ethanporcaro/eric-fulltext-meta huggingface dataset:
Evaluation of the Texas Technology Immersion Pilot: An Analysis of the Baseline Conditions and First-Year Implementation of Technology Immersion in Middle Schools. Executive Summary
Author: Shapley, Kelly
Date: 2006-12-00
Type: Reports - Evaluative
Subjects: Middle Schools,Public Schools,Technology Integration,Academic Achievement,Pilot Projects,Program Effectiveness,Institutional Characteristics,Access to Computers,Program Implementation,Readiness,Faculty Development,Middle School Teachers,Middle School Students,Laptop Computers,Technology Uses in Education,Technical Support,Instructional Leadership,Technology Planning

The Texas Education Agency (TEA) used Title II, Part D monies to fund a wireless learning environment for high-need middle schools through the Technology Immersion Pilot (TIP). A concurrent research project funded by a federal Evaluating State Education Technology Programs grant is scientifically evaluating whether student achievement improves over time as a result of exposure to technology immersion. Technology immersion encompasses multiple components, including a laptop computer for every middle school student and teacher, wireless access throughout the campus, online curricular and assessment resources, professional development and ongoing pedagogical support for curricular integration of technology resources, and technical support to maintain an immersed campus. The study of technology immersion employs a quasi-experimental research design with middle schools assigned to either treatment or control groups (22 schools in each). While the overarching purpose of the study is to scientifically test the effectiveness of technology immersion in increasing middle school students' achievement in core academic subjects, the evaluation also aims to examine the relationships that exist among contextual conditions, technology immersion, intervening factors, and student achievement. Data gathered through site visits to all participating middle school campuses in fall 2004 and spring 2005 allowed an in-depth examination of campus conditions, school and classroom activities, and educational roles and processes through interviews with key personnel, focus groups with teachers and students, inventories of technology resources, and reviews of documents. Major findings from the first year are summarized in this executive summary. [For the full report, &quot;Evaluation of the Texas Technology Immersion Pilot: An Analysis of the Baseline Conditions and First-Year Implementation of Technology Immersion in Middle School,&quot; see ED536299.]
Evaluation of the Texas Technology Immersion Pilot: First-Year Results. Executive Summary
Author: Shapley, Kelly
Date: 2006-04-00
Type: Reports - Research
Subjects: Middle Schools,Public Schools,Technology Integration,Academic Achievement,Pilot Projects,Program Effectiveness,Middle School Teachers,Middle School Students,Grade 6,Program Implementation,Institutional Characteristics,Teacher Characteristics,Student Characteristics,Access to Computers,Laptop Computers,School Culture,Computer Literacy,Technology Uses in Education,Instructional Innovation,Learner Engagement,Independent Study,Reading Achievement,Mathematics Achievement

The Technology Immersion Pilot (TIP) sets forth a vision for technology immersion in Texas public schools. The Texas Education Agency (TEA) directed nearly $14 million in federal Title II, Part D monies toward funding a wireless learning environment for high-need middle schools through a competitive grant process. A concurrent research project funded by a federal Evaluating State Educational Technology Programs grant is evaluating whether student achievement improves over time as a result of exposure to technology immersion. The Texas Center for Educational Research (TCER)--a non-profit research organization in Austin--is the TEA's primary partner in this landmark effort. The overarching purpose of the study is to conduct a scientifically based evaluation at the state level to test the effectiveness of technology immersion in increasing middle school students' achievement in core academic subjects. Technology immersion encompasses multiple components, including a laptop computer for every middle school student and teacher, wireless access throughout the campus, online curricular and assessment resources, professional development and ongoing pedagogical support for curricular integration of technology resources, and technical support to maintain an immersed campus. This executive summary highlights the major findings from the study. [For the full report, &quot;Evaluation of the Texas Technology Immersion Pilot: First-Year Results,&quot; see ED536290.]
Evaluation of the Texas Technology Immersion Pilot: An Analysis of the Baseline Conditions and First-Year Implementation of Technology Immersion in Middle School
Author: Shapley, Kelly
Date: 2006-12-00
Type: Reports - Evaluative
Subjects: Middle Schools,Public Schools,Technology Integration,Academic Achievement,Pilot Projects,Program Effectiveness,Institutional Characteristics,Access to Computers,Program Implementation,Readiness,Faculty Development,Middle School Teachers,Middle School Students,Laptop Computers,Technology Uses in Education,Technical Support,Instructional Leadership,Technology Planning

