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Estimating the replicability of technology education research.

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Title: Estimating the replicability of technology education research.
Authors: Buckley, Jeffrey1 jeffrey.buckley@tus.ie, Hyland, Tomás1, Seery, Niall1
Source: International Journal of Technology & Design Education. Sep2023, Vol. 33 Issue 4, p1243-1264. 22p.
Subject Terms: *Technology education, Truthfulness & falsehood, Statistics, Data extraction, Hypothesis
Abstract: Technology education research is a growing field, with the rate of growth increasing over the last 2 decades. As the field grows, it is paramount that credibility is maintained in published findings. To date there is no evidence to suggest a lack trust is warranted, however in the midst of the replication crisis there is need to ensure continued rigour. This article presents a z-curve analysis of the replicability of quantitative research in technology education since 1983 using statcheck for automated data extraction. The results indicate that authors often mis-report p-values, typically due to rounding errors, with a small percentage (1.59%) of inconsistently reported p-values leading to decision errors in terms of statistical inference. With respect to replicability, overall it is estimated that 55.7% of reported quantitative results in technology education would replicate, however since 2020 this estimate appears to be increasing. These results do not indicate specific findings which are likely or unlikely to replicate, but do suggest a need to invest effort in identifying studies which would have a high value in being replicated, particularly in the timeframe of work published from 2010 to 2020. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Technology & Design Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Technology+%26+Design+Education%22">International Journal of Technology & Design Education</searchLink>. Sep2023, Vol. 33 Issue 4, p1243-1264. 22p.
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  Data: *<searchLink fieldCode="DE" term="%22Technology+education%22">Technology education</searchLink><br /><searchLink fieldCode="DE" term="%22Truthfulness+%26+falsehood%22">Truthfulness & falsehood</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics%22">Statistics</searchLink><br /><searchLink fieldCode="DE" term="%22Data+extraction%22">Data extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Hypothesis%22">Hypothesis</searchLink>
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  Data: Technology education research is a growing field, with the rate of growth increasing over the last 2 decades. As the field grows, it is paramount that credibility is maintained in published findings. To date there is no evidence to suggest a lack trust is warranted, however in the midst of the replication crisis there is need to ensure continued rigour. This article presents a z-curve analysis of the replicability of quantitative research in technology education since 1983 using statcheck for automated data extraction. The results indicate that authors often mis-report p-values, typically due to rounding errors, with a small percentage (1.59%) of inconsistently reported p-values leading to decision errors in terms of statistical inference. With respect to replicability, overall it is estimated that 55.7% of reported quantitative results in technology education would replicate, however since 2020 this estimate appears to be increasing. These results do not indicate specific findings which are likely or unlikely to replicate, but do suggest a need to invest effort in identifying studies which would have a high value in being replicated, particularly in the timeframe of work published from 2010 to 2020. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of International Journal of Technology & Design Education is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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