ethanporcaro/eric-fulltext-meta huggingface dataset:
Identifying Styles and Paths toward Success in MOOCs
Author: Sharma, Kshitij
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Foreign Countries,Online Courses,Large Group Instruction,Student Characteristics,Classification,Learner Engagement,Academic Achievement,Active Learning,Computer Science Education,Programming,Video Equipment,Student Participation,Grades (Scholastic)

Current schemes to categorise MOOC students result from a single view on the population which either contains the engagement of the students or demographics or self reported motivation. We propose a new hierarchical student categorisation, which uses common online activities capturing both engagement and achievement of MOOC students. A first level is based on the online engagement with the course structure, i.e., whether they take part in graded activities or not. Based on this criterion, we divide students into two major categories: active students and viewers. The second levels are based on the different activities typically performed by the students in these two categories. For the &quot;active students&quot; we categorise them based on their final result. For the &quot;viewers&quot;, we further divide the category based on their engagement quotient, i.e., how much of the course content they follow and whether they involve with the non-mandatory exercises in the course or not. Further, in this contribution we analyse the behaviour of the students in different categories to highlight the basic differences among them. [For complete proceedings, see ED560503.]
Aligning K-12 and Postsecondary Career Pathways with Workforce Needs
Author: Zinth, Jennifer
Date: 2015-10-00
Type: Reports - Evaluative
Subjects: Postsecondary Education,Alignment (Education),Elementary Secondary Education,State Policy,Policy Formation,Career Education,State Action,Labor Needs,Profiles,Educational Policy,Management Information Systems,Change Strategies,Career Readiness

Since 2013, states have witnessed significant legislative activity related to secondary- and postsecondary-level career/technical education (CTE). One key goal of much recent policymaking activity has been to improve alignment between high school and postsecondary CTE programs, including by developing state or regional structures to design career pathways that prepare students for high-skill, high-demand jobs. This report provides a first look at state policymaking activity in 13 states. Policy activity summarized here (1) establishes a process for educators and employers to convene and use workforce data to set priorities, and (2) sets forth strategies to enhance and scale up career pathways bridging K-12 and postsecondary, designed to prepare students for high-skill, high-demand jobs. This review is intended to allow readers to determine whether policies have been adopted in these 13 states, and compare and contrast approaches.
Why 12th Grade Must Be Redesigned Now--and How
Author: Vargas, Joel
Date: 2015-10-00
Type: Reports - Descriptive
Subjects: Grade 12,Educational Change,College Readiness,College School Cooperation,High Schools,Elementary Secondary Education,Postsecondary Education,Career Readiness,Articulation (Education),Benchmarking,Partnerships in Education,Educational Practices,Capacity Building

This first report in a new series by Jobs For the Future (JFF) provides the rationale for restructuring 12th grade and tying it more tightly to the first year of college through new high school and college partnerships. The paper proposes a new common benchmark of readiness that high schools and colleges can work together to meet to ensure momentum toward earning postsecondary credentials. It also describes promising practices and addresses the formidable challenges of the inherent norms underlying our education systems that must be changed if we are to succeed in creating a shared transition zone. The paper concludes with ideas for how state policymakers and local practitioners can start the shift to a new normal. [Over several months in 2014-15, with support from the Bill &amp; Melinda Gates Foundation, JFF convened groups of K-12 and postsecondary innovators and researchers to generate new strategies to strengthen what schools and colleges can do to put more 12th graders on a path to college and career success. This series reflects the collective wisdom of these groups. An appendix provides a list of group participants.]
A Comparative Study of Classification and Regression Algorithms for Modelling Students' Academic Performance
Author: Strecht, Pedro
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Comparative Analysis,Classification,Regression (Statistics),Mathematics,Models,Academic Achievement,Prediction,Academic Failure,Grades (Scholastic),Educational Experiments,College Students,Foreign Countries,Statistical Analysis,Data Collection,Data Analysis

Predicting the success or failure of a student in a course or program is a problem that has recently been addressed using data mining techniques. In this paper we evaluate some of the most popular classification and regression algorithms on this problem. We address two problems: prediction of approval/failure and prediction of grade. The former is tackled as a classification task while the latter as a regression task. Separate models are trained for each course. The experiments were carried out using administrate data from the University of Porto, concerning approximately 700 courses. The algorithms with best results overall in classification were decision trees and SVM while in regression they were SVM, Random Forest, and AdaBoost.R2. However, in the classification setting, the algorithms are finding useful patterns, while, in regression, the models obtained are not able to beat a simple baseline. [This work was partially funded by projects financed by the North Portugal Regional Operational Programme (ON.2--O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF).] [For complete proceedings, see ED560503.]
Tapping New Pools of Talent: Preparing Opportunity Youth to Help Fill the Skills Gap
Author: Jobs for the Future
Date: 2015-08-00
Type: Reports - Descriptive
Subjects: Youth Opportunities,Youth Programs,Job Skills,Skill Development,Career Readiness,Postsecondary Education,College Readiness,Transitional Programs,Developmental Studies Programs,Change Strategies,Continuation Students,Best Practices,Employment Opportunities,Employment Qualifications,Career Guidance

