68: Book Review - The End of Ownership (Sheehan)
By Kerry Sheehan
In The End of Ownership: Personal Property in the Digital Age , Aaron Perzanowski and Jason Schultz walk us through a detailed and highly readable explanation of exactly how we’re losing our rights to own and control our media and devices, and what’s at stake for us individually and as a society. The authors carefully trace the technological changes and legal changes that have, they argue, eroded our rights to do as we please with our stuff. Among these changes are the shift towards cloud distribution and subscription models, expanding copyright and patent laws, Digital Rights Management (DRM), and use of End User License Agreements (EULAs) to assert all content is “licensed” rather than “owned.” And Perzanowski and Schultz present compelling evidence that many of us are unaware of what we’re giving up when we “buy” digital goods.
Ownership, as the authors explain, provides a lot of benefits. Most importantly, ownership of our stuff supports our individual autonomy, defined by the authors as our “sense of self-direction, that our behavior reflects our own preferences and choices rather than the dictates of some external authority.” It lets us choose what we do with the stuff that we buy – we can keep it, lend it, resell it, repair it, give it away, or modify it, without seeking anyone’s permission. Those rights have broader implications for society as a whole – when we can resell our stuff, we enable secondary and resale markets that help disseminate knowledge and technology, support intellectual privacy, and promote competition and user innovation. And they’re critical to the ability of libraries and archives to serve their missions – when a library owns the books or media in its collection, it can lend those books and media almost without restriction, and it generally will do so in a way that safeguards the intellectual privacy of its users.
These rights, long established for personal property, are safeguarded in part by copyright law’s “exhaustion doctrine.” As the authors make clear, that doctrine, which holds that some of a copyright holders’ rights to control what happens to a copy are “exhausted” when they sell the copy, is a necessary feature in copyright law’s effort to limit the powers granted to copyright holders so that overbroad copyright restrictions do not undermine the intended benefit to the public as a whole.
Throughout the book, Perzanowski and Schultz present a historical account of rights holder attempts to overcome exhaustion and exert more control over what people do with their media and devices. The authors describe book publishers’ hostile, “fearful” response to lending libraries in the 1930’s:
…a group of publishers hired PR pioneer Edward Bernays….to fight against used “dollar books” and the practice of book lending. Bernays decided to run a contest to “look for a pejorative word for the book borrower, the wretch who raised hell with book sales and deprived authors of earned royalties.”…Suggested names included “bookweevil,”…”libracide,” “booklooter,” “bookbum,” “culture vulture,” … with the winning entry being “booksneak.”
Publishers weren’t alone, the authors show that both record labels and Hollywood studios fought against the rise of secondary markets for music and home video rental, respectively. Hollywood fought a particularly aggressive battle against the VCR. In the end, the authors note, Hollywood continued to “resist[] the home video market,” at least until they gained more control over the distribution technology.
But while historically, overzealous rights holders may have been stymied to some extent by the law’s limitation of their rights, recent technological changes have made their quest a lot easier.
“In a little more than a decade,” the authors explain, we’ve seen dramatic changes in content distribution, from tangible copies, to digital downloads, to the cloud, and now, increasingly, to subscription services. These technological changes have precipitated corresponding changes in our abilities to own the works in our libraries. While, as the authors explain, copyright law has long relied on the existence of a physical copy to draw the lines between rights holders’ and copy owners’ respective rights, “[e]ach of these shifts in distribution technology has taken us another step away from the copy-centric vision at the heart of copyright law.” Unfortunately, the law hasn’t kept up: “ Even as copies escape our possession and disappear from our experience, copyright law continues to insist that without them, we only have the rights copyright holders are kind enough to grant us.”
Perzanowski and Schultz point to End User License Agreements (EULAs), with their excessive length, one-sided, take-it-or-leave-it nature, complicated legalese, and relentless insistence that what you buy is only “licensed” to you (not “owned”), as a main culprit behind the decline of ownership. They provide some pretty standout examples – including EULAs that exceed the lengths of classic works of literature, and those that claim to prevent a startling array of activity. For the authors, these EULAs
. . . create private regulatory schemes that impose all manner of obligations and restrictions, often without meaningful notice, much less assent. And in the process, licenses effectively rewrite the balance between creators and the public that our IP laws are meant to maintain. They are an effort to redefine sales, which transfer ownership to the buyer, as something more like conditional grants of access.
