ethanporcaro/eric-fulltext-meta huggingface dataset:
Valuing Diversity: Guidance for Labour Market Integration of Migrants. Working Paper No 24
Author: Moreno da Fonseca, Pedro
Date: 2014-09-00
Type: Reports - Research
Subjects: Immigrants,Foreign Countries,Retirement,Labor Force,Employers,Unions,Marketing,Communication Strategies,Skilled Workers,Definitions,Personal Autonomy,Employment Qualifications,Career Guidance,Socioeconomic Influences

Europe faces an increase in the age of its natural population and a reduction in available labour force. The retirement of a highly qualified workforce, alongside a rise in demand for medium- and high-skilled workers, will likely result in labour shortages in several sectors and countries. The movement of qualified, third-country immigrants into the European Union is needed for economic recovery. Guidance services are to the fore in the reception of third-country immigrants; they provide fundamental career information and career management skills (CMS), empowering individuals to acquire autonomy in managing their career in a new country. This Cedefop study analyses guidance strategies to support labour market integration of immigrants. Its findings suggest the need for greater engagement by employers, trade unions and immigrant communities, as well assurance of appropriate practitioner training and improved marketing and communication strategies. The following are appended: (1) List of definitions; and (2) List of abbreviations. A bibliography is also included.
Policy Handbook: Access to and Participation in Continuous Vocational Education and Training (CVET) in Europe. Working Paper No 25
Author: Dehmel, Alexandra
Date: 2014-10-00
Type: Reports - Descriptive
Subjects: Educational Policy,Guides,Disadvantaged,Vocational Education,Competition,Access to Education,Educational Quality,Foreign Countries,Educational Benefits,Workplace Learning,Human Resources,Best Practices

Continuous vocational education and training (CVET) for all is essential to respond to increased global competition and changing technological and socioeconomic requirements. What can be done to make use of the full potential that CVET has to offer individuals, enterprises, society and the economy? How can participation in CVET be increased and access to it extended, especially for disadvantaged groups that traditionally participate the least? How can high-quality provision be ensured? This CVET policy handbook addresses policy-makers, enterprises, social partners and other stakeholders. It aims at strengthening CVET by providing policy guidance illustrated with concrete examples of effective practices. It highlights the importance of CVET for smart and inclusive growth and shows the benefits of investing in it. It gives an overview of the current position in Europe and describes success factors and good practices for widening access and participation and for promoting high-quality CVET provision for all. The report also includes a List of abbreviations.
Reinventing Citizenship as Public Work: Citizen-Centered Democracy and the Empowerment Gap
Author: Boyte, Harry C.
Date: 2013-00-00
Type: Reports - Descriptive
Subjects: Civics,Citizenship Education,Democracy,Empowerment,Educational Change,Work Attitudes,Labor Force Development,Human Capital,Social Theories,Service Learning,Community Development,Change Agents

Calls for revitalization of civic education and civic learning are multiplying, but notions of work as a site of citizenship--for &quot;citizen teachers&quot; or &quot;citizen faculty members,&quot; for example--have largely disappeared. This paper begins with an overview of the dominant approaches to civic education and learning: &quot;civics&quot; (study of government) and &quot;communitarian&quot; (service and voluntarism) frameworks. Both have strengths. But neither explicitly addresses civic empowerment nor work as a site of citizenship. The result is that civic engagement and citizenship are not taken very seriously, public identities, such as the &quot;citizen as customer,&quot; which undermine robust, productive citizenship, continue to spread, and educators are under attack, with insufficient political resources to respond. This essay focuses on a third, emerging framework. In 2007, a group of engaged political and social theorists was convened by the journal of political theory, &quot;The Good Society&quot;. The group, which included Elinor Ostrom, Steve Elkin, Peter Levine, Jane Mansbridge, Rogers Smith, Karol Soltan, and the author, created The New Civic Politics, a framing statement for a new civic engagement approach based on civic agency and citizens as co-creators, and informed in part by theories and practices of public work developed by the Center for Democracy and Citizenship (CDC) and its partners. In this report, the author expands the argument that work and workplaces need to be brought in as sites of citizenship if revitalization of education as a civic vocation, civic learning, and a citizen-centered democracy is going to be seen.
The Decline of the English Department
Author: Schalin, Jay
Date: 2015-08-00
Type: Reports - Research
Subjects: English Departments,Educational Trends,Trend Analysis,Educational Change,Higher Education,Universities,Politics of Education,Degree Requirements,Enrollment Trends,Course Descriptions,Curriculum Development,English Curriculum,Role of Education,Employment Potential,Qualitative Research,Statistical Analysis

