Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming
The revealed analysis studies on pair programming so far indicate that pair programming has produced affirmative effects on some aspects of students’ performance. In the academic field, the usual practice of pair programming would be pairing the students in line with the programming skills of t...
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my.unimas.ir.366052022-09-12T02:47:14Z http://ir.unimas.my/id/eprint/36605/ Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming Chai, Soo See Goh, Kok Luong Wang, Hui Hui Wee, Bui Lin QA75 Electronic computers. Computer science The revealed analysis studies on pair programming so far indicate that pair programming has produced affirmative effects on some aspects of students’ performance. In the academic field, the usual practice of pair programming would be pairing the students in line with the programming skills of the students by the respective lecturers. This means, compatibility of the students in terms of their programming skills is the main focus when the pairing was done by the lecturers. Yet, research on elements that the students are looking into when they are given the liberty to decide on their partner in pair programming is lacking. In this study, a multi-layer perceptron (MLP) is developed to predict the preference of opting pair programming over solo programming. The Bayesian Information Criterion was used to select the best features in the prediction. The potential of unstructured text entered by the participants as comments in the questionnaire is incorporated in the MLP model to verify its capabilities towards prediction accuracy, i.e., to verify whether their comments are connected to their preference for pair programming versus solo programming. It was found that, when the students are given the freedom to choose their partner in pair programming, in the context of Malaysia, the students would pay attention to the ethnic criterion. This also suggests that the unstructured texts in the form of comments submitted by the participants in the questionnaire did not contribute to their choices on whether to undertake solo or pair programming. 2021 Proceeding PeerReviewed text en http://ir.unimas.my/id/eprint/36605/1/Chai%20Soo%20See.pdf Chai, Soo See and Goh, Kok Luong and Wang, Hui Hui and Wee, Bui Lin (2021) Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming. In: 2021 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), 13-15 Sept. 2021, Kota Kinabalu, Malaysia. https://ieeexplore.ieee.org/document/9573795 |
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QA75 Electronic computers. Computer science Chai, Soo See Goh, Kok Luong Wang, Hui Hui Wee, Bui Lin Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming |
description |
The revealed analysis studies on pair
programming so far indicate that pair programming has
produced affirmative effects on some aspects of students’
performance. In the academic field, the usual practice of pair
programming would be pairing the students in line with the
programming skills of the students by the respective lecturers.
This means, compatibility of the students in terms of their
programming skills is the main focus when the pairing was
done by the lecturers. Yet, research on elements that the
students are looking into when they are given the liberty to
decide on their partner in pair programming is lacking. In this
study, a multi-layer perceptron (MLP) is developed to predict
the preference of opting pair programming over solo
programming. The Bayesian Information Criterion was used to
select the best features in the prediction. The potential of
unstructured text entered by the participants as comments in
the questionnaire is incorporated in the MLP model to verify
its capabilities towards prediction accuracy, i.e., to verify
whether their comments are connected to their preference for
pair programming versus solo programming. It was found that,
when the students are given the freedom to choose their
partner in pair programming, in the context of Malaysia, the
students would pay attention to the ethnic criterion. This also
suggests that the unstructured texts in the form of comments
submitted by the participants in the questionnaire did not
contribute to their choices on whether to undertake solo or pair
programming. |
format |
Proceeding |
author |
Chai, Soo See Goh, Kok Luong Wang, Hui Hui Wee, Bui Lin |
author_facet |
Chai, Soo See Goh, Kok Luong Wang, Hui Hui Wee, Bui Lin |
author_sort |
Chai, Soo See |
title |
Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming |
title_short |
Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming |
title_full |
Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming |
title_fullStr |
Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming |
title_full_unstemmed |
Incorporating Unstructured Text in Multi-Layer Perceptron (MLP) Network: Factors Affecting Partner Selection in Pair Programming |
title_sort |
incorporating unstructured text in multi-layer perceptron (mlp) network: factors affecting partner selection in pair programming |
publishDate |
2021 |
url |
http://ir.unimas.my/id/eprint/36605/1/Chai%20Soo%20See.pdf http://ir.unimas.my/id/eprint/36605/ https://ieeexplore.ieee.org/document/9573795 |
_version_ |
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