ser Knowledge Modeling Data (Students' Knowledge Levels on DC Electrical Machines)

Donated on 6/19/2013

The dataset is about the users' learning activities and knowledge levels on subjects of DC Electrical Machines. The dataset had been obtained from online web-courses and reported in my Ph.D. Thesis.

Dataset Characteristics

Multivariate

Subject Area

Computer Science

Associated Tasks

Classification

Feature Type

Real

# Instances

403

# Features

5

Dataset Information

Additional Information

-- The users' knowledge class were classified by the authors using intuitive knowledge classifier (a hybrid ML technique of k-NN and meta-heuristic exploring methods), k-nearest neighbor algorithm. See article for more details on how the users' data was collected and evaluated by the user modeling server. Kahraman, H. T., Sagiroglu, S., Colak, I., Developing intuitive knowledge classifier and modeling of users' domain dependent data in web, Knowledge Based Systems, vol. 37, pp. 283-295, 2013. Kahraman, H. T. (2009). Designing and Application of Web-Based Adaptive Intelligent Education System. Gazi University Ph. D. Thesis, Turkey, 1-156.

Has Missing Values?

No

Variable Information

STG (The degree of study time for goal object materails), (input value) SCG (The degree of repetition number of user for goal object materails) (input value) STR (The degree of study time of user for related objects with goal object) (input value) LPR (The exam performance of user for related objects with goal object) (input value) PEG (The exam performance of user for goal objects) (input value) UNS (The knowledge level of user) (target value) Class Distribution: the class value (UNS). Very Low: 50 Low:129 Middle: 122 high 130

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Creators

Hamdi Kahraman

Ilhami Colak

Seref Sagiroglu

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