Throughout much of the 20th century, English departments were the crown jewels of the humanities. Exposure to great literature was often considered essential for students expected to assume lead roles in business, law, government, and society. Today, English departments have lost their position at the center of the American university. Enrollments have diminished or remained stagnant during a period of tremendous growth for universities in general. The modern English department has also lost its sense of purpose. Superficial and trendy topics have replaced great works from the Western literary canon. Traditional scholarship has given way to postmodern critiques, in which great literature is viewed as a source of oppression and social control instead of revealing truth and exploring universal ideals. This report discusses the decline of English departments and investigates the changes in the discipline over time, employing both empirical and qualitative methods. It also examines today's pressures on English departments--from student demand for vocational and pop-culture offerings to politicization of the faculty. The report documents changes in English degree requirements, course offerings, faculty research, and enrollment.
Roster of Astronomy Departments with Enrollment and Degree Data, 2014: Results from the 2014 Survey of Enrollments and Degrees. Focus On
Author: Nicholson, Starr
Date: 2015-09-00
Type: Reports - Evaluative
Subjects: Astronomy,Departments,Enrollment Rate,Graduation Rate,Annual Reports,School Statistics,College Students,Academic Degrees,Trend Analysis,Statistical Distributions

Undergraduate astronomy enrollments in the US continue to rise with junior and senior level enrollments exceeding the previous year's all-time high. The increasing undergraduate enrollments have produced 428 bachelor's in the 2013-14 academic year, also an all-time high. Undergraduate astronomy degree production will continue to rise given the increases seen in undergraduate enrollments. The first-year graduate student enrollments for fall 2014 were similar to the previous year with 187 students enrolled. The number of astronomy PhDs awarded has remained relatively unchanged in recent years, with 147 astronomy PhDs conferred in the class of 2014. This report contains detailed data from the annual Survey of Enrollments and Degrees. The survey was conducted in the fall of 2014 and includes all degree-granting astronomy departments in the United States. All but 5 of the 81 degree-granting astronomy departments contributed to the data supplied in this year's roster (94%). Thirty-eight are stand-alone astronomy departments and the remaining 43 are combined physics and astronomy departments. The totals above include data from the 76 responding departments as well as estimated data for the 5 non-responding departments.
Roster of Physics Departments with Enrollment and Degree Data, 2014: Results from the 2014 Survey of Enrollments and Degrees. Focus On
Author: Nicholson, Starr
Date: 2015-09-00
Type: Reports - Evaluative
Subjects: Physics,Departments,Annual Reports,Enrollment Rate,Graduation Rate,Academic Degrees,Trend Analysis,College Students,School Statistics,Statistical Distributions,National Surveys,College Freshmen,College Seniors,Undergraduate Students,Masters Degrees,Bachelors Degrees,Doctoral Degrees,Foreign Students

Physics bachelor's degree production has more than doubled since the recent low in 1999 and total enrollments in US undergraduate physics programs continue to increase. The all-time high of 7,526 bachelor's degrees in the class of 2014 represents the 15th consecutive year that the number of physics bachelor's conferred has increased. First-year graduate physics student enrollments have been relatively unchanged in recent years averaging around 3,200 students. The number of physics PhDs conferred continues the general decade long trend of increasing PhD production. The 1,803 physics PhDs conferred in the class of 2014 is a 3% increase from the previous year and represents a new all-time high for physics PhDs. This report contains detailed data from the annual Survey of Enrollments and Degrees. The survey was conducted in the fall of 2014 and covers all degree-granting physics departments in the United States. Of the 751 degree-granting physics departments, 679 (90%) contributed to the data supplied in this year's roster. The totals above include data from responding departments as well as estimated data for the 72 non-responding departments.
Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification
Author: Emond, Bruno
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Data Analysis,Classification,Learning Activities,Inquiry,Learning Processes,Student Behavior,Sequential Approach,Skills,Students

This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and social networks. As an example of our current research efforts, we applied temporal data mining analysis techniques to a PSLC DataShop data set [17, 18, 19, 20]. First, we show that process mining techniques allow for discovery of learning processes from student behaviours. Second, sequential pattern mining is used to classify students according to skill. Our results show that considering sequences of activities as opposed to single events improved classification by up to 230%. [For complete proceedings, see ED560503.]
Desirable Difficulty and Other Predictors of Effective Item Orderings
Author: Tang, Steven
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Intelligent Tutoring Systems,Difficulty Level,Bayesian Statistics,Models,Context Effect,Validity,Predictor Variables,Regression (Statistics),Statistical Analysis,Probability,Mathematics Instruction,Learning

