Analysis of the Requirements of Teaching Tasks
The following conclusions about media in learning are drawn primarily from Fleming's work. The purpose of this review is to provide a basis for the observations contained in Figure 6-1.
A key learning principle, according to Fleming, is that attention by the learner to appropriate instructional stimuli is fundamental to learning. To be effective, training must attract and hold the learner's attention. Instruction must also recognize that attention tends to be
- individual—the capacity to be attentive varies among individuals, and it varies for any individual at different times (e.g., fatigue or lack of background can cause attention to wander sooner than usual).
- selective—at any one time, a learner's attention can be focused on only a small part of the learning content.
- fluid—as a teaching topic changes, the learner must know when and how to shift attention; however, some learners may become distracted, confused, or otherwise lose the main point during shifts in attention.
- especially attracted to novelty, to moderate levels of complexity, and to the contents of more focused, less complex displays.
Perception and Recall
Perception requires that the learner selectively focus on and make sense of stimulation in the environment, including the learner's own internal states and responses (thoughts, feelings, and physiological states). In a sense, all education and training is intended to make learners capable of finer and more articulate perceptions and distinctions. Recall involves the ability to remember and make use of relevant prior learning, as well as of the learning acquired in a given situation.
Perception and recall in teaching draw on principles such as those below.
- Organization affects perception; that is, events, ideas, words, concepts, and other stimuli that are not organized in some meaningful way are more difficult to understand and remember than those that are.
- Perception and recall can be aided by comparison and contrast; similarity and grouping also assist recall.
- Presentations that focus on differences are distinguished better by learners, and their contents may be easier to recall.
Organization and Sequencing
Organization and sequencing are present in the learning models represented in Figure 6-1. In Chickering and Gamson's model, responding to diversity in learners' needs suggests the possibility of reorganizing and resequencing materials and activities. In regard to Moore's model, providing guidance and support has direct implications for organization and sequence. (Bloom's  “quality tutorials” could also extend to organization and sequence, depending upon the definition of “quality.”)
For Fleming, the organization and sequencing of materials is an important task in instructional planning. The general principles listed below particularly apply to media design.
- The first and last items in a sequence are especially important; introductions and summaries represent key learning opportunities.
- Modeling and demonstrations can result in learning. While learners eventually must become active in the process of acquiring skills and knowledge, students can also learn while watching. Active internal states produce intellectual engagement, just as psychomotor activity accompanies the learning of physical skills.
- Repetition and review increase learning up to a point. Repetition can be used to increase skill, automaticity, and speed; however, power (depth of understanding, breadth of proficiency) is usually not increased by repetition alone.
Instruction and Feedback
While learners require skilful instruction, they also require feedback to enable them to monitor their progress, to discover errors or misconceptions, and to recognize what they should do differently (or continue to do) to gain further proficiency. Not all feedback is equally useful, however, and not all learners require the same kind of feedback. Principles applicable to media design and use include those listed below.
- The more mature the learner, the more informative the feedback should be.
- With mature learners, correct answers should simply be marked “correct.” Mature learners tend to dislike excessively demonstrative praise.
- Feedback should be prompt, but it does not have to be immediate. Learners should know how much delay to expect in test results and marking.
- Exceptions to the above point occur when feedback on previous steps is needed before subsequent ones can be taken; when there is a safety concern (i.e., previous steps must be correct or later ones could result in a dangerous situation); or when the task is highly complex.
- Feedback can be reduced as the learner becomes more experienced and more proficient. Initially, feedback should be frequent for most learners, to ensure that they have a positive initial experience.
All of the models in Figure 6-1 recognize that quality instruction includes the presentation to the learner of appropriate explanations, with the option for additional feedback. Chickering and Gamson's reference to student-instructor “contact” implies this element in their model. Importantly for this discussion of media-based learning, none of the models assumes that contact or interaction need be face-to-face to be effective.