The Texas Education Agency (TEA) used Title II, Part D monies to fund a wireless learning environment for high-need middle schools through the Technology Immersion Pilot (TIP). A concurrent research project funded by a federal Evaluating State Education Technology Programs grant is scientifically evaluating whether student achievement improves over time as a result of exposure to technology immersion. Technology immersion encompasses multiple components, including a laptop computer for every middle school student and teacher, wireless access throughout the campus, online curricular and assessment resources, professional development and ongoing pedagogical support for curricular integration of technology resources, and technical support to maintain an immersed campus. The study of technology immersion employs a quasi-experimental research design with middle schools assigned to either treatment or control groups (22 schools in each). While the overarching purpose of the study is to scientifically test the effectiveness of technology immersion in increasing middle school students' achievement in core academic subjects, the evaluation also aims to examine the relationships that exist among contextual conditions, technology immersion, intervening factors, and student achievement. Data gathered through site visits to all participating middle school campuses in fall 2004 and spring 2005 allowed an in-depth examination of campus conditions, school and classroom activities, and educational roles and processes through interviews with key personnel, focus groups with teachers and students, inventories of technology resources, and reviews of documents. Appended are: (1) Technology Immersion Evaluation Design; (2) Characteristics of Technology;  and (3) Technology Use in Core Subjects. Individual chapters contain footnotes. (Contains 12 tables and 1 figure.) [For &quot;Evaluation of the Texas Technology Immersion Pilot: An Analysis of the Baseline Conditions and First-Year Implementation of Technology Immersion in Middle Schools. Executive Summary,&quot; see ED536297.]
Lower-Level Qualifications as a Stepping Stone for Young People. Occasional Paper
Author: Oliver, Damian
Date: 2012-00-00
Type: Numerical/Quantitative Data
Subjects: Foreign Countries,Outcomes of Education,Education Work Relationship,Vocational Education,Qualifications,Graduates,Comparative Analysis,Employment,Apprenticeships,Well Being,Disadvantaged Youth,Postsecondary Education,Young Adults,Gender Differences

Lower-level qualifications (certificate I and II programs) provide little or no immediate return to the individual in terms of increased wages. However, lower-level qualifications are intended to prepare students who would otherwise not be capable of enrolling in and completing a higher-level qualification or making a successful transition into the workplace, because of their ability, social circumstances, or previous educational experiences. The aim of this report is to test whether lower-level qualifications serve a broader purpose by functioning as a &quot;stepping stone&quot; to further study or into the labour market. The critical part of the methodology is the selection of the comparison group. Using data from the Longitudinal Surveys of Australian Youth (LSAY), the research matches certificate I and II graduates to other young people who share similar characteristics but who have neither completed nor are undertaking study or training at a higher level. The report compares their further study, training, employment and overall wellbeing outcomes two years after graduation and at age 26. The findings do not relate to certificate I or II qualifications completed as part of an apprenticeship or traineeship. Appended are: (1) Characteristics of certificate I and II students; and (2) Statistical methodology. (Contains 19 tables.)
The Value of Completing a VET Qualification. Occasional Paper
Author: Karmel, Tom
Date: 2012-00-00
Type: Reports - Research
Subjects: Qualifications,Employment Level,Vocational Education,Wages,Educational Benefits,Certification,Foreign Countries,Educational Attainment,Graduation Rate,Models,Outcomes of Education,Regression (Statistics),Education Work Relationship,Student Surveys

