This article was published in CAUSE/EFFECT journal, Volume 22 Number 2 1999. It was adapted and reprinted with permission from the publication Technology and Its Ramifications for Data Systems: Report of the Policy Panel on Technology, co-sponsored by the National Postsecondary Education Cooperative (NPEC) and The George Washington University, and carried out under the sponsorship of the National Center for Education Statistics (NCES), U.S. Department of Education.
Technology and Its Ramifications for Data Systems
This article is adapted and reprinted with permission from the publication Technology and Its Ramifications for Data Systems: Report of the Policy Panel on Technology, co-sponsored by the National Postsecondary Education Cooperative (NPEC) and The George Washington University, and carried out under the sponsorship of the National Center for Education Statistics (NCES), U.S. Department of Education.1
Widespread use of computer- and telecommunications-based tech- nologies to deliver instruction and provide access to information resources has the potential to change postsecondary education significantly--its organizational relationships, financial operations, student participation patterns, and faculty roles and responsibilities. Technology will result in the removal of time constraints--instruction will be available when the learner wants it--and place constraints--instruction will be available at a virtually unlimited number of locations. Technology will open a wider range of student choices resulting in a transformation from an institution-centered context for the delivery of instruction to a learner-centered emphasis. There will be greater competition and specialization across a wider range of educational providers, but at the same time there will be a greater need for providers to cooperate and share resources.
These changes have been underway for some time as nontraditional students--older adults, placebound by job and family responsibilities--have sought educational opportunities at locations and over time frames that are conducive to their needs and as institutions have responded in nontraditional ways--by expanding off-campus offerings and making courses available in evenings and over weekends. Technology, however, will both expand access to these opportunities and accelerate the pace at which they are sought and made available. The associated changes in academic and administrative operations will become more pressing, and so will their data ramifications.
Consider a course being delivered concurrently to students "affiliated" with several different institutions who are simultaneously taking instruction at multiple interactive audiovideo sites (some of which are owned by noncollegiate organizations). The course is being team-taught by several faculties, some of whom work for out-of-state institutions. Who owes tuition to whom, and who collects and reports it? Are students included in the fall enrollment count of the institution where they are registered or are they allocated to the institutions whose faculty taught the course? What is the unit cost of instruction in this example? How do we define in-state and out-of-state migration? In summary, what new data constructs will be required to describe this instructional delivery environment analytically?
Or consider a student acquiring new knowledge and skills via the Internet--tapping into learning modules and information resources created by faculty from several different institutions and receiving directions and asking questions of faculty mentors on an as-needed basis. Students with similar learning objectives work toward their goals independently and achieve them over different periods of time. Who defines when the knowledge and skill acquisition process has been completed under these conditions? On what basis is credit awarded? How is faculty workload measured? What does "full-time equivalent student" mean?
As computer- and telecommunications-based technologies are increasingly used to deliver instruction, adaptations will need to be made in postsecondary education administrative, planning, and policy development processes. These changes will bring about a need for new kinds of data--to support underlying analytical efforts and to describe this new environment through new measures.
On August 4 and 5, 1997, the National Postsecondary Education Cooperative (NPEC) and The George Washington University cosponsored a policy panel to explore the data ramification of changes within postsecondary education brought about through the expanded use of technology. The policy panel convened individuals who provided insights and prepared papers concerning the impacts of technology on data definitions and analytical conventions in the following areas: (1) new institutional and programmatic configurations, (2) understanding new faculty roles and work patterns, (3) measuring and analyzing student participation patterns, (4) assessing student progress and learning gains, and (5) analyzing revenue and expenditure flows. Summaries of the issues in each of these areas follow.
New Institutional and Programmatic Configurations
Technology will bring about many changes in conventional approaches to the delivery of postsecondary education. While students have historically come to "learning sites," students will increasingly participate at locations remote from the campus and the instructor. Rather than being affiliated with a single institution, students will be associated concurrently with multiple providers and modes of instruction. Educational services will become "unbundled" with different providers carrying out various functions including curricular development, delivery of instructional modules, provision of student services, student evaluation, and credentialing. Students will assume greater control over their educational experiences by designing programs that fit their specific needs with regard to program content, length, delivery mode, and location--a significant departure from the tradition of institutions defining the terms of their relationships with students (for example, the time and place of instruction, sequencing of courses, and placement decisions). Program completion will be defined increasingly by the knowledge gained and skills mastered rather than credit hours earned.
New Faculty Roles and Work Patterns
Faculty responsibilities and workloads will undoubtedly change as faculties become involved in technology-based delivery and instructional support systems. Less emphasis will be placed on lecturing and greater emphasis on facilitating the educational process. Efforts will be made to draw upon the capabilities of technology to increase student learning productivity by integrating technologies in ways that are tailored to the optimal learning modes of individual students, by capitalizing on the flexibility of technologies to make better use of student time, and by making faculty content and delivery specialists available to students independent of location. Faculty will be learning facilitators, intervening when needed and selectively providing motivation and assistance to students. Faculty will find it easier and more compelling to collaborate: faculty will increasingly work with multiple providers and institutions, team with other faculty, and make specialized contributions in skill and knowledge areas as well as in instructional functions (for example, courseware development). New definitions of faculty activities will be needed as well as new ways to measure faculty workload.
