Item Dimensionality Exploration by Means of Construct Map and Categorical Principal Components Analysis

Deliu, Gabriela; Miron, Cristina; Opariuc-Dan, Cristian

doi:10.33225/jbse/19.18.209

Cited by 5 publications

(2 citation statements)

References 15 publications

(11 reference statements)

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“…We selected the number of principal components depending on the specific area of application and the specific data set. However, we used the visual examination of a scree plot approach to determine the number of principal components [36]. Using a scree plot to determine the number of principal components is a common approach, by scanning the scree plot for a point where the amount of variance explained by each subsequent principal component begins to decline.…”

Section: Discussionmentioning

confidence: 99%

Cervical Cancer Perceived Risk Factors Behavior Using Logistic Regression Technique

Haraz,

Elzein,

Chamseddine

et al. 2024

Preprint

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Cervical cancer is one of the ailments that endangers the health of women all over the world and causes infertility. Fortunately, this disease can be avoided. Both the results and participation rates of the current preventative strategy remain poor. Hence, preventative or early detection methods remain challenging and open. In gynecology and computer science fields, few studies on identifying cervical cancer are based on behavior risk factor and machine learning. Moreover, various social and behavioral aspects might often make it more difficult to detect cervical cancer especially in low‑ and middle‑income countries (LMICs). Accordingly, focus on predicting the presence of cervical cancer through behavioral risk factors is the basic structure of this research. We proposed an approach to classify cervical cancer from a social-behavioral perspective using logistic regression to predict cervical cancer. We got significantly improved outcomes than the existing methods. Moreover, we used feature engineering to formulate less dimensionality as a pre-processing step and optimized parameters to be prepared for classification phase. The results proved that using the logistic regression with regularization type L1 had a promising performance. The accuracy of Logistic Regression (LR) L1 was 97.2%. Such results support the proposed work as a reliable classification predictive tool.

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Section: Discussionmentioning

confidence: 99%

Cervical Cancer Perceived Risk Factors Behavior Using Logistic Regression Technique

Haraz,

Elzein,

Chamseddine

et al. 2024

Preprint

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show abstract

“…TAM has been tested and validated in different contexts (Shih et al, 2013) and was extended with different external variables to increase its predictive power (Sepasgozar et al, 2019) resulting into generalized TAM that were reliable and valid as structure (Deliu et al, 2019). However, during this research the results were not found of other in-depth exploration on the adoption of DS tools across pre-service teachers in different national contexts.…”

Section: Introductionmentioning

confidence: 95%

Adoption of Digital Storytelling Tool in Natural Sciences and Technology Education by Pre-Service Teachers Using the Technology Acceptance Model

Lazar

Pânişoară

Pânișoară

2020

JBSE

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This research aimed to contribute to the overall understanding of pre-service teachers’ acceptance of the Digital Storytelling (DS) tool. The primary associations of the Technology Acceptance Model (TAM) were tested in the academic years 2017/2018 and 2018/2019 for statistical significance when the effects of the pre-service training teachers' digital age and status were controlled. Data from 296 pre-service teachers, from second and third study year, majority women considered vulnerable group were collected. The factor analysis and invariance tests on basic TAM were performed. The results revealed that DS tool usage intention was a function of perceived usefulness and ease of use. This research established the TAM applicability with the control variables addition to model the DS tool acceptance by pre-service teachers, as didactic material for natural sciences and technology education. Configural, metric, and scalar invariance were confirmed across both cross-temporal and cross-sectorial groups. Perceived ease of use of DS has strongly influenced both usefulness (β=.571, t=11.958, p<.0001) and intention to use of DS (β=.763, t=19.914, p<.0001), under the influences of the control variables. The outcomes contributed to the general understanding of DS pre-service teachers’ adoption relevant for natural sciences and technology education and for recognition of vulnerable category behavior. Keywords: digital storytelling tool, natural sciences didactics, technology education didactics, pre-service teachers’ digital age, pre-service teachers’ status, TAM model.

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Assessing the competences of the secondary school students for interpretation of movement graphics through standardized tests

Deliu

Ștefan

2020

Tim 19 Physics Conference

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Item Dimensionality Exploration by Means of Construct Map and Categorical Principal Components Analysis

Cited by 5 publications

References 15 publications

Cervical Cancer Perceived Risk Factors Behavior Using Logistic Regression Technique

Cervical Cancer Perceived Risk Factors Behavior Using Logistic Regression Technique

Adoption of Digital Storytelling Tool in Natural Sciences and Technology Education by Pre-Service Teachers Using the Technology Acceptance Model

Assessing the competences of the secondary school students for interpretation of movement graphics through standardized tests

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