Jan 15, 2001 - computer to solve a problem. ... Computer Aided Software Engineering .... read and write, are implied for all college-level courses. Other, less ...
Proceedings of the 37th Hawaii International Conference on System Sciences - 2004
eCAD: A Knowledge-Based Course Engineering System Timothy J. Ellis, Ph.D., Nova Southeastern University William Hafner, Ph.D., Nova Southeastern University Frank Mitropoulos, Ph.D., Nova Southeastern University Abstract Colleges and universities have increasingly migrated towards utilizing the World Wide Web to convey at least a part and, in many cases, their entire curricular offering. Despite this trend, there is inadequate support for the professors responsible for restructuring the courses they have refined over a career in the classroom for delivery via the Web. Teachers who are expert in their subject area and masters of their craft when in a classroom find themselves in the uncomfortable position of having to relearn how to teach in a new environment with little or no support. The process of planning and developing a course for delivery in an online environment is, in many significant aspects, analogous to the processes required to develop a software system. Both situations require the developer to manage resources through a series of steps with the goal of designing a product that effectively utilizes the computer to solve a problem. The procedures and tools used in software engineering to manage software system development, therefore, offer promise for developing online courses. Computer Aided Software Engineering (CASE) tools are of special interest by virtue of the support afforded the development process through computerization. This paper offers an architectural overview of a knowledge-based, course engineering system: eCAD (electronic Course Analysis & Design). The requirements for the system, the manner in which those criteria were developed and validated, and system design will be detailed. A working prototype will also be presented.
1. Problem Statement Academic institutions ranging from high school through graduate school and training facilities in business, government, and the military are increasingly taking advantage of the World Wide Web as a delivery mechanism for at least a part and, in many cases, their entire curricular offering [1][2]. Despite this trend, the process of how online offerings should be designed and developed remains problematic [3][4]. The course instructor – the individual traditionally responsible for
planning, designing and developing college courses – is often in the very uncomfortable position of having to make critical pedagogical decisions with incomplete information and inadequate preparation. A great deal of attention has been focused on the effective distribution and management of educational content for delivery in an online modality. Guidelines regarding the features and functionality of course management systems are being refined [5, 6], and great attention is being devoted to ensuring the reusability of learning objects across course management systems [7, 8]. There is, however, little to help the instructor plan, design and develop online educational programs. Despite suggestions and general guidelines [9, 10] and narrowly focused, partial design guidelines [11], the educator is often left to develop her or his own answers to two vital questions: which online tools will most effectively help the student learn, and how to use those tools to actually improve in the online learning environment. Teaching is not easy, regardless of the environment. Although a teacher may attempt all that is within her or his power to help a student master a subject, the activity of learning is indeed one that can only be accomplished by the student. Unfortunately, students differ widely in how they learn and what is effective in facilitating that process [12]. The difficulty is compounded at the postsecondary-level where teachers are primarily experts in the subject matter, not in educational processes and learning theory. The characteristics inherent in an online environment further compound the problem. Teachers, by-and-large, teach in the same manner in which they were taught [13]. Since few current teachers have experienced online learning as students, most are confronted with working in an environment for which they have no model. Furthermore, many of the aids available to the teacher in the classroom are not available online. The non-verbal cues that an experienced teacher can read to gauge student understanding are absent. The immediacy of the questionresponse-follow-up cycle is largely lost in the online environment. It is quite difficult to foster and maintain the peer-to-peer support system of a community of learners when that community is “virtual”. Teaching online does require a reevaluation of the pedagogical approach [14, 15].
