ArticleHeliyon2023
Improving the quality of reporting findings using computer data analysis applications in educational research in context.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed, 8 citations in OpenAlex.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Data analysis is an important step in the research process as it influences the quality and standard of reporting research findings. Based on a review of the content of 255 doctorate theses, the use of computer applications for data analysis in educational research was assessed. It was feasible to assess how extensively used and accepted computer packages had become in educational research using an aspect of the diffusion of innovations theory as part of the conceptual framework. The results showed that the use of computer applications to analyse data was more prevalent among researchers using quantitative and mixed-methods research methodologies than among qualitative educational researchers. Educational researchers have not yet fully adopted innovative computer data analysis techniques in their research. It is evident that they use traditional technologies more than computer applications in their research. Name dropping of the computer applications used without employing the language or visualisations features provided by the applications was rife. This article bridges the gap between methodological scholarship and the use of computer applications in data analysis. It illuminates the potential of computer software to enhance the quality of the reporting of findings. The article aims to contribute to improvements in the standard of research reporting and the attributes of the graduates. The practical methodological advice in this article is aimed at guiding researchers who consider using computer packages in data analysis, irrespective of their methodological orientation. It stimulates debate on the use of computer applications in data analysis.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.