A neuro-fuzzy model for evaluating and predicting computational thinking skills of students
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| Udgivet i: | Scientific Reports (Nature Publisher Group) vol. 15, no. 1 (2025), p. 36003-36016 |
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Nature Publishing Group
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| Online adgang: | Citation/Abstract Full Text Full Text - PDF |
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| 100 | 1 | |a Filiz, Ahsen |u Department of Mathematics and Science Education, Education Faculty, Biruni University, Istanbul, Turkey (ROR: https://ror.org/01nkhmn89) (GRID: grid.488405.5) (ISNI: 0000 0004 4673 0690) | |
| 245 | 1 | |a A neuro-fuzzy model for evaluating and predicting computational thinking skills of students | |
| 260 | |b Nature Publishing Group |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Computational thinking skill is an important skill individuals should acquire to meet the requirements of the digital age. The aim of the study is to predict the computational thinking skills of middle school students through ANFIS approach, which is an adaptive neural network-based fuzzy logic. Students’ computational thinking skill scores were predicted by creating a model based on grade level and academic achievement variables. Grade level and academic achievement served as the model’s input variables, and computational thinking skill scores served as the model’s output variable. Data were collected using personal information form and computational thinking scale. A comparison was made between students’ real and artificial computational thinking skill scores using statistical methods. In the study, a strong and favorable association between the artificial scores produced using the ANFIS technique and the actual scores was discovered. Furthermore, there was no statistically significant difference between the real and artificial scores for computational thinking skills. These results indicate that the ANFIS approach is a suitable alternative analysis method for predicting students’ computational thinking skills. The study provides a good example in the field of education where artificial intelligence can be used to predict students’ educational characteristics. | |
| 653 | |a Problem solving | ||
| 653 | |a Students | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Curricula | ||
| 653 | |a Communication | ||
| 653 | |a Interdisciplinary aspects | ||
| 653 | |a International organizations | ||
| 653 | |a Mathematics | ||
| 653 | |a 21st century | ||
| 653 | |a Learning activities | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Statistical methods | ||
| 653 | |a Fuzzy logic | ||
| 653 | |a Skills | ||
| 653 | |a Cooperative learning | ||
| 653 | |a Academic achievement | ||
| 653 | |a Neural networks | ||
| 653 | |a Digital Age | ||
| 653 | |a Algorithms | ||
| 653 | |a Critical thinking | ||
| 653 | |a Education | ||
| 653 | |a Digital literacy | ||
| 653 | |a Social | ||
| 653 | |a Economic | ||
| 773 | 0 | |t Scientific Reports (Nature Publisher Group) |g vol. 15, no. 1 (2025), p. 36003-36016 | |
| 786 | 0 | |d ProQuest |t Science Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3261606109/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3261606109/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3261606109/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |