The Sharp Edge of the Cube: Pedagogically Driven Instructional Design for Online Education
In our November issue, Nishikant Sonwalkar opened a discussion of pedagogical
learning styles with a feature article, “Changing the Interface of Education
with Revolutionary Learning Technologies.” Here, he follows the thread
further, focusing on pedagogically driven design principles for online education.
Pedagogy can be defined as the method by which educational content is exposed
to learners. There are more than 300 different pedagogical strategies that have
been proposed to define the underlying cognitive process. Activist, constructivist,
reflective, incidental, apprenticeship, inductive, deductive, collaborative—these
are just a few pedagogical theories that are widely debated.
Models for Online Learning
In the November issue of Syllabus, I proposed a “learning cube” that
combines six different media—text, graphics, audio, video, animation, and
simulation with five functional learning styles—apprenticeship, incidental,
inductive, deductive, and discovery. The learning cube (see Figure 1) is an
attempt to provide a framework in which multimedia assets can be correlated
with pedagogically driven learning styles.
Figure 1: The learning cube
Let’s take just one example of what the learning cube can reveal about
the potential of online pedagogy. The apprenticeship style of learning suggests
that educational content should unfold in a step-by-step procedural model; however,
the same content could be exposed in the form of a case study or story in the
incidental learning strategy. The intent of the learning cube-based pedagogical
model is to organize and sequence the multimedia content assets in a pedagogically
distinctive learning path that matches the style of individual learners. Ideally,
all learner preferences can be accommodated.
It is important to understand that pedagogy influences the methodology for
content sequencing and chunking, while instructional design enables an organized
structure for the dissemination of online courses.
Based on the learning cube, one can generate a simpler 2D model (see Figure
2) of a flexible cognitive approach to pedagogical strategies for online education.
The model correlates learning assets (media) with pedagogical learning styles.
The learning path scales from student-centered to teacher-centered relative
to involvement with media and the degree of independence offered by the learning
strategy. Presumably, the learning path could deviate based on perceived learner
needs in any given instance.
Figure 2: 2D pedagogical model for online education
In Search of Instructional Design
Instructional design is a process that enables conversion of raw content into
a structured distribution—e.g., into a lesson structure. Conventionally,
instructors have prepared lecture notes from reference books and textbooks on
a given subject. This is a process of converting domain knowledge into structured
lectures or lesson plans.
The instructional design for a Web course is still an art form. This is primarily
because of the variations in the nature of course content. The learning models
that are appropriate for course material are numerous, and a wide range of possibilities
exist for the course’s structure. Instructional design in the conventional
sense addresses the need for structuring course content to meet the curriculum.
However, in the context of online education, instructional design leads to information
design and chunking.
For asynchronous learning, it is extremely important to note that distributing
course content in the form of online textbooks (e.g., in PDF or HTML formats)
is not sufficient. Adding to this distribution format just causes information
overload on the course Web site, which can be detrimental to learning goals.
And a well-endowed course Web site cannot by itself deliver successful online
education.
Pedagogically Driven Instructional Design
Three issues are central to the development of pedagogically driven instructional
design for online education: learning style-based instructional design, design
parameters, and the design and development procedure.
Learning Style-Based Instructional Design
In my previous article, brief definitions of the learning styles for the learning
cube were provided. Here, I’ve augmented those definitions with listings
of recommended content and media objects, in order to illustrate the multiple
media available to any given learner and to show how the learning styles—apprenticeship,
incidental, inductive, deductive, and discovery—can influence the instructional
design of an online course.
Apprenticeship. The apprenticeship style uses a “building block”
approach for presenting concepts in a step-by-step procedural learning style.
This approach is particularly appropriate for the task-oriented areas where
one can identify clear step-by-step procedures.
Recommended content and media objects include:
- Text (explanations, descriptions, examples)
- Graphics or animated illustrations (explanations, descriptions, illustrations,
demonstrations, examples)
- Audio (explanations, examples)
- Video (explanations, examples)
Incidental. The incidental style is based on “events” that
trigger the learning experience. The events usually occur in a less formal context
and often assume a story format. Learners begin with an event that introduces
the concept and provokes questions about it. Learners are then prompted to knowledge
presented in the steps that may lead to procedures about the target concept.
Explanations are then provided.
Recommended content and media objects include:
- Text (explanations, stories)
- Graphics or animated illustrations (explanations, descriptions, illustrations,
demonstrations, examples)
- Audio (procedures, examples)
- Video (steps, procedures, examples)
Inductive. The inductive style suggests that learners first be introduced
to a concept or a target principle using specific examples that pertain to a
broader topic area. The examples enable learners to develop their own connection
between the concept and the examples that confirm the principle. The examples
lead to conclusions or questions about the material, which may then be confirmed,
refined, or answered with subsequent explanations.
Recommended content and media objects include:
- Text (explanations, examples)
- Graphics or animated illustrations (explanations, descriptions, illustrations,
demonstrations, examples)
- Audio (explanations, examples)
- Video (explanations, examples)
Deductive. The deductive style is based on stimulating the discernment
of trends through the presentation of data, simulations, graphs, charts, or
other data. Based on the data provided, learners are instructed to infer concepts
and postulates. Additional explanations are then provided if necessary. The
examples or data presented lead to the concept that is part of the learning
objectives.
Recommended content and media objects include:
- Simulations (interactive simulations, virtual labs)
- Text (explanations, prompt questions)
- Graphics or animated illustrations (explanations, descriptions, illustrations,
demonstrations, examples)
- Audio (explanations, examples)
- Video (explanations, examples)
Discovery. The discovery style is based on an inquiry method of learning
in which the learner understands concepts in a “learn by doing” methodology.
