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- Genre: Art--Study and teaching--Technological innovations.
- Genre: Cartographic
- Creators: Arizona State University
Description
When cartographers and graphic designers create maps they choose typefaces. Often, serif and sans serif typefaces are paired together to represent different information on a map. Typefaces have a communicated tone and choosing the correct typeface combination to send the intended message can be challenging. The purpose of this study was to create an analysis of the aesthetic characteristics of typeface pairings to assist map creators when choosing typefaces. An online survey was utilized to collect responses from graphic designers who have been trained in at least one year or more in design from a higher education institution. There were 30 participants in the study and they scored 24 typeface pairings, 12 differentiating and 12 superfamily, on 48 maps. Scoring was done on eight aesthetic characteristics: friendly, whimsical, cheap, neutral, bland, corporate, serious and modern. The researcher conducted an analysis of each typeface’s microaesthetics and then compared these to the survey’s scored aesthetic characteristics. It was concluded that there are many factors that go into comparing the typeface pairings of serif and sans serif typeface combinations. However, a selection of a superfamily typeface pairing is better than selecting a differentiating pairing. Future research should focus on conducting studies with a varying amount of typeface styles. Also, to include less maps per survey and a survey completion status bar.
ContributorsFinden, Nathan (Author) / Ralston, Laurie (Thesis advisor) / Carrasquilla, Christina (Committee member) / Westover, William (Committee member) / Arizona State University (Publisher)
Created2018
Description
The present study explored the use of augmented reality (AR) technology to support cognitive modeling in an art-based learning environment. The AR application used in this study made visible the thought processes and observational techniques of art experts for the learning benefit of novices through digital annotations, overlays, and side-by-side comparisons that when viewed on mobile device appear directly on works of art.
Using a 2 x 3 factorial design, this study compared learner outcomes and motivation across technologies (audio-only, video, AR) and groupings (individuals, dyads) with 182 undergraduate and graduate students who were self-identified art novices. Learner outcomes were measured by post-activity spoken responses to a painting reproduction with the pre-activity response as a moderating variable. Motivation was measured by the sum score of a reduced version of the Instructional Materials Motivational Survey (IMMS), accounting for attention, relevance, confidence, and satisfaction, with total time spent in learning activity as the moderating variable. Information on participant demographics, technology usage, and art experience was also collected.
Participants were randomly assigned to one of six conditions that differed by technology and grouping before completing a learning activity where they viewed four high-resolution, printed-to-scale painting reproductions in a gallery-like setting while listening to audio-recorded conversations of two experts discussing the actual paintings. All participants listened to expert conversations but the video and AR conditions received visual supports via mobile device.
Though no main effects were found for technology or groupings, findings did include statistically significant higher learner outcomes in the elements of design subscale (characteristics most represented by the visual supports of the AR application) than the audio-only conditions. When participants saw digital representations of line, shape, and color directly on the paintings, they were more likely to identify those same features in the post-activity painting. Seeing what the experts see, in a situated environment, resulted in evidence that participants began to view paintings in a manner similar to the experts. This is evidence of the value of the temporal and spatial contiguity afforded by AR in cognitive modeling learning environments.
Using a 2 x 3 factorial design, this study compared learner outcomes and motivation across technologies (audio-only, video, AR) and groupings (individuals, dyads) with 182 undergraduate and graduate students who were self-identified art novices. Learner outcomes were measured by post-activity spoken responses to a painting reproduction with the pre-activity response as a moderating variable. Motivation was measured by the sum score of a reduced version of the Instructional Materials Motivational Survey (IMMS), accounting for attention, relevance, confidence, and satisfaction, with total time spent in learning activity as the moderating variable. Information on participant demographics, technology usage, and art experience was also collected.
Participants were randomly assigned to one of six conditions that differed by technology and grouping before completing a learning activity where they viewed four high-resolution, printed-to-scale painting reproductions in a gallery-like setting while listening to audio-recorded conversations of two experts discussing the actual paintings. All participants listened to expert conversations but the video and AR conditions received visual supports via mobile device.
Though no main effects were found for technology or groupings, findings did include statistically significant higher learner outcomes in the elements of design subscale (characteristics most represented by the visual supports of the AR application) than the audio-only conditions. When participants saw digital representations of line, shape, and color directly on the paintings, they were more likely to identify those same features in the post-activity painting. Seeing what the experts see, in a situated environment, resulted in evidence that participants began to view paintings in a manner similar to the experts. This is evidence of the value of the temporal and spatial contiguity afforded by AR in cognitive modeling learning environments.
ContributorsShapera, Daniel Michael (Author) / Atkinson, Robert K (Thesis advisor) / Nelson, Brian C (Committee member) / Erickson, Mary (Committee member) / Arizona State University (Publisher)
Created2016