TY - GEN
T1 - Enhancing automated assessment for engineering MOOCs
AU - Beg, Azam
AU - Alhemeiri, Mouza M.
AU - Beg, Ajmal
PY - 2017
Y1 - 2017
N2 - Massive Open Online Courses (MOOCs) have the potential to free up learners from the bounds of time and space. Considering the likelihood of large numbers of students enrolling in a MOOC, the ability to create large numbers of test question and answers is highly desirable. In this paper, we present a set of algorithms for automatically creating questions for different courses in electrical/computer engineering (ECE). We have implemented the algorithms in a common scripting language. We have included examples of test questions for two different ECE courses. However, the presented methodology can be applied to many other courses. An advantage of our methodology is that it eliminates the need for the purchase and maintenance of a commercial design-software package.
AB - Massive Open Online Courses (MOOCs) have the potential to free up learners from the bounds of time and space. Considering the likelihood of large numbers of students enrolling in a MOOC, the ability to create large numbers of test question and answers is highly desirable. In this paper, we present a set of algorithms for automatically creating questions for different courses in electrical/computer engineering (ECE). We have implemented the algorithms in a common scripting language. We have included examples of test questions for two different ECE courses. However, the presented methodology can be applied to many other courses. An advantage of our methodology is that it eliminates the need for the purchase and maintenance of a commercial design-software package.
KW - Automated assessment
KW - Boolean equation
KW - Computer engineering
KW - Electrical
KW - Logic circuit
KW - Massive open online course
KW - Verilog hardware desctiption language (HDL) model
UR - http://www.scopus.com/inward/record.url?scp=85031762101&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85031762101&partnerID=8YFLogxK
U2 - 10.2316/P.2017.853-023
DO - 10.2316/P.2017.853-023
M3 - Conference contribution
AN - SCOPUS:85031762101
T3 - Proceedings of the IASTED International Conference on Modelling, Simulation and Identification, MSI 2017
SP - 50
EP - 54
BT - Proceedings of the IASTED International Conference on Modelling, Simulation and Identification, MSI 2017
PB - Acta Press
T2 - 2017 IASTED International Conference on Modelling, Simulation and Identification, MSI 2017
Y2 - 19 July 2017 through 20 July 2017
ER -