Learners test the boundaries of their own knowledge and ability by first engaging
in an interactive exercise, simulation, or quiz.
Recommended content and media objects include:
- Simulations (interactive simulations, virtual labs)
- Text (explanations, prompt questions)
- Graphics or animated illustrations (explanations, descriptions, illustrations,
demonstrations, examples)
- Audio (explanations, examples)
- Video (explanations, examples)
Design Parameters
The design parameters are numerous and need careful consideration. A few important
decision parameters include learning objectives, pedagogical learning styles,
synchronous vs. asynchronous, textbook vs. experiment-based, media assets and
enhancements, duration of delivery, technological constraints, and educational
standards.
Learning objectives. Learning objectives are often loosely defined and,
as such, do not provide much help in the development of the instructional design.
For example, if the learning objective is “to teach a course in introductory
fluid mechanics,” it d'es not help define what the scope and extent of
the course content will be. It is important, therefore, to describe the course
objectives in the form of a finite set of fundamental concepts that will be
taught in the online course. A pedagogically driven instructional design requires
that the course objectives be defined in terms of concepts.
Pedagogical learning styles. The pedagogical learning styles—apprenticeship,
incidental, inductive, deductive, and discovery—define the pedagogical
strategy for the exposition of the course content. The intent of the lesson
strategy and the relevant media assets are chosen based on the examples given
in the previous section.
Synchronous vs. asynchronous. The instructional design will change dramatically
based on whether the instructor is available to students by synchronous communication
online or by asynchronous e-mail. The predominant mode for online courses will
be asynchronous, so appropriate devices such as chat rooms, discussion boards,
and news groups need to be included in the instructional design.
Textbook vs. virtual experiment-based. The content development to support
online education will change if the source is a textbook. The textbook, in the
conventional sense, is sequenced in terms of chapters, sections, and subsections.
In the case of online courses, content is defined in terms of course structure
hierarchy. Besides viewing course content creation in terms of the hypermedia
textbook, it is important to define the interaction between instructor and student.
And the educational environment needs to be designed around content objects
that are presented in the multiple learning styles developed in the hypermedia
(Web) environment (see Figure 3).
Figure 3: Design of a hypermedia textbook-based course
The online virtual experimental course requires a much different design method.
In Web-based experimental courses, termed Web labs (see Figure 4), the content
is developed as a set of simulations that support discovery-based learning.
Such environments could include animation, 3D visual simulations, or virtual
reality-based immersion learning. Such simulations are called hypermedia laboratories,
and they connect to the interactive asynchronous interface between instructors
and learners.
Figure 4: Design of a hypermedia-based Web lab course
Media assets and enhancements. Media assets—text, graphics, audio,
video, animation, and simulation—constitute the content collection for
an online course. The instructional design can take advantage of the learner’s
cognitive preferences if the content is available in each of the various media
formats.
Duration of delivery. Perhaps it’s obvious that a semester-long
course will require much more content for instructional design, compared to
a two-week-long “short course.” Stand-and-deliver lectures, when converted
to online, computer-based instruction, actually require more content to ensure
that the concepts are presented in an interactive, multimedia fashion. In a
purely asynchronous online environment, the duration can vary, so it is essential
to provide instructor feedback for the duration of the course.
Technological constraints. Technological constraints are important design
variables—especially in relation to the success of interactive Web pages
that can be accessed via the Internet. The network bandwidth limitations on
accessing an online course using a 56 kilobits/sec modem are severe when compared
to accessing a course in the workplace using a T1 line that provides close to
a 1 megabit/sec connection speed.
Web browsers pose technical limitations on the media objects that can be distributed
via the Web. Similarly, Internet servers, video servers, and chat servers demand
careful consideration in instructional designs.
Educational standards. The evolving standards, such as Instructional
Management System (IMS), Aviation Industry Courseware Committee (AICC) standards,
and Sharable Courseware Objects Reference Model (SCORM), provide guidelines
for course structure object hierarchy, course structure objects, learning assets,
and assessment models.
Design and Development Procedure
It is important to note that the procedure involved in the creation, design,
and development of online education requires participation from the domain expert—to
envision the course structure, formulate a strategy for pedagogical presentation
with multiple learning styles, and specify the content sources (see Figure 5).
Figure 5: The design and development procedure
It is essential that the content experts work closely with the instructional
designer to develop the appropriate pedagogical strategy, and work with Web
developers and graphic designers to create an effective graphical user interface.
Next, content is collected from the appropriate sources, with copyright permissions,
and converted into formats compatible for delivery via Web pages. Once the content
is converted into Web-compatible formats, it is chunked to meet the instructional
design requirements to create learning assets and objects. These learning assets
are described with metadata standards and loaded into databases that are compatible
with IMS, AICC, or SCORM standards.
At this point in development, content is prepared for deployment via the Web,
and the Web course pages are made available to content experts for final editing.
Once the final edits are made, all the hypermedia learning assets are assembled
and compiled to follow the learning styles for online courses. It is essential
to conduct user interface testing with a focus group in order to fix any problems
that may arise regarding page layout or navigation.
Education is a process that requires the design and development of media content
in the context of pedagogical learning styles. It is crucial that the design
of the next generation of online courses take into consideration a large degree
of flexibility in learning styles and support interaction between instructor
and learners in the asynchronous environment.
