Developing Prescriptive Taxonomies for Distance Learning Instructional Design

Developing Prescriptive Taxonomies for Distance Learning Instructional Design

Vincent Elliott Lasnik (Independent Information Architect, USA)
Copyright: © 2009 |Pages: 15
DOI: 10.4018/978-1-60566-198-8.ch088
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Abstract

One of the central problems and corresponding challenges facing the multidisciplinary fields of distance learning and instructional design has been in the construction of theory-grounded, research-based taxonomies for prescribing what particular strategies and approaches should be employed when, how, and in what combination to be most effective and efficient for teaching specific knowledge domains and performance outcomes. While numerous scholars and practioners across a wide range of associated instructional design fields have created a rich variety of effective, efficient, and very current prescriptions for obtaining specific learning outcomes in specific situations (Anderson & Elloumi, 2004; Marzano, 2000; Merrill, 2002a; Nelson & Stolterman, 2003; Reigeluth, 1999a; Shedroff, 1999; Wiley, 2002), to date, no single theory-grounded and research-verified unifying taxonomic scheme has successfully emerged to address all existing and potential educational problems across the phenomena of human learning and performance.
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Introduction

There are simple answers to all complex problems… and they are uniformly wrong. -- H.L. Mencken

One of the central problems and corresponding challenges facing the multidisciplinary fields of distance learning and instructional design has been in the construction of theory-grounded, research-based taxonomies for prescribing what particular strategies and approaches should be employed when, how, and in what combination to be most effective and efficient for teaching specific knowledge domains and performance outcomes. While numerous scholars and practioners across a wide range of associated instructional design fields have created a rich variety of effective, efficient, and very current prescriptions for obtaining specific learning outcomes in specific situations (Anderson & Elloumi, 2004; Marzano, 2000; Merrill, 2002a; Nelson & Stolterman, 2003; Reigeluth, 1999a; Shedroff, 1999; Wiley, 2002), to date, no single theory-grounded and research-verified unifying taxonomic scheme has successfully emerged to address all existing and potential educational problems across the phenomena of human learning and performance.

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Main Focus: Instructional Taxonomies - What They Are And Why They Matter

In his hallmark narrative work on the complexities of successfully building a learning environment, media pioneer Edgar Dale identified important considerations for the development of any prescriptive taxonomy for instruction, as well as this encyclopedia broadly conceived:

Indeed product and process must not be separated, any more than we would separate form and content…A major issue in all learning deals with the processes by which learning experiences become structured, organized, mapped, patterned, clustered, and systemized. We group experiences, using some kind of framework, paradigm…schema, summary, matrix, model, unit, brief, diagram, category, concept, hierarchy, grid, or outline. We use hierarchies, superordination and subordination…All these terms indicate a linking, a relating of experience on the basis of their differences and likenesses. Process and product, form and content become fused, structured. (pp. 82-83)

Key Terms in this Chapter

Instructional Design: An applied, cross-disciplinary professional (postgraduate) design discipline that integrates human learning theory and instructional practice to develop, produce, implement, and evaluate effective educational experiences and learning environments to improve human performance outcomes, knowledge construction, and the acquisition of robust transfer competencies.

Granularity: Granularity is a hierarchical concept associated with the relative degree of complexity of a component part to its aggregate, subsuming structure. Fine silt is more granular than sand, which is more granular than rock, and so forth. In taxonomic development, the smaller the relative size to the taxons (units) of classification, the higher the degree of granularity. In instructional design, the concept of granularity is multifaceted, and can refer to the size of learning units or scope (e.g., degree or certificate curricula, courses, lessons, modules, activities); learning element prioritization or sequencing (e.g., logical order of lessons, concept formation and skill acquisition to optimize scaffolding in new knowledge construction); content domains architecture (e.g., superordinate concepts, subordinate concepts, rules, principles); teaching strategy (e.g., individual vs. group learning, passive learner/expository vs. active leaner/discovery, inductive vs. deductive, tutorial vs. simulation, abstract vs. problem-oriented, synchronous online chat vs. asynchronous threaded discussions, etc.); media design and utilization (e.g., relative size and complexity of single components or combined components, type of media element including text, graphics/visuals, audio, animation, degree of user control, etc.); and learner assessment (e.g., conventional declarative-convergent testing using multiple-choice, matching, and short-answer questions vs. holistic, constructivist-divergent portfolios with demonstration work-product artifacts from individual and group projects, internships, and service learning).