Completion rates are an obvious performance indicator for the vocational education and training (VET) sector. Previously published figures indicated overall completion rates as low as 27%. One response to this is the argument that there are many students who do not need to complete their qualification as they acquire the skills they need without going through the entire curriculum of a qualification. For them, completion is not an issue. To throw further light on this issue this paper identifies groups of students for whom there is a clear benefit in completing their qualification. The authors use data from the 2009 Student Outcomes Survey to test whether completion is beneficial in relation to a number of predefined post-study outcomes. These are employment, further study, a combination of employment or further study, &quot;improved&quot; employment, occupational status and salary. The authors find that completion has an overall strong positive effect on these pay-off variables. However, the extent of the pay-off varies greatly across different groups of students. Appended are: (1) Model results; and (2) Tree diagrams. (Contains 15 figures, 9 tables and 10 footnotes.) [For the 2006 edition of the report, see ED495916.]
Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort: Wave 2 (2010)-- Questionnaire. Technical Report 71A
Author: National Centre for Vocational Education Research
Date: 2012-00-00
Type: Tests/Questionnaires
Subjects: Foreign Countries,National Surveys,Longitudinal Studies,Questionnaires,Educational Attainment,Vocational Education,Academic Education,Workplace Learning,Secondary Education,Education Work Relationship,Postsecondary Education,Employment,Job Applicants,Labor Force Nonparticipants,Family (Sociological Unit),Income,Health,Attitudes

The Longitudinal Surveys of Australian Youth (LSAY) program studies the progress of several groups of young Australians as they move from school into post-secondary education and work. This technical paper contains the questionnaire for the LSAY 2009 cohort Wave 2 (2010) data set.
Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort: Wave 1 (2009)--Frequency Tables. Technical Report 70
Author: National Centre for Vocational Education Research
Date: 2012-00-00
Type: Numerical/Quantitative Data
Subjects: Foreign Countries,National Surveys,Longitudinal Studies,Individual Characteristics,Family (Sociological Unit),Family Environment,Reading,Time on Task,Institutional Characteristics,Educational Environment,Teacher Student Relationship,English Instruction,Libraries,Reading Strategies,Access to Computers,Computer Use,Educational Attainment,Leisure Time,Employment,Academic Achievement,School Attitudes,Academic Aspiration,Scientific Attitudes,Work Experience,Vocational Education,Achievement Tests

The Longitudinal Surveys of Australian Youth (LSAY) program studies the progress of several groups of young Australians as they move from school into post-secondary education and work. Since 2003, the LSAY program has been integrated with the Programme for International Student Assessment (PISA) conducted by the Organisation for Economic Cooperation and Development. This technical report contains the frequency tables for the LSAY 2009 cohort Wave 1 (2009) dataset.
Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort: Wave 2 (2010)--Frequency Tables. Technical Report 71B
Author: National Centre for Vocational Education Research
Date: 2012-00-00
Type: Numerical/Quantitative Data
Subjects: Foreign Countries,Education Work Relationship,Longitudinal Studies,Cohort Analysis,Youth Programs,Research Reports,Developmental Studies Programs,Incidence,Tables (Data),Statistical Data,Program Effectiveness,Educational Attainment,Academic Aspiration,Occupational Aspiration,Work Experience,Intellectual Disciplines

The Longitudinal Surveys of Australian Youth (LSAY) program studies the progress of several groups of young Australians as they move from school into post-secondary education and work. This technical paper contains the frequency tables for the LSAY 2009 cohort Wave 2 (2010) data set.
Longitudinal Surveys of Australian Youth (LSAY) 2009 Cohort: Wave 3 (2011)--Questionnaire. Technical Report 72A
Author: National Centre for Vocational Education Research
Date: 2012-00-00
Type: Tests/Questionnaires
Subjects: Measures (Individuals),Foreign Countries,Education Work Relationship,Research Reports,Questionnaires,Longitudinal Studies,Developmental Studies Programs,Youth Opportunities,Youth Programs,National Surveys,Test Items,Educational Attainment,Academic Aspiration,Occupational Aspiration,Progress Monitoring,Work Experience,Educational Research