More than 6 million young people in the United States are out of school, out of work, and, often it seems, out of luck. That's 17 percent of Americans between the ages of 16 and 24. This population includes dropouts and high school graduates, former foster children and juveniles in court custody; youth caring for siblings and teens cycling in and out of low-wage jobs. Once known as &quot;disconnected,&quot; they are increasingly called &quot;opportunity youth.&quot; Despite growing up in difficult circumstances--they represent a large opportunity for investing in our nations workforce and our future. This brief focuses on strategies for strengthening education and employment pathways that prepare opportunity youth for jobs that can lead to productive careers. It is part of a series from JFF's conference Bridging the Gap: Postsecondary Pathways for Underprepared Learners.
Language to Completion: Success in an Educational Data Mining Massive Open Online Class
Author: Crossley, Scott
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Online Courses,Large Group Instruction,Information Retrieval,Data Analysis,Academic Achievement,Dropouts,Academic Persistence,Discourse Analysis,Natural Language Processing,Computer Mediated Communication,Discussion Groups,Predictor Variables,Success,Accuracy,Multivariate Analysis,Discriminant Analysis,Statistical Analysis

Completion rates for massive open online classes (MOOCs) are notoriously low, but learner intent is an important factor. By studying students who drop out despite their intent to complete the MOOC, it may be possible to develop interventions to improve retention and learning outcomes. Previous research into predicting MOOC completion has focused on click-streams, demographics, and sentiment analysis. This study uses natural language processing (NLP) to examine if the language in the discussion forum of an educational data mining MOOC is predictive of successful class completion. The analysis is applied to a subsample of 320 students who completed at least one graded assignment and produced at least 50 words in discussion forums. The findings indicate that the language produced by students can predict with substantial accuracy (67.8%) whether students complete the MOOC. This predictive power suggests that NLP can help us both to understand student retention in MOOCs and to develop automated signals of student success. [For complete proceedings, see ED560503.]
Predicting Student Grade Based on Free-Style Comments Using Word2Vec and ANN by Considering Prediction Results Obtained in Consecutive Lessons
Author: Luo, Jingyi
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Grades (Scholastic),Prediction,Feedback (Response),Student Attitudes,Educational Experiments,Accuracy,Student Evaluation,Discourse Analysis,Measures (Individuals),Artificial Intelligence,Questionnaires,Correlation,Self Evaluation (Individuals)

Continuously tracking students during a whole semester plays a vital role to enable a teacher to grasp their learning situation, attitude and motivation. It also helps to give correct assessment and useful feedback to them. To this end, we ask students to write their comments just after each lesson, because student comments reflect their learning attitude towards the lesson, understanding of course contents, and difficulties of learning. In this paper, we propose a new method to predict final student grades. The method employs Word2Vec and Artifical Neural Network (ANN) to predict student grade in each lesson based on their comments freely written just after the lesson. In addition, we apply a window function to the predicted results obtained in consecutive lessons to keep track of each student's learning situation. The experiment results show that the prediction correct rate reached 80% by considering the predicted student grades from six consecutive lessons, and a final rate became 94% from all 15 lessons. The results illustrate that our proposed method continuously tracked student learning situation and improved prediction performance of final student grades as the lessons go by. [For complete proceedings, see ED560503.]
Learning Behavior Characterization with Multi-Feature, Hierarchical Activity Sequences
Author: Ye, Cheng
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Learning Activities,Learning Processes,Data Collection,Student Behavior,Sequential Approach,Middle School Students,Secondary School Science,Science Instruction,Problem Solving,Classification,Comparative Analysis,Sequential Learning,Information Retrieval,Mathematical Concepts,Data Analysis

This paper discusses Multi-Feature Hierarchical Sequential Pattern Mining, MFH-SPAM, a novel algorithm that efficiently extracts patterns from students' learning activity sequences. This algorithm extends an existing sequential pattern mining algorithm by dynamically selecting the level of specificity for hierarchically-defined features individually for each pattern. Consequently, MFH-SPAM operates on a larger space of patterns in the activity sequences. In this paper, we employ a differential version of MFH-SPAM to extract a small set of patterns that best differentiate students with different learning behavior profiles in the Betty's Brain system. Our results illustrate that: (1) MFH-SPAM identifies important patterns missed by traditional sequence mining approaches; and (2) the differential patterns provide additional information for characterizing learning behaviors. This has implications for developing targeted and adaptive scaffolding in open-ended learning environments. [For complete proceedings, see ED560503.]
Promising Practices in Young Adult Employment: Lessons Learned from EMT Career Pathway Programs
Author: Leung, Loh-Sze
Date: 2015-00-00
Type: Reports - Research
Subjects: Young Adults,Employment,Emergency Medical Technicians,Case Studies,Labor Force Development,Allied Health Occupations Education,Allied Health Personnel,Partnerships in Education,Adult Education

