Classification of Strategies for Solving Programming Problems using AoI Sequence Analysis

Abstract : This eye tracking study examines participants' visual attention when solving algorithmic problems in the form of programming problems. The stimuli consisted of a problem statement, example output, and a set of multiple-choice questions regarding variables, data types, and operations needed to solve the programming problems. We recorded eye movements of students and performed an Area of Interest (AoI) sequence analysis to identify reading strategies in terms of participants' performance and visual effort. Using classical eye tracking metrics and a visual AoI sequence analysis we identified two main groups of participants-effective and ineffective problem solvers. This indicates that diversity of participants' mental schemas leads to a difference in their performance. Therefore, identifying how participants' reading behavior varies at a finer level of granularity warrants further investigation.
Complete list of metadatas

Cited literature [20 references]  Display  Hide  Download

https://hal.inria.fr/hal-02084127
Contributor : Tanja Blascheck <>
Submitted on : Friday, March 29, 2019 - 2:11:39 PM
Last modification on : Tuesday, April 9, 2019 - 2:25:04 PM
Long-term archiving on: Sunday, June 30, 2019 - 2:47:15 PM

File

Obaidellah_2019_Classification...
Files produced by the author(s)

Identifiers

Collections

Citation

Unaizah Obaidellah, Michael Raschke, Tanja Blascheck. Classification of Strategies for Solving Programming Problems using AoI Sequence Analysis. ETRA 2019 - Symposium on Eye Tracking Research and Applications, Jun 2019, Denver, United States. ⟨10.1145/3314111.3319825⟩. ⟨hal-02084127⟩

Share

Metrics

Record views

85

Files downloads

267