Individual Differences, Teaching Approaches and New Media: Core Concepts: Theory & Research: Universal Design for Learning: CAST

Within the complex neural network of the brain, we have identified three spatially and functionally distinguishable but interconnected networks essential for learning and important in understanding individual differences: recognition, strategic, and affective networks. Every learner is unique. Labeling students as disabled, average or gifted make broad assumptions about the similarities of learners within categories (missing the differences) and about the differences between learners across categories (missing the similarities).

The kinds of learning for which each brain network is specialized demand different approaches to teaching and different uses of media. In this section we highlight individual differences, teaching approaches, and the kinds of flexibility needed in media as they relate to each of the three neural networks essential for learning.

Individual Differences in Recognition Systems

Specific differences in the recognition networks of individual learners range from the subtle to the profound. Recognition cortex in Einstein�s brain was disproportionately allocated to spatial cognition. In school he had difficulty learning to read, recognize letter patterns and sound-symbol connections, but he was a genius at visualizing the deepest fundamentals of physics.

For varied reasons, students find particular means of representation most suitable for them: some thrive in lectures, others obtain information effectively from text, while still others learn best through visual media such as diagrams, illustrations, charts, or video. One student with a proclivity for art may find an image more comprehensive than a verbal description, while another who is deaf will be shut out completely if only a verbal description is provided.

Teaching Pattern Recognition

Pattern recognition is an act of categorization requiring awareness of the critical features that identify that particular pattern in many different contexts. Teaching pattern recognition involves helping learners identify patterns in varied contexts, remember them, use them when learning new related patterns, and apply them.

Teaching recognition requires making the target pattern explicit, emphasizing it (so that it can be differentiated from surrounding information and readily recognized in the future), offering opportunities for practice (both recognizing and using the pattern), providing feedback and supporting the interest level of the learner so that they will remain engaged in the task. Some methods for emphasizing pattern include highlighting it in context, isolating it, grouping it with like patterns, contrasting it with different patterns, and articulating the key qualities or "rules" if they apply. See Chapter 6 of Teaching Every Student in the Digital Age (http://www.cast.org/teachingeverystudent/ideas/tes/chapter6_4.cfm).

Media flexibility for Recognition Networks

To adjust to different recognition networks, UDL learning materials provide multiple representations of target patterns so that learners can select the medium or media of preference, or elect to use multiple media simultaneously. It is essential to consider the learning goal when providing multiple representations.

Some patterns transcend media and can be taught in whatever medium most suits the learner. For example, a sequence of events can be effectively conveyed through text, images with no text, images with text, a sequence of sounds, voice, animation, or video. For example, when teaching the sequence of Chinese dynasties, there is nothing inherent in the subject matter to suggest that one medium would be more appropriate than another. Here, teachers can adjust media according to learner preferences and needs because the essence of the lesson is maintained across media representations. Different media options can be offered to highlight, practice and apply the pattern in various contexts.

Use of alternative media may not be appropriate for some kinds of learning goals. For example, when students are learning to discern the structure of a story, providing a visual map of the story might eliminate the challenge. Further, text to speech supports could eliminate necessary resistance for students learning to decode words.

Individual Differences in Strategic Networks

Individual differences in frontal networks account for much individual variation in fine motor skill, physical coordination, and capacities for planning, organization, strategic thinking and expression. Learners differ dramatically in their ability to acquire and "automatize" routines such as forming letters, typing, spelling, or multiplication, in their ability to plan and organize an evening's workload or a lengthy project, in their ability to monitor their own progress and revise their strategies or to seek help, as well as many other aspects of learning.

Collage of photographs showing different learning styles.

Students also differ widely in their ability to use different kinds of tools. Students with motor difficulties may be marginally able or unable to use a keyboard or mouse. Students with speech difficulties may be unable to present their ideas orally. Those with language and learning disabilities may find that they must allocate so much attention to the mechanics of producing written text that it is difficult to communicate effectively in that medium. A brilliant musician may produce an adequate written paper in text, but if given the opportunity to write a song to fulfill the assignment, she may excel.

