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Is a Picture Worth of Thousand Words?

Effective Example Link:
https://images-na.ssl-images-amazon.com/images/I/717si1BWeUL._SL1500_.jpg

Ineffective Example Link:
https://dryuc24b85zbr.cloudfront.net/tes/resources/11401360/image?width=500&height=500&version=1479719949989

“A picture is worth 1,000 words” is the same as saying “knowledge is power, where knowledge resources are unlimited” (Laureate Education, 2010d). Learners can only see traditional views unless development or self-directed learning seeks additional forms of literacy to make sense of the picture or knowledge (Laureate Education, 2010d). Understanding information is contingent on the learner’s internal motivation, learning direction, prior knowledge exposure, and recall of data to working memory (Laureate Education, 2010d & Mayer, 2014, p. 86). In conclusion, for a picture to be worth any words; or knowledge to be considered any valuable form of power, the learner must cognitively process the multimedia-instruction in working memory STE, store relevant bits in long-term memory LTE, and effectively communicate the new knowledge. 

The human information processing system or STE is limited in capacity by cognitive load storage (Laureate Education, 2010b). Effective use of graphics in instructional design can help reduce the cognitive load in STE by relating depicted imagery with relevant LTE, eliminating processing time. An example of the effective use of graphics in instructional design is illustrated in the Pool Rules sign.

Meaningful learning is the result of two multimedia instruction goals: remembering and understanding (Mayer, 2014, p. 21). The graphic showing the pool rules adhere to the integrated comprehension of text and picture theory ICTP. In the broader framework of human cognition, the graphic has semiotics to visualize the textual description (Mayer, 2014, p. 83). The symbol used in the graphic is the universal symbol consisting of a circle with a backslash through the middle. The use of red color for the vector recalls LTE relevant to sensory input: Green means go, yellow means slow down, and red means stop. What makes this symbol so effective is the ability to instantly trigger visual sensors relating new information as prior experience with the color directions of a traffic light. Active processing of LTE and new information in STE learners apply generalized prior knowledge as automatic metacognition, easing the strain on cognitive load (Laureate Education, 2010c) The icon inside of each “universal no sign” furthers comprehension of the specific line of text with a fast recognizable image through effective white space or spacial proximity. The typography is designed with a visual color system to form information hierarchy.

An example of weak use of graphics in an instructional setting is demonstrated in “how to brush your teeth.” The images do have relevance to the content in the photographic learning process. However, the spatial correlation is not directly connected to the subject text. The image’s meaning and purpose are to help further cognitive processing. However, the images do not require me to think further than what is being visually processed. In my opinion, in order for a graphic to have a practical instructional purpose is to use the “squint” test. Squinting your eyes helps blur the body copy, leaving you with the main points needed from that instructional piece. If the learner can not tell the subject matter of the information from vectorized text headings, combined with the images, there is a missing link in the design process. With the “how to brush your teeth” image, the main design flaw is information hierarchy represented in the textual description is not visible. Adjusting line spacing, size, and style of the existing text applying one graphic and one

 In my opinion, the graphics are purposeful by using multimedia learning theories. These design approaches generate meaningful learning through depictive learning. As an instructional designer, graphics should be purposefully used to stimulate visual imagery relevant to the textual description but allows further understanding through cognitive activity (Laureate Education, 2010e). The graphic’s size, color, and resolution provide guidelines, media outlets, and any complications to instructional designers. The use of rasterized, or vectorized graphics can display differently for computer-based screens, and printed material (Laureate Education, 2010b). Instructional designers need to understand the audience to determine if vectorized images can be used in replacing photographic pixel images without losing the validity of newly presented knowledge. 

Resources:

Laureate Education (Producer). (2010b). Introduction to graphics [Video file]. Baltimore, MD: Author.

Laureate Education (Producer). (2010c). Multimedia learning theory [Video file]. Baltimore, MD: Author.

Laureate Education (Producer). (2010d). Technology-centered vs. learner-centered instruction [Video file]. Baltimore, MD: Author.

Laureate Education (Producer). (2010e). What is multimedia? [Video file]. Baltimore, MD: Author.