And unfortunately, despite their departure from some of contract law’s core principles, some courts have permitted their enforcement, “so long as the license recites the proper incantations.”
The authors are at their most poetic in their criticism of Digital Rights Management (DRM) and Section 1201 of the DMCA , perhaps the worst scourges of ownership in the book. As they point out, even in the absence of restrictive EULA terms, DRM embeds rights holders’ control directly into our technologies themselves – in our cars, our toys, our insulin pumps and heart monitors. Comparing it to Ray Bradbury’s Farenheit 451, they explain:
While not nearly as dramatic as flamethrowers and fighting robot dogs, the unilateral right to enforce such restrictions through DRM exerts many of the types of social control Bradbury feared. Reading, listening, and watching become contingent and surveilled. That system dramatically shifts power and autonomy away from individuals in favor of retailers and rights holders, allowing for enforcement without anything approaching due process.
As Perzanowski and Schultz explain, these shifts aren’t just about our relationship to our stuff. They recalibrate the relationship between rights holders and consumers on a broad scale:
When we say that personal property rights are being eroded or eliminated in the digital marketplace, we mean that rights to use, to control, to keep, and to transfer purchases – physical and digital – are being plucked from the bundle of rights purchasers have historically enjoyed and given instead to IP rights holders. That in turn means that those rights holders are given greater control over how each of us consume media, use our devices, interact with our friends and family, spend our money, and live our lives. Cast in these terms, it is clear that there is a looming conflict between the respective rights of consumers and IP rights holders.
The authors repeatedly remind us that who makes the decision between what is owned and what is licensed is crucial – both on the individual and societal scale. When we allow companies to define when we can own our stuff, through EULAs or Digital Rights Management, we shift crucially important decisions about how our society should work away from legislatures, courts, and public processes, to private entities with little incentive to serve our interests. And, when we don’t know exactly what we give up when we “buy” digital goods, we’re not making an informed choice. Further, when we opt for mere access over ownership, our choices have broader societal effects. The more we shift to licensing and subscription models, the more it may become harder for those who would rather own their stuff to exercise that option – stores close, companies shift distribution models, and some works disappear from the market.
In the end, Perzanowski and Schultz leave us with a thread of hope that we still might see a future for ownership of digital goods. They believe that at least some courts and policy makers, and “[p]erhaps more importantly, readers, listeners, and tinkerers – ordinary people – are expressing their own reluctance to accept ownership as an artifact of some bygone predigital era.” And they provide a set of arguments and reform proposals to martial in the fight to save ownership before it’s too late. They lay out an array of technological and legal strategies to reduce deceptive practices, curb abusive EULAs, and, reform copyright law. The most thoroughly developed of these proposes a legislative restructuring of copyright exhaustion in a flexible, multi-factor format, in part modeled on the United States’ fair use doctrine. It’s a good idea, and it would probably work. But (and the authors acknowledge this) even modest attempts at reform have failed to garner the necessary support in Congress to move forward. A more ambitious proposal, like this one, seems at least unlikely in the near term.
Overall, the End of Ownership is a deeply concerning exposition of how we’re losing valuable rights. The questions it raises about whether and how we can preserve the benefits of ownership in the digital age will likely continue to be relevant even as technology, and the law, evolve. Most critically, it asks us to rethink who we want making the decisions that shape how we live our lives. While the book tackles complex issues in law and technology, it does so in a way that’s accessible and interesting both for lawyers and laypersons alike. The book’s ample real world examples of everything from disappearing e-book libraries, to tractors, dolls, and medical devices resistant to their owners’ control bring home both the impact of abstract legal doctrines and the urgency of their reform.
Thanks to Electronic Frontier Foundation .
____________________
Kerry Maeve Sheehan is a former consulting policy strategist with the Electronic Frontier Foundation , focusing on intellectual property and net neutrality. She currently works for the Internet Law & Policy Foundry . This review was reprinted from The Seattle Star.
Book Review: The End of Ownership by
Kerry Sheehan
is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.


6.3: Section 6.3 Repeated Measures ANOVA Assumptions, Interpretation, and Write Up
At the end of this section you should be able to answer the following questions:
- What are the assumptions that need to be met before performing a Repeated Measures ANOVA?
- What different hypotheses are testable when using an ANOVA repeated measures design?
Let’s look now at a repeated measures ANOVA. A repeated measures ANOVA is used to compare three or more group means when the participants are the same in each group.  For example, you could use a repeated measures ANOVA to better understand whether there is a difference in anxiety levels after a group therapy program. You could measure anxiety levels at three time points, such as at the start of the program, one month after the program is completed, and then six months after the program is completed.
