This study explores the potential to enhance the performance of convolutional neural networks (CNNs) for automated scoring of kinematic graph answers through data augmentation using Deep Convolutional Generative Adversarial Networks (DCGANs). By developing and fine-tuning a DCGAN model to generate high-quality graph images, we explored its…

The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…

The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…

This survey of 510 special education teachers found that most teachers collect, record, and use data on student performance to determine instructional effectiveness, appropriate time to move students to the next skill, and which objectives have been met. Only one-third of teachers used graphs for displaying and interpreting data. (Author/JDD)

Criteria that may be used to assess the quality of individualized education programs (IEPs) for handicapped students are presented, along with nine examples of procedures for recording/displaying pupil performance data, and seven guidelines for modifying instructional programs. After discussing the rationale for IEPs, the following three indices…