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2. The Obvious Approach The typical solution for implementing an online course is to directly port materials developed for classroom delivery of the course to a Web site. This porting can take the form of Web pages containing class notes, copies of PowerPoint presentations, videos of lectures, and various synchronous (i.e. chat rooms) and asynchronous (i.e. threaded discussion forums) simulations of classroom discussion [9, 16]. Although one cannot help but use prior experiences in teaching a course when developing a new implementation, the direct porting of materials to the Web is usually not effective. Often, a support technician who lacks expertise in both the subject matter and pedagogical theory does the translation of the materials for Web delivery. When the instructor or professor does the porting, a lack of experience with the tools available in an online learning environment and a general lack of technical expertise can serve as significant impediments [3]. Regardless of how the porting is accomplished, the critical consideration is often ignored: the online learning environment is essentially different than the classroom environment and the techniques that worked quite adequately in the classroom might well be totally ineffective in a Web-based course [14, 15, 17]. The problems with directly porting educational expertise developed in the classroom to the Web-based environment do not end with course delivery. Meaningful evaluation of the effectiveness of the course is essential. Often, however, online courses are evaluated using tools developed for the classroom environment. The value of these tools in evaluating and improving classroom instruction has long been questioned. Their value, when applied to the significantly different online environment is even more questionable since they have never been validated for that environment and response rates are historically quite low. Meaningful evaluation that could be used to monitor and improve online learning experiences is, at best, difficult [18, 19].
3. Instructional Design Many schools are addressing these difficulties by assembling multi-disciplinary teams headed by an instructional designer to aid the professor design her or his online course implementation [20]. Instructional design can be defined as: “The development of instruction for specified goals and objectives in which (1) the organized sequential selection of components is made on the basis of information, data, and theoretical principles at every stage and (2) the product is tested in real-world situations both during development and at the end of the development process.” [21, p. 408]
There are a number of different theories supporting and models for instructional design [22, 23, 24, 25]. Dick and Carey [26] developed a very inclusive, nine-step model of the design process. Step 1: Identify the instructional goals. The goals for instruction are, basically, the ultimate result desired for the curriculum, course, or lesson. Examples of goals for a graduate-level, information systems course in multimedia would include: 1) be an informed consumer of mediaenhanced business products; 2) understand the set of technologies that enable computer-based, multimedia products; and 3) be aware of the processes and challenges inherent in developing media-enhanced products. Step 2: Instructional analysis. Instructional analysis entails identifying the skills that are requisite in order to perform each of the goals. For example, to meet the first goal identified for the multimedia course – to be an informed consumer of media-enhanced business products – one must be able to: 1) perform a basic cost-benefit analysis; 2) develop a rubric to rate the strengths and weakness of media-enhanced products; and 3) evaluate the strengths and weakness of media-enhanced products to meet specific business needs. Step 3: Expected learner characteristics. Every instructional process assumes that participants will possess certain competencies. Some, such as the ability to read and write, are implied for all college-level courses. Other, less obvious, more specific competencies also apply and must be specified as part of the instructional design process. For example, one of the assumed competencies for the information systems course in multimedia is that the student understands the basics of cost-benefit analysis. Step 4: Develop learning outcomes. The learning outcomes must clearly specify what the student should be able to do, the conditions under which the student should produce the desired behavior, and how well the student must be able to perform it if she or he is to attain the goals specified for the course. In addition to focusing on the specific behavior, each learning outcome must also reflect the level of cognitive activity expected of the student. Although educational researchers have developed many different taxonomies for categorizing level of cognitive activity [24, 25], Bloom’ Taxonomy [22] remains a widely accepted model for developing learning outcomes. Bloom identified a sequence of six levels of cognitive activity and associated specific types of student behavior for each. Table 1 summarizes those levels and a representative sample of associated behaviors. The process of developing learning outcomes entails three steps: identify the specific topic or subject matter to be learned, decide what level of cognitive activity is necessary for satisfactory mastery of that topic, and identify what student behavior is necessary to demonstrate that cognitive activity. For example, in an introductory
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Table 1: Bloom’s Levels of Cognitive Activity and Associated Behaviors Level of Cognitive Activity Knowledge Comprehension Application
Analysis Synthesis
Evaluation
Samples of Associated Student Behavior list, define, tell, describe, identify, show, label, collect, examine, tabulate, quote, name summarize, describe, interpret, contrast, predict, associate, distinguish, estimate, differentiate, discuss, extend demonstrate, calculate, complete, illustrate, show, solve, examine, modify, relate, change, classify, experiment, discover separate, order, explain, connect, classify, arrange, divide, compare, select, explain combine, integrate, modify, rearrange, substitute, plan, design, invent, compose, formulate, prepare, generalize, rewrite assess, decide, rank, grade, test, measure, recommend, convince, select, judge, explain, discriminate, support, conclude, compare
