present paper focuses on the approach, which corresponds to the virtual learning in the artificial environment, and should be considered as situational and action-based, because the features of its application are determined each time by the specific conditions of training and the virtual educational situation that exists only in this area, at this time, between specific subjects and objects of education. The objective of the study is to determine possible ways of university learning process optimization. This paper is a preliminary attempt to show that integration of educational game elements to virtual learning environments will help students to reach educational goals in the process of study and familiarize with the norms and values of society. [For the complete proceedings, see ED590269.]
Approaches to State Workforce Development Systems. Education Trends
Author: Anderson, Lexi
Date: 2018-10-00
Type: Reports - Descriptive
Subjects: Labor Force Development,Postsecondary Education,Education Work Relationship,State Government,Information Utilization,Alignment (Education),Labor Needs,Graduates,Federal Legislation,Stakeholders,Partnerships in Education,Leadership,Federal Aid

As states continue movement toward ambitious attainment goals, many are calling increased attention to post-graduation outcomes--including workforce development and graduate impact on a state's economy. Along with state initiatives and task forces, an increase in workforce development legislation highlights a movement toward codifying progress. Legislation in 2018 pertained to clear career pathways, financial incentives and strong partnerships or working groups. Coupled with the recent passage of the Strengthening Career and Technical Education for the 21st Century Act at the federal level, this recent legislation illustrates a clear focus on workforce development and forward progress. To take a deeper look, Education Commission of the States visited four states to gain an on-the-ground perspective of these developments in postsecondary and workforce alignment. In addition to highlighting trending workforce development legislation and key findings from those state visits, this brief provides questions states might consider in their progress to align postsecondary credential outcomes with workforce needs.
Section 619 Preschool Program: Federal Appropriations and National Child Count 1977-2017. Updated April 17, 2018
Author: Lazara, A., Comp.
Date: 2018-04-17
Type: Numerical/Quantitative Data
Subjects: Disabilities,Educational Legislation,Federal Legislation,Equal Education,Young Children,Special Education,Federal Aid,Resource Allocation,Expenditures,Tables (Data)

Part B, Section 619 of the Individuals with Disabilities Education Act (IDEA) is intended to help ensure that all eligible preschool children with disabilities, aged 3-5 years, receive special education and related services. This growth/comparison chart shows the federal appropriations allocated for Part B Section 619, the number of children served, and the federal dollars allocated per child each year from federal fiscal year (FFY) 1977 through FFY 2017.
Part C Infant and Toddler Program: Federal Appropriations and National Child Count 1987-2017. Updated April 17, 2018
Author: Lazara, A., Comp.
Date: 2018-04-17
Type: Numerical/Quantitative Data
Subjects: Educational Legislation,Disabilities,Federal Legislation,Equal Education,Infants,Toddlers,Early Intervention,Federal Aid,Resource Allocation,Expenditures,Tables (Data)

Part C of the Individuals with Disabilities Education Act (IDEA) is intended to help ensure that all eligible infants and toddlers with disabilities (aged birth-2) and their families receive early intervention services. This chart shows the federal appropriations allocated for the Part C program, the number of children served, and the federal dollars allocated per child each year from federal fiscal year (FFY) 1987 through FFY 2017.
Weakly Informative Prior for Point Estimation of Covariance Matrices in Hierarchical Models
Author: Chung, Yeojin
Date: 2015-00-00
Type: Journal Articles
Subjects: Regression (Statistics),Hierarchical Linear Modeling,Bayesian Statistics,Statistical Inference,Computation,Matrices,Statistical Analysis,Maximum Likelihood Statistics,Educational Research

When fitting hierarchical regression models, maximum likelihood (ML) estimation has computational (and, for some users, philosophical) advantages compared to full Bayesian inference, but when the number of groups is small, estimates of the covariance matrix [sigma] of group-level varying coefficients are often degenerate. One can do better, even from a purely point estimation perspective, by using a prior distribution or penalty function. In this article, we use Bayes modal estimation to obtain positive definite covariance matrix estimates. We recommend a class of Wishart (not inverse-Wishart) priors for [sigma] with a default choice of hyperparameters, that is, the degrees of freedom are set equal to the number of varying coefficients plus 2, and the scale matrix is the identity matrix multiplied by a value that is large relative to the scale of the problem. This prior is equivalent to independent gamma priors for the eigenvalues of [sigma] with shape parameter 1.5 and rate parameter close to 0. It is also equivalent to independent gamma priors for the variances with the same hyperparameters multiplied by a function of the correlation coefficients. With this default prior, the posterior mode for [sigma] is always strictly positive definite. Furthermore, the resulting uncertainty for the fixed coefficients is less underestimated than under classical ML or restricted maximum likelihood estimation. We also suggest an extension of our method that can be used when stronger prior information is available for some of the variances or correlations. [This paper was published in &quot;Journal of Educational and Behavioral Statistics&quot; (EJ1057844).]
Stan: A Probabilistic Programming Language
Author: Carpenter, Bob
Date: 2017-01-00
Type: Journal Articles
Subjects: Programming Languages,Probability,Bayesian Statistics,Monte Carlo Methods,Statistical Inference,Maximum Likelihood Statistics,Computation,Statistical Distributions,Computer Software

Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood estimates are calculated using optimization methods such as the limited memory Broyden-Fletcher-Goldfarb-Shanno algorithm. Stan is also a platform for computing log densities and their gradients and Hessians, which can be used in alternative algorithms such as variational Bayes, expectation propagation, and marginal inference using approximate integration. To this end, Stan is set up so that the densities, gradients, and Hessians, along with intermediate quantities of the algorithm such as acceptance probabilities, are easily accessible. Stan can be called from the command line using the &quot;cmdstan&quot; package, through R using the &quot;rstan&quot; package, and through Python using the &quot;pystan&quot; package. All three interfaces support sampling and optimization-based inference with diagnostics and posterior analysis. &quot;rstan&quot; and &quot;pystan&quot; also provide access to log probabilities, gradients, Hessians, parameter transforms, and specialized plotting.
Massive Open Online Courses (MOOCs): Why Do We Need Them?
Author: Inchiparamban, Sandychris
Date: 2016-00-00
Type: Reports - Evaluative
Subjects: Large Group Instruction,Online Courses,Educational Technology,Technology Uses in Education,Distance Education

Massive Open Online Courses, or MOOCs, are online courses that cater to a huge population. MOOCs have been around for quite some time; however, they have begun to gain importance only in recent years. With technology-infused classroom instructions on the rise, techno-savvy students with little patience for hour-long (or even longer) lectures and the necessity to earn has led to the popularity of online courses among the student population. The obvious benefits of taking up online courses include, among others, self-paced learning, learning while earning, and learning from absolutely anywhere. An upcoming form of online learning is the massive open online courses (MOOCs). This paper discusses the concept of MOOCs, their history, and their need in the present scenario. This paper also focuses on the benefits and the possible challenges that MOOCs face.
A Flexible, Interpretable Framework for Assessing Sensitivity to Unmeasured Confounding
Author: Dorie, Vincent
Date: 2016-00-00
Type: Journal Articles
Subjects: Bayesian Statistics,Mathematical Models,Causal Models,Statistical Bias,Nonparametric Statistics,Research Problems,Error of Measurement,Statistical Inference,Monte Carlo Methods,Markov Processes,Medicine

When estimating causal effects, unmeasured confounding and model misspecification are both potential sources of bias. We propose a method to simultaneously address both issues in the form of a semi-parametric sensitivity analysis. In particular, our approach incorporates Bayesian Additive Regression Trees into a two-parameter sensitivity analysis strategy that assesses sensitivity of posterior distributions of treatment effects to choices of sensitivity parameters. This results in an easily interpretable framework for testing for the impact of an unmeasured confounder that also limits the number of modeling assumptions. We evaluate our approach in a large-scale simulation setting and with high blood pressure data taken from the Third National Health and Nutrition Examination Survey. The model is implemented as open-source software, integrated into the treatSens package for the R statistical programming language.
Introducing the Content Acquisition Podcast Professional Development Process: Supporting Vocabulary Instruction for Inclusive Middle School Science Teachers
Author: Kennedy, Michael J.
Date: 2018-00-00
Type: Journal Articles
Subjects: Middle School Teachers,Science Teachers,Vocabulary,Faculty Development,Inclusion,Multimedia Instruction,Telecommunications,Intervention,Instructional Effectiveness,Pilot Projects,Teacher Attitudes,Teacher Improvement,Disabilities,Middle School Students,Achievement Gains,Observation

Improving inclusive middle school science teachers' vocabulary instruction is a critical step toward helping those professionals support the learning needs of all students. In this Institute of Education Sciences (IES)-funded project, inclusive science teachers received professional development using elements of a multimedia-based approach called the Content Acquisition Podcast Professional Development (CAP-PD) intervention process. In this article, the authors discuss the three iterative pilot studies conducted as a part of this project and how each contributed to its development. Drawing on a theoretical framework that considers the characteristics of effective professional development, CAP-PD has three elements: (a) use of instructional videos that highlight the steps of practices and embed modeling videos to demonstrate practice, (b) preproduced instructional materials that support the implementation of evidence-based practices, and (c) feedback for teachers using data outputs from a classroom observation tool developed as a part of this project. Across studies, teachers who engaged in the CAP-PD process made important gains in terms of how much time they spent delivering evidence-based vocabulary instruction and the number of different practices implemented with fidelity. Future research should address questions of the lasting impact of this process on student learning and how to adapt the CAP-PD to help teachers do more than improve their vocabulary instruction. [This article was published in &quot;Teacher Education and Special Education&quot; (EJ1176453).]