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	<title>statistical understanding in biomedical education &#8211; Science</title>
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	<title>statistical understanding in biomedical education &#8211; Science</title>
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		<title>Supporting quantitative skills in biomedical science with smart worksheets: intentions, impact and barriers to engagement</title>
		<link>https://scienmag.com/supporting-quantitative-skills-in-biomedical-science-with-smart-worksheets-intentions-impact-and-barriers-to-engagement/</link>
		
		<dc:creator><![CDATA[Ophelia Keating]]></dc:creator>
		<pubDate>Sat, 17 Oct 2026 06:10:39 +0000</pubDate>
				<category><![CDATA[Medicine]]></category>
		<category><![CDATA[Science News]]></category>
		<category><![CDATA[addressing math gaps in biomedical science students]]></category>
		<category><![CDATA[barriers]]></category>
		<category><![CDATA[barriers to learning mathematics in science]]></category>
		<category><![CDATA[biomedical]]></category>
		<category><![CDATA[biomedical science quantitative skills development]]></category>
		<category><![CDATA[digital tools for numeracy in biomedical studies]]></category>
		<category><![CDATA[engagement]]></category>
		<category><![CDATA[feedback and error correction in digital learning]]></category>
		<category><![CDATA[impact]]></category>
		<category><![CDATA[impact of asynchronous learning tools]]></category>
		<category><![CDATA[improving practical assessment skills in biomedical students]]></category>
		<category><![CDATA[intentions]]></category>
		<category><![CDATA[Quantitative]]></category>
		<category><![CDATA[role of technology in science numeracy]]></category>
		<category><![CDATA[Science]]></category>
		<category><![CDATA[Scientific Research]]></category>
		<category><![CDATA[skills]]></category>
		<category><![CDATA[smart]]></category>
		<category><![CDATA[smart worksheets for science education]]></category>
		<category><![CDATA[statistical understanding in biomedical education]]></category>
		<category><![CDATA[student engagement with educational technology]]></category>
		<category><![CDATA[Supporting]]></category>
		<category><![CDATA[university-level science education innovations]]></category>
		<category><![CDATA[worksheets]]></category>
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					<description><![CDATA[Every year, hundreds of thousands of students arrive at university with one shared weakness: the maths hiding inside their science. In biomedical science, where pipetting volumes, dilution factors, calibration curves and statistical spread underpin nearly every practical assessment, that weakness]]></description>
										<content:encoded><![CDATA[<p>Every year, hundreds of thousands of students arrive at university with one shared weakness: the maths hiding inside their science. In biomedical science, where pipetting volumes, dilution factors, calibration curves and statistical spread underpin nearly every practical assessment, that weakness can quietly decide who passes and who drops out. A new study from Northumbria University, published in the British Journal of Biomedical Science, has now mapped exactly how students interact with a set of digital tools designed to fix it — and the results reveal a stark gap between what students intend to do and what they actually do.</p>
<p>The research team, led by Stephany Veuger of Northumbria University alongside Leanne Williams of the University of Warwick and LearnSci, Emily Coyte of LearnSci and Sue Jones of the Institute of Biomedical Science, surveyed 779 students enrolled across Levels 3 to 6 of the university&#8217;s BSc Biomedical Science programme. The students were offered five asynchronous Smart Worksheets, developed by the education technology company LearnSci in collaboration with the Institute of Biomedical Science, covering fundamental numeracy, units and conversions, scientific formulae, data visualisation and graphs, and averages, spread and precision. Each worksheet delivers instant, targeted feedback on incorrect answers, catering to specific errors and common misconceptions, and generates an end report showing completion and score by learning outcome.</p>
<p>Before the worksheets were deployed, the researchers ran a first survey to gauge perceived calculation confidence, extracurricular commitments and intent to use the resources. A second survey followed the deployment to correlate intention with actual usage. The response rate for the first survey was 42 percent, with 387 students participating; the second survey attracted 155 responses. Across the cohort, 66.9 percent of participants were female, 33.3 percent male and 1.5 percent non-binary, broadly representative of the programme overall. Just under 60 percent of respondents identified with one or more widening participation characteristics, including socio-economic background, disability, first-in-family status and care experience.</p>
<p>Contrary to prevailing concerns about student disengagement, self-reported engagement with course content was high, with Level 5 students the most optimistic. Students also generally considered themselves fairly confident with calculation questions, and there was no significant difference in reported confidence across levels of study. But when the researchers correlated confidence with the number of widening participation characteristics a student held, a highly significant pattern emerged: the more characteristics, the lower the reported confidence, with a Kruskal-Wallis H of 14.507 and p equal to 0.002. Male students reported feeling significantly more confident than female students, while international students rated themselves slightly higher than home students, though the latter difference was not statistically significant.</p>