The Longitudinal Surveys of Australian Youth (LSAY) program studies the progress of several groups of young Australians as they move from school into post-secondary education and work. This technical paper contains the questionnaire for the LSAY 2009 cohort Wave 3 (2011) data set.
Balancing Self-Directed Learning with Expert Mentoring: The Science Writing Heuristic Approach
Author: Shelley, Mack
Date: 2012-00-00
Type: Reports - Research
Subjects: Thinking Skills,Heuristics,Educational Change,Novices,Mentors,Writing (Composition),Critical Thinking,Outcomes of Education,Science Education,Persuasive Discourse,Tables (Data)

This study focuses on the implementation of the Science Writing Heuristic (SWH) curriculum (Hand, 2007), which combines current understandings of learning as a cognitive and negotiated process with the techniques of argument-based inquiry, critical thinking skills, and writing to strengthen student outcomes. Success of SWH is dependent on the teachers who are implementing the curriculum in the classroom. Central to the SWH philosophy is the emphasis on self-direction. An often mistaken assumption regarding self-direction is that students are doing all of the work. A key to mastery is what is put in front of the student. As important as the emphasis on self-direction is the selection of appropriate materials leading to achievable endpoints. The degree of success of the SWH curriculum relies on an appropriate balance of self-direction and expert mentoring, which necessarily is the blend of the students and the work they are doing. SWH requires that the teacher adapts, stops, redirects, responds, and so on. Great problems often are solved by beginners or novices to the field. The best teachers appreciate the beginner's mind and do not get in the way, even when something appears like a false start. Appended are: (1) References; and (2) Tables and Figures. (Contains 3 figures and 6 tables.)
Effectiveness of Small-Group Tutoring Interventions for Improving the Mathematical Problem-Solving Performance of Third-Grade Students with Mathematics Difficulties: A Randomized Experiment
Author: Jitendra, Asha K.
Date: 2012-00-00
Type: Reports - Research
Subjects: Mathematics Achievement,Tutoring,Problem Solving,Word Problems (Mathematics),Small Group Instruction,Program Effectiveness,Mathematics Skills,Grade 3,Elementary School Mathematics,Elementary School Students,Comparative Analysis,Teaching Methods,Metacognition,At Risk Students,Standardized Tests

The present research assessed the efficacy of two tutoring protocols for improving the mathematics outcomes of at-risk third-grade students. Results indicated that students in the schema-based instruction (SBI) group outperformed students in the control group on word problem solving performance after 30 hours of problem-solving experience, but the problem-solving performance was not maintained 8 weeks following the tutoring intervention. However, the SBI condition led to superior performance on a standardized mathematics achievement test compared with the control group. With respect to metacognitive strategy knowledge, the SBI condition outscored the control condition. Further, results suggested that SBI was equally effective for students from various at-risk subgroups. These findings demonstrate the efficacy of SBI tutoring conducted by trained tutors. (Contains 3 tables.)
EEG Estimates of Cognitive Workload and Engagement Predict Math Problem Solving Outcomes
Author: Beal, Carole R.
Date: 2012-00-00
Type: Reports - Research
Subjects: Prediction,Problem Solving,Cognitive Ability,Diagnostic Tests,Brain Hemisphere Functions,Student Attitudes,Difficulty Level,Acoustics,Neurosciences,Educational Research,College Students

