Author
Listed:
- Enrique Sánchez Acosta
(Department of Computer Science, Universidad Europea, Madrid, Spain)
- Juan José Escribano Otero
(Department of Computer Science, Universidad Europea, Madrid, Spain)
Abstract
Presently, most platforms used on the selection of Massive Open Online Courses (MOOC) available online have various automated methods of assessment. These type of tools are based on applications that analyze the answers using a pre-correction algorithm. Most of these programs run several types of automatic assessment, but the possible use of the technology for each of them differs with respect to the kind of automation applied. The role of technology in the objective test for online education has become extremely common, so it can be found in various MOOC platforms with this type of questions or quizzes, because the assessment system can be fully computerized (from the test design to its correction and reporting). However, not all of the assessment instruments can be easily implemented in automatic mode with the use of technology. This paper seeks to research and clarify a type of assessment tool in which the use of technologies is quite low, namely, the essay question type and within them, the short answer question type or free text question type, using regular expressions. The large number of students who would be in MOOC prevents a teacher from assessing responses of thousands of students in a finite time without the aid of technology. This research analyzes the results of an MOOC from hundreds of students to verify that the use of regular expressions in an MOOC platform is not only recommended but also necessary.
Suggested Citation
Enrique Sánchez Acosta & Juan José Escribano Otero, 2014.
"Automated Assessment of Free Text Questions for MOOC Using Regular Expressions,"
Information Resources Management Journal (IRMJ), IGI Global, vol. 27(2), pages 1-13, April.
Handle:
RePEc:igg:rmj000:v:27:y:2014:i:2:p:1-13
Download full text from publisher
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:igg:rmj000:v:27:y:2014:i:2:p:1-13. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Journal Editor (email available below). General contact details of provider: https://www.igi-global.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.