Meta-Skills in Information Systems Education

Ralph D. Westfall
California State University, Long Beach
westfalr@acm.org

ABSTRACT

Information technology has a major impact on almost every area of the current environment, and it is expected to have even greater impacts in the future. Therefore it is important to teach students content related to the component technologies, and the soft skills necessary to work with them in organizations. However the rapid rate of change makes information technology fundamentally different from many other fields of study. New knowledge is continually being added, while much of the existing knowledge is becoming obsolete. Therefore it is also necessary to specifically teach students meta-skills that will enable them to keep themselves up-to-date in this field after they complete their formal education. This paper identifies four meta-skills: technology scanning, technology evaluation, technology assimilation, and debugging. It also describes a series of information systems course assignments designed to develop these meta-skills, and provides 11 specific heuristics for technology evaluation.

INTRODUCTION

Introductory information systems classes typically address two different types of issues. The first is factual content related to the technologies and how they work, and the second is interpersonal and management “soft skills” (1). The latter category can include the ability to work cooperatively, planning and organizing, dealing with ambiguity, working with customers, oral and written communications, etc. (5)

After teaching introductory information systems courses for several years, I began to realize that these skills were not enough. Information technology is fundamentally different from other fields, and its unique characteristics have major impacts on any field of study with a large IT component. Therefore teaching approaches that may be adequate for other courses of study are not sufficient for fields where IT is the central component or a major aspect. The differences also require professionals in this field to follow a more disciplined approach to keeping themselves up-to-date than practitioners in other fields.

UNIQUE CHARACTERISTICS OF IT

Information technology is a large and complex field. Other fields of study--for example, economics, history, or philosophy--are also large and complex. In IT or other fields, students need to assimilate a large base of existing knowledge to become competent. It is after students achieve a level of competence, however, that the unique characteristics of IT become most obvious.

In other fields, the large and complex body of knowledge accumulated over hundreds or even thousands of years. In information technology, the knowledge base developed in approximately fifty years. In other fields, knowledge is added slowly to the existing base, and usually complements rather than supersedes that base. For example, students still learn Newtonian mechanics in physics courses. In information technology, new knowledge is added at an extremely rapid pace. Not only is knowledge accumulating faster, the newer knowledge often makes some of the existing knowledge either obsolete, or less important and less central to the field than it was before. My colleague Douglas Shook uses the analogy of a pipeline, where new material entering at one end forces out older material at the other end. As a result, new knowledge represents a much larger proportion of the total in IT-related fields.

Cunningham and Bocock (4) report evidence of the rapid growth of new knowledge in IT-related fields. They found that, over a seven year period, the median age of citations in a journal dealing with computer networks was four years. In other words, half of the references had been published within the last four years. The median age of citations in a journal on operating systems was only three years. They also mention an unpublished study they conducted, which indicated a median age of five years for citations in articles on information systems. Although these figures are comparable to median ages for some other scientific fields--see table in (4)--this could be misleading because new knowledge in other fields tends to complement rather than displace existing knowledge.

“Clockspeed” is another way of looking at the rate of change in the IT industries. Mendelson and Pillai (6) report objective measures of: 1-the rate of decline in input prices, 2-product life cycle, and 3-proportion of revenues from products introduced within 12 months. They found that “The rate of change in the [IT] industry’s external environment, including developments in technology, consumer preferences, and market conditions, by far exceeds that of other industries.”

The rapid rate of change already makes it difficult to keep up-to-date in this field, and it appears that the rate of change is accelerating. The following section describes the multiple positive-feedback loops that contribute to the increasing rate of change.

Feedback Loops in Information Technology

Engineers often incorporate negative-feedback loops in designs of physical structures and processes, to prevent small perturbations from escalating to destructive levels. On the other hand, in the logical world of information technology, the feedback loops appear to be positive and therefore self-reinforcing.

A B

Technology suppliers Technology users

Tool suppliers Technology suppliers

Knowledge creators Knowledge users

Figure 1. Positive feedback loops that accelerate the rate of change of IT

Figure 1 diagrams the following relationships:

· Technology suppliers and users. The Intels, Microsofts, and Sun Microsystems of the world supply new technologies. Organizations adopt these technologies and become more efficient and competitive in their industries. This puts pressure on their competitors to adopt similar technologies to catch up, or to adopt new technologies to leapfrog the previous innovators. This, along with the efforts of the previous innovators to maintain their advantage, leads to additional demand for existing and even newer technologies, which the suppliers are happy to meet. Bohr (3) suggests that one of the fundamental bases of this technological progress--the exponential growth in microprocessor capacities, first identified by Moore (7)--will continue “for at least three to four more [microprocessor architecture] generations.” He also notes that other technologies could become viable alternatives after the industry reaches the theoretical limits of silicon-based chips.)