Repeated Measures ANOVA Assumptions
For a Repeated Measures ANOVA there are two or more independent variables (factors) that can be denoted by the levels of each Independent Variable (IV).
For example, in a design with 2 IVs, the ANOVA is described as A X B ANOVA
(A = Number of levels of IV1; B = Numbers of levels of IV2)
Meanings of the levels of factors can change when researchers shift between between-subjects designs and within-subjects designs.
For between-subjects design, levels can be thought of as different groups of the factor.
For within-subjects design, levels can be thought of as different conditions of the factor.
There are also several assumptions that go with Repeated Measures ANOVA:
- The dependent variable (the variable of interest) needs a continuous scale (i.e., the data needs to be at either an interval or ratio measurement).
- The “within-groups” variable must have two or more groups that are related or have “matched pairs”. As in the Paired-samples T-test, matched pairs mean that the same participants are present in both groups (i.e. measuring the same persons twice).
- There should be no spurious outliers.
- The dependent variable should be normally or near-to-normally distributed for each group. It is worth noting that the t-test is robust for minor violations in normality, however, if your data is very non-normal, it would be worth using a non-parametric test or bootstrapping (see later chapters).
- The data must have what is known as “sphericity”. This means that amount of variable across the differences for all of the groups (both within and between) must be equal or near-to-equal the variances of the differences between all combinations of related groups must be equal. This can be tested using statistical software.
Repeated Measures ANOVA Interpretation
In our example below, the researchers are interested in the effects of more than 1 IV on a DV, which in this case are the effects of a social support program and gender on perceived levels of life satisfaction.
In the scenario, there are 2 factors or IVs:
Life satisfaction (pre- and post-program: 2 levels) X gender (male and female: 2 levels)
PowerPoint: Repeated Measures ANOVA
To view the output for the example Repeated Measures ANOVA output, please click on the following link:
For this test, the statistical program used was Jamovi, which is freely available to use. The first two slides show the steps to get produce the results. The third slide shows the output with any highlighting.
Hypothesis
Often when using an ANOVA repeated measures design, three or more different hypotheses are testable. A main effect of factor 1, a main effect of factor 2, and an interaction effect of both factor 1 and factor 2. As you can see in the figure, there is a 3-way design to this ANOVA = A X B X C
Interaction
Answers the question similar to “moderation effect” in regression
Determines whether differences that can be attributed to a factor are consistent at all levels of the other factor/s or differences that can be attributed to a factor depending on the level of the other factor.
Run the analysis
In this example, we are interested in the effects of more than 1 IV on the DV. In this case, we want to know the effects of a social support program and gender on perceived levels of life satisfaction. We want to know if the program works in improving perceptions of life satisfaction (Factor 2), and if gender can play a role in levels of life satisfaction (Factor 2). Finally, we want to know if both males and females improve at the same rate in the intervention.
In the scenario, there are 2 factors or IVs
Program (pre- and post-program: 2 levels) X gender (male and female: 2 levels)
Effects to test in ANOVA :
-
- Main program effect (Time)
- Main gender effect (Gender)
- Interaction effect of time and gender
Jamovi Interface
As you can see, there is a number of things to enter into Jamovi, which we will cover in the slides.
Homogeneity
In this case, as we are only texting two groups, and two time points, Homogeneity isn’t a major consideration in the overall analysis. However, as you can see in red, you do want these values to be greater than .05 when testing multiple groups/timepoints.
Within groups
The within-groups results can be seen here. In green is the main effect for time, which is our primary within groups variable. The results are significant, which shows a change from pre- to post-scores. The large red circle shows the interaction of gender and time, which is of interest as well. As this interaction is significant, this shows that when moving from pre- to post-intervention, male and female participants scores’ show a different rate of change. The small red circle is the overall degrees of freedom for the model, which you will need when reporting the results.
Between groups
As you can see in the large red circle, the results of the between-groups analysis shows that there is a difference between males and females.
Main effects
The results of the main effects can be seen here. In the green circles are the means for the groups/time points, and in the red is the actual comparison tests. As we can see here, there was an improvement in scores from pre- to post-intervention, and females tended to score more highly.
