00990nas a2200169 4500008004100000245010900041210006900150260000900219520035400228653000800582653001900590100002200609700001900631700002000650700001800670856013200688 2023 eng d00aInteractive Network Visualization of Educational Standards, Learning Resources and Learning Progressions0 aInteractive Network Visualization of Educational Standards Learn c20233 aWe present a novel, network- and browser-based visualization of the Next Generation Science Standards (NGSS). The NGSS are meant to guide (USA) K-12 science and engineering learning and are almost always presented using text and tables. Their connectivity, however, lends them well for network modeling and interactive network visualization.
10aBIS10aDesign Program1 aReitsma, Reindert1 aHoglund, Brian1 aAchatz, Nikolas1 aMarks, Andrea u/biblio/interactive-network-visualization-educational-standards-learning-resources-and-learning01604nas a2200193 4500008004100000245010800041210006900149260000900218520090100227653000801128653001901136100002201155700001901177700001801196700001601214700001801230710001801248856014401266 2020 eng d00aK-12 Engineering and the Next Generation Science Standards (NGSS): A Network Visualization and Analysis0 aK12 Engineering and the Next Generation Science Standards NGSS A c20203 aWe present an interactive network visualization of the Next Generation Science Standards (NGSS) and its coverage by collections of aligned curriculum. The visualization presents an alternative to the usual presentation of the NGSS as a set of linked tables. Users can view entire grade bands, search for or drill down to the level of individual NGSS standards or curricular items, or display groups of standards across grade bands. NGSS-aligned curriculum collections can be switched on and off to visually explore their NGSS coverage. Viewing the NGSS and associated curriculum this way facilitates navigating the NGSS and can help with assessment of alignments as lacking or anomalous. Modeling the NGSS as a network also allows for the computation of network metrics to provide insight into core characteristics of the network. It also provides for detecting anomalies and unexpected patterns.10aBIS10aDesign Program1 aReitsma, Reindert1 aHoglund, Brian1 aMarks, Andrea1 aChaker, Dua1 aMarks, Andrea1 aEmptyAuthNode uhttps://strategy.asee.org/k-12-engineering-and-the-next-generation-science-standards-a-network-visualization-and-analysis-resource-exchange01838nas a2200157 4500008004100000245007600041210006700117260000900184490000600193520133400199653000801533653001901541100002201560700001801582856008001600 2019 eng d00aThe Future of Data: Too Much Visualization Too Little Understanding?0 aFuture of Data Too Much Visualization Too Little Understanding c20190 v23 aData is part of our lives. Information visualizations help us make sense of this data and possibly help us make changes because of it. In this paper, however, we estimate some of the consequences of what seems an ominous trend, namely the needless complication and beautification of such visualizations. We argue that with increased availability of data and ever more powerful and easy to use visualization software, it becomes easy to succumb to the temptation to impress rather than to communicate. And so we wonder: is a future filled with visualizations that are visually complex and stunning, yet fail to properly communicate the data emerging? To assess some of the consequences of this practice we selected five examples from published sources, developed far simpler (and less attractive) versions from the identical data, randomly exposed these visualizations to subjects and asked simple questions about the displayed data. We find that, on average, it takes subjects longer to comprehend the complex versions, that it takes subjects longer to extract information from these versions and that they make more and larger errors doing so. The experiment shows that subjects eventually do learn how to navigate the complex versions, but by then they have spent significantly more time and made serious interpretative errors.10aBIS10aDesign Program1 aReitsma, Reindert1 aMarks, Andrea uhttps://quod.lib.umich.edu/d/dialectic/14932326.0002.207?view=text;rgn=main