1,723,796 research outputs found
Daniel Stokols & Oladele Ogunseitan
No full textOral history between Oladele Ogunseitan, Oladele Ogunseitan, Professor of Public Health, founding Chair of the Department of Population Health and Disease Prevention, and Professor of Social Ecology, and Daniel Stokols, Research Professor and Chancellor’s Professor Emeritus in Psychology and Social Behavior and Planning, Policy, and Design, and founding Dean of the School of Social Ecology
PATIENT SATISFACTION WITH PSYCHOTHERAPY IN A NIGERIAN TERTIARY HOSPITAL
No full textCorrespondence: Olaitan Temitayo Oladele, Mental Health Department, LAUTECH Teaching Hospital, Ogbomoso, Oyo state, Nigeria. +2348032069238, Email: [email protected]
Ideology and Oladele Balogun’s perspective on parenthood and the ‘educated person’
No full textEnormous but undue accentuation has been given to the acquisition of certificates and degrees over competence in Africa. Not only does this expand the gulf between thought and praxis, it also implies the compromised course of knowledge production and reproduction in Africa. As a result of the vegetative and epileptic nature of the development agenda in Africa, there has been as many theories as there are scholars who are seeking theoretical solutions but with almost nothing tangible. Oladele Balogun has shown intellectual concerns over this too but with a plausible panacea. Taking traditional Yoruba culture as his cue, Balogun sees a connection between ‘parenthood’ and traditional Yoruba perception of the ‘educated person’ as crucial elements for human development drive in Africa. While I concede that these in themselves are necessary, I contest their sufficiency. Hence, I add a third category – Ideology.Keywords: Oladele Balogun, Parenthood, Pedagogy, Yoruba, Ideolog
The conventional versus a constructionist Scratch programming and first-year students' achievements in higher education classes: experimental data.
No full textGlobally, learning or teaching the first programming (popularly called CS1) remains a significant educational challenge. Indicators such as CS1 students' engagement, failure and attrition rates, and lack of diversity, continue to show the need for innovating the learning or teaching of novice computer science students. To ease initiating novices to programming, Scratch, a visual programming language, has become a staple of K-12 CS1 classes.
As outcomes of a research project aiming to explore a constructionist Scratch pedagogy with novice CS students in higher education, we present these datasets. In the research lasting two successive academic sessions, we conducted two quasi-experimental studies involving four intact CS1 classes in selected public polytechnic in the north central Nigeria. In each study, we randomly assigned the classes to the experimental and control groups, constituting the constructionist Scratch and the conventional CS1 classes, respectively.
Instruments for collecting data include a student profile questionnaire, a pretest, and posttest. Sequel to ethical clearance and permission from the selected schools, we conducted each study during the first semester of each academic session, in the first seven to eight weeks. During the first to second week, we administered students who consented to take part with the questionnaire and the pretest. Learning or teaching in the two classes lasted six weeks. Then both classes took the posttest. An independent CS educator who is not part of this research marked all the achievement tests, following a rubric prepared by the first author. To strengthen the research design and the possibility of arriving at valid causal evidence, we employed a Coarsened Exact Matching (CEM) algorithm to generate matched samples of experimental and control data, which we used in the analysis.
Data presented here includes the raw, unmatched and matched experimental datasets from both studies. A researcher can make use of the data:
To explore if some background variables not addressed in the original research may moderate CS1 students' achievements. For instance, their prior achievements in mathematics, physics, or English.
To uncover some interesting patterns using machine learning algorithms.
To validate the outcome of the original experiment by using the unmatched, matched or newly generated matched samples.
The authors welcome further research collaborations in using the data or the accompanying research instruments.
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sj-docx-1-cjr-10.1177_07340168221142909 - Supplemental material for Pandemic Policing and Community Engagement: Preparedness, Legitimacy and Public Support During the COVID-19 Crisis in Nigeria
No full textSupplemental material, sj-docx-1-cjr-10.1177_07340168221142909 for Pandemic Policing
and Community Engagement: Preparedness, Legitimacy
and Public Support During
the COVID-19 Crisis in Nigeria by Richard Abayomi Aborisade and Oladele Adelere Adeleke in Criminal Justice Review</p
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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