Interactions
In this case, we have used follow-up post hoc t-tests to test the difference across gender at each timepoint. This is to further examine the interaction of gender and time. The means for each group at each timepoint can be seen in green, and the results of the posthoc are in red. In this case, it is apparent from the results, that while both males and females improved pre to post-intervention, female participants started with greater life satisfaction, and saw greater improvement following the intervention than males.
Repeated Measures ANOVA Write Up
The following presents a write up for a Repeated Measures ANOVA:
The analysis showed both a significant main effect for time, F (1,365) = 1473.02, p < .001, n p2 = 0.80, and gender, F (1,365) = 19.40, p < .001, n p2 = 0.05, as well as a significant interaction of time and gender F (1,365) = 7.50, p = .006, n p2 = 0.02. Two follow up independent samples t-tests were conducted comparing life satisfaction for male and female participants at time 1 and time 2; t (365) = -4.35, p < .001, d = 0.25, and t (365) = 4.32, p < .001, d = 0.27, respectively. The results showed that female participants reported higher scores than males at both pre- and post-intervention. (Graphs should be included when reporting these results.)


5.9: Torsion
This section describes the concept of gravitational torsion. It can be skipped without loss of continuity, provided that you accept the symmetry property \(\Gamma^{a}_{[bc]} = 0\) without worrying about what it means physically or what empirical evidence supports it.
Exercise \(\PageIndex{1}\)
Self-check: Interpret the mathematical meaning of the equation \(\Gamma^{a}_{[bc]} = 0\), which is expressed in the notation introduced earlier .
Are Scalars Path-dependent?
It seems clear that something like the covariant derivative is needed for vectors, since they have a direction in spacetime, and thus their measures vary when the measure of spacetime itself varies. Since scalars don’t have a direction in spacetime, the same reasoning doesn’t apply to them, and this is reflected in our rules for covariant derivatives. The covariant derivative has one \(\Gamma\) term for every index of the tensor being differentiated, so for a scalar there should be no \(\Gamma\) terms at all, i.e., \(\nabla_{a}\) is the same as \(\partial_{a}\).
But just because derivatives of scalars don’t require special treatment for this particular reason , that doesn’t mean they are guaranteed to behave as we intuitively expect, in the strange world of coordinate-invariant relativity.
One possible way for scalars to behave counterintuitively would be by analogy with parallel transport of vectors. If we stick a vector in a box (as with, e.g., the gyroscopes aboard Gravity Probe B) and carry it around a closed loop, it changes. Could the same happen with a scalar? This is extremely counterintuitive, since there is no reason to imagine such an effect in any of the models we’ve constructed of curved spaces. In fact, it is not just counterintuitive but mathematically impossible, according to the following argument. The only reason we can interpret the vector-in-a-box effect as arising from the geometry of spacetime is that it applies equally to all vectors. If, for example, it only applied to the magnetic polarization vectors of ferromagnetic substances, then we would interpret it as a magnetic field living in spacetime, not a property of spacetime itself. If the value of a scalar-in-a-box was path-dependent, and this path-dependence was a geometric property of spacetime, then it would have to apply to all scalars, including, say, masses and charges of particles. Thus if an electron’s mass increased by 1% when transported in a box along a certain path, its charge would have to increase by 1% as well. But then its charge-to-mass ratio would remain invariant, and this is a contradiction, since the charge-to-mass ratio is also a scalar, and should have felt the same 1% effect. Since the varying scalar-in-a-box idea leads to a contradiction, it wasn’t a coincidence that we couldn’t find a model that produced such an effect; a theory that lacks self-consistency doesn’t have any models.
Exercise \(\PageIndex{2}\)
Self-check: Explain why parallel transporting a vector can only rotate it, not change its magnitude.
There is, however, a different way in which scalars could behave counterintuitively, and this one is mathematically self-consistent. Suppose that Helen lives in two spatial dimensions and owns a thermometer. She wants to measure the spatial variation of temperature, in particular its mixed second derivative \(\frac{\partial^{2} T}{\partial x \partial y}\). At home in the morning at point A, she prepares by calibrating her gyrocompass to point north and measuring the temperature. Then she travels \(\ell\) = 1 km east along a geodesic to B, consults her gyrocompass, and turns north. She continues one kilometer north to C, samples the change in temperature \(\Delta T_{1}\) relative to her home, and then retraces her steps to come home for lunch. In the afternoon, she checks her work by carrying out the same process, but this time she interchanges the roles of north and east, traveling along ADE. If she were living in a flat space, this would form the other two sides of a square, and her afternoon temperature sample \(\Delta T_{2}\) would be at the same point in space C as her morning sample. She actually doesn’t recognize the landscape, so the sample points C and E are different, but this just confirms what she already knew: the space isn’t flat. 10
Note
This point was mentioned in section 5.4 , in connection with the definition of the Riemann tensor.
