ethanporcaro/eric-fulltext-meta huggingface dataset:
Design, Motivation and Performance in a Cooperative MOOC Course
Author: Castaño, Carlos
Date: 2015-01-00
Type: Journal Articles
Subjects: Online Courses,Large Group Instruction,Educational Technology,Technology Uses in Education,Delphi Technique,Instructional Design,Surveys,Academic Achievement,Teaching Methods,Higher Education,Social Media,Statistical Analysis,Correlation,Student Motivation,Student Surveys,Foreign Countries,Likert Scales,College Students

MOOCs are seen as the latest evolution in online learning and, since their launch in 2008, they have become an integral part of university course curricula. Despite the social success of these courses, the learning design and efficacy of their results have been questioned. Most current research has focused more on discussing their potential to offer quality, large-scale education worldwide rather than measuring learning outcomes. This paper shows the results of a research study that focused on the pedagogical design of a cooperative MOOC and its influence on motivation and academic results. A Delphi study was used to validate the design, and the motivation variable was controlled using the Instructional Materials Motivation Survey (IMMS). Academic performance was assessed through evidence-based learning. The paper argues that design, which is defined by the students' intensive use of social networks and the activities they carry out in their Personal Learning Environments, has an influence on performance, and the variable that mediates in that relationship is the level of satisfaction with the perception of the design. The academic results obtained and the students' motivation support the use of cooperative MOOCs in university education.
Literature and Practice: A Critical Review of MOOCs
Author: Chiappe-Laverde, Andres
Date: 2015-01-00
Type: Reports - Research
Subjects: Online Courses,Literature Reviews,Educational Practices,Journal Articles,Virtual Classrooms,Instructional Effectiveness,Open Education,Teaching Methods,Educational Environment,Educational Technology,Instructional Innovation

This article focuses on a review of both literature and practical experiences concerning MOOCs. The literature analyzed was published in peer-reviewed journals between 2007 and 2013. 268 items were selected for this study, of which 100 were analyzed in detail. The issues raised by this analysis were used as the criteria for the analysis of 10 current empirical MOOC experiences. The literature study highlighted the rapid growth in interest in understanding MOOCs and seeking to understand the pedagogic frameworks most relevant to their adoption and the importance of the concept of openness embodied within them. More recently a new emphasis has been emerging where institutional factors, particularly those concerned with financial viability, certification and retention have been highlighted. The analysis of current practice showed that many of the concerns in the academic literature were absent from not only the practices embodied in current MOOC-based learning experiences but seem to have been ignored in the conceptual phase of implementing a MOOC-based teaching model. In practice therefore, most of the current MOOC offer is only a pale reflection of the conceptualization that gave them rise and has been shown to be significant in the literature. In particular the true essence encapsulated in the concept described as Openness has been largely lost in practice.
Using Robust Variance Estimation to Combine Multiple Regression Estimates with Meta-Analysis
Author: Williams, Ryan
Date: 2013-00-00
Type: Reports - Research
Subjects: Robustness (Statistics),Multiple Regression Analysis,Meta Analysis,Effect Size,Monte Carlo Methods,Intervals

The purpose of this study was to explore the use of robust variance estimation for combining commonly specified multiple regression models and for combining sample-dependent focal slope estimates from diversely specified models. The proposed estimator obviates traditionally required information about the covariance structure of the dependent effect size estimates, making it a potentially flexible method for conducing meta-analyses of regression estimates. A series of Monte Carlo simulations were conducted to explore the performance of the robust variance estimator under different meta-analytic conditions. The results of the simulations for this approach were promising. The robust confidence intervals for each set of parameter combinations were close to nominal probability content in nearly all of the specified conditions. Robust Variance Estimation and Meta-Analysis is appended.
Sustainability of Fidelity of Implementation over Time, in the Context of a Prekindergarten Mathematics Curriculum and Professional Development Scale-Up Intervention
Author: Wolfe, Christopher B.
Date: 2013-00-00
Type: Reports - Research
Subjects: Fidelity,Intervention,Mathematics Curriculum,Professional Development,Preschool Education,Preschool Teachers,Kindergarten,Mathematics,Mathematics Achievement,Mathematics Instruction,Sustainability