database course, normalization is a core topic area, students are commonly expected to progress to at least the application level of cognition, and typically students demonstrate that mastery by solving one or more problems. The learning outcome describing this expectation might be: The student will be able to solve a database normalization problem by bringing a dataset into Third Normal Form compliance. Step 5: Design measures of learner performance. Performance measures are essential for determining if the students are in fact meeting the learning outcomes specified for the course. Measures may take the form of test questions, research papers, discussion forum participation, or project-based exercises, to name just a few examples. The assignment to measure the learning outcome described above in Step 4 might be to normalize a sample data set. Step 6: Determine instructional strategy. Once the learning outcomes have been identified for a course, the instructor must determine the instructional strategy by specifying which pedagogical tools should be used to facilitate the students’ attainment of each specific outcome [23, 27]. For online-delivered courses, there are actually three components to this step. First, a decision must be made regarding the time-dependency of the course: asynchronous, synchronous, or hybrid. Second, a catalog must be developed that lists the pedagogical tools available for the selected time-dependency, the effective uses for each tool, and the known limitations of each. After the resource catalog has been developed, the instructor can then select the appropriate instrument or instruments for each learning outcome. Figure 1 illustrates a catalog of online pedagogical tools used in a graduate school of computer and information sciences.
Step 7: Select or develop instructional materials. During this step, the course as designed is built or customized. Videos are filmed, compressed, and placed on Web sites, threaded discussion forums are created, chat rooms established, class notes converted to Webdeliverable format, and the entire package is assembled into a seamless whole ready for student use. This stage is the point in the development process where most online educational tools such as Learning Space, WebCT, and Blackboard start [28]. Step 8: Formative evaluation. Prior to implementing the course, the instructional materials and strategies selected for the course are evaluated to ensure they are, in fact, efficacious in helping students attain the learning outcomes for which they were designed. Formative evaluations typically range in scope from tests involving single students through tests of small groups to tests in full classes. The goal of formative evaluation is to highlight specific instructional materials or strategies that are not effective and to make point-by-point changes in the course design prior to deployment. Step 9: Summative evaluation. The final step in instructional design is to determine if the course as a whole meets the instructional goals identified at the start of the process. Summative evaluations may be implemented as limited pilot studies prior to full deployment of the course, or may be conducted after the course has been offered for several iterations. Although the instructional design model has been well established as a method for producing courses, there are some inherent weaknesses in this approach. Since the process is quite lengthy and demanding, few faculty members have either the time or the background to direct instructional design. Leadership of the process usually falls to a professional instructional designer, with the
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Pedagogical Tool Email
Features, Uses, and Limitations • One-to-one and one-to-many communication • Teacher-student(s), student-teacher, student-student(s) • Primarily text, but graphic and audio potential • No or minimal pre-course preparation • Moderate to heavy in-course attention • Minimal demands on student’s system
Threaded discussion board
• • • • • • •
One-to-many communication Teacher-students, student-teacher, student-students Supports student-student collaboration Primarily text, but full multimedia capability through attachments Minimal pre-course preparation Moderate in-course attention Minimal demands on student’s system
Online PowerPoint presentation
• • • • •
Convey course content normally delivered by demonstration. Full multimedia potential (narration, animation, video, etc.) Moderate to heavy pre-course preparation Minimal in-course attention Moderate demands on student’s system
Streaming video
• • • • •
Convey course content normally delivered by lecture. Full multimedia potential (narration, animation, video, etc.) Heavy pre-course preparation Minimal in-course attention Heavy demands on student’s system
Group practical application, completed locally on the computer, but developed collaboratively through use of email and threaded discussion forum
• Provide avenue for constructive learning environment through collaborative, hands-on learning opportunities. • Hybrid stand-alone and interactive experience • Moderate pre-course preparation • Moderate in-course attention • Moderate demands on student’s system
Peer-reviewed research paper
• Encourage and measure acquisition of the learning outcomes that are process oriented. • Student-to-teacher and student-to-student interactivity • Moderate pre-course preparation • Heavy in-course attention • Minimal demands on student’s system
Technical briefs
• Encourage and measure acquisition of learning outcomes that are content oriented • Student-teacher, teacher-student interaction • Moderate to heavy pre-course preparation • Moderate to heave in-course attention • Minimal demands on student’s system Figure 1: Asynchronous Pedagogical Tools
course instructor assuming something of the consumer role. Concerns ranging from academic freedom to ownership of intellectual property cause many instructors
to be very reluctant to participate in instructional design efforts and, by extension, to modify their courses for delivery via an online modality.