Teaching Strategic Skills

Learning a skill is a different kind of process than learning to recognize a pattern. Consider a child learning to ride a bike. The child becomes interested and excited about learning to ride by watching other more experienced riders. Once she is ready to begin she needs help getting started because riding a bike requires a complex interrelated skill set, too difficult to acquire all at once. An expert bike rider scaffolds her early efforts with training wheels or a balancing hand on the back of the seat. With the right support and lots of practice she begins to get the hang of it; the expert raises the training wheels and assists less and less. Finally the child is ready to ride on her own. She practices until the skill be comes more or less automatic, allowing her to direct her thoughts and energy toward more complex riding tasks � like handling difficult terrain or enjoying the scenery as she rides.

Media flexibility for Strategic Networks

Individualizing all aspects of apprenticeship is difficult to do in a traditional classroom with traditional materials. Although teachers can model skills for an entire classroom of students, there is usually no practical way for them to offer individualized feedback, customized practice and scaffolding or individual opportunities to demonstrate skill.

Because timely individualized feedback is a critical component of apprenticeship learning, media flexibility can provide only part of the solution for individualizing strategic skills instruction. Media flexibility can support apprenticeship learning in the following ways:

Each of these models can be stored on individual computers or on line, and can be called up as needed by different learners.

Although individualized substantive, and relevant feedback is very difficult to automate via a commuter, various tools can be used effectively to help students learn to self-monitor.

These kinds of adjustments give learners with very different strategic networks the chance to build skill and demonstrate competence in ways that suit them.

Individual Differences in Affective Networks

Individual differences in affective networks are reflected in differences in what attracts, motivates, and engages us. The same task, book, or teaching approach may build competence and confidence in some students while frustrating or boring others.

Students become deeply engaged in learning for many different reasons (e.g., fascination with subject matter, correct level of challenge, making progress and learning at a suitable rate or connecting with an authentic real life purpose). Equally diverse are the reasons that students lose their learning spark (e.g., a creative child who encountres failure because of difficulties with written organization and spelling, a child who thrives on exploration and experimentation continually required to memorize facts, or a child who excels but is given little feedback and encouragement).

Just as other parts of the brain learn from practice, the affective network learns patterns of feeling and emotional response from experiences over time. Past experience teaches us to repeat activities that give us pleasure or satisfaction and avoid the ones that cause pain, boredom or humiliation. Over time, experiences that do not engage learners, for whatever reason, can erode their willingness and ultimately their ability to work and to persist.

Teaching to Support Engagement

Because different students become or fail to become engaged in learning for very different reasons, teachers need to have multiple approaches to engagement at their disposal. Ideally, they should be able to support students' varied affective networks through variable content, levels of challenge, and learning contexts. For any given student, teachers need to be able to provide content that is interesting, at an appropriate level of challenge, has appropriate supports and scaffolds that can be withdrawn as skill improves and contains timely, personally relevant feedback so that the student can observe progress and adjust accordingly. The combination of these options should vastly increase the number of students who become and remain engaged in learning, building the "habit" of responding to challenge with enthusiasm and persistence. See Chapter 6 of Teaching Every Student in the Digital Age (http://www.cast.org/teachingeverystudent/ideas/tes/chapter6_6.cfm).

Media Flexibility for Affective Networks

Digital materials and electronic networks have the potential to provide the required flexibility for affective learning but developers, researchers, and educators will have to ensure that sound pedagogy guides the development of new digital curricula. For example, consider the issue of subject matter interest. In a mathematics exercise, students could in theory select content according to their interests and work with numbers in the context of their choice. In print, one might theoretically have to have as many books as students. But on-line, a selection of links can provide varied content to be used in a single exercise, allowing students to follow their interests within a structured framework. Similarly, for practice building fluency and comprehension in reading, students could select from a variety of on-line fiction and nonfiction options at an appropriate reading level for them.