Digital Imagery

From E-Learning Faculty Modules


Module Summary

The nature of e-learning and its being built on an electronic substructure means that images are relatively easy to distribute, share, manipulate, analyze, and integrate into the learning. Full repositories of images may be shared for analytical depth. Subscription-based digital repositories do not only contain articles but plenty of multimedia—including audio files, video, and imagery. Images are embedded into learning sequences. They are major parts of virtual immersive worlds and various simulations and digital labs. Digital images are embedded into slideshows, photo albums, assessments, and various textual contents.


Learners will...

  • Explain what digital imagery used in e-learning is
  • Describe the different dimensions of digital imagery (vs. print imagery)
  • Explain the types of digital imagery used in e-learning
  • Describe some ways that imagery is used in e-learning
  • List some of the technologies used for capturing and creating digital imagery for e-learning
  • Explain how digital imagery adds value to some different types of online learning
  • Find and integrate open-source digital imagery

Module Pretest

1. What is “digital imagery,” and how is it used in e-learning? What are some principles for the uses of digital imagery in e-learning?

2. What are the dimensions of images (as in 1D, 2D, 3D, 4D, and others)? What types of information do these dimensions convey?

3. What types of digital imagery are used in e-learning?

4. What are some ways that imagery is used in e-learning?

5. What are some technologies used for capturing and creating digital imagery for e-learning?

6. How does digital imagery add value to different types of online learning?

7. What is open-source digital imagery? Where can it be found? What are some general rights to use open-source digital imagery?

Main Contents

Higher education has long had a history of being text-based, with plenty of reading, word-based lectures, and writing. That tendency has also affected some online learning. Educational research suggests that there should be multiple streams of information delivery and inter-communications—and with the popularization of multimedia in online learning—various types of imagery have become more widely used. These are delivered through learning / course management systems (L/CMS), digital repositories, websites, social networking sites, blogs, wikis, and a range of technological substructures.

Digital Imagery Used in E-Learning and Basic Principles for their Use

Visual imagery may enhance human perception, cognition, and learning of particular conceptual relationships. They may enhance their skills in nuanced diagnosis and analysis by analyzing photos of particular signs and symptoms of diseases. They may see examples and illustrations of various concepts that would be elusive through the uses of words alone. They may understand processes and sequences with greater time-based clarity through time-lapse images. They may be able to visualize spatial relationships—such as on maps and blueprints—with greater clarity. Visual imagery may convey ideas with greater clarity. Some types of designs and plans may only be conveyed visually in fields such as radiography, architecture, some forms of digital art, and others.

There are complex visual paths through the human brain that process various aspects of visual information—light, color, darkness, shapes, words, faces, and spatial relationships. While visual memory is fairly short, the human brain has a large capacity for long-term visual recognition and memory (once visual images are reinforced sufficiently to be added into the long-term memory).

Basic Principles

1. Photorealistic imagery should reflect reality—in terms of color balance, size, and back story. This means that diagnostic images should include clear color information and measures against some objective size. These should be accurate and non-manipulated in terms of context. Accompanying captions should contribute to viewer understandings, and these should not confuse image users. (More recent digital cameras capture metadata such as GPS coordinates—for even more information-rich captures.)

2. Imagery should add informational and learning value. They should not be decorative. They generally should not be clip art.

3. Imagery should have clear provenance and origins. Users should know where the images came from. They should observe intellectual property (IP) in the uses of these resources. Open-source imagery should still be cited for proper crediting.

Different Dimensionality in Digital Imagery (vs. Print Imagery)

All images may be understood to exist on particular planes. The simplest ones are 1D to 4D. A 1D (one-dimensional) image consists of a pixel. It exists on one plane. A 2D (two-dimensional) image exists on the x and the y planes. This image has length and width. An image on a sheet of paper is a 2D image. A 3D (three-dimensional) image consists of length, width and depth. This type of image exists along the x, y, and z axes. A 4D (four-dimensional) image consists of a 3D image with movement (over time) added.

Examples of Various Dimensions of Images

2D Imagery: sketches, drawings, diagrams, timelines, charts, tables, icons, symbols, screenshots, photorealistic photographs, montages, non-photorealistic images and depictions, video grabs, satellite imagery, acoustical imagery

3D Imagery: 3D metaworlds, fractals, haptic-visual interfaces, augmented reality, ambient spaces, 3D video, holography

Dr. Leon James of the University of Hawaii offers an online image of various body planes in a 3D conceptualization.


