Building Learning Architectures: Domain Instruction Server (DIS)
Juan E. Gilbert1
Auburn University
Computer Science & Software Engineering
107 Dunstan Hall
Auburn, AL 36849 USA
gilbert@eng.auburn.edu
Dale-Marie Wilson1
Auburn University
Computer Science & Software Engineering
107 Dunstan Hall
Auburn, AL 36849 USA
wilsodc@eng.auburn.edu
Abstract: Web based instruction is growing at an incredible rate. Teachers, instructors,
trainers and several others are putting their instructional content online. The format, style
and media types vary from instructor to instructor. In essence web based instruction is
being done by an unknown number of people in an unknown number of ways using
different media types and platforms. In this paper, an instruction repository will be
introduced that has the ability to unite all web based instruction under one umbrella. The
media types, platforms, instructors and formats will remain independent. The repository
creates a new learning architecture for web based instruction.
Introduction
The web has been heavily populated with instruction. There is an unknown number of
instructional lessons on the web. Finding useful instruction on the web is a very difficult task. This task
creates the need for an unifying repository. The creation of such a repository would facilitate ease of
search, reuse and universal access. This learning architecture would create a new model of instruction. In
the traditional classroom, there exists a one-to-many instructor-student model. There is one instructor
teaching many students. In a tutoring environment, there exists a one-to-one instructor-student model.
Implementing this new learning architecture, the instructional model will be changed to a many-to-one
instructor-student model (Gilbert 1999). This repository of instruction will provide each student with many
instructors facilitating a many-to-one instructional model. In this instructional model, the major task is
matching students to instructors that accommodate their learning style (Dunn 1978). In the sections that
follow, the architecture for a distributed instruction repository will be discussed.
Repository Model
The internet consists of several domain name servers. Each domain name server contains a list of
domain names, i.e.: www.eng.auburn.edu , and a corresponding IP address. When a browser connects to the
web, it will ask a domain name server for an IP address before it is connected to the requested web site.
This model can be adopted to define a learning architecture that consists of an instruction repository with
domain names and instructional meta data.
In the instruction repository, instructors/teachers can submit queries that will yield a domain name.
The domain name will correspond to an instructional lesson on the web. This function is similar to the
domain name service, but it also models credit card processing on the web. For example, most electronic
commerce sites buy or lease merchant services from a merchant service provider. The merchant service
provider gives the store owner access to their credit card processing server. The store owner submits a
query to the credit card processing server and the server returns a response code. The response code
informs the store owner of an acceptance or rejection of the credit card transaction. By combining the
credit card processing model and the domain name service model, a new learning architecture can be
implemented. This new learning architecture is the Domain Instruction Server (DIS) environment.
Domain Instruction Server (DIS)
The Domain Instruction Server (DIS) is a repository consisting of web deliverable instructional
lessons. The sequential organization of a collection of instructional lessons defines a course. Instructional
lessons are created by an instructor and placed on a web server. The web server may belong to their
college, school, company, internet service provider or it may be their own personal machine. In any case,
the web server is world accessible and it contains their instructional lessons. Each instructional lesson has
several common attributes. These attributes can be viewed as instructional meta data.
The instructional meta data associated with each instructional lesson is uniquely identified by a
location attribute. The location attribute is a web address that points to the first page of the instructional
lesson. For example, if an instructor creates a web based course that consists of 30 instructional lessons.
Each instructional lesson will have a first page. This first page will have a corresponding web address. This
web address will be stored as part of the meta data for each instructional lesson. All subsequent pages that
follow the first page will be linked from the first page. A few of the other meta data attributes are:
00Lesson Name
00Instructor's Contact Information (name, email, etc.)
00Instruction Method-Media (i.e. Visual, Audio, Video)
00End Of Lesson Quiz Location
00Lowest Passing Score
00Assistant(s) Contact Information (i.e. Graders)
00General Description
These attributes are common across all instructional lessons stored within the repository. By collecting
several instructional lessons from several instructors the repository creates a high level view for each
course as seen in figure 1.
Figure 1: High level view
In figure 1, there are three instructors teaching the same course. This course is composed of five lessons
and fifteen different instructional lessons. Each row in figure 1 corresponds to a lesson, i.e. an entry on a
syllabus. The columns under each instructor represent an individual course taught by the above instructor.
Each instructor teaches the same course using a different media type or style. Each rectangle in figure 1 is
an instructional lesson consisting of all the meta data mentioned above. Figure 1 is a high level view of the
DIS organization. The lower level architecture is discussed next.
DIS Architecture
The architecture that supports the DIS environment is very flexible. The primary objective in
defining the architecture is to obtain total flexibility with respect to varying platforms across various
implementations. This architecture must be platform independent, universally accessible and easy to use.
With these requirements in mind, the architecture in figure 2 was defined.
Figure 2: DIS Architecture
In figure 2, there are three layers. The first layer consists of the students. These are designated by
the diamonds. The students are using a web browser to connect to the second layer. The second layer is
composed of multiple delivery systems.
Delivery systems are the middleware that provide instructor flexibility for their instructional
lesson selection process. Within the DIS architecture, there exists the concept of instruction method
selection. As described by figure 1, the DIS contains several instructional lessons. These instructional
lessons have to be selected for use. The process of selecting an instructional lesson for use is called
"instruction method selection" (Gilbert 2000) Within instruction method selection the tasks of how, when
and which instructional lesson to select must be addressed. For example, in figure 1 there are three different
instructors teaching the same course consisting of five different instructional lessons. The first instructor
may choose to use instructional lesson number 2 before instructional lesson number 1. In this case, the
sequence of the instructional lessons for the first instructor would be 2, 1, 3, 4 and 5. The other instructors
will sequence their units as 1, 2, 3, 4 and 5. This difference in instructional lesson sequencing can be
facilitated through the use of two different delivery systems. Each delivery system uses the same repository
to select instructional lessons, yet the order in which the instructional lessons are selected differs. Delivery
systems may also vary on how and when to select an instructional lesson.
