Research Article
Analysis of Computational Thinking Ability Student Mathematics with Application Problem Based Learning Model
@INPROCEEDINGS{10.4108/eai.1-11-2022.2326172, author={Junita Sari Sihotang and Bornok Sinaga and Hamidah Nasution}, title={Analysis of Computational Thinking Ability Student Mathematics with Application Problem Based Learning Model}, proceedings={Proceedings of the 4th International Conference on Science and Technology Applications, ICoSTA 2022, 1-2 November 2022, Medan, North Sumatera Province, Indonesia}, publisher={EAI}, proceedings_a={ICOSTA}, year={2023}, month={1}, keywords={analysis computational thinking ability problem based learning}, doi={10.4108/eai.1-11-2022.2326172} }
- Junita Sari Sihotang
Bornok Sinaga
Hamidah Nasution
Year: 2023
Analysis of Computational Thinking Ability Student Mathematics with Application Problem Based Learning Model
ICOSTA
EAI
DOI: 10.4108/eai.1-11-2022.2326172
Abstract
This study aims to: (1) Describing students’ mathematical computational thinking ability after applying the problem based learning’s (PBL) model; (2) Describing students' difficulties in completing the students' mathematical computational thinking ability test after applying the problem based learning (PBL) model. The subjects of this study were students are 8th grade student of SMP Negeri 4 Tebing Tinggi in the 2022/2023 academic year while the object in this study was the students' mathematical computational thinking ability by applying a problem based learning model. The results showed that: (1) Students' mathematical computational thinking ability is getting better after the implementation of the problem based learning (PBL) model compared to previous learning that still uses conventional learning. From 42 students, there are 10 students who have high category of mathematical computational thinking ability, 23 students who have medium category, and 9 students who have low category. For each indicator, it is described as follows: The decomposition indicator of the average value of students in the medium category, the pattern recognition indicator in the medium category, the algorithm in the medium category, abstraction and generalization in the low category (2) Students with high category have no difficulty in any indicator, students with moderate category have difficulty in procedure and concept’s criteria.