z-logo
open-access-imgOpen Access
Automated Problem Generator For Asynchronous Learning
Author(s) -
Thomas A. Lacksonen
Publication year - 2020
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--8944
Subject(s) - computer science , asynchronous communication , generator (circuit theory) , asynchronous learning , artificial intelligence , computer network , synchronous learning , psychology , mathematics education , teaching method , power (physics) , physics , quantum mechanics , cooperative learning
An Engineering Economy course was taught in an asynchronous learning environment. Since the course is primarily mathematical story problem-based material, a technique was required to replace the traditional ‘instructor solves problems at the chalkboard’ portion of a lecture-based course. The Dynamic Engineering Economy Problem (DEEP) generators were designed on a spreadsheet. Each of the 29 generators could create quasi-random problem sets and solutions for one class of engineering economy problems. To assist students, context-sensitive help was provided for all data elements and problem sections. Students were guided to the solution stepby-step, with answer checking, partial solution, or complete solution available at each step. Upon completion of one problem, additional problems could be generated if desired. Visual Basic macros attached to the spreadsheet generated problems, calculated solutions, checked student answers, and displayed solutions. The generators were used in both an asynchronous distance education section and a self-paced computer lab-based section of Engineering Economy. In both cases, the hands-on learning led to high student satisfaction and a significant understanding of the material. Similar generators could be developed for the problem-based component of any technical course.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom