Monitoring student frustration level using Blackbox logs

dc.contributor.author	Kurtiker, P.
dc.contributor.author	Wagh, R.S.
dc.date.accessioned	2018-08-30T05:22:45Z
dc.date.available	2018-08-30T05:22:45Z
dc.date.issued	2018
dc.identifier.citation	18. Int. Conf. on Advanced Learning Technologies (ICALT) 9-13 July 2018, Mumbai, India. 2018; 225-226.	en_US
dc.identifier.uri	http://dx.doi.org/10.1109/ICALT.2018.00119
dc.identifier.uri	http://irgu.unigoa.ac.in/drs/handle/unigoa/5384
dc.description.abstract	We use the worldwide source code repository Blackbox to detect frustration among the learners. This study measures frustration by calculating individual student Error Quotient (EQ) score per laboratory session. So higher the EQ score higher is the frustration, similarly lower the EQ score lower is the frustration. The threshold of 0.5 is set, so if the score is greater than or equal to 0.5 the student is said to be frustrated. Similarly, the average score across each laboratory session for each individual student is calculated. The result shows that 13 out of 20 students were frustrated for Object Oriented Programming (OOP) laboratory sessions. The validation was carried out by human observers with the inter rater reliability of Cohens' Kappa as exceptionally high.	en_US
dc.publisher	IEEE	en_US
dc.subject	Computer Science and Technology	en_US
dc.title	Monitoring student frustration level using Blackbox logs	en_US
dc.type	Conference article	en_US