Analyzing Student Participation Patterns
Student participation patterns have become more complex as larger numbers of older, nontraditional students have pursued postsecondary education goals. Expanded use of technology will accelerate these trends, and the need to address related data and analytical issues will likely become more pressing. As technology results in multiple providers and modes of delivery, it will become more difficult to learn about student participation by seeking information from institutions. New ways will need to be found to link student data across providers, some of which may not be traditional institutions and learning modes. Asynchronous modes of learning made possible by computer-based systems and the Internet raise questions about when learning begins and how long it lasts. Self-paced, asynchronous experiences also tend to undermine the utility of time-based proxies for student participation and outcomes (for example, retention and graduation rates and enrollment census dates) and also have implications for credentialing and the portability of credentials. Furthermore, many administrative operations depend upon traditional student attendance measures, including assessment of student charges, unit cost analyses, administration of student financial aid, recording student progress, budget formulas, and determining eligibility for professional licenses. Pressing questions will need to be addressed such as how traditional institution-based data collection systems can be linked to student-based data collection systems and how "old" data points can be mapped to "new" data points so valid trend analyses and comparative analyses can still be carried out.
Assessment of Student Progress and Learning Gains
A wider array of providers and a more market-oriented environment will place a higher premium on information about the quality of learning experiences in consumer choice, accountability, and regulatory contexts. However, measuring student progress depends upon having insights regarding "progress toward what?" With technology, students will to an even greater extent determine learning goals--and will be the source of information about learning goals. Students will proceed toward learning goals at different paces and with different rhythms, rendering largely irrelevant traditional measures of "seat time" as the principal indicators of student progress. Competency-based measures will likely become increasingly important as the basis of academic accounting. Analysts have historically encountered challenges in studying the relationships among input, environmental, and outcome variables, but the simultaneous delivery of multiple learning experiences, by multiple providers, using multiple delivery systems will add a new dimension of complexity to studies of the effects of inputs and environment on learning gains. Computer-based instructional delivery systems provide greatly enhanced opportunities to capture timely data about student behaviors, learning strategies, and patterns of achievement, but they also heighten concerns about confidentiality and privacy with respect to student data. Issues related to privacy and confidentiality will be exacerbated by the ease with which vast amounts of data can be captured and accessed via technology.
Analysis of Revenue and Expenditure Streams
While current accounting systems appear capable of accommodating revenues and expenditures related to technology-based systems, difficulties could be encountered in reconciling revenues and expenditures across the fund accounting procedures used in postsecondary education with the charts of accounts and accounting procedures used by noncollegiate providers of instruction and student services. In addition, procedures for allocating expenditures and revenues across multiple providers pose some troublesome questions: How are student tuition and fees collected from multiple sites that are supported by different providers and staffed by faculty from different institutions to be distributed? Similarly, what proportion of the costs of shared facilities, faculty, and equipment will be paid by the various providers? How will revenues and expenditures for shared and unbundled operations be reported, and by whom? What are the ramifications for student financial aid allocations? New categories of costs (for example, for courseware development, telecommunications equipment and services, faculty development, remodeling and rewiring facilities, electronic storage and transmittal of information) will likely need to be defined, and a shift in the relative importance of certain costs will undoubtedly occur, resulting in a need to make modifications in reporting categories and aggregations. Similarly, new student and faculty activities may require new classifications and definitions or may require clarification as to how they are classified in current program structures (that is, is responding to student questions via e-mail a support activity or a direct instructional activity?). Since new modes of delivery based upon technology will need to co-exist with traditional instructional delivery across postsecondary education, accounting and reporting systems will need to be designed to accommodate multiple delivery systems simultaneously.
Responding to these issues in a timely and meaningful way presents a significant challenge for developing national data systems and improving their utility for policy analysis at all levels within postsecondary education.
Endnotes
1 The report was prepared for the National Postsecondary Education Cooperative (NPEC) Subcommittee on the Policy Panel on Technology, chaired by Virginia McMillan, executive vice president, Illinois Community College Board. Report authors and panel contributors included Thomas Campbell, George Connick, Michael Dolence, Peter Ewell, Patricia Freitag, Dennis Holmes, Frank Jewett, Sally Johnstone, Dennis Jones, Richard Markwood, William Massy, James Mingle, Edward Neal, Burks Oakley, Ronald Phipps, and Robin Zuniga. G. Phillip Cartwright synthesized their contributions and Robert Wallhaus, NPEC consultant, provided introductory and summary sections. The full report is available on the NCES Web site as a PDF document (http://nces.ed.gov/pubs98/98279.pdf) or by contacting Nancy Schantz at the National Center for Education Statistics, Office of Educational Research and Improvement, U.S. Department of Education, 202-219-1590.