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Automated Grading of Access® Databases Using the Matlab® Database Toolbox

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Conference

2017 ASEE Annual Conference & Exposition

Location

Columbus, Ohio

Publication Date

June 24, 2017

Start Date

June 24, 2017

End Date

June 28, 2018

Conference Session

CoED: Computer Science Topics

Tagged Division

Computers in Education

Page Count

9

Permanent URL

https://peer.asee.org/27647

Download Count

30

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Paper Authors

biography

Curtis Cohenour P.E. Ohio University

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Dr. Cohenour is an Assistant Professor in the Ohio University Engineering Technology and Management Department, in Athens, Ohio. He received a Bachelor of Science degree from West Virginia Institute of Technology in 1980, a Master of Science degree from Ohio University in 1988, and a Ph. D. in Electrical Engineering from Ohio University in 2009. He is a registered professional engineer in West Virginia, and Ohio.

Dr. Cohenour has worked in Industry as an electrical engineer and project manager. He joined Ohio University in 2002 as a research engineer working for the Ohio University Avionics Engineering Center. He has worked on projects covering a wide variety of avionics and navigation systems such as, the Instrument Landing System (ILS), Microwave Landing System (MLS), Distance Measuring Equipment (DME), LAAS, WAAS, and GPS.

His recent work has included research with the Air Force Research Laboratory in Dayton, Ohio, aimed at understanding and correcting image geo-registration errors from a number of airborne platforms.

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biography

Audra Lynn Hilterbran Ohio University

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Audra Hilterbran is an instructional technologist in the Russ College of Engineering and Technology at Ohio University, Athens, Ohio. She works with faculty to design and redesign courses through best practices in technology integration. She is currently pursuing a PhD in Instructional Technology. Her background is in Applied Linguistics and English as a Second Language (ESL) instruction. She also teaches courses in Computer Assisted Language Learning. Her research interests include learning aptitudes, usability testing, and the facilitation of classroom communication.

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Abstract

This evidence based paper describes an automated method of grading Microsoft Access® databases using the MATLAB® Database Toolbox. A total of 70 students completed an average of 50 individual database assignments per week over a five-week portion of a semester. The assignments were from the Benchmark Series Microsoft® Access® 2013 (BM) text. The course schedule covered two chapters every week. Students were required to import and manipulate either raw text data or a partially completed database to complete each assignment. Students were given unique starter data to discourage academic dishonesty. The automated grader compared each student database submission with the starter data and a truth database. In addition, the database relations, keys, and data types were compared to the truth and graded. Graded assignments were returned to students within one day of submission, thus eliminating a potential bottlenecking of instructor feedback. The use of the grader allows for increased formative assessment opportunities rather than a reliance on traditional, summative examinations. Automated grading offers a flexible and reliable tool for instructors to provide objective, detailed, and timely feedback to students. The features of the automated grader, current outcomes, and future directions are discussed.

Cohenour, C., & Hilterbran, A. L. (2017, June), Automated Grading of Access® Databases Using the Matlab® Database Toolbox Paper presented at 2017 ASEE Annual Conference & Exposition, Columbus, Ohio. https://peer.asee.org/27647

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