Multiple-choice question generation with auto-generated distractors for computer-assisted educational assessment

2021 ◽  
Author(s):  
Bidyut Das ◽  
Mukta Majumder ◽  
Santanu Phadikar ◽  
Arif Ahmed Sekh
Keyword(s):  
Multiple Choice ◽  
Educational Assessment ◽  
Multiple Choice Question ◽  
Computer Assisted ◽  
Question Generation

Methods and Tools for Online Objective Testing

2011 ◽  
pp. 1409-1417
Author(s):  
Gennaro Costagliola ◽  
Filomena Ferrucci ◽  
Vittorio Fuccella
Keyword(s):  
Correct Answer ◽  
Multiple Choice ◽  
Question Type ◽  
Multiple Choice Question ◽  
Computer Assisted ◽  
Objective Testing ◽  
E Learning ◽  
Objective Tests ◽  
Knowledge Evaluation

Online Testing, also known as Computer Assisted Assessment (CAA), is a sector of e-learning aimed at assessing learner’s knowledge through e-learning means. In recent years, the means for knowledge evaluation have evolved in order to satisfy the necessity of evaluating a big mass of learners in strict times: objective tests, more rapidly assessable, have gained a heavier weight in the determination of learners’ results. Multiple Choice question type is extremely popular in objective tests, since, among other advantages, a large number of tests based on it can be easily corrected automatically. These items are composed of a stem and a list of options. The stem is the text that states the question. The only correct answer is called the key, whilst the incorrect answers are called distractors (Woodford & Bancroft, 2005).

Pedagogical Ontology Modelling for Cell Biology Domain With an Algorithm for Question Generation

2021 ◽  
pp. 144-168
Author(s):  
Gerard Deepak ◽  
Ayush Kumar ◽  
Santhanavijayan A. ◽  
Pushpa C. N. ◽  
Thriveni J. ◽  
...  
Keyword(s):  
Cell Biology ◽  
Domain Knowledge ◽  
Multiple Choice ◽  
Multiple Choice Question ◽  
Question Generation ◽  
Cell Organelles ◽  
Domain Experts ◽  
Educational Pedagogy ◽  
And Behavior ◽  
The Relationship

In this chapter, an ontology that structures all the cell organelles and their parts are modelled to cognitively model domain knowledge by explicitly establishing relationships among them. The ontologies are modelled depicting the cell as a system and the parts of the cell as the subclasses of the cell along with various functionalities and behavior. The model further focuses on education pedagogy to generate questions based on the modelled ontologies. Furthermore, the defined ontologies are made consistent by defining the classes and the relationship between them, initializing the instances and axiomatizing the developed ontological content. The modelled ontologies are semiotically evaluated using various learners and domain experts. An overall reuse ratio of 0.91 has been achieved, and the proposed ontology has been differentiated from the existing cell ontologies by focusing on an educational pedagogy. Ultimately, an ontology-focused algorithm for multiple choice question generation has been proposed for cell biology as a domain of choice with an accuracy of 90.03%.

scholarly journals Ontology-Based Multiple Choice Question Generation

2015 ◽  
Vol 30 (2) ◽  
pp. 183-188 ◽  
Author(s):  
Tahani Alsubait ◽  
Bijan Parsia ◽  
Ulrike Sattler
Keyword(s):  
Multiple Choice ◽  
Multiple Choice Question ◽  
Question Generation

A Novel Student-Led Approach to Multiple-Choice Question Generation and Online Database Creation, With Targeted Clinician Input

2015 ◽  
Vol 27 (2) ◽  
pp. 182-188 ◽  
Author(s):  
Benjamin H. L. Harris ◽  
Jason L. Walsh ◽  
Saadia Tayyaba ◽  
David A. Harris ◽  
David J. Wilson ◽  
...  
Keyword(s):  
Multiple Choice ◽  
Multiple Choice Question ◽  
Online Database ◽  
Question Generation
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