Learning requires engagement with the subject matter, and engagement often implies some kind of performance. In the case of psychomotor skills, the activity is usually physical, with evaluation dependent on observable outcomes. Occasionally, however, an activity may be completely or largely mental, according to the following principles.
- Activities that encourage the formation in the learner of mental images increase learning. Activities that require the learner first to process and then to reproduce a version of the original information do more to encourage learning than do rote reproduction and imitation alone.
- Language use accompanying or providing context for newly learned concepts increases learning; for example, composing a verbal narrative while learning complex or abstract material assists in retention. This principle can even extend to psychomotor skills, which is the reasoning behind “visualization” exercises in sports.
The use of experience and practice in learning requires willing learner participation and the conscientious application of new skills and knowledge for proficiency to develop. Peter Garrison quotes Galison's observation that moving from declarative knowledge (knowing that something is true, or how something might theoretically be done), through procedural knowledge (knowing how an activity is performed), to craft knowledge (being able to perform a procedure or to use knowledge with expert proficiency) requires practice, feedback, and application. Craft knowledge, the distinction between the novice and the expert, is the objective of many kinds of academic learning, and all higher-level skill training.
As are the tasks of instruction and feedback, learner involvement is common to all three learning models under discussion here (Figure 6-1). Time on task is added to show that participation must be purposive and relevant. The noun “cooperation” and the adjective “active” in Chickering and Gamson's model add the notion that the learner's involvement should be more than passive observation of others' efforts or conclusions, a position with definite implications for media implementation.
Concept Formation and Higher-Order Thinking
The learning of concepts or principles is often intended to be part of a process leading to engagement with other, related concepts. In formulations such as Gagne's, below, the learning sequence is hierarchical, and as the learner moves up the sequence, more complex orders of reasoning are required:
- Signal learning—involuntary responses; for example, the startle response, or removing a hand from heat.
- Stimulus-response learning—voluntary, selective responses; for example, signaling in response to a specific cue, or imitating an action.
- Motor-chain learning—performing a sequence of actions in a certain order; for example, dancing, parallel parking, or replacing a light bulb.
- Verbal association or verbal chaining—reciting correct responses to cues; for example, singing the lyrics of a song, reciting the alphabet, or translating a word from one language to another.
- Multiple discrimination—responding differently to similar stimuli; for example, distinguishing individual but related members of a group, or giving an appropriate English equivalent for a foreign word.
- Concept learning—responding to new stimuli according to properties they share with previously encountered stimuli, or comparing properties of phenomena; for example, estimating the characteristics of similar objects based on knowledge about their composition (a large rock vs. a large pillow), identifying members of a group (saltwater vs. freshwater fish), and distinguishing examples and non-examples of a class or phenomenon (vegetables vs. non-vegetables).
- Principle learning—putting two or more concepts together in a relationship (without necessarily being able to explain the underlying rule governing the relationship); for example, applying physical laws (“matter expands when heated”) or mathematical theorems.
- Problem-solving—recalling previously learned principles and using them in combination to achieve a goal; for example, selecting and combining facts in an essay to persuade, analyzing a problem to determine its cause, or solving a complex problem by selecting and applying previously learned facts and principles.
Higher-order thinking skills (HOTS) are a challenge in technology-based learning. A persistent criticism of computer-assisted learning (CAL) and case-based learning using intelligent agents and artificial intelligence algorithms has been their failure to move beyond the mere identification and use of facts, to creative and synergistic linking of concepts.
In Figure 6-1, HOTS are present by implication in two of the models, in references to improved reading and study skills, and in the objective of communicating high expectations to learners. However, the lack of specific reference to concept formation or higher-order thinking in these models, and the other apparent gaps in the resulting table, may be less a lapse than a reminder in this discussion that somehow these tasks must be addressed in media-based learning. The developers of the pre-online models represented in Figure 6-1 undoubtedly accept that higher-order outcomes are preferred. The challenge to media developers is to make this objective specific and achievable, as discussed below.