Although there is growing interest in implementation fidelity, little research has been reported on the sustainability over time of faithful implementations of learning innovations. This study examined the sustainability of teachers' implementation fidelity to the components of a prekindergarten mathematics intervention two full years after external support ceased. The authors hypothesized that an innovation based on coherent learning trajectories, wherein teachers increase their familiarity with mathematical goals, hypothesized developmental paths leading to the achievement of those goals, and activities designed to enable children to attain those goals, positively impacts teachers' sustained and faithful implementation of the innovation. This research draws from a large-scale up study of professional development across two diverse research settings. Conclusions report that teachers exposed to the PD during the intervention continue to demonstrate high levels of fidelity to the underlying curriculum two years past exposure and without continued project support. Teachers with more experience demonstrated significantly faster rates of growth than their less experienced colleagues, and higher initial levels of fidelity to the whole group component. A table and a figure are appended.
Propensity Score Estimation with Data Mining Techniques: Alternatives to Logistic Regression
Author: Keller, Bryan S. B.
Date: 2013-00-00
Type: Reports - Research
Subjects: Probability,Scores,Statistical Analysis,Statistical Bias,Quasiexperimental Design,Regression (Statistics),Mathematical Models,Research Methodology,Evaluation Methods,Simulation,Error of Measurement,Accuracy

Propensity score analysis (PSA) is a methodological technique which may correct for selection bias in a quasi-experiment by modeling the selection process using observed covariates. Because logistic regression is well understood by researchers in a variety of fields and easy to implement in a number of popular software packages, it has traditionally been the most frequently used method for modeling selection in PSA. There are, however, circumstances under which logistic regression may not perform well. The most important disadvantage of a propensity score (PS) estimation approach that uses logistic regression is the need for iterative specification of the model, which can be rather time intensive and comes with no guarantee of success, in particular with many covariates. A careful review of the burgeoning PS estimation literature has shown that the neural network and the support vector machine (SVM) are promising alternatives to logistic regression which avoid the need for respecification because they automatically model nonlinearities in the selection response surface, and are well suited for high-dimensional data. These two methods, although promising, are heretofore largely or completely empirically untested in this context. Through simulation, this study examines the conditions under which logistic regression is relatively robust to model misspecification and the conditions under which the neural network or the support vector machine will provide a less biased estimate of the effect of a treatment. Researchers evaluate through simulation, and make available a program written in R which carries out a cross-validated grid search for the optimal tuning parameters for the data mining methods based on maximizing the balance as opposed to minimizing the prediction error. The results of the simulation study clearly demonstrate that the misspecification of the PS model via logistic regression leads to the potential for gross bias in the estimate of the treatment effect when there are nonlinear or nonadditive confounders. The data mining techniques were less biased and had smaller mean square error in that case. The simulation study further explores the effect of the number of covariates and the number and strength of higher order confounders on the performance of the PS estimation methods. The authors provide recommendations based on the simulation study results in hopes of guiding researchers to make informed decisions about which propensity score estimation technique to use for their given situation in order to maximize the accuracy and efficiency of research. A table is appended.
The Effects of Research-Based Curriculum Materials and Curriculum-Based Professional Development on High School Science Achievement: Results of a Cluster-Randomized Trial
Author: Taylor, Joseph
Date: 2013-00-00
Type: Reports - Research
Subjects: Instructional Materials,Student Interests,Science Achievement,Secondary School Science,High School Students,Educational Improvement,Interdisciplinary Approach,Science Curriculum,Faculty Development,Science Teachers,Rural Schools,Suburban Schools,Grade 9,Grade 10,Comparative Analysis,Conventional Instruction,Randomized Controlled Trials,Educational Research,Hierarchical Linear Modeling

Effective instructional materials can be valuable interventions to improve student interest and achievement in science (National Research Council [NRC], 2007); yet, analyses indicate that many science instructional materials and curricula are fragmented, lack coherence, and are not carefully articulated through a sequence of grade levels (AAAS, 2001; Schmidt et al., 2001). In order to improve student achievement in science, school districts need evidence about the efficacy of instructional materials so they can make sound decisions about their science programs. In addition, science education researchers and curriculum developers can benefit from a better understanding of the characteristics of instructional materials and PD that promote student achievement. The purpose of this study is to examine the efficacy of an intervention that consists of research-based multidisciplinary science curriculum materials for high school students and curriculum-based professional development (PD) for teachers using the materials. The study took place in traditional high schools the state of Washington. Approximately half of the schools were in rural settings in central Washington, the other half were in suburban settings in western Washington. The study sample included nearly 4,000 ninth and tenth grade students nested within 18 high schools. The teacher sample within these 18 schools included 54 teachers. Ninth and tenth grade science teachers in nine treatment schools received curriculum materials and seven days of curriculum-based professional development for each of two years. Teachers in nine comparison schools continued to use extant instructional materials and receive extant professional development (i.e., business-as-usual). A cluster-randomized trial design (Raudenbush et al., 2002) was used where schools were randomly assigned to treatment conditions. Findings showed that research-based science instructional materials with supporting curriculum-based PD have a strong positive effect on classroom instruction and a modest but noteworthy effect on student achievement. One figure is appended.
Structural Equation Modeling of Knowledge Content Improvement Using Inquiry Based Instruction
Author: Reeves, Christopher Gonwa
Date: 2013-00-00
Type: Reports - Research
Subjects: Structural Equation Models,Inquiry,Science Education,Student Evaluation,Cognitive Ability,Achievement Tests,Standardized Tests,Experimental Groups,Control Groups,Heuristics,Science Tests,Reading Tests,Mathematics Tests,Scores,Content Area Writing,Science Instruction,Cognitive Development,Elementary School Students

