Sunday, October 11, 2009

Week 3 - Instructional Design, 10/7

I want to begin with an implication of policy guided by the assertion that technology is most effectively applied to the margins of the distribution of achievers. The logical result would be a single-tailed distribution in which the lower tail would be pushed toward the center, while the upper tail would project toward even higher achievement.

This is a potentially reasonable compromise between “no children left behind” and “supporting our highest achievers”. The moral question of whether or not the majority at the center of the original distribution are being ignored still remains, although the policy need not prevent them from availing of technology. If the assertion holds, however, then they will likely see only a marginal benefit.

This week marked a continuation of the discussion of Instructional Design strategies. Two additional strategies were introduced that warrant a comparison with ABCD (see week 2). These are ADDIE, which is better suited for product development, and ASSURE, which is designed for teachers within learning environments. Although somewhat orthogonal, both of these approaches appear to encompass ABCD. In ADDIE, Analysis encompasses Audience, Behavior and Condition of ABCD, while Design encompasses Degree. In ASSURE, “Analyze Learners” encompasses Audience and Condition, while “State Objectives” encompasses Behavior and Degree. Futhermore, both of these strategies provide implementation and evaluation objectives that are only implied by ABCD. Still, ABCD places a greater emphasis on evaluating conditions and defining measurable objectives, which are critical to the process of Instructional Design. Two other comparable strategies that merit attention are Dick & Carey, which is similar to ASSURE with additional subdivisions, and Instructional Development Learning System, which is comparable to ADDIE.

Despite the richness of these Instructional Design Strategies, their effectiveness is limited when not informed by a fundamental educational theory or system, particularly when defining learning objectives and evaluation metrics. One widely cited system (although, as its creator noted, the original treatise is largely unread!) is Bloom's Taxonomy [of Educational Objectives]. Currently, there exist three generally accepted dimensions of learning: Cognitive, Psychomotor, and Affective. Nonetheless, Bloom argued that the Taxonomy is extensible, which begs the question of which additional domains should be considered. Dr. Kim suggested the Social Domain, while I will put forth the Creative Domain. The following fictional example demonstrates the application of this (extended) Taxonomy to Behavioral objectives where the goal is to develop a new technology that will assist in the learning of mathematical related rates problems:

CognitiveStudents will be able to solve related rates problems
PsychomotorStudents will be able to use tools to construct visual graphical relationships in related rates problems
AffectiveStudents will exhibit a positive attitude toward learning related rates
SocialStudents will exhibit the ability to share ideas about related rates in small and large group settings
CreativeStudents will create a visual or auditory artifact that is inspired by their concept of related rates.

Clearly this is a rushed and simplistic example, which could be extended to include the hierarchies of learning within each domain. However, it is certainly sufficient to illustrate the richness of determining Behavioral objectives when guided by the structure of a systematic learning theory.

Another topic of discussion this week is the growing trend of the Online Charter School. These centers of learning offer an alternative for marginalized communities that cannot provide a complete range of learning opportunities for their residents. To wit, Dr. Kim noted that 17% of students surveyed in an on-line-learning study would not or could not attend traditional universities (due to familial, occupational, and other obligations or limiting factors). Still, it is clear that there are limitations to the effectiveness of the current institutions. For instance, the dropout rate of the University of Phoenix is 40% (although attrition rates are lower for those who participated in online high school learning). In order to strengthen online/distance learning to meet the needs of these marginal populations, it is helpful to consider the aspects of traditional environments that are not present in existing online environments. Areas include differentiated instruction, effective assessment, psychomotor activities, affective and social development, as well as creative opportunities. Although it is unlikely that an online forum will ever provide the richness of an interactive human environment, in cases where such opportunities are not available, it is incumbent on distance learning designers to account for these arguably fundamental educational needs.

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