4D Imagery: 3D video, 3D animations, avatars, maquettes and models, live data-fed images

Types of Digital Imagery Used in E-Learning

There are a number of ways to conceptualize the types of digital imagery used in e-learning. Some are still images, and others are dynamic or moving ones. Some are stand-alone, and others are integrated with multimedia or text or other elements to promote the learning. Some are used to convey facts, and others are expressive and creative. Some are representative of contents from the world while others are imaginary. Some are derived from real-world objects while others are “born digital.” Some are realistic and natural while others are highly stylized and artificial. High-fidelity images are those that are informative and information-rich; low-fidelity images are often low-resolution and light in terms of information. Some depictions are holistic while others are partial (with image decompositions). Extreme visualizations may range from nano-level scales to meso-scales (extremely small sizes to extremely large sizes). Many image captures may be enhanced with microscope or telescope enhancements.

Still Imagery for the Web: .jpg, .gif, and .png

Video on the Web: .mov, .wmv, .rm, .flv / .swf (with interactivity), and .mp4 (podcasts)

Ways that Imagery is Used in E-Learning

One broad way to conceptualize these types of imagery is by pedagogical purpose (the main educational use of the particular visual). A Learning Environment

Visuals may be used to create a particular learning environment aligned with learning in a particular domain field. Virtual immersive worlds may capture a full learning environment with automated interactivity, digital artifacts, and interactive avatars (including those with artificial intelligence).

Conceptual / Mental Modeling

A “conceptual” model is an expert’s conceptualization of a particular field. A “mental” model is a non-expert’s conceptualization of a particular field. One major role of learners is to close the gap between their own mental models and the more accurate and complex conceptual model.

Creativity, Design, and Planning

Visuals may be used to express individual or group creativity, designs, and plans. Digital artworks, blueprints, land or building plans, and other elements may be expressed on digital palates and designs.

Some visuals may be mixed-mode images—with image morphing, photo-mosaicing, cartoon rendering, computerized drawings, digital etching and photogravure effects, machine created art (based on high-level maths—via chaos tools, morphogenesis, “cellular machines” and “neuronal co-evolution” tools), digital sculpting, and other digital editing effects.

Machinima or “machine cinema” may capture dramaturgy and live interaction creativity. Virtual fly-throughs of 3D structures and landscapes may immerse individuals in fantasy landscapes.

Processes and Procedures

Digital visuals may express how a process or procedure changes over time. Slideshows, photo albums, digital timelines, and other forms of visual expression may show linear or non-linear time relationships. They may convey step-by-step processes. They may show causes and effects over time, such as pre- and post- contrasting images.

Spatial Relationships

Digital cartography, maps, and aerial-view images may show spatial relationships. Other spatial relationships may be reflected in image maps with interactive elements that may integrate additional information.

Complex Informational Relationships

Interactive visuals are being used to convey complex interrelationships between various data sets. Complex interactive graphics (See Hans Rosling’s TED conference presentation that demonstrates some of these complex applications: capture rich information streams and effects over time, as well as complex nuanced interaction effects.

Social Relationships

The appearances of digital avatars in immersive worlds may enhance social interactions and relationships between the humans embodying the avatars.

Simulations and Reconstructions

Digital visuals may be used create / re-create particular experiences and events. Some simulations are full-sensory and involve multiple perceptual streams of information. Others are merely environments that evoke particular sensations or contexts. Digital versions of “wet labs” and “dissection” experiences are some examples of simulations. Optical illusions may be created using digital means.

Troubleshooting, Problem-Solving

Some imagery may be used for setting up problem-solving scenarios for learners. Images may be used to show what learners should look for—such as a simulation of identifying risks in luggage as viewed through a simulated x-ray machine or signs and symptoms to pay attention to in plant samples.

Data Culling

Data may be culled from an image in many ways. One common example is the pulling out of visual information from high-resolution digital imagery captured by digital still cameras and from camcorders. Oftentimes, much more is captured than the human eye may have noticed at the moment of capture.

Visuals are used to represent various data sets, from which may be extracted particular data patterns.

Sensors placed in various environments may also capture information that is represented visually for easier mental manageability by human assessors.

More advanced forms of data culling involve hyperspectral imaging, acoustic imaging, x-ray, and other types of information captures with information captured and conveyed as visuals.


Digital visuals may project how a scenario or object changes into the future. Predictive analytics or trendlining may be done—for example, predicting weather patterns into the near-term. Faces may be “aged” into the future. Soft objects may be animated or deformed based on different projected circumstances. As another example, simulated accidents may be projected into 3D spaces to simulate gas dispersions or crowd behaviors—for disaster response planning. Traffic patterns may be projected based on a variety of theoretical street designs.