Instructional lessons are generally selected after one instructional lesson has been completed. This
process is common between all delivery systems. In general, each instructional lesson contains an
evaluation measure. Typically, the evaluation measure is in the form of a quiz. Based upon the student's
performance on the instructional lesson's quiz, the next instructional lesson can be selected. Gilbert (2000)
used case-based reasoning (Kolodner 1993) as the instruction method selection technique. For example,
when a student completed an instructional lesson, the student was given a quiz. If the student scored 80%
or better on the quiz, the next logical instructional lesson was selected using the same instructor's method.
The 80% can be viewed as an instruction method selection threshold. If the student scored below 80%, the
student was forced to retake the lesson using a different instruction method. The instruction method was
selected by treating the student's quiz as a case which was compared to other quiz cases. If there was a
match, then the student was assigned an instructional lesson based upon a previously observed quiz case.
Gilbert's method of instruction selection was implemented using one specific delivery system. It is possible
to implement other methods. For example, it is possible to implement a delivery system that uses neural
networks to perform instruction method selection when students perform below 75% on an instructional
lesson's quiz. Also, delivery systems can vary across user interfaces. The user interface for each delivery
system could be different. Delivery systems consist of at least four major components.
00Instructional lesson sequencing.
00Instruction method selection threshold.
00Instruction method selection technique.
00User interface.
It is possible that delivery systems may consist of more components, but the four listed above are a
minimum.
The DIS environment may be composed of more than one server. Figure 2 illustrates an
implementation with one server. Figure 3 show a possible configuration that contains more than one server.
Figure 3's implementation models the domain name server implementation. There may be multiple servers,
but each server contains the same information. In figures 2 and 3, each server contains a database. This
database is the repository that contains all of the meta data for each instructional lesson. Instructional
lessons are added to the database by the instructors. Instructors must subscribe to the DIS service. This is
accomplished by filling out a form on one of the servers that is part of the system. Once an instructor
subscribes, they will have the ability to register their instructional lessons. Registration is accomplished by
putting your instructional lessons' meta data into the database by using the forms. After the instructor and
their instructional lessons are added to the database, the instructor can start using a delivery system. All
delivery systems communicate with the server using the same communication protocol.
Figure 3: Multiple Servers Architecture
Delivery systems submit queries to the DIS using the HTTP form POST protocol. The most
common query will be a request for a list of instructional lessons associated with a course. The first step to
submitting a query is the creation of a form in html code. In most cases, the form will consists of hidden
fields with specified values. Figure 4 gives an example of a query that requests a list of all the instructional
lessons for an Algebra II course. The html code in figure 4 contains several hidden form attributes. For
example, the R_URL attribute contains the web address of where to send the results of this query. The
results of this query will be sent using the HTTP form POST method as well.
Figure 4: Sample query from a delivery system
<FORM ACTION="https://00dis" METHOD="POST">
<INPUT type="hidden" name="R_URL" value="https://00script">
<input type="hidden" name="Login" value="Your-DIS-ID">
<input type="hidden" name="Course" value="Algebra II">
<input type="hidden" name="Query" value="List_All_IU">
</FORM>
In other words, the delivery system will post a message to a server within the DIS environment. The server
will read the form attributes and execute the corresponding query. The results will be written to the user's
browser and immediately posted to the web address in the R_URL field. The Course, Login and Query
attributes are very straight forward. These attributes correspond to the course being taught, the instructor's
login and the query that is to be executed. This simple query is a small example of how the delivery system
communicates with the server(s) within the DIS environment.
Conclusion
The DIS environment defines a learning architecture for web based instruction. The DIS
environment is designed to work with schools, universities, industry, individuals, etc. DIS serves the
purpose of adding a new instructional, many-to-one instructor-student model for web based instruction.
This new model of instruction will link students to instructors that before now, may have been impossible
to learn from. This will be extremely useful for rural school systems that are experiencing teacher
shortages. With the increase of instruction on the web, DIS provides an interface for instructors to find
existing lessons under a common interface. This will increase the use and reuse of instructional lessons on
the web. Learning architectures for web based instruction should facilitate ease of search, use, reuse and
adaptability. The DIS architecture is designed to accomplish all of those features.
References
Dunn, K., & Dunn, R. (1978) Teaching students through their individual learning styles . reston, VA:
National Council of Principles.
Gilbert, J. E. & Han, C. Y. (2000). Cast Based Reasoning Applied to Instruction Method Selection for
Intelligent Tutoring Systems. In Workshop Proceedings of ITS'2000: Fifth International Conference on
Intelligent Tutoring Systems , Montreal, CA, pp. 11-15.
Gilbert, J. E. & Han, C. Y. (1999). Arthur: An Adaptive Instruction System based on Learning Styles. In
Proceedings of M/SET 99: International Conference on Mathematics/Science Education & Technology ,
San Antonio, TX: Association for the Advancement of Computing in Education, pp. 100-105.
Kolodner, J. L., (1993). Case-Based Reasoning . San Mateo, CA: Morgan Kaufmann.
1
The research of this author is supported under the National Science Foundation grant #EIA-0085952.
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