Predicting the Culturally Responsive Teacher Roles With Cultural Intelligence and Self-Efficacy Using Machine Learning Classification Algorithms

Karataş, Kasım; Arpacı, İbrahim; Yildirim, Yusuf

doi:10.1177/00131245221087999

Cited by 9 publications

(6 citation statements)

References 95 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Thus, the restructuring of teacher education programs is imperative to ensure inclusivity and a reflection of diverse perspectives. This approach facilitates the development of a profound understanding of cultural diversity among preservice teachers, equipping them with the requisite skills and knowledge to effectively cater to the needs of a diverse student body (Karataş et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

Predicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANN

Arpaci,

Karataş,

Gün

et al. 2024

Psychology in the Schools

Self Cite

View full text Add to dashboard Cite

This study aims to investigate the predictive role of cultural intelligence, motivation to teach, and “culturally responsive classroom management self‐efficacy” (CRCMSE) in teachers’ sense of efficacy. The study utilized a combination of “structural equation modeling” (SEM), deep learning, and “artificial neural network” (ANN) to analyze data collected from 1061 preservice teachers. The SEM analysis indicated that cultural intelligence, motivation to teach, and CRCMSE significantly predicted the sense of efficacy of the teacher candidates, accounting for 59% of the variance. Additionally, the ANN model accurately predicted the teachers’ sense of efficacy with 75.71% and 75.17% accuracy for training and testing, respectively. The sensitivity analysis revealed that CRCMSE played the most crucial role in predicting the preservice teachers’ sense of efficacy. The deep learning model also predicted the sense of efficacy with an overall accuracy of 74.18%. The utilization of a multimodal analysis approach facilitated the identification of both linear and nonlinear relationships between the constructs.

show abstract

Section: Discussionmentioning

confidence: 99%

Predicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANN

Arpaci,

Karataş,

Gün

et al. 2024

Psychology in the Schools

Self Cite

View full text Add to dashboard Cite

show abstract

“…The concept of culturally responsive teaching was implemented in classrooms with students from diverse backgrounds and cultures [32]. Particularly, Karats et al [33] characterized culturally responsive teaching as an approach to understanding students in constructing respective knowledge, learning about student life, being conscious of sociocultural aspects, recognizing diversity, and employing culturally appropriate teaching strategies to support all students. Remedial educators should practice culturally responsive teaching to improve existing remedial educational practices.…”

Section: Literature Reviewmentioning

confidence: 99%

The challenges of implementing cultural-based teaching in remedial education: analyses and recommendations

Anuas,

Nasri,

Alias

2024

IJERE

View full text Add to dashboard Cite

<span lang="EN-US">In remedial education, teachers play a crucial role in ensuring students from diverse backgrounds master language literacy skills. The current implementation of cultural-based teaching is perceived as an effort to assist remedial students from diverse backgrounds and cultures to learn effectively. The study aims to analyze teachers’ perceptions of challenges in implementing cultural-based teaching in remedial education for language literacy. The study employed a quantitative approach by distributing questionnaires to 252 remedial teachers recruited randomly from primary schools in the Malaysian middle-state zone. The collected data were evaluated descriptively, and the results revealed that these teachers experienced challenges in four areas, namely teaching resources, remedial curricula, teacher knowledge, and time allocation. Moreover, the findings demonstrated that demographic factors, such as gender, school location, and years of teaching experience, did not produce significant impacts on the aforementioned challenges. Simultaneously, this study explored teachers’ perceptions of recommending culturally responsive teaching approaches in remedial education as an alternative to the current cultural-based teaching methodology</span><span lang="EN-US">.</span>

show abstract

“…Another merit is that the algorithm becomes shorter and simpler by trimming any useless parts of the rule. This makes the algorithm easier to understand and interpret than other algorithms [12]. Multilayer perceptrons (MPs) are a class of feed-forward artificial neural networks (ANNs).…”

Section: Literature Reviewmentioning

confidence: 99%

Adaptive Analysis of Machine Learning Algorithms on Medical Datasets for Disease Prediction

Elsayed,

Ismail,

Abdel-Gawad

et al. 2024

Information Sci. Appl.

View full text Add to dashboard Cite

This paper aims to analyze and evaluate the performance of different classification algorithms on medical datasets and gives some tips and guidelines for choosing the right algorithm for the dataset. For this purpose, twelve medical datasets were selected from the UCI repository, including breast cancer data, chronic kidney disease, cryotherapy, hepatitis, immunotherapy, Indian Liver Patient Dataset (ILPD), liver disorders, pima diabetes, risk factors cervical cancer, statlog (heart) dataset, dermatology and lung cancer. The selected classifiers for performance evaluation are Bagging, IBK, J48, JRip, Multilayer Perceptron (MP), Naïve Bayes (NB), Support Vector Machine (SVM), ZeroR and Voting Frequency Intervals (VFI). The algorithms were implemented on datasets using the WEKA tool and 10-fold cross-validation. Experimental results and analysis for all measures were introduced to guideline researchers who seek to achieve and how to balance different measures. Additionally, challenges and future directions were presented at the end of this paper.

show abstract

Predicting the Culturally Responsive Teacher Roles With Cultural Intelligence and Self-Efficacy Using Machine Learning Classification Algorithms

Cited by 9 publications

References 95 publications

Predicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANN

Predicting teachers’ sense of efficacy: A multimodal analysis integrating SEM, deep learning, and ANN

The challenges of implementing cultural-based teaching in remedial education: analyses and recommendations

Adaptive Analysis of Machine Learning Algorithms on Medical Datasets for Disease Prediction

Contact Info

Product

Resources

About