Taxonomy: From the Greek taxis (for arrangement, order) and nomos (law): Every serious taxonomy is an organizational scheme that includes a system representing structure, order, and relationship. Some form of hierarchical structure is generally defined, but this may be multidimensional and nonlinear in form. The purpose, domain, attributes and granularity of schema vary, but all taxonomies attempt to provide a robust (i.e., logical, coherent, cohesive, internally consistent) architecture. Prominent examples include the widely adopted schema of Carl Linnaeus (biology) and Dmitrii Mendeleev (The Periodic Table of Elements). Most taxonomies contain their own nomenclature for describing the taxons (singular) and taxa (plural) that correspond to formal units in the classification scheme, such as kingdom, phylum, class, order, family, genus, species (adapted from Linnaeus). Taxonomies may evolve over time. Neither systems of Linnaeus or Mendeleev are exactly in the original form when they were first presented, but they are fundamentally and substantially the same in all relevant aspects and overall structure, changing only as our knowledge of science changed over time to add additional granularity to the taxons and taxa of their brilliantly original and enduring descriptive taxonomies.

Hybrid Learning Taxonomy: A comprehensive organizational scheme in applied learning and instructional design theory and practice that integrates both descriptive and prescriptive taxonomic domains. While a number of conceptually useful hybrid learning taxonomies have been proposed, there is, to date, no single, inclusive, unifying hybrid taxonomy that effectively synthesizes all of the design elements of instruction to sufficient practical levels of granularity and application.

User-Centered Design: User-centered (a cognitive/perceptual term) and usage-centered (a behavioral/functional term) are postmodern design descriptors often arbitrarily or ambiguously defined and interchangeably used and misused. In the context of 21st century instructional product design theory and practice, user-centered design focuses on constructing a user experience and environment with physical and virtual affordances that are manipulable, controllable, customizable, and adaptable from the essential perspective of the conceptual model of the learner. This means both (a) the learner’s metamodel of their own learning processes and the learning activities and environment, and (b) the designer’s model of the learner and the corresponding educational activity and experience, with the former driving and superseding the latter in the design solution. Thus, the conceptual model of the learner becomes the superordinate principle guiding the design process and learning outcomes (i.e., the highest level of the prescriptive taxonomy). Usage-centered design focuses primarily on the functional goal-based behavior of learners and structuring activities, procedures, processes, and corresponding affordances to optimize the effectiveness of the learner to efficiently accomplish those intrinsic goals. In both of these approaches, however, the conventionally deterministic structure of the content and the underlying information architecture of the knowledge domain are secondary considerations, while the learner’s conceptual model and intrinsic goal-driven behavior provide the guiding blueprint for the instructional design solution.

Descriptive Taxonomy: In educational theory and practice, an organizational scheme for classifying the structure of conditions for learning describing the approaches, types, events, methods, and goals of instruction. While affective and psychomotor capabilities are also of importance, classic instructional design theory has focused on the cognitive domain and has been exemplified by the widely adopted hierarchical taxonomies of Bloom (1956) and Gagne, Briggs, and Wager (1992).

Prescriptive Taxonomy: In educational theory and practice, an organizational scheme for specifying the optimal and appropriate approaches, types, events, methods, media, strategies, techniques, activities, tasks, projects, scope and sequence of instruction to achieve corresponding specific learning objectives and desired performance outcomes. While numerous scholars and practioners across a wide range of associated instructional design fields have created a rich variety of effective and efficient prescriptions for obtaining specific learning outcomes in specific situations, to date no single theory-grounded and research-verified unifying taxonomic scheme has successfully emerged to address all existing and potential educational problems across the phenomena of human learning.

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