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Direct linkDanielle S. McNamara; Scott A. Crossley; Rod D. Roscoe; Laura K. Allen; Jianmin Dai – Grantee Submission, 2015
This study evaluates the use of a hierarchical classification approach to automated assessment of essays. Automated essay scoring (AES) generally relies onmachine learning techniques that compute essay scores using a set of text variables. Unlike previous studies that rely on regression models, this study computes essay scores using a hierarchical…
Descriptors: Automation, Scoring, Essays, Persuasive Discourse
Figg, Stephanie D.; Rogers, Karen B.; McCormick, John; Low, Renae – Journal of Advanced Academics, 2012
The study aimed to empirically verify findings from qualitative studies that showed selective consumers could be distinguished from underachievers with regard to academic self-perception and thinking style preference. Participants, gifted males from an independent secondary boys' school in Sydney, Australia, were categorized as achieving,…
Descriptors: Foreign Countries, Self Concept, Private Schools, Qualitative Research
Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed. – International Working Group on Educational Data Mining, 2009
The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…
Descriptors: Data Analysis, Educational Research, Conferences (Gatherings), Foreign Countries