· Tool suppliers and technology suppliers. The creators of new technologies use tools to create the technologies they supply. For example, software developers use computers and integrated development environments to create more software. As the tools get better, productivity increases and this also causes the rate of change to accelerate.

· Knowledge creators and users. Knowledge is expanding exponentially. Price (9) found that scientific knowledge was doubling every 10 to 15 years. With improved tools for data acquisition and analysis plus faster communications between researchers, the rate of growth is probably faster now. Some of the new knowledge feeds into the IT area to facilitate creation of new technologies or tools, or new applications of existing technologies. Information systems also provide easier access to internal and external knowledge that knowledge users and creators employ to achieve their objectives.

ADJUSTING TO THE DIFFERENCES

For an educator in this field, the challenge is: How do I prepare my students to successfully manage their careers in the context of this rapid change? What skills can I teach that will enable them and their organizations to not just cope with the technological advances, but to prosper from them?

Since the IT area is so large, complex, and rapidly changing, it would be impractical for any individual to develop and maintain extensive knowledge and skills related to all the new developments. Nor would it be a good idea to try. Some of the new developments will be successful, while others will not. It is not a good investment to put time and money into technologies that will not succeed. The classic example is the Betamax VCRs of the 1980s, which were not able to compete with VHS units. At this time there are few movies available for use on Betamax equipment, even though it is technologically superior.

The following discussion is from the perspective of organizational uses of information technology. It emphasizes the academic discipline of information systems that I teach. However much of the discussion should be relevant to other fields with large IT components, such as computer science or electrical engineering, or to IT-oriented aspects of other disciplines, such as the increasing use of IT in medicine.

The Learning Needs Model

Because of the differences between IT-related and other fields, I now take a different approach to teaching information systems. My courses continue to provide students with knowledge and skills related to current technologies. However the courses also provide homework and exercises to develop meta-skills, to help students successfully cope with the breadth, complexity, and rapid rate of change in information technology after they complete their formal education.

Figure 2. The traditional introductory information systems class model (12)

I have embodied these meta-skills in an approach to teaching information systems courses that I call the “learning needs model” (12). In the usual approach, diagrammed in Figure 2, the emphasis is on providing students with knowledge and skills in current technologies. This traditional model thus prepares them for entry into the workforce, but does not address the rapid growth of information technology that will continue to affect them long after they leave the academic setting.

Figure 3. The learning needs model for introductory information systems classes (11)

The learning needs model, as shown in Figure 3, provides content related to current technologies that is relevant to students’ initial career positions. However it also provides them with the skills they will need to keep up-to-date with new technologies that will subsequently be important to their careers and organizations. I have identified four important meta-skills for dealing with information technology, which I have incorporated into the learning needs model:

1. Technology scanning
2. Evaluating new technologies
3. Learning to use and assimilate new technologies
4. Debugging systems that do not work as (it seems) they should

The third and fourth items on this list receive implicit coverage for most majors in college degree programs, even though they are not usually identified as meta-skills. At present, most college students have to know how to use some information technologies in order to graduate. They will need to know a word processing program and a web browser. Depending on their major, they may also need to learn to use programs for spreadsheets, graphics, presentations, or databases. If they major in information systems or computer science, they will learn programming and fourth generation languages, systems analysis technologies, etc. The more applications they learn, the more proficient they will become in the meta-skills of assimilation and debugging.

However they learn these skills in an academic setting, where the instructor recommends reading material and provides instruction. To keep themselves up-to-date after graduation, students will have to either continue taking training in a structured format, or develop “self-service” learning skills that will enable them to select and use learning materials on their own. In my introductory information systems classes, I provide specific assignments to teach such self-service skills. (I discuss this in more detail in the section on Instantiating the Learning Needs Model.)

Although typical college curricula at least implicitly include the third and fourth meta-skills, it appears to me that the first and second meta-skills--technology scanning and technology evaluation--are hardly addressed at all. I have taught introductory information systems classes in several schools using a variety of textbooks, and have found little explicit attention to technology scanning and evaluation per se in these texts. And if introductory technology-oriented classes do not cover this subject, it is even less likely to be included in programs for less technical majors.