A key element in science education is establishing and maintaining linkages between teachers and researchers that can eventuate in enhanced student outcomes. Determining when and where a new educational program or intervention results in an enhanced outcome can be sensitive to many different forces that the researcher must carefully manage. The target of inquiry-based approach is to increase cognitive abilities such as critical thinking. However, students, teachers, and schools are evaluated based on content student knowledge. Statistical modeling choices affect the ability to determine the efficacy of the intervention and the ability to identify those students who receive the greatest and least benefit from the intervention. As it is imperative to determine how an increase in cognitive abilities corresponds to an increase in content across different demographics and learning abilities, the effect of some of the statistical modeling choices were investigated. Students' progress on the Iowa Test of Basic Skills (ITBS) was modeled over two years of implementation of the inquiry-based learning approach. A control group of students not receiving the science writing heuristic (SWH) learning approach was used for comparison. The study was conducted with Iowa elementary school students, in grades 3-6, with 24 school buildings randomly assigned to treatment and 24 to control. Structural equations modeling of student test scores in reading, math, and science content were created. Modeling mutually exclusive subsets of the data provided for results, that in some cases, were substantially different from a structural equation model created using all of the student data. The separate models identified that the special education students have the greatest improvement in their mathematics test scores with increased exposure to the science writing heuristic. Traditional students' math scores also benefit from the science writing heuristic learning approach. However, this does not appear to be the case for gifted and talented students. The science writing heuristic targets critical thinking and cognitive abilities. It is not surprising that the largest treatment path coefficients are seen for the treatment to math score improvement paths. While the science writing heuristic is implemented as a learning approach to teaching science, the approach focuses on cognitive development over content. Figures and a table are appended.
A Study on the Pedagogical Components of Massive Online Courses
Author: Raposo-Rivas, Manuela
Date: 2015-01-00
Type: Journal Articles
Subjects: Online Courses,Instructional Design,Spanish,Mixed Methods Research,Content Analysis,Statistical Analysis,Data Collection,Classification,Benchmarking,Web Based Instruction,Componential Analysis,Validity

At the end of the first decade of the 21st century, the rapid growth in the MOOCs offering brought about a new educational landscape, posing new challenges to teaching and learning, mainly due to massive participation, ubiquity and free enrollment. These courses embody a confluence of technological and pedagogical mediations yet to be fully explored. This study, applying an instrument of educational and interactive indicators on a MOOC (INdiMOOC-EdI) designed by the authors, seeks to ascertain the pedagogical components of MOOCs delivered in the Spanish language in order to establish which course features are platform dependent. An exploratory sequential mixed methods study was carried out on a total of 117 courses within 10 different platforms via an instrument developed and validated ad hoc. The data obtained is subjected to a content analysis for a qualitative perspective; while a quantitative perspective is obtained through a statistical analysis complemented with classification algorithms typical in data mining. The results suggest that the different platform providers condition the pedagogical design of the MOOCs in five key areas: learning, activities and tasks, means and resources, interactivity and assessment. It concludes with a series of descriptive, educational and interactive indicators that can be a pedagogical benchmark for future MOOCs.
The Relationship between Gender, Ethnicity, and Technology on the Impact of Mathematics Achievement in an After-School Program
Author: Huang, Xudong
Date: 2013-00-00
Type: Reports - Research
Subjects: Gender Differences,Racial Differences,Ethnic Groups,Technology Uses in Education,Educational Technology,Mathematics Achievement,Correlation,After School Programs,Intelligent Tutoring Systems,Grade 6,Achievement Gap,White Students,African American Students,Randomized Controlled Trials,Conventional Instruction,Secondary Schools,Program Effectiveness,Standardized Tests,Grade 5