Online adaptive tutoring systems are increasingly being used in classrooms as a way to provide guided learning for students. Such tutors have the potential to provide tailored feedback based on specific student needs and misunderstandings. Bayesian knowledge tracing (BKT) is used to model student knowledge when knowledge is assumed to be changing throughout a single assessment period. The basic BKT model assumes that the chance a student transitions from &quot;not knowing&quot; to &quot;knowing&quot; after each item is the same, with each item in the tutor considered a learning opportunity. It could be the case, however, that learning is actually context sensitive; context in our analysis is the order in which the items were administered. In this paper, we use BKT models to find such context sensitive transition probabilities in a mathematics tutoring system and offer a methodology to test the significance of our model based findings. We employ cross validation techniques to find models where including item ordering context improves predictive capability compared to the base BKT models. We then use regression testing to try to find features that may predict the effectiveness of an item ordering. [For complete proceedings, see ED560503.]
Variations in Learning Rate: Student Classification Based on Systematic Residual Error Patterns across Practice Opportunities
Author: Liu, Ran
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Models,Regression (Statistics),Learning,Classification,Error Patterns,Accuracy,Predictive Validity,Pretests Posttests,Statistical Analysis,Students,Geometry,Algebra,English,Grammar,Statistics,Bayesian Statistics

A growing body of research suggests that accounting for student specific variability in educational data can improve modeling accuracy and may have implications for individualizing instruction. The Additive Factors Model (AFM), a logistic regression model used to fit educational data and discover/refine skill models of learning, contains a parameter that individualizes for overall student ability but not for student learning rate. Here, we show that adding a per-student learning rate parameter to AFM overall does not improve predictive accuracy. In contrast, classifying students into three &quot;learning rate&quot; groups using residual error patterns, and adding a per-group learning rate parameter to AFM, substantially and consistently improves predictive accuracy across 8 datasets spanning the domains of Geometry, Algebra, English grammar, and Statistics. In a subset of datasets for which there are pre- and post-test data, we observe a systematic relationship between learning rate group and pre-topost-test gains. This suggests there is both predictive power and external validity in modeling these distinct learning rate groups. [For complete proceedings, see ED560503.]
Evaluating the Relevance of Educational Videos Using BKT and Big Data
Author: MacHardy, Zachary
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Educational Technology,Video Technology,Units of Study,Multimedia Materials,Instructional Material Evaluation,Bayesian Statistics,Relevance (Education),Online Courses,Electronic Learning,Statistical Data,School Statistics,Models,Evaluation Methods

Along with the advent of MOOCs and other online learning platforms such as Khan Academy, the role of online education has continued to grow in relation to that of traditional on-campus instruction. Rather than tackle the problem of evaluating large educational units such as entire online courses, this paper approaches a smaller problem: exploring a framework for evaluating more granular educational units, in this case, short educational videos. We have chosen to leverage an adaptation of traditional Bayesian Knowledge Tracing (BKT), intended to incorporate the usage of video content in addition to assessment activity. By exploring the change in predictive error when alternately including or omitting video activity, we suggest a metric for determining the relevance of videos to associated assessments. To validate our hypothesis and demonstrate the application of our proposed methods we use data obtained from both the popular Khan Academy website and two MOOCs offered by Stanford University in the summer of 2014. [For complete proceedings, see ED560503.]
Measuring Problem Solving Skills in Plants vs. Zombies 2
Author: Shute, Valerie J.
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Middle School Students,Problem Solving,Educational Games,Bayesian Statistics,Student Evaluation,Evaluation Methods,Validity,Models,Educational Indicators,Pilot Projects,Data Collection,Correlation,Measures (Individuals)

We are using stealth assessment, embedded in &quot;Plants vs. Zombies 2,&quot; to measure middle-school students' problem solving skills. This project started by developing a problem solving competency model based on a thorough review of the literature. Next, we identified relevant in-game indicators that would provide evidence about students' levels on the various problem-solving facets. Our problem solving model was implemented in the game via Bayesian networks. To validate the stealth assessment, we ran a small pilot study to collect data from students who played our game-based assessment and completed an external problem solving measure (&quot;MicroDYN&quot;). Preliminary results indicate that problem solving estimates derived from the game significantly correlate with the external measure, suggesting that our stealth assessment is valid. Our next steps include running a larger validation study (in progress) and developing tools to help educators interpret the results of the assessment. [For complete proceedings, see ED560503.]
Strategic Game Moves Mediate Implicit Science Learning
Author: Rowe, Elizabeth
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Educational Games,Science Instruction,Video Games,Coding,Comparative Analysis,Learning Strategies,Scientific Concepts,Path Analysis,Technology Uses in Education,Educational Technology,Pretests Posttests,Protocol Analysis,Hierarchical Linear Modeling,Scores,High School Students,Secondary School Science