Introductory information systems courses typically do address the issue of the competitive implications for organizations--e.g., references to Porter’s (8) “five forces model”--of applications of specific technologies. Nevertheless, they do not consider the evaluation of the characteristics and possibilities of technologies apart from specific applications.

This lack of coverage is unfortunate, because evaluation of the underlying technologies logically precedes analysis of applications. It also logically precedes the meta-skills of assimilation and debugging, which most curricula implicitly include. Assimilating a new technology requires a large investment of time and other resources, so it is important to identify technologies that are more likely to reward such investments.

To give students practice in technology scanning and assimilation, I assign activities early in the semester that require them to identify promising technologies. To assist with this, I provide a set of heuristics for identifying “important” technologies. The heuristics, discussed below in the section on “Heuristics for Identifying Promising Technologies,” provide a framework for evaluating whether a new information technology is likely to be successful and used extensively or not. The students then use the heuristics to identify software applications that embody promising technologies and that are relevant to their individual career plans. They then download trial or beta versions of these applications from the Internet and use them in their term projects.

Although developed in an academic setting for the benefit of students, these heuristics can be useful to professionals and decision-makers in organizations. Both individuals and organizations have constraints on their time and resources. Using these heuristics can help prioritize efforts to keep up-to-date with advances in IT, and can also assist in investment decisions about new technologies.

HEURISTICS FOR IDENTIFYING PROMISING TECHNOLOGIES

To aid my students in prioritizing their learning efforts in subsequent courses, and especially after they finish college, I give them the following heuristics for identifying technologies that are more likely to succeed. Note that people should use these heuristics in the context of their own situations. Students need to focus them on new technologies that are relevant to their specific career plans. People making decisions about investments should focus them on technologies relevant to their industries.

Individual Heuristics

Items in this group are relatively independent of each other. A technology could rate high on one of these heuristics, even though the others have low ratings or are not applicable. A strong enough showing on just one of these heuristics might be adequate to assure the success of a technology vis a vis alternatives.

1. Labor or cost savings. Labor savings is the classic rationale for implementing IT. A new technology or system--for example robots--displaces a specified quantity of labor, at the relevant hourly rates including fringe benefits and wage increases. Because of the association between labor savings and cost savings, I also include other cost savings this category even though they may not reduce labor. This heuristic applies to technologies that make it possible to produce the same outputs, but at less cost.

2. Speeds up process. Some technologies speed up processes, although they do not produce labor savings. A sophisticated workflow system could replace physical transfers of documents by electronic communications, even though it did not reduce either the cost of the transfers or the amount of labor in processing the documents.

3. Improves quality. It might be possible to use new IT to produce essentially the same products or services, but with higher quality. The designers of the Java programming language deliberately excluded features of C and C++ that make them error prone. To the extent this strategy is successful, programs written in Java will be of higher quality.

4. Increases flexibility or adaptability. IT can make it possible to produce the same outputs in more varieties, or to rapidly switch production from one variety to another. IT makes it possible for magazine publishers to produce different editions for regional markets. Airline reservation systems make it possible to respond rapidly to competitors’ actions.

5. Enables innovation. The preceding heuristics refer to the impact of new IT on the production of existing products and services. Sometimes, however, IT makes it possible to create something that is different from what was available before. The Web browser is a key component in enabling electronic commerce for individual consumers.

6. Enables improved decisions. One of the classic concepts in this field is the use of information systems to assist in decision making. (This is a higher level skill, because improved decision making--or related activities such as planning or design--can result in many of the other benefits listed above.) IT can improve decision making by providing access to more or better data, information and knowledge, and by more efficiently converting data into higher-value information and knowledge.

7. Strong sponsorship. This could reflect the market position of the organization providing the technology, for example Microsoft with its version of the web browser. Other aspects of sponsorship include standards committees or organizations, and government procurement specifications. Stanford economist Brian Arthur (2) describes this as “network effects.” He notes that a product that is used with, or complements, products with a large market share benefits from a de facto standard, for example the IBM PC architecture.

8. Improves quality of life. Technologies that make work safer or more interesting fit into this category. Software companies sometimes exploit this factor by offering free or short-term trial versions to individual consumers over the Internet. If the software is helpful and enjoyable to use at home, individuals may lobby their organizations to purchase it for use at work.