The gap among ethnicities and gender in mathematics achievement is a well-known problem. While the gap has been shrinking over the past three decades, it has not completely diminished (Jencks &amp; Phillips, 1998; McGraw, Lubienski, &amp; Strutchens, 2006). The ALEKS, Assessment and LEarning in Knowledge Spaces, tutoring system is one promising example of a technology that can target this problem. ALEKS is a Web-based intelligent tutoring system (ITS) that instructs students on the mathematical topics that they are most ready to learn, assesses students' current knowledge, and evaluates student performance on problems related to those topics. In order to better understand the role that technology can play in decreasing achievement gaps for gender and ethnicity, the authors examined the effect of interacting with ALEKS in a 6th grade students' math after-school program. In order to answer the question, Does ALEKS reduce the math achievement gap between two ethnicities (White and African American) compared to a teacher?, a randomized experiment was implemented in which students are either assigned to use ALEKS or are assigned to be taught structured lesson plans from a teacher. The experiment was conducted as an after-school program at five secondary schools in a school district in west Tennessee using a population of 102 students with excellent attendance (45 out of 50 days). This left the teacher condition with 22 males, 29 females; 11 white students and 40 African American students. The ALEKS condition had 28 males, 23 females; 11 white students and 40 African American students. The program was conducted for 25 weeks with 40 days of instruction and 10 days of review assessments. Results from the study suggest that the ITS (ALEKS) helps reduce the achievement gap between ethnicities. While more research is needed, it would appear that the ALEKS condition was able to offer equivalent help to students with different levels of performances, while the teachers' help tends to average performers. One table and one figure are appended.
Review of the Non-Experimental Evidence from Developmental and Cognitive Psychological, Education Science and Neuroscience That Provided the Impetus for the Development of the Intervention
Author: Grissmer, David
Date: 2013-00-00
Type: Reports - Research
Subjects: Evidence,Intervention,Developmental Psychology,Cognitive Psychology,Neurosciences,Science Education,Predictor Variables,Reading Achievement,Mathematics Achievement,Kindergarten,Reading Readiness,Readiness,Reading Instruction,Mathematics Instruction,Psychomotor Skills,Thinking Skills,Longitudinal Studies,Children,Surveys

Duncan et al. (2007) presented a new methodology for identifying kindergarten readiness factors and quantifying their importance by determining which of children's developing skills measured around kindergarten entrance would predict later reading and math achievement. The main objectives of this paper are threefold: (a) provide new empirical evidence that fine motor skills, a developmental skill measured at school entry but not included in Duncan's et al.'s (2007) analysis, is strongly predictive of later scores, (b) present several sensitivity analyses that extend Duncan et al.'s findings, including assessing the predictive power of a child's knowledge of the world, and (c) review the developmental, cognitive, and neuroscience literature to assess and suggest mechanisms for a link between early motor skills and later achievement. Three large scale longitudinal data sets are used in this study. They are the Early Childhood Longitudinal Survey- Kindergarten Cohort (ECLS-K), the British Birth Cohort Study (BCS), and the National Longitudinal Survey of Youth (NLSY). The results indicated that gross motor skills were not a significant predictor of later achievement but that fine motor skills were a very strong and consistent predictor of later achievement. A table is appended.
Teaching Early Knowledge of Whole Number Concepts through Technology: Findings from a Feasibility Study of an iPad Delivered Kindergarten Mathematics Intervention
Author: Shanley, Lina
Date: 2013-00-00
Type: Reports - Research
Subjects: Kindergarten,Mathematics Instruction,Number Concepts,Numeracy,Technology Uses in Education,Handheld Devices,Intervention,Response to Intervention,Feasibility Studies,Mixed Methods Research,Regression (Statistics),Instructional Effectiveness,Program Implementation,Mathematics Achievement,Achievement Gains,At Risk Students

Children enter kindergarten with variable levels of mathematics skill and knowledge gained from informal learning opportunities at home, preschool, and daycare. Many perform well once they receive formal mathematics instruction. However, if students do not develop an initial understanding of the most basic aspects of formal mathematics, they are likely to have difficulty understanding or succeeding at mathematics they will encounter in first grade and beyond. The primary research for this study was how successful was the classroom implementation of the KinderTEK mathematics intervention during the project's Feasibility Testing phase. The KinderTEK feasibility study was conducted winter/spring of 2013 in a moderate sized school district in the Pacific Northwest. KinderTEK was implemented in 10 classes; a mix of morning and afternoon classes taught by six teachers, two at each school. Teacher and student satisfaction with the KinderTEK student app drawn from interviews and survey response data indicated that the majority of students and teachers were satisfied with KinderTEK. The conclusions reported studies that seek to determine the overall impact and effectiveness of an individualized, technologically delivered kindergarten mathematics intervention face significant challenges. However, in spite of the challenges, the results are important to the iterative process of curriculum development. Lessons learned throughout usability trials and the feasibility study reported became valuable tools for the continued adaptation and refinement of the KinderTEK intervention in preparation for larger scale pilot study investigations. Tables are appended.