Investigating the Performance of Artificial Neural Networks in Predicting Affective Responses

In this study it is aimed to examine the performance of an artificial neural network trained using items reflecting a latent trait in predicting responses to an item reflecting the same trait. This latent trait is the awareness of being able to communicate with people from different cultures, which is included in the PISA 2018 application. Relevant scale items were used as research variables. In addition to determining the extent to which the predicted responses overlap with the actual responses by analyzing the artificial neural network models, it was examined how the predicted responses affect the assumed latent construct and the reliability of the responses. Thus, the performance of artificial neural networks in predicting responses to affective items was evaluated.

Authors

Institutions

Publication Details

Journal
Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi
Published
2024-11-19
DOI
https://doi.org/10.21031/epod.1525454
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Investigating the Performance of Artificial Neural Networks in Predicting Affective Responses

İzzettin AYDOĞAN, Osman Tat
Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi
Data Mining and Machine Learning Applications
article

Investigating the Performance of Artificial Neural Networks in Predicting Affective Responses

İzzettin AYDOĞAN, Osman Tat
article en

Abstract

In this study it is aimed to examine the performance of an artificial neural network trained using items reflecting a latent trait in predicting responses to an item reflecting the same trait. This latent trait is the awareness of being able to communicate with people from different cultures, which is included in the PISA 2018 application. Relevant scale items were used as research variables. In addition to determining the extent to which the predicted responses overlap with the actual responses by analyzing the artificial neural network models, it was examined how the predicted responses affect the assumed latent construct and the reliability of the responses. Thus, the performance of artificial neural networks in predicting responses to affective items was evaluated.

Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi
Van Yüzüncü Yıl Üniversitesi (TR)
Openalex Percentile: Top 61%
Data Mining and Machine Learning Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Investigating the Performance of Artificial Neural Networks in Predicting Affective Responses — İzzettin AYDOĞAN, Osman Tat · Eğitimde ve Psikolojide Ölçme ve Değerlendirme Dergisi (2024) | TGRS Research Map | TGRS