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1. Attitudes Toward and Usage of Animations in an Interactive Textbook for Material and Energy Balances

   https://doi.org/10.18260/1-2--36728  

   Stone, Sidney; Liberatore, Matthew (January 2021, ASEE Annual Meeting)

   null (Ed.)

   Attitudes Toward and Usage of Animations in an Interactive Textbook for Material and Energy Balances Abstract The concept of active learning or “learning by doing” is applied to animations within an interactive textbook in this contribution. A Material and Energy Balance (MEB) course for undergraduate chemical engineering students has generated large data sets by using an interactive textbook from zyBooks. MEB is a foundational course that includes new terminology, the basic principles of mass and energy conservation, and tools for problem solving. Here, outside of class engagement is measured using student views of multi-step animations that introduce MEB concepts in small chunks. Students usage of the interactive textbook have been logged for several years and reading participation was measured as high as 99% by median. Within the reading participation data are the clicks to start, complete, and re-watch over 100 animations across the book, which has not been explored in detail. This paper addresses research questions specifically related to animations. First, do students complete viewing an interactive animation and what is the rate of re-watch? Next, do certain animations gather re-watch views across several cohorts? Also, what is students’ understanding and attitude about using animations in their engineering education? We will administer pre- and post-surveys to understand students’ interest in chemical engineering as well as animation use. 

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2. Clustering of Animation View Times in an Interactive Textbook for Material and Energy Balances

   Hilsabeck, Tanner; Crockett, Breanne; Parsaei, Amir; Xu, Kevin S.; Liberatore, Matthew W. (June 2023, ASEE Annual Conference proceedings)

   Data science tools can help elucidate trends from clickstreams and other interactions generated by students actively using interactive textbooks. Specifically, data generated when using animations, which are multi-step visuals with text captions, will be presented in this work. Each animation step divides content into appropriate chunks, and so aligns with tenets of cognitive load theory. Both the quantity and timing of students’ clicks record provide large data sets when examining students across hundreds of animations and multiple cohorts. Specifically, an interactive textbook for a chemical engineering course in Material and Energy Balances will be examined and build upon data presented previously. While most of the previous data focused on very high reading completion rates (>99% median) compared to traditional textbooks (20-50%), a deeper examination of how long students take when watching animations will be explored. With over 140 unique animations and tens of thousands of completed views over five cohorts, a spectral clustering algorithm applied to students’ animation view times distinguished several types of animation watching behavior as well as monitor changes in this animation watching behavior over the course of a semester. After examining different numbers of clusters, two or three clusters in each chapter captured the animation usage. These clusters usually correspond to a group of students who watched animations at 1x speed (longer), another group who watched at 2x speed (shorter), and a third group, when present, who watched irregularly, including skipping animations. Overall, more students belonged to the belonged to the cluster with longer view times, with 63% of students aggregated over all cohorts and chapters compared to 35% of students in the cluster with shorter view times. The remaining 2% of students belonged to the irregular cluster, which was present in less than one quarter of the chapters. Many students stayed in the same cluster between chapters, while a smaller fraction switched between the longer and shorter clusters. 

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3. Animated Vega-Lite: Unifying Animation with a Grammar of Interactive Graphics

   https://doi.org/https://doi.org/10.48550/arXiv.2208.03869  

   Zong, Jonathan; Pollock, Josh; Wootton, Dylan; Satyanarayan, Arvind (August 2022, IEEE Visualization Conference)

   We present Animated Vega-Lite, a set of extensions to Vega-Lite that model animated visualizations as time-varying data queries. In contrast to alternate approaches for specifying animated visualizations, which prize a highly expressive design space, Animated Vega-Lite prioritizes unifying animation with the language's existing abstractions for static and interactive visualizations to enable authors to smoothly move between or combine these modalities. Thus, to compose animation with static visualizations, we represent time as an encoding channel. Time encodings map a data field to animation keyframes, providing a lightweight specification for animations without interaction. To compose animation and interaction, we also represent time as an event stream; Vega-Lite selections, which provide dynamic data queries, are now driven not only by input events but by timer ticks as well. We evaluate the expressiveness of our approach through a gallery of diverse examples that demonstrate coverage over taxonomies of both interaction and animation. We also critically reflect on the conceptual affordances and limitations of our contribution by interviewing five expert developers of existing animation grammars. These reflections highlight the key motivating role of in-the-wild examples, and identify three central tradeoffs: the language design process, the types of animated transitions supported, and how the systems model keyframes. 

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4. Effectiveness of Undergraduate-Generated Animations: Increasing Comprehension and Engagement for Neuroscience Majors and Non-Majors

   https://doi.org/10.1177/00986283211023061  

   Reed, Catherine L.; Hagen, Emilia; Bukach, Cindy M.; Couperus, Jane W. (July 2021, Teaching of Psychology)

   Background: Animations of scientific concepts may improve comprehension by explaining and visualizing the steps of complex processes, but unless they engage student interest in meaningful ways, their effectiveness as teaching tools is limited. We achieve this through a novel approach to animation design that includes the target audience (undergraduates) so that the resultant animations align with their learner characteristics. Objective: This case study investigated whether undergraduate-generated animations were more effective educational tools than informationally equivalent text-and-illustration presentations and whether learners’ background influenced the relative benefits of animations. Method: Incorporating feedback from faculty and undergraduates, we created animations and text-plus-illustration content to explain how neural signals are generated and measured by scalp electrodes. Neuroscience majors and non-majors were presented with either animations or static presentations followed by comprehension and engagement assessments. Results: Both groups showed comprehension and engagement benefits for animations. Although majors showed better overall comprehension, animations improved comprehension for non-majors over static presentations. Conclusion: When educational content is directed for a target audience, animations can be more effective teaching tools for a broader student audience. Teaching Implications: The relevance of online tools for remote instruction makes animations, developed for and by undergraduates, important tools for effectively introducing difficult content. 

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5. Physical Cyclic Animations

   https://doi.org/10.1145/3606938  

   Jia, Shiyang; Wang, Stephanie; Li, Tzu-Mao; Chern, Albert (August 2023, Proceedings of the ACM on Computer Graphics and Interactive Techniques)

   We address the problem of synthesizing physical animations that can loop seamlessly. We formulate a variational approach by deriving a physical law in a periodic time domain. The trajectory of the animation is represented as a parametric closed curve, and the physical law corresponds to minimizing the bending energy of the curve. Compared to traditional keyframe animation approaches, our formulation is constraint-free, which allows us to apply a standard Gauss--Newton solver. We further propose a fast projection method to efficiently generate an initial guess close to the desired animation. Our method can handle a variety of physical cyclic animations, including clothes, soft bodies with collisions, and N-body systems. 

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