Validation of Automated Scoring of Science Assessments.
Constructed response items can both measure the coherence of student ideas and serve as reflective experiences to strengthen instruction. We report on new automated scoring technologies that can reduce the cost and complexity of scoring constructed-response items. This study explored the accuracy of c-rater-ML, an automated scoring engine developed by Educational Testing Service, for scoring eight science inquiry items that require students to use evidence to explain complex phenomena. Automated scoring showed satisfactory agreement with human scoring for all test takers as well as specific subgroups. These findings suggest that c-rater-ML offers a promising solution to scoring constructed-response science items and has the potential to increase the use of these items in both instruction and assessment. © 2015 Wiley Periodicals, Inc. J Res Sci Teach 53: 215–233, 2016.
Cloud computing allows the cloud customer to hoard their data on the remote store and endow them to utilize the On-demand high quality applications with super colossal computational power. As prodigious amount of data are stored on the cloud, it inevitably acquaint new security hazards such as data integrity, data availability problems in the system. To overcome these issues, we propose an extensible mechanism to perform data integrity auditing by delegating it to the Third Party Auditor (TPA) in a privacy preserving manner. This design is formulated based on tagging and hash tag table which supports the updates in the data and also it identifies the deleterious servers. With the use of TPA, it also reduces the burden of Cloud Service Provider (CSP).