A4 Article in conference proceedings
Estimating Programming Exercise Difficulty using Performance Factors Analysis (2020)


Tirronen, Ville; Tirronen, Maria (2020). Estimating Programming Exercise Difficulty using Performance Factors Analysis. In FIE 2020 : Proceedings of the 50th IEEE Frontiers in Education Conference (Conference proceedings : Frontiers in Education Conference. IEEE. DOI: 10.1109/FIE44824.2020.9274142


JYU authors or editors


Publication details

All authors or editors: Tirronen, Ville; Tirronen, Maria

Parent publication: FIE 2020 : Proceedings of the 50th IEEE Frontiers in Education Conference

Conference:

  • Frontiers in Education Conference

Place and date of conference: Uppsala, Sweden, 21.-24.10.2020

ISBN: 978-1-7281-8962-8

eISBN: 9781728189611

Journal or series: Conference proceedings : Frontiers in Education Conference

ISSN: 1539-4565

eISSN: 2377-634X

Publication year: 2020

Publisher: IEEE

Publication country: United States

Publication language: English

DOI: https://doi.org/10.1109/FIE44824.2020.9274142

Open Access: Publication channel is not openly available

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/74032


Abstract

This Work in Progress Paper studies student and exercise modelling based on pass/fail log data gathered from an introductory programming course. Contemporary education capitalizes on the communications technology and remote study. This can create distance between the teacher and students and the resulting lack of awareness of the difficulties students encounter can lead to low student satisfaction, dropout and poor grades. In many cases, various technological solutions are used to collect individual exercise submissions, but there are little resources for indexing or modelling the exercises in depth. Exercise specific feedback from students may not be easily obtainable either. In the present study, we attempt to create student-exercises models solely on pass/fail log data by using statistical techniques. We conclude that such data is insufficient for student modelling, but that it can be used to credibly estimate the difficulty of programming exercises.


Keywords: information technology; study; students; modelling (creation related to information); evaluation; direction (instruction and guidance); contentment; study performance

Free keywords: exercise modelling; intelligent tutor; learning factors analysis; performance factors analysis


Contributing organizations


Ministry reporting: Yes

Preliminary JUFO rating: 1


Last updated on 2021-08-02 at 14:50