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Showing 1 to 15 of 21 results Save | Export
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Ndudi O. Ezeamuzie; Jessica S. C. Leung; Dennis C. L. Fung; Mercy N. Ezeamuzie – Journal of Computer Assisted Learning, 2024
Background: Computational thinking is derived from arguments that the underlying practices in computer science augment problem-solving. Most studies investigated computational thinking development as a function of learners' factors, instructional strategies and learning environment. However, the influence of the wider community such as educational…
Descriptors: Educational Policy, Predictor Variables, Computation, Thinking Skills
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Gardner, Josh; Brooks, Christopher – Journal of Learning Analytics, 2018
Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…
Descriptors: Prediction, Models, Evaluation, Evaluation Methods
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Santiago Berrezueta Ed. – Lecture Notes in Educational Technology, 2023
The proceedings of the 18th edition of Latin American Conference on Learning Technologies (LACLO) demonstrates the developments in the research of learning science, learning resources, challenges and solutions. This Proceedings book showcases a collection of quality articles that explores and discusses trending topics in education in the upcoming…
Descriptors: Educational Technology, Active Learning, Design, Telecommunications
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Kovanovic, Vitomir; Gaševic, Dragan; Dawson, Shane; Joksimovic, Srecko; Baker, Ryan S.; Hatala, Marek – Journal of Learning Analytics, 2015
With widespread adoption of Learning Management Systems (LMS) and other learning technology, large amounts of data--commonly known as trace data--are readily accessible to researchers. Trace data has been extensively used to calculate time that students spend on different learning activities--typically referred to as time-on-task. These measures…
Descriptors: Time on Task, Computation, Validity, Data Analysis
Rickles, Jordan H.; Hansen, Mark; Wang, Jia – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2013
In this paper we examine ways to conceptualize and address potential bias that can arise when the mechanism for missing outcome data is at least partially associated with treatment assignment, an issue we refer to as treatment confounded missingness (TCM). In discussing TCM, we bring together concepts from the methodological literature on missing…
Descriptors: Data, Bias, Data Analysis, Statistical Analysis
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Suleman, Qaiser; Hussain, Ishtiaq – Journal of Education and Practice, 2016
The purpose of the research paper was to investigate the effect of eclectic learning approach on the academic achievement and retention of students in English at elementary level. A sample of forty students of 8th grade randomly selected from Government Boys High School Khurram District Karak was used. It was an experimental study and that's why…
Descriptors: Elementary School Students, Academic Achievement, School Holding Power, Pretests Posttests
Jones, Nathan; Steiner, Peter; Cook, Tom – Society for Research on Educational Effectiveness, 2011
In this study the authors test whether matching using intact local groups improves causal estimates over those produced using propensity score matching at the student level. Like the recent analysis of Wilde and Hollister (2007), they draw on data from Project STAR to estimate the effect of small class sizes on student achievement. They propose a…
Descriptors: Matched Groups, Control Groups, Scores, Computation
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Blikstein, Paulo; Worsley, Marcelo; Piech, Chris; Sahami, Mehran; Cooper, Steven; Koller, Daphne – Journal of the Learning Sciences, 2014
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and…
Descriptors: Programming, Computer Science Education, Learning Processes, Introductory Courses
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Feldman, Betsy J.; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2012
In longitudinal education studies, assuming that dropout and missing data occur completely at random is often unrealistic. When the probability of dropout depends on covariates and observed responses (called "missing at random" [MAR]), or on values of responses that are missing (called "informative" or "not missing at random" [NMAR]),…
Descriptors: Dropouts, Academic Achievement, Longitudinal Studies, Computation
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Mariano, Louis T.; McCaffrey, Daniel F.; Lockwood, J. R. – Journal of Educational and Behavioral Statistics, 2010
There is an increasing interest in using longitudinal measures of student achievement to estimate individual teacher effects. Current multivariate models assume each teacher has a single effect on student outcomes that persists undiminished to all future test administrations (complete persistence [CP]) or can diminish with time but remains…
Descriptors: Persistence, Academic Achievement, Data Analysis, Teacher Influence
Lipscomb, Stephen; Chiang, Hanley; Gill, Brian – Mathematica Policy Research, Inc., 2012
The Commonwealth of Pennsylvania plans to develop a new statewide evaluation system for teachers and principals in its public schools by school year 2013-2014. To inform the development of this evaluation system, the Team Pennsylvania Foundation (Team PA) undertook the first phase of the Pennsylvania Teacher and Principal Evaluation…
Descriptors: Academic Achievement, Models, Outcomes of Education, Teacher Evaluation
Lipscomb, Stephen; Chiang, Hanley; Gill, Brian – Mathematica Policy Research, Inc., 2012
The Commonwealth of Pennsylvania plans to develop a new statewide evaluation system for teachers and principals in its public schools by school year 2013-2014. To inform the development of this evaluation system, the Team Pennsylvania Foundation (Team PA) undertook the first phase of the Pennsylvania Teacher and Principal Evaluation…
Descriptors: Academic Achievement, Models, Outcomes of Education, Teacher Evaluation
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Sampson, Demetrios G., Ed.; Ifenthaler, Dirk, Ed.; Isaías, Pedro, Ed.; Mascia, Maria Lidia, Ed. – International Association for Development of the Information Society, 2019
These proceedings contain the papers of the 16th International Conference on Cognition and Exploratory Learning in the Digital Age (CELDA 2019), held during November 7-9, 2019, which has been organized by the International Association for Development of the Information Society (IADIS) and co-organised by University Degli Studi di Cagliari, Italy.…
Descriptors: Teaching Methods, Cooperative Learning, Engineering Education, Critical Thinking
Dahl, Gordon; Lochner, Lance – Institute for Research on Poverty, 2009
Past estimates of the effect of family income on child development have often been plagued by endogeneity and measurement error. In this paper, we use two simulated instrumental variables strategies to estimate the causal effect of income on children's math and reading achievement. Our identification derives from the large, non-linear changes…
Descriptors: Family Income, Academic Achievement, Evidence, Tax Credits
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Gorard, Stephen – Social Research Update, 1999
Describes two methods commonly used to calculate achievement gaps and suggests problems in the calculation of achievement gaps. One method uses percentage points as a form of "common currency"; the other calculates the change over time in proportion to the figures that are changing. Discusses reasons the second method may be preferable. (SLD)
Descriptors: Academic Achievement, Achievement Gains, Change, Computation
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