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Percent “ideal” solution
The instructional design process, furthermore, follows what is essentially a linear developmental model, rather like the traditional Waterfall model for software design [29]. This model connotes that a course is a “finished product” at the time of deployment, creating something of a static course design. Since there are always changes in student profile, online capabilities, and the discipline being taught, courses must be inherently quite dynamic. The instructional design model offers no formal procedures for incorporating this environmentalchange data into the course design.
analysis phase. These software engineering models do not, however, adequately address the dynamic nature of software development in which products are never truly “completed”. The evolutionary model does offer a dynamic development process. It enables developers to produce acceptable product versions that meet customer minimum needs but continuously evolve toward the “ideal” customer solution. The evolutionary model combines elements of the linear sequential model (applied repetitively) with the
Analysis Design Code Test
Analysis Design Code Test Analysis Design Code Test
Delivery Version n
Delivery Version 2
Delivery Version 1
Time
Figure 2 Evolutionary Development Model
4. Learning from Software Engineering 4.1. Alternative Design Models The process of designing courses, especially those to be delivered via an online modality, is strikingly similar to the process necessary to develop a computer product such as a multimedia encyclopedia or video game. The field of software engineering has developed many different process models for the software development which offer greater flexibility in creating products capable of being adapted to changing needs. The Waterfall or linear sequential model that parallels the instructional design process described earlier is designed for straight-line development. Basically, this model assumes that a complete system will be delivered after the analysis, design, code, and test sequence has been completed. Models such as the prototyping and the WINWIN Spiral [30] enrich the design process by actively engaging the prospective end users during the
iterative philosophy of prototyping. Referring to the Figure 2, the model applies analysis, design, code and test activities to produce incremental product releases as time progresses. Each linear sequence produces a more fully functional deliverable “increment” of the software [31]. The evolutionary model delivers software in small but usable pieces, called “increments.” In general, each increment builds on those that have already been delivered. Since each iteration of a college course builds upon the experiences of previous offerings, the evolutionary process model appears to offer a more robust development process than the essentially linear instructional design model.
4.2. Automating the Process with CASE Instructors can borrow more than just a more robust design model from the software engineering field. One of the greatest strengths inherent in the structure of the software development lifecycle (SDL) model is the capacity to support the development process through
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computerization with Computer Aided Software Engineering (CASE) tools. CASE tools automate a significant amount of the software development process. A similar automation to the instructional design process offers the promise of placing a significant portion, if not total control of the course design process back in the hands of the course instructor, thereby addressing one of the major challenges in online learning.
