NDLI: Mining Relevant Examples for Learning in ITS Student Models

Content Provider	IEEE Xplore Digital Library
Author	Chaturvedi, R. Ezeife, C.I.
Copyright Year	2014
Description	Author affiliation: Sch. of Comput. Sci., Univ. of Windsor, Windsor, ON, Canada (Chaturvedi, R.; Ezeife, C.I.)
Abstract	An Intelligent Tutoring System (ITS) provides direct customized instruction or feedback to students while they perform a task in a tutoring system without the intervention of a human. One of the main functions of an ITS system is to present its students with course materials that are most appropriate to their current knowledge of domain concepts, example being one of the course materials. ITS systems typically compare and analyze student model (SM) components for student's current knowledge of concepts (main topics, e.g. Scanf in C programming) that are required to understand the next example (e.g. Codes for scanf) suitable for learning a task (e.g. Write C code to read 2 integers from the keyboard). Existing systems such as NavEx and PADS perform an exhaustive matching of student knowledge level with all examples in the database. This research proposes a task-based technique for managing and classifying examples for more effective retrieval of relevant examples for learning a task. We propose a system called EASK for translating task and example solutions into concepts for similarity matching, which is more readily available, easily extendible and adaptable to other domains. Examples and tasks are represented as vectors of weights computed with term frequency measure TFIDF that signify the importance of a concept for an example. Examples most similar to a task are found by using a classification method called k-NN, which finds the closeness between different objects such as examples and tasks using cosine similarity measure and selecting the k objects (examples) with highest similarity scores. As a by-product, k-NN also predicts the class label (difficulty level) of the task. Our proposed model achieves this prediction with 89% accuracy.
Starting Page	743
Ending Page	750
File Size	247111
Page Count	8
File Format	PDF
ISBN	9781479962396
DOI	10.1109/CIT.2014.31
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-11
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Analytical models Adaptation models example-based Learning Computational modeling data mining Materials student model adaptation Vectors Indexes classification
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
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8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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