Hierarchical linear modelling of educational outcomes in secondary schools: What matters – teachers’ or administrators’ input?

Ekpenyong, John Asuquo; Owan, Valentine Joseph; Ogar, Joseph O.; Undie, John A.

doi:10.1080/2331186x.2022.2133491

Cited by 11 publications

(22 citation statements)

References 49 publications

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“…Three-factor Confirmatory Factor Analysis Model of the Questionnaire According to Owan et al (2021), the CFA "determines the accuracy with which variables measure their respective factors (constructs); assesses the acceptability or otherwise of hypothesized models based on theoretical models; verifies the existence of relationships established by the EFA between observed variables (indicators) and their supposed constructs" (p. 11). Furthermore, a CFA was conducted to confirm the EFA's results and gauge the theoretical models' acceptance (Ekpenyong, et al, 2022;Owan, Owan, & Lata,2022). The Maximum Likelihood (ML) estimation technique was used for the CFA analysis in the current study, with the result presented in Figure 1.…”

Section: Confirmatory Factor Analysis (Cfa)mentioning

confidence: 99%

Digital Learning Technology Usage and Teaching Effectiveness of Business Educators in Nigeria’s South-South Universities

Stephen Bepeh,

Ojini,

Udo

et al. 2023

JCT

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All subjects may be taught well, but a big part of it is how the instructor uses technology to make learning beneficial for the learners. This study investigated the extent to which digital learning technologies’ usage influences the teaching effectiveness of business educators in Nigeria’s South-South universities. Two specific objectives were established and two null hypotheses were tested. The level of significance was set at 0.05. Relevant literature was reviewed. The study adopted a predictive correctional research design. The study participants were 170 business educators from twelve universities in South-South Nigeria. No sample was drawn because the population was manageable. Data was generated using a 24-item Likert scale questionnaire called the "Digital Learning Technologies and Teaching Effectiveness Questionnaire (DLTTEQ). Seven experts from the University of Calabar validated the DLTTEQ. The study’s assumptions were evaluated using simple linear regression. The use of virtual reality simulation and teleconferencing by business educators in Nigeria’s South-South universities was found to significantly predict their teaching effectiveness. Sequel to the research findings, the study recommends that the national government should foster simulation-based education by building a digital learning environment appropriate for Business Education. The insights of this study call for the implementation of international best practices in order to help learners and instructors transition from digital immigrants to electronic natives.

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Section: Confirmatory Factor Analysis (Cfa)mentioning

confidence: 99%

Digital Learning Technology Usage and Teaching Effectiveness of Business Educators in Nigeria’s South-South Universities

Stephen Bepeh,

Ojini,

Udo

et al. 2023

JCT

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“…There was a need to develop and validate the tools due to the unavailability of a previously developed instrument to measure the variables of this study, especially in the study's context. The EOQ was designed to measure students' affective and psychomotor outcomes (See Ekpenyong et al, 2022;, while students' cognitive outcome was measured using average scores from their sessional results. The FIQ (four points scale) had 13 items, CIQ (four points scale) had 18 items, and the EOQ (six points scale) had 30 items.…”

Section: Measures and Instrumentsmentioning

confidence: 99%

“…Figures 3 and 4 show that the CFA loadings per construct were almost identical to those of the EFA. The CFA figure for the EOQ can be found in two studies from the same project (Ekpenyong et al, 2022;. The fit of the CFA models was evaluated using several fit indices such as the Chi-Square, GFI ("Goodness of Fit Index"), NFI ("Normed Fit Index"), RFI ("Relative Fit Index"), IFI ("Incremental Fit Index"), TLI ("Tucker-Lewis Index"), CFI ("Comparative Index"), and RMSEA ("Root Mean Square Error of Approximation").…”

Section: Confirmatory Factor Analysis (Cfa)mentioning

confidence: 99%

“…Under Bloom's taxonomy, learning objectives should be structured to modify learners' cognitive, affective and psychomotor attributes (Bloom, 1994;Bloom et al, 1956;Krathwohl, 2002). Therefore, a complete assessment of students' learning outcomes must focus on three domains to give a better picture of how educational goals are attained (Bassey et al, 2019;Ekpenyong et al, 2022;Owan, Ekpenyong et al, 2022). To bridge the gap in the literature on students' learning outcomes, the cognitive, affective and psychomotor dimensions were all considered in the present study.…”

Section: Introductionmentioning

confidence: 99%

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Family and community inputs as predictors of students overall, cognitive, affective and psychomotor learning outcomes in secondary schools

Ekpenyong

Owan

Mbon

et al. 2023

JPR

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“…These outcomes are important because they impact students' ability to succeed in school and their future careers and reflect the education system's effectiveness. Learning outcomes are measured by the quality of students' cognitive, affective, and psychomotor skills after exposure to lesson contents and experiences in the short-or long-term (Ekpenyong et al, 2022;. Cognitive learning outcomes refer to students' knowledge, understanding, and intellectual development from their educational experiences.…”

Section: Introductionmentioning

confidence: 99%

Predicting students’ multidimensional learning outcomes in public secondary schools: The roles of school facilities, administrative expenses and curriculum

2023

JALT

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Previous research has assessed school facilities, administrative expenditures and curriculum and their relative contributions to students' cognitive learning outcomes. This suggested the need to investigate further how these predictors may impact students' affective and psychomotor outcomes. The current research studied the combined and relative prediction of school facilities, administrative expenses and curriculum on students' overall cognitive, affective and psychomotor learning outcomes in public secondary schools. A cross-sectional research design was employed in this study, involving 87 school administrators and a randomly selected group of 915 senior secondary class II (SS2) students. For data collection, we utilised the School Inputs Questionnaire (SIQ) and Educational Outcomes Questionnaire (EOQ), both developed by the researchers and validated through expert assessments, including content validity, Exploratory Factor Analysis (EFA) for dimensionality, Confirmatory Factor Analysis (CFA) for goodness of fit, and reliability using Cronbach's alpha. The results of these assessments demonstrated acceptable outcomes aligned with international standards. Hierarchical regression analysis was conducted to analyse the collected data. The findings indicated that enhancing the provision of quality school facilities, administrative expenses, and school curricula improved students' overall cognitive, affective, and psychomotor learning outcomes. Specifically, administrative expenses and school curriculum had significant predictive power for students' overall cognitive, affective, and psychomotor learning outcomes. However, while school facilities significantly predicted students' overall, affective, and psychomotor dimensions, they did not significantly predict the cognitive dimension. These findings offer valuable insights for policymakers and educators aiming to enhance the educational quality in public secondary schools.

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Hierarchical linear modelling of educational outcomes in secondary schools: What matters – teachers’ or administrators’ input?

Cited by 11 publications

References 49 publications

Digital Learning Technology Usage and Teaching Effectiveness of Business Educators in Nigeria’s South-South Universities

Digital Learning Technology Usage and Teaching Effectiveness of Business Educators in Nigeria’s South-South Universities

Family and community inputs as predictors of students overall, cognitive, affective and psychomotor learning outcomes in secondary schools

Predicting students’ multidimensional learning outcomes in public secondary schools: The roles of school facilities, administrative expenses and curriculum

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