4.3. Implications for Professor-Based Design
technology. The system flow diagram for the product is displayed in Figure 4. The knowledge-based capability inherent in the system is provided by a Value History Database module. Four ‘generator’ modules corresponding to the four major steps in each cycle within the evolutionary design process complete the system. The functional descriptions of the modules are detailed in the following paragraphs. Learning Outcome Generator: This module accepts the following inputs from the course instructor: specific topics or subject matter to be learned, the level of learning desired for each topic, and the student behavior that would indicate mastery at the desired level. The system provides input in the form of suggested action verbs appropriate for the desired level of learning for each topic. This module processes the inputs into well-formed learning outcomes, and outputs those learning outcomes to the Assignment Generator, Course Evaluation Generator, and Scratchpad modules. Assignment Generator: This module accepts as inputs
Borrowing from the software engineering field offers promise to college professor tasked with developing or translating courses for delivery in an online modality. The four-step, iterative design process inherent in the evolutionary development model (Figure 2), supported by computer aided design software potentially gives the teacher the systemic support necessary to effectively direct the course planning and design process. The balance of this paper will describe the processes followed in developing eCAD, a knowledge-based, automated 1) User-friendly, no computer expertise necessary course engineering system 2) Guidance through instructional design process based upon an evolutionary a) Build learning outcomes perspective of course b) Select appropriate online tool(s) to attain learning outcomes development. c) Build assignments and evaluation criteria
5. eCAD 5.1 Requirements A group of seven professors with a minimum of five years experience teaching in online environments formed an Expert Panel to develop the requirements for the eCAD system. The backgrounds of the members of the Expert Panel included experience in software development, human computer interaction, information systems, and educational technology. The requirements identified by this panel are summarized in Figure 3.
d) Build course schedule, pacing and sequence of activities e) Build course evaluation instrument 3) Build and dynamically update value history a) Components i) Learning outcomes ii) Online pedagogical resources iii) Assignments b) Updated from i) Student evaluations ii) Instructor evaluations iii) Grades 4) Manage course evaluation a) Course-specific evaluation of i) Learning outcomes ii) Pedagogical resources iii) Assignments b) Data used to update value history i) Learning outcomes ii) Pedagogical resources iii) Assignments 5) “Hooks” into existing course management systems (WebCT, Blackboard, etc.)
Figure 3: eCAD Requirements Specification
5.2 Design The requirements for eCAD were translated into a design by the primary researchers, two of whom each had in excess of 20 years experience in software development and the other with over 10 years experience in educational
well formed learning outcomes from the Learning Outcome Generator module. It also accepts inputs from the system in the form of suggested types of online pedagogical resources and specific assignments appropriate for a given learning outcome, based upon data from the Value History Database. Based upon these
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inputs, this module guides the instructor through the process of identifying an assignment type – based on online pedagogical tool selected – and specific assignment(s) for each learning outcome. The assignments developed in this module are output to the Schedule Generator, Course Evaluation Generator and Scratchpad modules.
input to the Learning Outcome and Assignment Generator modules.
5.3. The Product
eCAD is currently in its first prototype. A screenshot from the Learning Outcome Generator is displayed in Figure 5, followed by brief description of the module. Because of space constraints, the Resource Assignment remaining modules are Learning Course Selector Deveoper Schedule Outcome Evaluation described without Generator Generator Generator screenshots. Assignment Generator The home page for eCAD offers the user "Scratchpad" access to all of the system’s modules. The Learning Outcome Online Resource Assignment home page is always Repository Repository Repository available in the Course Management background and allows System Value History Database the user to freely move from module to module Figure 4 eCAD System Flow while designing the course. Schedule Generator: This module accepts input from The Learning Outcome Generator helps the instructor the Assignment Generator module in the form of a list of plan the educational goals for the course. If the course had course assignments, plus input from the instructor for already been offered, learning outcomes previously term start and end dates, assignment sequence, and days identified, together with a success rating from the Value per assignment. The module guides the instructor through History Database, are listed. The instructor is guided the process of planning the scheduling, flow, and pacing through a three-step process for building new learning of the assignments, and outputs a course schedule to the outcomes. In Step 1, topics of importance are entered. In Course Evaluation Generator and Scratchpad modules. Step 2, for each topic, the instructor: selects the level of Course Evaluation Generator: This module accepts learning that is necessary; selects the action verbs inputs from the Learning Outcome Generator (learning appropriate for that level; and enters a brief description of outcomes) and the Assignment Generator (assignment what the student would do to demonstrate