Mayer, R. E. (2014). The Cambridge Handbook of Multimedia Learning (2nd ed.). Cambridge University Press

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Mayer’s Multimedia Principles

The theory of multimedia learning is derived from the multimedia principle, MP (Mayer, 2019, p.43). MP asserts learners develop deeper understanding levels of knowledge when presented as words and pictures than that of words alone (Mayer, 2019, p.43). Meaningful learning requires information processing in working memory, which has a limited capacity. Knowledge transfer or storage in long term memory, LTE requires working memory storage to recall and integrate with new knowledge, which requires additional space.  

The cognitive capacity of a learner has three demands that influence the amount of storage in STE. To illustrate the three demands, STE will be compared to a cloud and the demands as moisture droplets. When working memory is overloaded, knowledge is released. When a cloud has too much moisture, it will rain. Clouds are essential to our atmosphere, carrying moisture to other locations to be integrated with different landscapes and environments. Essential processing, making mental representations of new knowledge, and generative processing, making sense of new knowledge, are essential in STE (Mayer, 2019, p.43) Extraneous processing is the moisture that causes knowledge to be released due to cognitive overload. Instructional designers must use multimedia and MP to eliminate extraneous knowledge while using words and pictures to manage essential processing and grow generative processing; as a result, organize and transfer knowledge to LTE (Mayer, 2019, p.43)

A multimedia instructional message’s design must demonstrate five cognitive processes in order to foster meaningful learning (Mayer, 2019, p.54) While there is not a hierarchical approach, learners must Select relevant words and pictures, construct models through the organization of words and pictures, and bridge the gap between verbal and pictorial models with prior knowledge (Mayer, 2019,p.54). Multimedia depicts words and images through the eyes and ears processed in sensory memory. The dual-channel approach illustrates knowledge processing through verbal or pictorial sensors. Designers need to generate that eye-catching presentation with great audio and visuals to foster self-directive learning; sensory memory is very brief. Designers must limit multimedia to relevant situational information for learners to manipulate and select incoming messages (Mayer, 2019, p.53) 

Mayer design elements of multimedia learning to outline how multimedia promotes an expert level of understanding. The twelve principles illustrate how learners process words and pictures based on structure, spatial, schematics, and humanizing social components. Out of the design tactics, the temporal contiguity principle stuck out to me the most. The temporal contiguity principle states that individuals learn better when words and pictures are presented simultaneously (Thais, 2019). This principle makes sense as spatial contiguity highlights the ability for a deeper understanding of words and pictures that are close in the spatial distance (Thais, 2019). A shape is presented on-screen with the name of a color written on the shape. The written color name does not correspond with the fill color of the shape showed simultaneously. If asked to read, the color printed metacognition forefronts traditional processing, resulting in the name of the fill color, not the name of the color. 

To further research on design characteristics of multimedia, I reviewed an article titled Cognitive Load in Interactive Knowledge Construction” from Learning and Instructions journal. In the article, the correlation between STE, and cognitive load when presented with hypermedia. Hypermedia, the learner, must filter information through navigation pages and selecting information among the links available (Verhoeven et al., 2009, p. 371). In this approach, compared to the web, instructional direction go against the signaling principle and the coherence principle (Thais, 2019). The use of knowledge on the internet does not eliminate any extraneous processing, nor did the instruction signal where learners should navigate. The capacity of STE is limited to the sensors that trigger dual channeling and process only selected images or text. In this example, prior researchers might classify this as a recipe for cognitive overload. The article highlighted the evolution of eye-tracking technology and human-computer interaction software to “test” a learner’s prior knowledge’s influence hypermedia cognitive capacity (Verhoeven et al., 2009, p. 374). 

Multimedia knowledge construction is depended on cognitive load. Three main conclusions were drawn from the assessment. Cognitive capacity is drive by prior personal knowledge, motivation, and perspective (Verhoeven et al., 2009, p. 374). Learning outcomes have a connection with mediated task demands (Verhoeven et al., 2009, p. 374). Lastly, meaningful learning is clearly related to interactivity, control, and collaboration (Verhoeven et al., 2009, p. 374). Adaptive instructional environments that possess task demands and support levels that are aligned with the level of understanding and capacity of the individual learner have a reduction in cognitive load (Verhoeven et al., 2009, p. 374).

