@inproceedings{fabcf40dc2f44473b346bd90abd7501e,
title = "Competency mining in large data sets: Preparing large scale investigations in computer science education",
abstract = "In preparation of large scale surveys on computer science competencies, we are developing proper competency models and evaluation methodologies, aiming to define competencies by sets of exiting questions that are testing congruent abilities. For this purpose, we have to look for sets of test questions that are measuring joint psychometric constructs (competencies) according to the responses of the test persons. We have developed a methodology for this goal by applying latent trait analysis on all combinations of questions of a certain test. After identifying suitable sets of questions, we test the fit of the mono-parametric Rasch Model and evaluate the distribution of person parameters. As a test bed for first feasibility studies, we have utilized the large scale Bebras Contest in Germany 2009. The results show that this methodology works and might result one day in a set of empirically founded competencies in the field of Computational Thinking.",
keywords = "Competencies, Computational thinking, Item response theory, Large scale studies, Rasch model",
author = "Peter Hubwieser and Andreas M{\"u}hling",
note = "Publisher Copyright: Copyright {\textcopyright} 2014 SCITEPRESS - Science and Technology Publications All rights reserved.; 6th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2014 ; Conference date: 21-10-2014 Through 24-10-2014",
year = "2014",
doi = "10.5220/0005129203150322",
language = "English",
series = "KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
publisher = "INSTICC Press",
pages = "315--322",
editor = "Ana Fred and Joaquim Filipe and Joaquim Filipe",
booktitle = "KDIR 2014 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
}