In the present study, the authors focused on the use of electroencephalography (EEG) data about cognitive workload and sustained attention to predict math problem solving outcomes. EEG data were recorded as students solved a series of easy and difficult math problems. Sequences of attention and cognitive workload estimates derived from the EEG signals were used to train a Support Vector Machine ([SVM], a machine learning classifier) to predict the outcome of the problem: correct or incorrect answer. The authors were also interested in learning if the EEG estimates would be different for easy and hard problems, as suggested by the results of Chaouachi et al. (2011), and if the estimates would be related to the students' self-report of how difficult the problem was. The preliminary results suggest that using the estimates of Engagement and Workload from EEG data can predict problem solving outcomes better than the base rate of performance on the problems. In general, predictions that utilized both signal sources tended to be better, although this was not consistently observed. Predictions were somewhat better for easy problems, perhaps because students solved those items more quickly; prediction accuracy tends to decline with the amount of time the student works on the problem, perhaps due to increased noise in the sensor data streams. Overall, the results were consistent with other recent studies suggesting that the application of neuroscience methods may be a valuable addition to education research. (Contains 2 tables.)
Learning Communities for Developmental Education Students: A Synthesis of Findings from Randomized Experiments at Six Community Colleges
Author: Weiss, Michael J.
Date: 2012-00-00
Type: Reports - Research
Subjects: Outcomes of Education,Community Colleges,Educational Objectives,Developmental Studies Programs,Educational Experiments,Two Year College Students,Academic Support Services,Remedial Programs,English Instruction,Remedial Mathematics,Grouping (Instructional Purposes),Comparative Analysis,Demonstration Programs,Experimental Groups,Control Groups,Academic Records,Grades (Scholastic),Interviews,Focus Groups,Statistical Analysis,Program Effectiveness,Student Characteristics,Federal Programs

Community college stakeholders are searching with increasing urgency for approaches with the potential to improve the success rates for community college students, particularly those in need of developmental education. &quot;Learning communities,&quot; which place cohorts of students together in two or more courses for one semester, are a popular instructional reform community colleges are implementing to improve the outcomes of developmental education students, and have previously been associated with positive social, psychological, and academic outcomes in non-experimental and quasi-experimental research (Engstrom &amp; Tinto, 2008; Stefanou &amp; Salisbury-Glennon, 2002; Tinto, 1997; Tinto, 1998; Zhao &amp; Kuh, 2004). This paper synthesizes results from six random assignment evaluations of developmental education learning communities programs. Five of the six programs were part of the National Center for Postsecondary Research's (NCPR) Learning Communities Demonstration, and the sixth was studied as part of MDRC's Opening Doors Demonstration. The primary question addressed in this study is whether learning communities, compared to &quot;business as usual,&quot; lead to better educational outcomes for students who are placed into developmental English and math in community colleges. The authors also examine whether the effects of learning communities vary across colleges and subgroups. (Contains 4 figures, 2 tables, and 6 footnotes.)
Incorporating Learning into the Cognitive Assessment Framework
Author: Studer, Cassandra
Date: 2012-00-00
Type: Reports - Research
Subjects: Foreign Countries,Data Analysis,Cognitive Measurement,Measurement Techniques,Educational Assessment,Student Evaluation,Models,Federal Aid,Educational Research,Evaluation Utilization,Simulation,Second Language Learning,English (Second Language),Pretests Posttests,Evaluation Methods,College Students,Web Based Instruction,Cloze Procedure,Language Tests

The authors aimed to incorporate learning into the cognitive assessment framework that exists for static assessment data. In order to accomplish this, they derive a common likelihood function for dynamic models and introduce Parameter Driven Process for Change + Cognitive Diagnosis Model (PDPC + CDM), a dynamic model which tracks learning indirectly through student membership in latent states which drive the distributions of the student parameter in the static portion of the model. They described this model both theoretically and empirically through application to the article data set (Chan, 2012). One limitation of this data set is that the items are single skill. In order to truly test PDPC + CDM, the authors need to find data that have items with multiple skills. In general, by adding a dynamic component to the cognitive assessment framework, they provide education researchers with a method to track individual student learning while taking item and skill features into consideration. In addition, one could use a model such as this to define learning trajectories which could lead to better instructional methods and sequences (Haertel, 2012). Teachers could also use this information to better focus their lessons. One goal for the future would be to make these models accessible to researchers and teachers who can use the results to further student learning and the field of education research. (Contains 2 figures.) [This work was supported in part by the Program for Interdisciplinary Education Research, Carnegie Mellon University, under Institute for Education Sciences, Department of Education.]