In Conclusion, the twelve design elements crafted by Richard Mayer outline a successful connection with cognitive science and information processing. All instructional design projects start at assessing where to start the new knowledge. If the target audience has an expert level of understanding, navigation, signaling, or limiting words or pictures, coherence can be driven by metacognition. As demonstrated in the cognitive theory of multimedia learning, brief sensory triggers STE for further processing. For meaningful learning in hypermedia or the internet, navigation, and self-directed coherence eliminate cognitive load through prior knowledge. 

Resources:

Thais. (2019, January 19). Richard Mayer on Multimedia Learning. Love for Learning – Craft your eLearning Solution. https://mylove4learning.com/richard-mayer-on-multimedia-learning/

Mayer, R. E. (2014). The Cambridge Handbook of Multimedia Learning (2nd ed.). Cambridge University Press

Verhoeven, L., Schnotz, W., & Paas, F. (2009). Cognitive load in Interactive Knowledge Construction. Learning and Instruction19(5), 369-375. https://doi.org/10.1016/j.learninstruc.2009.02.002

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Interactivity: Giving Learners Control

Hana Feels by Gavin Inglis is an interactive story where a girl named Hana, engages dialogue with different people (Inglis, n.d.). The learner assumes the character communicating with Hana. The learner has different responses to provide Hanah, which leads to discovering how Hana feels after her refection on the interaction.

The experience highlights the emotional impacts on people can have during and after tough conversations. Initial reaction to the simulation, for me, was confusion around the role of the learner, and how their interactivity and engagement was needed. The overall storytelling technique was applied and visually enhanced by the conversation bubbles, showing a direct correlation of a conversation stimulation (Huang, 2004). Once into the module and interacting with Hana in the first conversation, the learner will feel intrinsically motivated by the model’s need for interactivity. The learner usually is required to learn from the model so that a selection would be made. In making their response, the response to the input rate was decreed through the responses provided. Once the learner selects an answer, they are committed to leaning, and the faster the response output is, the learner, the better chance of retaining and boosting self-regulated learning (Mayer, 2014). 

Having tough or hard conversations is always a challenge. In the module Hana Feels, the learner is engaged by the immediate response they receive after their selection. From here, hypertext links different replies to the learner giving a since of user control. While free use of learner control can hinder learning objectives, Hana Feels provides boundary controls through providing the response options. The interactivity enhanced the learning objections from two different approaches. In real-world interactions, you can never predict what Hana is going to respond to. There is no guided research referencing in the simulation, just as you would not reference how-to books in front of Hana for a response in real life. The second enhancement is provided trough micro-modules where the emotional implications are not known at the time of a hard conversation but developed post conversation. The pacing and algorithms that provide the boundary control responses work to its benefit by allowing the full simulation, like a quiz or an essay, but allows real-time feedback at the end on how the conversation went and could be influenced. This provides support for learners at all knowledge levels can fully understand the information provided and synthesize their responses. 

References:

Huang, C. (2004). Designing high-quality interactive, multimedia learning modules. Computerized Medical Imaging and Graphics. 29 (2005) 223–233

Inglis, G. (n.d.). Hana Feels. Hana Feels. https://hanafeels.com

Mayer, R. E. (2014a). The Cambridge handbook of multimedia learning. New York: University of Cambridge.

flash-port-3

Social Enviroments implications on learner

To address if the element of “social” environments, impact on learning environments is the same, you have to understand the role of social behavior and the implications on learning. Constructivism view humans construct knowledge by adapting meaning from a previous stimulus-response in the current relevant context (Jenkins, 2006). The process of knowledge is interpreted as a “personal world” or by “mind’s adaptations” that is all internally driven (Jenkins, 2006). Piaget furthered constructivist reach by describing biological readiness, life experiences, and structures that play a crucial role in self-constructing information (Jenkins, 2006). Social environments offer the transference of an individual’s prior skills or processes, allowing learners to voice their point of view and influence the organization of information.  