The National Fund for Workforce Solution's Young Adult Initiatives aim to test and implement new strategies for targeting America's young adults and share this information so that employers and workforce development can join forces in investing in the millions of young adults across the nation. This case study will focus on challenges and opportunities for young adults in emergency medical services, a part of the health care sector that includes emergency medical technicians (EMTs) and paramedics. Specifically, this case study highlights EMT training partnerships implemented by CareerWorks: Greater Newark Workforce Funders Collaborative in New Jersey and the Bay Area Workforce Funding Collaborative (BAWFC) in California. It also integrates lessons learned from a similar project implemented several years ago by SkillWorks: Partners for a Productive Workforce in Boston, Massachusetts. While only the BAWFC specifically limited recruitment for this program to young adults, all of the collaboratives recruited and enrolled a significant proportion of young adults in their EMT training programs. The goal of this report is to share lessons learned and draw conclusions aimed at informing future efforts to train and prepare young adults for emergency medical services (EMS) or similar career pathways.
Investigation of High School Students' Environmental Attitudes in Terms of Some Demographic Variables
Author: Koruoglu, Nergiz
Date: 2015-10-00
Type: Journal Articles
Subjects: Foreign Countries,High School Students,Student Attitudes,Demography,Predictor Variables,Environment,Environmental Education,Rating Scales,Age Differences,Gender Differences,Parent Background,Educational Attainment,Comparative Analysis,Statistical Analysis

Studying individuals and students' attitudes towards environment and factors affecting students to be responsible individuals towards their environment may provide help towards the solution of environmental problems. In this study, it is aimed to evaluate environmental attitudes of high school students in terms of some variables. The sample of the study consists of 330 participants of whom 145 are male and 185 are female having studied in a High School in Balikesir (in western Turkey). In the study, as a means of data collection, Environmental Attitude Scale (EAS) and the personal information form have been used. The EAS which consists of 35 items is composed of 4 sub-dimensions as &quot;Environmental awareness&quot;, &quot;Attitude toward recovery&quot;, &quot;Attitude toward recycling&quot; and &quot;Environmental consciousness and behavior&quot;. According to the findings, considering the analysis of the EAS, statistically a considerable difference was reached between the sub-dimensions of the EAS and the gender, grade and parent education level variables. However, a considerable difference was not found between the branch of students and some sub-dimensions of the EAS. &quot;Items and Factor Structures of the Environmental Attitude Scale (EAS)&quot; is appended.
SFL in the IPEIT Classroom: Going beyond the Spoken and the Written to the Social
Author: Ben Elouidhnine, Hedia
Date: 2015-09-00
Type: Reports - Research
Subjects: English for Special Purposes,Engineering Education,College Freshmen,Linguistics,Language Usage,Socialization,Second Language Learning,Speech,Writing Assignments,Foreign Countries,Questionnaires,Case Studies,Protocol Analysis

Language use cannot be divorced from the context in which it takes place. In the academic circles, the context can be twofold: one concerned with language learning while the other interested in language assessment. The aim of this research paper is to shed light on both perspectives by setting a high premium on the speaking performances and the writing assignments of the first-year &quot;preparatory engineering&quot; students (FYPESs). Hence, the targeted field of enquiry would be that of ESP. The point is to draw a convergence line between both foci while showing their close congruence with &quot;Systemic Functional Linguistics&quot; (SFL). In this regard, both written and spoken corpora were collected to present genre-based pedagogy as one of the crucial aspects of SFL educational linguistic work. A semi-structured questionnaire was also conducted for the sake of data corroboration. The overarching aim is to introduce both productive levels of performance as essential paths towards FYPESs' language use and socialization into the ESP classroom &quot;culture&quot;. Ultimately, the &quot;systemic functional perspective&quot; of the English language, in general, and ESP, in particular, is targeted, being a &quot;system&quot; that &quot;functions&quot; not only linguistically but equally socially in the Tunisian ESP teaching setting. &quot;A Questionnaire for Students&quot; is appended.
Discrimination-Aware Classifiers for Student Performance Prediction
Author: Luo, Ling
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Classification,Data Analysis,Case Studies,Prediction,Enrollment,Student Evaluation,Comparative Analysis,Discriminant Analysis,Accuracy,Association Measures,Decision Support Systems,Mathematics,Scores