Other Issues

The additional factors listed below are also relevant to evaluating new information technologies. These factors could interact with the individual heuristics I listed above.

1. Market size. This represents a scaling factor for the individual heuristics. Generally a new technology that can save labor, speed up processes, etc. in a wide variety of situations will be more likely to be successful than one that is only applicable to a smaller or niche market.

2. General categories. In analyzing new technologies, it can be helpful to be aware of the general categories into which they fall. DVD is a new technology, but it is also an extension of a general category--storage media--that has been around for a long time. Items in a general category may appear quite different--for example punched cards, magnetic tape, and CD-ROMs--even though they perform essentially the same functions. Differences in appearances could hide underlying relationships and cause people to overlook relevant comparisons.

3. Future potential. The most valuable application of these heuristics is identifying technologies that will be more important in the future, and thus worthy of an exploratory investment of time or money. For this purpose, it could be useful to identify the factors that currently prevent or limit the impact of specific individual heuristics, and then determine when or how these barriers might be overcome. Consider a new technology that offers substantial labor savings, but costs so much that it provides no net benefit at present. The relevant issue becomes whether, or when and how much, costs will decline.

Another issue to consider is the possibility that, before it reaches its apparent future potential, an auspicious new technology could be overtaken by another. ISDN initially looked very promising, but market demand for its level of bandwidth was slow in developing. At present, the Internet and multimedia computers are creating demand for higher bandwidth, but technologies with substantially higher capacities than ISDN (e.g., xDSL, direct satellite transmission, cable data services) are becoming available.

INSTANTIATING THE LEARNING NEEDS MODEL

Over the course of several years teaching introductory IS classes, I have developed the following set of assignments, which provide a substantial amount of practice in meta-skills for information technology. I designed these assignments to be cumulative and mutually reinforcing, to increase the learning impact.

1. Technology self assessment. Each student writes a one- to two-page analysis that includes an assessment of current technology skills and attitudes in relation to their career expectations. I encourage the students to check on-line job listings relevant to their career plans, to identify technology skills for which potential employers are looking. The paper concludes with a tentative identification of “learning needs”: applications and other information technologies that the student should consider studying more intensively to promote her or his planned career.

Some students express reservations about this assignment, because it comes at the start of the semester prior to their exposure to the content of the class. I encourage them to do the best they can with their limited knowledge, with the understanding that they can iteratively refine their ideas as the course progresses. My grading emphasizes quality of analysis and presentation, rather than depth of technical knowledge.

2. Technology scanning and evaluation. I provide an introductory lecture on the heuristics described in the box, and an in-class exercise to reinforce the lecture content. I also provide URLs for information technology trade publications, as a source of information on new technologies that are becoming available. I encourage the students to get into the habit of checking these web sites regularly. To reinforce this habit, I provide participation credit for students who give brief verbal reports on new technologies which, based on the heuristics, could be important to their own or other students’ careers.

3. Finding self-service learning sources. I designed this team assignment to demonstrate the breadth and depth of sources of information on software and technologies, and to show students that they can access this wealth of information when learning new technologies. I could ask the teams to find books, tutorials, etc. that relate to learning needs identified in the first assignment. However because of the diversity of students’ career plans, the amount and quality of relevant sources of information on software might vary substantially between teams.

To make the learning experiences more consistent, this assignment requires each team to find two sources of information--one print and one electronic--for each of two very standard technologies: UNIX, and SQL. The electronic sources can include the World Wide, tutorials on local computers, training videos, etc. The students submit their findings by e-mail, and I create a web page that lists the sources separately for each technology.

4. Self-service technology learning. To demonstrate to students that they can assimilate technologies on their own, I have a two-part assignment that requires the teams to do simple activities with UNIX and SQL. I do not provide any instruction in the technologies; the teams have to use the information sources from the previous assignment (or anything else they can find) to do the work.

For the assignments, the students have to fill in the blanks on one-page worksheets. I encourage the students to use their UNIX (e-mail) accounts to test their answers to the ten UNIX questions (e.g., what is the command to list files? create a subdirectory? etc?) For SQL, I have students download the SSQL (sic) public domain software package (10) available at many large shareware sites. They then can use this package to test the SQL code they develop for five very simple queries to produce the specified results.