mastery of the types, based on online resource, and specific topic at the desired level. Step 2 is completed by the assignments). Based upon these inputs, it develops a Learning Outcome Generator building a well-formed course-specific evaluation that measures attainment of learning outcome that the instructor can either accept or learning outcomes and effectiveness of assignments, from edit. In Step 3, the instructor compiles the list of learning both the student and instructor perspectives. The outcomes for the course by adding learning outcomes evaluation is output to the Scratchpad module. from previous offerings of the course (if any) to the list of Scratchpad: This module accepts inputs from the the new outcomes developed in the previous steps. The previously described “generator” modules and serves as a learning outcomes developed through the Learning review and editing site for the instructor. The instructor Outcome Generator are passed to the Assignment can review and change any of the course elements through Generator, Course Evaluation Generator, and Scratchpad this module. Output from this module goes to the Course modules. Management System (WebCT, Blackboard, etc) in use at The functioning of the Assignment Generator is the school. similar to the Learning Outcome Generator. If the course Value History Database: The final module of the had been offered previously, the assignments used and eCAD system is a database of the course evaluations. This related ratings from the Value History Database are listed. module accepts as input from the Course Management For each learning outcome identified for the current System both student and instructor assessments of the course offering, the instructor is guided through a twodegree to which the learning outcomes were met and step process for building an appropriate assignment. In effectiveness of the assignments in promoting attainment Step 1, the instructor is offered a list of recommended of those outcomes. The data from this database serves as
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categories of online resources with value ratings based upon the level of learning identified in the learning outcome. The instructor selects the category of online resource desired and the specifics of the assignment. In Step 2, the instructor compiles the assignments for the course by adding assignments from previous offerings of the course (if any) to the list of the new assignments developed in the previous step. The assignments developed through the Assignment Generator are passed to the Schedule Generator, Course Evaluation Generator, and Scratchpad modules. The functioning of the Schedule Generator is relatively simple. As in the case of the previous two modules, the instructor can view previous course schedules if available. The instructor is guided through the process of building the course schedule by: entering the starting and ending dates of the course, the order in which the assignments should be done, and the number of days necessary for each assignment. The generator suggests a schedule for the assignments that the instructor
can accept or edit. The schedule is passed to the Scratchpad module. The Evaluation Generator, as the name implies, builds an evaluation for the course, based upon the learning outcomes, assignments, and schedule developed in the previous modules. The instructor can review and edit the evaluation questions automatically developed by this module. The Scratchpad stores all the information – learning outcomes, assignments, and schedule – applicable to a specific offering of a specific course. It allows the instructor to view the course materials as a whole and make any desired changes. The course materials are passed from the Scratchpad to the Course Management System – WebCT, Blackboard, etc. – in use at the school. The Value History Database serves as the foundation for the eCAD system. The data from the course evaluations completed by the students and the instructor, plus the grades earned on each assignment are stored. This historical data is averaged and used to calculate the
Figure 5: Learning Outcome Generator
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value ratings for learning outcomes, category of online resource, and specific assignments used in the Learning Outcome Generator and Assignment Generator modules.
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6. Summary and Future Research Courses are, without question, being successfully delivered via online modalities [32, 33]. Courses in Engineering and other technical curricula are likewise being effectively developed and delivered in both oncampus and online environments [34, 35, 36]. There are certainly a large number of process models such as the instructional design model that present potential as a solution to the problem of developing courses for an online environment [24]. This paper explored the potential of adapting the SDL model widely used in software engineering as a particularly promising process model. There is an intuitive appeal to adapting a tool developed by the computer industry to plan a course that will be delivered predominately via computer-mediated communication. Developing an effective college-level course is indeed complex and challenging. When the need to adapt the course to an emerging, poorly defined and imperfectly understood delivery system such as an online learning environment is added to the developmental burden, the difficulty becomes exponentially greater. The structure and support inherent in a formalized development process supported by a computerized development system offers great promise as means of addressing this difficulty. The eCAD system described in this paper offers promise as a tool to facilitate development of courses for delivery via an online medium.
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0-7695-2056-1/04 $17.00 (C) 2004 IEEE
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