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Heilman and Smith [13] reported that the system achieved 43.3 % acceptability for the top 10 ranked questions and produced an average of 6.8 acceptable questions per 250 words on Wikipedia texts.
An interim prioritisation process involving diverse organisations identified the top 25 ranked questions.
The TAs who ranked questions on Bloom's taxonomy showed a high level of agreement.
In the final plenary session, the groups came together, and collectively discussed the emerging aggregate ranking, to identify and agree on the highest ranked questions.
The full 'long list' of 146 questions used for prioritisation and the 25 top ranked questions considered at the final workshop are available as Supplementary data S4 and S5, available in Age and Ageing online.
Put the number next to the questions on the exam paper or homework sheet and then choose the highest ranked questions.
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The highest ranked question was, "What strategies are effective in increasing demand for and use of skilled attendance?" highlighting the importance of the time of birth and the issue of access to providers who have an appropriate level of skill.
In a recent research priority ranking on reduction of stillbirths and preterm deliveries at the community level, the highest ranked question was: "Evaluate the financial barriers to facility births at the community level (user fee exemption, emergency loans, conditional cash transfers, transportation vouchers, etc)." [ 32].
The highest ranked question in this survey was "What strategies are effective in increasing demand for, and use of skilled attendance?" In this study, a diverse group of experts used the CHRNI methodology to systematically identify and determine research priorities for neonatal health and survival in complex humanitarian emergencies.
Rather than just providing videos of lectures and scanned class handouts, MITx takes things a step further further with "embedded quizzes, immediate feedback, student-ranked questions and answers, online laboratories and student-paced learning".
Theses scales would ask users to rank questions like: "Using technology x improved my job performance" (to measure the perceived usefulness).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com