In my opinion, online pedagogy can offer the same “social” environment as a traditional classroom setting but hinder the ability to advance to the next level of understanding. Howard Gardner stated there are three types of learners, native, traditional, and expert, and if the misconceptions are not challenged, the level of understanding will remain the same. The zone of proximal development describes the kind of learning environment that enables effective knowledge transfer and cognitive development (Laureate Education, n.d.). In applying both approaches, one can produce an active learning environment that is conducive to both external experiences and cognitive processing (Ormrod, Schunk, & Gredler, 2009). When looking at learning strategies and styles that each _ism favors, it doesn’t hinder the ability to influence learning, just merely suggestions that favor memory storage and organization. In the Constructivist point of view, a learner can construct their understanding based on the social environment (Ormrod, Schunk, & Gredler, 2009) ; the variable to me would be the learner’s level of understanding. Instructional settings typically viewed as social offer groups, activities, feedback, and open dialogue between leaner that foster intuitive thinking. However, emerging technology now gives us the ability to see them still visually and communicate openly in realtime, creating the same atmospheric factors. To help guide instruction, facilitators must demonstrate the ability to create a social presence, or the ability of learners to project personal characteristics, experiences, and influences into a community presenting as if “real people” (Kilgore, 2016).

Resources:

Jenkins, J. (2006). Constructivism. In Encyclopedia of educational leadership and administration. Retrieved from http://knowledge.sagepub.com.ezp.waldenulibrary.org/view/edleadership/n121.xml

Kilgore, W. (2016, November 14). Social Learning in Online Environments – Humanizing Online Teaching and Learning. Retrieved May 28, 2020, from https://humanmooc.pressbooks.com/chapter/social-learning-in-online-environments/ 

Laureate Education (Producer). (n.d.). Theory of social cognitive development [Video file]. Baltimore, MD: Author.

Ormrod, J., Schunk, D., & Gredler, M. (2009). Learning theories and instruction (Laureate custom edition). New York, NY: Pearson.

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commentary on “_isms as a Filter, not a blinker”

The ability to pinpoint how learning occurs is equally complex as the brain itself. We know how the brain receives stimulus through receptors, how the brain processes related sensory triggers in different parts of the lobes, and how transmission of signals increases as the response. While learning has shown no defined link between neuroscience, the brain’s ability to react on sensory response correlates with psychology, and how the mind interprets its environment. The theorist has illustrated many different _isms: constructivism, behaviorism, cognitivism, and a modern approach connectivism (Kerr, 2007). Each theory has beneficial contributions and limitations which help evolve the next theoretical practice. Offering solutions to another’s pitfalls will not always answer how the human brain processes information (Kapp, 2007).

In response, I agree with Kerr’s statement, “_isms are important but use them as a filter, not a blinker” (Kerr, 2007). Using one approach to facilitate learning would pose challenges when recalling information due to the limited relatable situational context needed to organize LTM effectively (Ormrod, Schunk, & Gredler, 2009). Down’s conceptualized the popular behaviorist stimulus and response approach in an analogy of a Los Vegas slot machine about Kerr’s explanation of _isms compared to a nuclear explosion disaster plan. Physically placing the coin into the slot, pulling down the handle, hearing the sounds, seeing the lights, and awareness of the environmental surroundings all play an essential factor in the appeal of the game leading players to try again. When presented with the opportunity to play a slot machine in a similar casino, the player will recall relevant situational knowledge from prior experiences and emotions, leading them to play again (Downs, 2017). Removing the flashing lights and fun sounds will not prevent spending money to play again; however, it removes sensory triggers leaving players with a less emotional connection with the game (Ormrod, Schunk, & Gredler, 2009). In Kerr’s analogy, a nuclear meltdown alert should have a list of procedures when combined with cognitivism that prevents us from being a machine (Kerr, 2007). If we used only situational influences around learning, we wouldn’t have a developed action plan because the stimuli have yet to be presented, just as a player wouldn’t typically sit at a slot machine only to feed it coins. Appling _isms as a filter would allow instructors to apply generalized concepts for information processing, and enable tailoring options to remove unimpactful methods.

Resources

Downes, S. (2017, January 1). Design: Behaviorism Has Its Place Commentary by Stephen Downes. Retrieved May 20, 2020, from https://www.downes.ca/cgi-bin/page.cgi?post=37333

Kapp, K. (2007, January 2). Out and About: Discussion on Educational Schools of Thought « Karl Kapp. Retrieved May 20, 2020, from http://karlkapp.com/out-and-about-discussion-on-educational/

Kerr, B. (2007, January 1). _isms as filter, not blinker. Retrieved May 20, 2020, from http://billkerr2.blogspot.com/2007/01/isms-as-filter-not-blinker.html

Ormrod, J., Schunk, D., & Gredler, M. (2009). Learning Theories and Instruction (Laureate custom ed.). New York, NY: Pearson.

