Abstract
Online education offers strong intrinsic potential for advancing and augmenting teaching and learning through broadening and deepening access. Proponents of online education further claim extrinsic potential – that it should be less costly and just as effective as traditional education, if not more so. They consider the instruction equally or more effective relative to such factors as the depth of course content presented, student outcomes and breadth of access (Duderstadt, 2000; Allen & Seaman, 2003; Gomory, 2001).1 Are these claims accurate? How would we gauge their accuracy? What data would we collect? How would we make sense of that data? As in medicine and other social domains, there is a long-standing tradition in research on education of measuring the comparative costs and benefits of different interventions or modes of operation. Prominent examples of such interventions as assessed in this manner have included curricular reform, personnel restructuring, special programs, infrastructure improvements and class size innovations. The goal of these measurements is to identify the best course of action by gauging the relative ratio of cost to benefit. Policy may then be informed by the results of those measurements. Cost-benefit (C/B) studies include a range of research that may focus on effectiveness, efficiency, utility or simply overall benefits. Policy concerns and other constraints on (or drivers of) research may favor one sort of C/B study over another. Nowhere is this clearer than in the case of online learning and technology, which by its nature is an excellent candidate for cost-effectiveness (C/E) research.
INTRODUCTION
Online education offers strong intrinsic potential for advancing and augmenting teaching and learning through broadening and deepening access. Proponents of online education further claim extrinsic potential – that it should be less costly and just as effective as traditional education, if not more so. They consider the instruction equally or more effective relative to such factors as the depth of course content presented, student outcomes and breadth of access (Duderstadt, 2000; Allen & Seaman, 2003; Gomory, 2001).1 Are these claims accurate? How would we gauge their accuracy? What data would we collect? How would we make sense of that data?
As in medicine and other social domains, there is a long-standing tradition in research on education of measuring the comparative costs and benefits of different interventions or modes of operation. Prominent examples of such interventions as assessed in this manner have included curricular reform, personnel restructuring, special programs, infrastructure improvements and class size innovations. The goal of these measurements is to identify the best course of action by gauging the relative ratio of cost to benefit. Policy may then be informed by the results of those measurements. Cost-benefit (C/B) studies include a range of research that may focus on effectiveness, efficiency, utility or simply overall benefits. Policy concerns and other constraints on (or drivers of) research may favor one sort of C/B study over another. Nowhere is this clearer than in the case of online learning and technology, which by its nature is an excellent candidate for cost-effectiveness (C/E) research.
BACKGROUND
Why C/E Research on Online Learning and Technology?
From a policy perspective, the main question concerning the creation or deployment of any new technology is whether in the balance it advances our abilities and outcomes in the instances in which it is deployed. In the broad domain of instructional technology, the answer to this question depends on whether teaching and learning are better in the new technologically mediated instructional context than in other comparable contexts, notably including traditional, face-to-face instruction (Finkelstein & Scholz, 2000). In the particular case of online education, such comparisons may be appropriately drawn with other forms of technologically enhanced instruction, including teaching via other media that help bridge distances and broaden access, such as radio or television. For comparisons of this sort, the goal is to tease out different ways in which traditional or new means of teaching and learning are more successful than the going alternative (Bates, 1995). In this regard, the two leading indicators are cost and effectiveness. Looking at costs tells us how affordable the alternatives are and whether savings or reductions in cost growth are possible. This in turn can tell us whether the institution can be fiscally responsible in pursuing the innovation (Rumble, 1997). Looking at effectiveness tells us whether and to what degree the technology is an enabling one. A technology may be considered enabling in the instructional context if it facilitates teaching and learning at levels of performance and quality consonant with or exceeding past practice. This in turn can tell us whether the institution can be educationally responsible in pursuing the innovation. From these two facets of cost and effectiveness, the pertinent C/E question emerges: Can online technologies be used to deliver instruction in ways that reduce or control costs and sustain or augment educational outcomes? If so, how? Beyond pure research aims, such studies thereby address two paramount policy concerns.
Key Terms in this Chapter
Meta-Analysis: The statistical analysis of a group of relevantly similar experimental studies, in order to summarize their results considered as a whole.
Cost-Effectiveness Study: A kind of policy study that aims to identify the ratio of costs to effectiveness for a given set of alternative activities or interventions, and to indicate whether that ratio is more favorable for one alternative or another.
Control Group: The group in an experimental study that does not receive experimental treatment, and is otherwise similar to the group receiving the treatment in all relevant respects.
Treatment Group: The group in an experimental study that receives experimental treatment and is otherwise similar to the group not receiving the treatment, in all relevant respects.
Instructional Media: Modes of communication in which teaching take place, such as instruction by face-to-face interaction, lessons by radio, deployment of curricula or interactive learning via the Internet, and so forth.
Randomized Sample: A group of subjects (participants) in a study selected without regard to any particular characteristics, to help ensure that measured effects of the experimental treatment on members of that group are not brought about by some shared characteristic other than the treatment.
Baseline Data: The data in a study captured before an intervention or innovation is introduced in an experimental setting, in order to describe the situation before the experimental intervention or innovation is effected.
Cost-Benefit Study: A kind of policy study that aims to identify the ratio of costs to benefits for a given activity or set of activities, and so indicate whether the benefits merit the costs.
Marginal Costs: Costs of repeating an activity, beyond the fixed costs initially incurred.
Fixed Costs: One-time costs that must be incurred for an activity to occur.
Activities Based Costing: A costing method that assesses a given activity in terms of component costs for all persons and resources involved in the activity; the alternative is parsing costs of an activity by looking at aggregate cost data for only those key institutions or units directly responsible for that activity.
Cost Center: Administrative units of an institution, identified in terms of its responsibility for a given set of costs (rather than identified in terms of its functions per se). Cost center costing looks at aggregate charges to individual units rather than costs for particular activities which, per ABC costing, may be distributed across numerous cost centers.