<p>When offered bespoke resources focused on consolidating calculation skills directly relevant to high-stakes assessment, 93.9 percent of students said they were very likely or likely to use them. Students with lower self-reported confidence were significantly more likely to state an intention to engage, suggesting those who stand to gain the most are aware of it. Yet the usage analytics told a different story: only 25.3 percent of the 779 enrolled students engaged with at least one of the five resources, and just 5.6 percent used all five. Engagement was highest at Level 5, where 45.1 percent used one or more worksheets, followed by Level 3 at 31.4 percent, Level 4 at 20.9 percent and a striking 0.8 percent at Level 6.</p>
<p>The reasons students gave for not engaging were overwhelmingly practical. Of those who did not use the worksheets, 40.9 percent said they did not know about them and 28.8 percent said they did not have time. Open comments from students who selected other reasons were primarily composed of the phrase I forgot. Content analysis of encouraging and discouraging factors showed that ease of access and use, relevance to course content and quality of feedback were the strongest motivators, while difficulty navigating the resources, excessive content length and perceived irrelevance were the strongest deterrents. For some students, compulsory use was itself seen as a barrier.</p>
<p>The time pressure students face is escalating as they progress through their degree. Over 86 percent of Level 6 students reported weekly work or caring commitments, compared with 63.3 percent of Level 3 students, with hours increasing significantly across the years of study. Level 6 students were working or caring more hours than any other year group, with 12.5 percent working or caring over 21 hours a week. The researchers note that current credit-associated workload models, which expect roughly 35 to 40 hours of study per week including contact hours, simply do not accommodate such levels of external commitment, and that the impact falls disproportionately on students with the greatest financial hardship.</p>
<p>Regardless of initial confidence, students consistently rated the Smart Worksheet content as appropriate and highly valuable. A majority of 71 percent found the level of the worksheets to be about right, with a symmetrical split between a little too difficult and a little too easy. No respondents claimed the resources were much too difficult. Between 73 and 74.6 percent of students agreed or strongly agreed that the worksheets had a broader impact on their learning, helping them identify strengths and weaknesses, feel more confident in calculations, engage more with the module and feel more prepared for future assessments. When asked how much they would recommend the resources on a scale of one to ten, 59 percent selected eight or above.</p>
<p>The study challenges the traditional assumption that final year students are more autonomous and need less support. The authors argue that students are increasingly fitting their degree around their lives rather than the other way around, and that those who can attend all timetabled sessions may now be only those in a privileged position. They recommend increasing visibility and clarity through regular discussion in lectures and short demonstrations, integrating the worksheets into timetabled seminars and tutorials, and sharing evidence of impact by comparing academic performance between users and non-users. They also suggest recognising and rewarding students in paid employment through work-based learning recognition, accepting content for skills portfolios or even credits.</p>
<p>The findings underscore the need for comprehensive and clearly communicated support mechanisms for all students navigating an increasingly complex academic, financial and personal landscape. The researchers plan a longitudinal study tracking student confidence, engagement and academic performance over time, alongside comparative analysis of assessment scores between users and non-users, to clarify the relationship between confidence and attainment. They also intend to explore correlations between worksheet completion and module performance, considering timing of completion relative to assessment deadlines. For now, the message is clear: flexible, high-value asynchronous resources are crucial for time-poor students, and the barriers to engagement are primarily time and capacity-related rather than motivational.</p>
<p><strong>Subject of Research:</strong> Smart worksheets boost biomedical science quantitative skills but engagement gap persists, study finds</p>
<p><strong>Article Title:</strong> Supporting quantitative skills in biomedical science with smart worksheets: intentions, impact and barriers to engagement</p>
<p><strong>Article References:</strong> Williams, L., Coyte, E., Jones, S., &amp; Veuger, S. (2026). Supporting quantitative skills in biomedical science with smart worksheets: intentions, impact and barriers to engagement. <em>British Journal of Biomedical Science, 83</em>, Article 15078. <a href="https://doi.org/10.3389/bjbs.2026.15078" rel="noopener noreferrer">https://doi.org/10.3389/bjbs.2026.15078</a></p>
<p><strong>Image Credits:</strong> AI Generated</p>
<p><strong>DOI:</strong> <a href="https://doi.org/10.3389/bjbs.2026.15078" rel="noopener noreferrer">10.3389/bjbs.2026.15078</a></p>
<p><strong>Keywords:</strong> Supporting, quantitative, skills, biomedical, science, smart, worksheets, intentions, impact, barriers, engagement, scientific research</p>
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