Augmented Real Spaces

Various digital technologies are used to augment human experiences in real spaces whether the individual is wearing the technologies (as in head-mounted devices, smart devices, mobile devices, or smart clothing) or the images are projected into lived spaces. Real spaces may be augmented with mobile devices for fully mobile experiences—that may be location-agnostic. Other “built” spaces (digital installations, smart rooms and houses) will be location- or place-sensitive.

Technologies Used for Capturing and Creating Digital Imagery for E-Learning

A variety of equipment may be used to capture raw materials that may be turned into digital imagery. Camcorders may capture video and sound for computer-based editing. Scanners (flatbed and others) may capture flat or 3D imagery. Microscope-mounted digital cameras may capture microscopic images. Mobile phones and devices may capture low-resolution images. Sensors also capture fairly low-resolution images. More high-end automated cameras for closed circuit television monitoring may also capture fairly low-resolution images. Computational photography setups offer enhanced image capture with digital sensors, optics, and lighting—along with other strategies. Satellite image captures are also used to capture land forms, human-created structures, weather patterns, and other imagery.

Freehand drawing programs, pens and tablets, and various visualization technologies enhance human abilities to illustrate and express using visual means.

There are other types of equipment and software tools, but these others are not widely used in higher education and so will not be mentioned here.

Value-Added Digital Imagery

Imagery that is valuable in its raw form usually is valuable because of the informational value—such as photo-realistic images. Other images may be captured for particular aims—such as branding, storytelling, evoking moods, and so on.

Finding and Integrating Open-Source Digital Imagery

Open-source imagery may be both royalty-free and copyright free or released to the public domain. Various repositories, organizations, and companies may make these available for widespread use. It is important to learn the provenance of the imagery. Also, it is important to credit the source through proper citations. Lastly, it’s helpful to keep a record of the copyright release policies of the source at the time of the image download.


There are various links of examples below.

How To

Possible Pitfalls

The uses of digital imagery in e-learning are critical for many types of value-added learning. Some possible challenges are that there are various costs to investing in the capture of raw imagery. The equipment for still and moving images capture is expensive. The learning curve is fairly high to use the equipment and then to do “post production” on the still and moving images. The archival of the raw and processed images and footage will require plenty of digital storage space. To protect against misuse of such images and visuals, owners often have to use digital right management (DRM) techniques and technologies.

There must be sufficient thought put into how imagery will enhance the learning. All intellectual property (IP) laws will need to be followed. All digital visuals and such works should also be rendered accessible, with text equivalents of the informational value of still images and transcriptions (or captions) of multimedia, video, and simulations.

In addition, owners of digital contents are often required to maintain and update the works to ensure that they are available into the future. It would be helpful to consider the entire lifespan of a particular work to understand “the total cost of ownership.”

Module Post-Test

1. What is “digital imagery,” and how is it used in e-learning? What are some principles for the uses of digital imagery in e-learning?

2. What are the dimensions of images (as in 1D, 2D, 3D, 4D, and others)? What types of information do these dimensions convey?

3. What types of digital imagery are used in e-learning?

4. What are some ways that imagery is used in e-learning?

5. What are some technologies used for capturing and creating digital imagery for e-learning?

6. How does digital imagery add value to different types of online learning?

7. What is open-source digital imagery? Where can it be found? What are some general rights to use open-source digital imagery?


Hai-Jew, S. (2010). Digital Imagery and Informational Graphics in E-Learning: Maximizing Visual Technologies. IGI-Global.

Types of Digital Visuals in E-Learning

Extra Resources

Open-Source Digital Imagery

Public Domain Resources: Many US government sites release their contents to the public domain.

Centers for Disease Control and Prevention (CDC)

Federal Emergency Management Agency (FEMA)

National Oceanographic and Atmospheric Administration (NOAA)

National Weather Service

US Food and Drug Administration (FDA)

US Department of Education (ED)

US Department of Agriculture (USDA)

US Department of Health and Human Services (HHS)

Photo-Sharing Sites: Some photo-sharing sites have policies that involve the release of contents for larger use by the public.


Company Sites: Some companies add value to their products by making free imagery available.

Microsoft Free Clipart and Photos

Online Encyclopedias: Online Encyclopedias with Creative Commons or public domain rights releases include the following:


Notes: Policies may change, so people should always read the fine print. Please use proper citations. If possible, pay attention to the provenance of the information, so you know where a particular resource came from.