Curriculum models for computer science are developed in a
number of ways. A systematic approach to curriculum development would identify
who are the stakeholders in the final product of the curriculum, (e.g., the
graduated student) and determine the requirements of those stakeholders.
Stakeholders also include industry, government (SCANS, 1991), graduate research
institutions, and funding providers. A well designed curriculum is likely to be
influenced by a number of sources including prospective employers,
recommendations from professional bodies (e.g. ACM), the internal faculty,
government standards, and general commentaries on curriculum matters by
external reviewerscommentators.
External reviewers commentators
could include advisors, curriculum design experts, expert teaching and research
faculty, and those who make general statements on curriculum matters in
professional publications. Research influencing curriculum development should
not only include computer science research, which provides the direction for
future educational needs, but also educational (e.g. Hanson, 1995) and skills
research (e.g, Ericsson and Charness, 1994)
A top-down approach to instructional curriculum design
is generally encouraged by most experts where the high level learning outcomes
are specified for the curriculum (Dick and Carey , 1996; Moore and Kearsley,
1996) ). Once the desired high-level learning
objectives outcomes have
been agreed upon, they will be refined into more specific competencies and
courses emerge from assembly of targeted related learning
outcomesobjectives. Educational researchers have
developed techniques to assist in this process, e.g. Edmondson (1993); Dede (1990)).
Specific learning outcomes should drive the selection and development of
learning resources, technologies that mediate the educational experience, and
assessment.
This is an idealized model of curriculum development and is seldom completely applied, especially in traditional course development. Often curricula are developed with little reference to outside sources. The curriculum is a result of compromises between the views of internal faculty as to what is appropriate to teach. Many curriculum developers approach the problem as one of identifying courses rather than identifying desired learning outcomes. If we take the analogy with software engineering this is akin to identifying the sub-system architecture prior determining the systems requirements. Specific learning outcomes, if they are articulated, are derived in a bottom-up design process from the chosen learning materials (usually textbooks).
The systematic top-down process (instructional systems
approach) and the informal bottom-up process (traditional reliance upon
existing faculty expertise) are two extremes and most curriculum development
falls between these .these. As new curricula are developed or
existing curriculaum
revised (a frequent occurrence in computer science), there has been a trend
towards the more systematic approach, with accreditation and review processes
expecting specified learning outcomes and clear rationales given for design
choices.
Course developers are often constrained in the learning
materials available, most especially in the rapid deployment world of computer
technologies. The traditional learning tool has been the textbook, which
attempts to cover the learning requirements for a whole course. A textbook is
seldom an optimal solution for a course developed using a top-down model,
unless it was research and written to meet a
specific need recognized by an expert or experts. ItA textbook may
miss some important learning outcomes for a course or be a poor tool in
facilitating others, it often does not provide assessment tools or support
different learning styles (Harmin, 1994; Macfarlane and Smaldino, 1997). To supplement the textbook, course
developers frequently have to design or obtain a great deal of additional
material, e.g. notes, diagrams, animations, assignments, tutorials, and
computer-aided learning modules.
It is possible to seek existingseek existing
materials on the Internet and elsewhere; however this is a difficult process
due to the differing standards of description used for materials. Often
materials must be downloaded and examined before a determination can be made
regarding its efficacy in meeting the course needs. This source suffers the same problem as textbooks in being large
packages, which are often only in part useful. When course developers put
effort into developing holistically their own learning
materials for a particular course the benefits of the resulting material are
seldom made available beyond the target course.
This project will assist in moving the curriculum design process to a more systematic level. The project will achieve this by providing learning materials of sufficient granularity to address specific learning outcomes. It will facilitate access to learning material thorough a repository of learning objects with attached meta-data. A key element of the learning object’s meta-data will be the specific learning outcomes and objectives that the object addresses.
In some perspectives, the concept of a learning object is
restricted to a unit of computer-aided learning. In our perspective a learning
object is any any
self-contained learning resource that can be digitized is appropriately
tagged according to meta-data standards* and is locatable via meta data
indexing and searching services.. The key defining feature is not the
delivery technology, but the fact that it addresses a specific learning
objective outcomes.
Thus a learning object may be a Java applet that contains an interactive
simulation of a particular concept in operation, a collection of bibliographic
citations, or it may be a text document describing an interactive group
exercise that can be carried out in a classroom.
To envisage how the learning object repository might work consider the following scenario:
Professor Smith at the Newtown University is developing a new course in “Systems Analysis and Design using UML”. This course is to be added to the undergraduate program in computer science. The professor has identified a number of specific learning objectives, including the following examples.
By the end of this course students should be able to:
“provide a critique of a given sequence diagram”
“convert a class diagram into C++ code”
Professor Smith selects the web reference for the learning object repository, he selects search and enters the keywords “ UML “ and “sequence”. The search results in the display of several learning objectives related to these keywords, one of which,“provide an analysis of a sequence diagram”, sounds similar to what he is looking for. Selecting the identified objective results in the display of a list of learning objects aimed at achieving this learning outcome, it will also display associated assessment objects. Selecting on each object name will display its detailed meta-data. Included in the meta-data would be such information as type of learning object (e.g. whether it is instructions for a tutorial exercise or a Java applet containing interactive practice exercise), technology requirements (e.g. requires Internet Explorer version 4 or later), peer reviews of the object’s quality, student feedback on their experience using the objects, the learning model applied*. After selecting one of the objects, Professor Smith then enters the second objective, this time there are no associated learning objectives. The systems asks him if he wants to record this as an unfulfilled need, he selects yes and the learning objective is recorded as one where a need for learning objects exist. Professor Smith does a search for unfulfilled needs using “UML” as a keyword; this results in a list of several learning outcomes that have been entered by other professors. Professor Smith notes that a small computer-aided learning program he recently developed could fulfill one of the outcomes. He selects ‘submit learning object’ and is then given a form to fill in the standard meta-data, after doing this he is able to submit his object. Once submitted an email is automatically sent to all those professors who have registered an interest in this learning objective. In this way the depository will fill with a variety of learning objects, using a variety of media and technologies; and supporting a variety of learning styles.
ACM Curricula Recommendations. http://www.acm.org/education/curricula.html
Dede, C. (1990). The evolution of distance learning: Technology-mediated interactive learning. Journal of Research on Computing in Education, 22, 247-264,
Dick, W. and Carey, L. (1996. The systematic design of instruction. New York: HarperCollins Publishers.
Edmondson, K. M. (1993). Concept mapping for the development of medical curricula. Paper presented at the Annual Conference of the American Educational Research Association, Atlanta, GA. (Eric Document Reproduction Services No. ED 360 322)
Hansen R.E. (1995). Five Principles for guiding curriculum development practice: The case of technological teacher education. Journal of Industrial Teacher Education, 32 (2), p. 30-50.
Harmin, M. (1994). Inspiring active learning: A handbook for teachers. Alexandria, VAS: Association for Supervision and Curriculum Development.
Ericsson, K. A., and Charness, N. (1994). “Expert performance: Its structure and acquisition”. American Psychologist, 49, 725-747.
Macfarlane, C. and Smaldino, S. (1997). The electronic classroom at a distance. In. R. Rittenhouse and D. Spillers (eds.), Modernizing the curriculum: The electronic classroom. Springfield, MO: Charles Thomas Publisher.
Moore, M., and Kearsley, G. (1996) Distance education: A systems view. Boston: Wadsworth Publishing Company.
SCANS (1991), Secretary’s commission on achieving necessary skills, Department of Labor. http://www.ed.gov/databases/ERIC_Digests/ed389879.html