5. Evaluating self-service learning sources. After using the sources to complete the previous assignments, students should better understand the relationship between the characteristics of a learning source and its usefulness in assimilating a technology. To reinforce this experience, I have the teams rate and rank the four sources they found in the third assignment, and write an analysis comparing and contrasting their usefulness. The goal of this assignment is to increase their ability to select sources of information that will be most useful when the students deal with new technologies later in their careers.

6. Software evaluation and assimilation term project. The final assignment is an integrative 10-15 page term paper. This project builds on previous assignments, requiring the teams to:

a) identify some software technology(s) that appears promising, based on the heuristics and in context of the career plans of one or more team members

b) find two or three download sites that offer software that embodies these promising technology(s), and compare and contrast the sites. The sites should include commercial software, and at least one site has to offer over 100 titles. The Internet is becoming an increasingly prominent distribution mechanism for a tremendous variety of software, and this demonstrates that students can use the Internet to find software and technologies that can further their careers.

c) download and install one software package, and describe the installation experiences. The software needs to have a total of at least 35 choices in the top-level drop-down menus, and should not be a simple utility such as a virus checker.

d) use the software to “do something useful” for a business-oriented small project

e) reevaluate the software based on actual usage

In addition to IT meta-skills, these assignments provide students with practice in writing and analysis. To develop oral communication skills and share knowledge among the teams, I have each student use presentation software to do an individual report on the results of one of the assignments.

CONCLUSION

The breadth, complexity, and rapid pace of change make it difficult to keep up-to-date with, and make good decisions about, information technology. If IT was a very specialized field, relevant only to niche markets and a few specialists, it would be possible for most people to avoid the subject because of its difficult characteristics. However IT is now a part of every person’s life, at least in the industrialized nations. Furthermore, IT decisions can have a tremendous impact on the success and failure of organizations, and significant impacts on individual careers. Therefore educators need to teach meta-skills to enable their students to keep themselves up-to-date with this field after they leave school.

The learning needs model described above, with accompanying heuristics, can teach these meta-skills to students to prepare them for more effective continuous learning during their careers. In addition, the heuristics can help established professionals make better decisions in regard to new information technologies. In either case, meta-skills can enable people to benefit from rather than being harmed by the rapid rate of change in information technology.

REFERENCES

[1] Ahmadi, M. and M. Brabston. “MIS Education: Differences in Academic Practice and Business Managers’ Expectations.” Journal of Computer Information Systems, 38:2, 1997/1998, pp. 18-25.

[2] Arthur, W. B. “Increasing Returns and the New World of Business.” Harvard Business Review 74:4, 1996, pp. 100-109.

[3] Bohr, M. “Silicon Trends and Limits.” Communications of the ACM, 41:3, 1998, pp. 80-87.

[4] Cunningham, S. J. and D. Bocock, “Obsolescence of Computing Literature.” Scientometrics, 34:2, 1995, pp. 255-262.

[5] Lee, D. M. S., E. M. Trauth, and D. Farwell. “Critical Skills and Knowledge Requirements of IS Professionals: A Joint Academic/Industry Investigation.” MIS Quarterly, 19:3, 1995, pp. 313-340.

[6] Mendelson, H. and R. R. Pillai. “Clockspeed and Information Response: Evidence from the Information Technology Industry.” Information Systems Research, 9:4, 1998, pp. 415-433.

[7] Moore, G. E. “Cramming More Components on Integrated Circuits.” Electronics, 38:8, 1965, pp. 114-117.

[8] Porter, M. E. Competitive Advantage: Creating and Sustaining Superior Performance, Free Press, New York, 1985.

[9] Price, D. J. d. S. Science Since Babylon (enlarged ed.), Yale University Press, New Haven, CT, 1975.

[11] Westfall, R. “Evaluation and Assimilation Skills as Key Knowledge Aspects of Information Technology Literacy.”position paper at National Research Council, Computer Science and Telecommunications Board workshop on What Everyone Should Know about Information Technology, Irvine, Calif., January 14-15, 1998, (www.cyberg8t.com/westfalr/it_litrc.htm).

[12] Westfall, R. D. “Using the Learning Needs Model in Introductory Information Systems Classes.” Proc. Decision Sciences Institute Annual Meeting, San Diego, CA, Nov. 22-25, 1997, pp. 106-108, (www.cyberg8t.com/westfalr/lrn_need.html).