Educational games have the potential to be innovative forms of learning assessment, by allowing us to not just study their knowledge but the process that takes students to that knowledge. This paper examines the mediating role of players' moves in digital games on changes in their pre-post classroom measures of implicit science learning. We applied automated detectors of strategic moves, built and validated from game log data combined with coded videos of gameplay of 69 students, to a new and larger sample of gameplay data. These data were collected as part of national implementation study of the physical science game, &quot;Impulse&quot;. This study compared 213 students in 21 classrooms that only played the game and 180 students in 18 classrooms in where the players' teacher used game examples to bridge the implicit science learning in the game with explicit science content covered in class. We analyzed how learning outcomes between conditions were associated with six strategic moves students made during gameplay. Three of the strategic moves observed are consistent with an implicit understanding of Newton's First Law, the other three strategic moves were not. Path analyses suggest the mediating role of strategic moves on students' implicit science learning is different between the two conditions. [For complete proceedings, see ED560503.]
Video-Based Affect Detection in Noninteractive Learning Environments
Author: Chen, Yuxuan
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Affective Behavior,Nonverbal Communication,Video Technology,Comprehension,Visual Perception,Student Attitudes,Human Body,College Students,Classification

The current paper explores possible solutions to the problem of detecting affective states from facial expressions during text/diagram comprehension, a context devoid of interactive events that can be used to infer affect. These data present an interesting challenge for face-based affect detection because likely locations of affective facial expressions within videos of students' faces are entirely unknown. In the current study, students engaged in a text/diagram comprehension activity after which they self-reported their levels of confusion, frustration, and engagement. Data were chosen from various locations within the videos, and texture-based facial features were extracted to build affect detectors. Varying amounts of data were used as well to determine an appropriate window of data to analyze for each affect detector. Detector performance was measured using Area Under the ROC Curve (AUC), where chance level is 0.5 and perfect classification is 1. Confusion (AUC = 0.637), engagement (AUC = 0.554), and frustration (AUC = 0.609) were detected at above-chance levels. Prospects for improving the method of finding likely positions of affective states are also discussed. [For complete proceedings, see ED560503.]
Modeling Classroom Discourse: Do Models That Predict Dialogic Instruction Properties Generalize across Populations?
Author: Samei, Borhan
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Academic Discourse,Discourse Analysis,Dialogs (Language),Instruction,Teaching Methods,Models,Classification,Linguistics,Population Groups,Correlation,Middle Schools,Urban Schools,Rural Schools

It has previously been shown that the effective use of dialogic instruction has a positive impact on student achievement. In this study, we investigate whether linguistic features used to classify properties of classroom discourse generalize across different subpopulations. Results showed that the machine learned models perform equally well when trained and validated on different subpopulations. Correlation-Based Feature Subset evaluation revealed an inclusion relationship between different subsets in terms of their most predictive features. [For complete proceedings, see ED560503.]
Learning Analytics Platform, towards an Open Scalable Streaming Solution for Education
Author: Lewkow, Nicholas
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Electronic Learning,Data Analysis,Higher Education,Elementary Secondary Education,Feedback (Response),Computer System Design,Open Source Technology

Next generation digital learning environments require delivering &quot;just-in-time feedback&quot; to learners and those who support them. Unlike traditional business intelligence environments, streaming data requires resilient infrastructure that can move data at scale from heterogeneous data sources, process the data quickly for use across several data pipelines, and serve the data to a variety of applications. As a solution to this problem, we have designed and deployed into production the Learning Analytics Platform (LAP), which can ingest data from different education systems using standardized IMS Caliper events. The education events are triggered by student and instructor activity within Caliper instrumented learning systems. Once sent to the LAP, events are transformed and stored in a data store where they can be used for student, educator, and administrator visualizations as well as education driven analytics research. Two McGraw-Hill Education platforms, Connect, used for higher education, and Engrade, for K-12, are currently instrumented to send the LAP event data which in turn feeds visualizations for educational insight. Future plans for the LAP include collection of education event data from a wide variety of proprietary and open source education platforms, computational engines for predictive analytics, and an open API for third-party analytics using LAP data. [For complete proceedings, see ED560503.]