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ABSTRACTComputational modelling is widely used in biological science. Therefore, biology students need to learn computational modelling. However, there is a lack of evidence about how to teach computational modelling in biology and what the effects are on student learning. The purpose of this intervention-control study was to investigate how knowledge in computational modelling is associated with knowledge acquisition in biology. Participants were 118 students (17 to 19 years of age) enrolled in first and second year of Danish High School. The intervention group (n = 81) received teaching in biology and computational modelling while the comparison group (n = 37) received teaching in biology using textbook models. Both groups received two sessions, each of approximately 120 minutes. The study used mixed methods to analyse students’ knowledge of biology and computational modelling. Participants in the intervention group showed statistically significant improvements in their biological knowledge and computational modelling knowledge. The study is one of the first to investigate the effect of computational modelling on high school students’ learning of biology. The study discusses how biology could be an important subject where students can learn computing concepts central in the endeavour to introduce computing in high school education.

In recent years, dental education has witnessed significant advancements and curriculum shifts in response to evolving healthcare needs, technological advances, and changing societal demands. As a result, dental universities worldwide have undergone substantial curriculum changes to ensure the adequate education and training of future dental professionals. The purpose of this study was to delineate the curriculum innovations over the past 20 years, with a focus on content within the current dental curriculum at universities worldwide. The articles reviewed for this manuscript were published from 2000 to June 2023. Search queries were conducted in four databases: Embase, PubMed, Web of Science, and ERIC, yielding 367 unique studies. Of these, 31 were included in the final synthesis. The nine principal subject matter themes identified in the thematic analysis of these articles were critical scientific thinking, computational thinking, global mindset, geriatric dental care, interprofessional teamwork, transition to practice, local community, integration, and lifelong learning. The themes were modeled and mapped in a three‐axis figure, elucidating the interconnections between the themes. The identified themes signify the trajectory that dental education has taken and provide insights into the future course of the dental profession.

Copyright of Tandlaegebladet is the property of Tandlaegeforeningen and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. 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.)

Copyright of Tandlaegebladet is the property of Tandlaegeforeningen and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. 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.)

Copyright of Tandlaegebladet is the property of Tandlaegeforeningen and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. 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.)

The visual exploration of large databases raises a number of unresolved inference problems and calls for new interaction patterns between multiple disciplines—both at the conceptual and technical level. We present an approach that is based on the interaction of four disciplines: database systems, statistical analyses, perceptual and cognitive psychology, and scientific visualization. At the conceptual level we offer perceptual and cognitive insights to guide the information visualization process. We then choose cluster surfaces to exemplify the data mining process, to discuss the tasks involved, and to work out the interaction patterns. [Copyright &y& Elsevier]