Designs that Unclog Working Memory

The Organ

The human brain has an unlimited capacity for evolving knowledge. In instructional design, learners must be the center of all stages of a specific module via research, development, design, or implementation. How humans understand and process information through brain-based behavior can help deliver knowledge in ways that learners can receive, process, and store information adequately for later retrieval. While there is no direct link between neuroscience and how the brain processes information, there is excellent scientific evidence that the link has yet to be discovered (Jensen, 2008). Therefore, as facilitators of learning, it is crucial to understand how the brain, as an organ, functions (neuroscience) concerning education.

Inside the Cortex is where information processed is categorized into somatosensory (Parental lobes), visual (Occipital lobes), complex auditory (Temporal lobes), and lastly, “human” activities ( frontal lobes) (Ormrod, Schunk, & Gredler, 2009). After the Cortex’s lobes receive the information, knowledge remains in working memory until it is organized and stored for another similar stimulus. In summary, all knowledge is processed through the brain. How the brain uses perception, and relatability to organize and retrieve information can be classified as cognitive psychology backed by neuroscience. There is no direct relation between the two; however, one can’t exist without the other.

Information Overload

As outlined, the Cortex inside the brain is responsible for triggering responses to presented by stimuli, which can be presented in various fashions to the sensory receptors. Instructional designers can use neuroscience and how the brain interprets information through the effective use of sensory. Designing training plans should not over stimulate the sensory receptors in the CNS. Overwhelming the brain with the stimulus is no different than overworking your liver by consuming alcohol. Knowledge can be received and used while given a specific task, but with the more stimulus responses triggered, the less is committed organized long term memory. 

Cerbin defines working memory as the mental space where we do conscious, progressive thinking; however, that space has limited capacity (Cerbin, n.d.). This temporary storage allows cognitive information processing to manipulate storage later (Gutierrez, 2014). Think of working memory as a bucket; when full, the information is tossed or spilled. Even though the plastic material the bucket, made of is thin plastic, the design indentations of the bucket still lower the storage capacity. The working memory, “bucket,” uses part of the storage with tasks processed in an automatic method. When working memory is full, and the learner is challenged with many things to organize, overload sets in often resulting in a disengaged learner, but more importantly, the inability to recall responses.

Karla Gutierrez, SH!FT Disruptive eLearning contributor outlines how to design eLearning using working memory strategies, activities, and resources that will enhance cognitive processing skills using brain-function while not overstimulating. Working memory strategies help achieve a schema, receiving parts of the objective in smaller pieces (Ormrod, Schunk, & Gredler, 2009). To manage the information at each level of the pedagogy, activities, and resources help learners store information in an organization to easily retrieve under relatable circumstances. 

Conclusion 

All learning starts with the neuroscience of the brain. These discoveries have helped us understand how the brain receives processes and stores information. Where the brain stores, the data is contengient on the amount of working memory in use. To ensure learning is as simplistic for learners to process, instructional designers can use SH!FT’s suggested working memory strategies, activities, and resources. 


Resources

Cerbin, B. (n.d.). Working Memory as a Bottleneck in Learning – Exploring How Students Learn. Retrieved May 19, 2020, from https://sites.google.com/a/uwlax.edu/exploring-how-students-learn/working-memory-as-a-bottleneck-in-learning

Gutierrez, K. (2014, July 22). Designing eLearning to Maximize the Working Memory. Retrieved May 19, 2020, from https://www.shiftelearning.com/blog/bid/351491/Designing-eLearning-to-Maximize-the-Working-Memory

Jensen, Eric P. (2008). A Fresh Look at Brain-Based Education. Phi Delta Kappan89(6), 408–410. Retrieved from https://www.teachers.net/gazette/OCT08/jensen/

Ormrod, J., Schunk, D., & Gredler, M. (2009). Learning theories and instruction (Laureate custom edition). New York, NY: Pearson.