In this paper we consider discrimination-aware classification of educational data. Mining and using rules that distinguish groups of students based on sensitive attributes such as gender and nationality may lead to discrimination. It is desirable to keep the sensitive attributes during the training of a classifier to avoid information loss but decrease the undesirable correlation between the sensitive attributes and the class attribute when building the classifier. We illustrate, motivate, and solve the problem, and present a case study for predicting student exam performance based on enrollment information and assessment results during the semester. We evaluate the performance of two discrimination-aware classifiers and compare them with their non-discrimination-aware counterparts. The results show that the discrimination-aware classifiers are able to reduce discrimination with trivial loss in accuracy. The proposed method can help teachers to predict student performance accurately without discrimination. [For complete proceedings, see ED560503.]
Learning the Creative Potential of Students by Mining a Word Association Task
Author: Olivares-Rodríguez, Cristian
Date: 2015-06-00
Type: Speeches/Meeting Papers
Subjects: Creativity,Associative Learning,Accuracy,Classification,Models,Prediction,Computation,Educational Experiments,Creative Thinking,Information Retrieval

Creativity is a relevant skill for human beings in order to overcome complex problems and reach novel solutions based on unexpected associations of concepts. Thus, the education of creativity becomes relevant, but there are not tools to automatically track the creative potential of learners over time. This work provides a novel set of behavioural features about creativity based on associative skills. These associations are processed to define two models that depict students' creative potential. This way, we have reached an acceptable accuracy rate in the classification of creative potential, hence we have found concrete evidence regarding the ability to automatically predict the creative potential of students based on their association capabilities. [This work was partially funded by the Erasmus Mundus SUD-UE program. For complete proceedings, see ED560503.]
Promising Practices in Young Adult Employment: Hands-On Multidisciplinary Career Exploration and Mentorships
Author: Wagner, Stacey
Date: 2015-00-00
Type: Reports - Research
Subjects: Young Adults,Youth Employment,Labor Force Development,Case Studies,Employment Programs,High School Students,Career Exploration,Design,Engineering,Construction Industry,Information Technology,Program Effectiveness,Partnerships in Education,Experiential Learning,Hands on Science,Program Design,Agency Role,Youth Programs,Out of School Youth

The National Fund for Workforce Solution's Young Adult Initiatives aim to test and implement new strategies for targeting America's young adults and share this information so that employers and workforce development can join forces in investing in the millions of young adults across the nation. This case study focuses on promising findings from two programs supported by the Milwaukee Area Workforce Funding Alliance. These programs were designed to expose high school students to promising careers in design, construction, and information technology. Drawing from these programs, this report considers which program characteristics fostered success and how other cities can design similar programs. Lessons from the partnership include: (1) When working with young adults, remember that the learning context needs to include hands-on, experiential lessons that tie back to academic work; (2) When designing the program, ensure that the partners each fulfill a specific role and make sure each partner knows what that role is; and (3) If the partnership starts from employer demands, it will be more successful than if academia or community-based organizations put together a program and then try to get employers to participate. The successful practices detailed in this report are anticipated to benefit from the Workforce Innovation and Opportunity Act (WIOA) youth program, which requires that, by 2016, 75 percent of workforce board youth funding be spent on out-of-school youth.
Foreign Language Learners' Views on the Importance of Learning the Target Language Pronunciation
Author: Çakir, Ismail
Date: 2014-00-00
Type: Reports - Research
Subjects: Pronunciation,Second Language Learning,English (Second Language),College Students,Student Attitudes,Likert Scales,Statistical Analysis,Questionnaires,Attitude Measures,Foreign Countries

Pronunciation is one of the controversial topics in the field of English language teaching as a second or foreign language. The aim of this study is to understand the attitudes of prep class students at Kastamonu University (state university) in Turkey towards the importance of pronunciation in language learning. Therefore, a pronunciation attitude inventory (PAI) was implemented in order to achieve this goal. 58 students who were from different majors such as business management, forest engineering, tourism and hotel management, etc. attended the research at total, and they were asked to give their opinions about 12 statements by using five-point Likert scale aiming at eliciting the attitudes of the participants from the strongest (always or almost always true of me) to the weakest (never or almost never true of me). The descriptive results of the answers were analyzed by using SPSS 16 program. The responses given to the items in the questionnaire that intended to figure out the attitudes of the participants towards correct pronunciation in learning foreign language prove that pronunciation conveys a significant role in the target language learning, and it needs to be specifically handled by the instructors throughout the teaching process. &quot;The Pronunciation Attitude Inventory&quot; (PAI) is appended.