None of this seems surprising yet, but there are now two qualitatively different ways that her analysis of her data could turn out, indicating qualitatively different things about the laws of physics in her universe. The definition of the derivative as a limit requires that she repeat the experiment at smaller scales. As \(\ell\) → 0, the result for \(\frac{\partial^{2} T}{\partial x \partial y}\) should approach a definite limit, and the error should diminish in proportion to \(\ell\). In particular the difference between the results inferred from \(\Delta T_{1}\) and \(\Delta T_{2}\) indicate an error, and the discrepancy between the second derivatives inferred from them should shrink appropriately as \(\ell\) shrinks. Suppose this doesn’t happen. Since partial derivatives commute, we conclude that her measuring procedure is not the same as a partial derivative. Let’s call her measuring procedure \(\nabla\), so that she is observing a discrepancy between \(\nabla_{x} \nabla_{y}\) and \(\nabla_{y} \nabla_{x}\). The fact that the commutator \(\nabla_{x} \nabla_{y} − \nabla_{y} \nabla_{x}\) doesn’t vanish cannot be explained by the Christoffel symbols, because what she’s differentiating is a scalar. Since the discrepancy arises entirely from the failure of \(\Delta T_{1} − \Delta T_{2}\) to scale down appropriately, the conclusion is that the distance \(\delta\) between the two sampling points is not scaling down as quickly as we expect. In our familiar models of two-dimensional spaces as surfaces embedded in three-space, we always have \(\delta \sim \ell^{3}\) for small \(\ell\), but she has found that it only shrinks as quickly as \(\ell^{2}\).
For a clue as to what is going on, note that the commutator \(\nabla_{x} \nabla_{y} − \nabla_{y} \nabla_{x}\) has a particular handedness to it. For example, it flips its sign under a reflection across the line y = x. When we “parallel”-transport vectors, they aren’t actually staying parallel. In this hypothetical universe, a vector in a box transported by a small distance \(\ell\) rotates by an angle proportional to \(\ell\). This effect is called torsion. Although no torsion effect shows up in our familiar models, that is not because torsion lacks self-consistency. Models of spaces with torsion do exist. In particular, we can see that torsion doesn’t lead to the same kind of logical contradiction as the varying-scalar-in-a-box idea. Since all vectors twist by the same amount when transported, inner products are preserved, so it is not possible to put two vectors in one box and get the scalar-in-a-box paradox by watching their inner product change when the box is transported.
Note that the elbows ABC and ADE are not right angles. If Helen had brought a pair of gyrocompasses with her, one for x and one for y, she would have found that the right angle between the gyrocompasses was preserved under parallel transport, but that a gyrocompass initially tangent to a geodesic did not remain so. There are in fact two inequivalent definitions of a geodesic in a space with torsion. The shortest path between two points is not necessarily the same as the straightest possible path, i.e., the one that parallel-transports its own tangent vector.
The Torsion Tensor
Since torsion is odd under parity, it must be represented by an odd-rank tensor, which we call \(\tau^{c}_{ab}\) and define according to
\[(\nabla_{a} \nabla_{b} - \nabla_{b} \nabla_{a})f = - \tau^{c}_{ab} \nabla_{c} f,\]
where f is any scalar field, such as the temperature in the preceding section. There are two different ways in which a space can be non-Euclidean: it can have curvature, or it can have torsion. For a full discussion of how to handle the mathematics of a spacetime with both curvature and torsion, see the article by Steuard Jensen at http://www.slimy.com/~steuard/teaching/tutorials/GRtorsion.pdf . For our present purposes, the main mathematical fact worth noting is that vanishing torsion is equivalent to the symmetry \(\Gamma^{a}_{bc} = \Gamma^{a}_{cb}\) of the Christoffel symbols. Using the notation introduced earlier , \(\Gamma^{a}_{[bc]} = 0\) if \(\tau = 0\).
Exercise \(\PageIndex{3}\)
Self-check: Use an argument similar to the one in example 5 to prove that no model of a two-space embedded in a three-space can have torsion.
Generalizing to more dimensions, the torsion tensor is odd under the full spacetime reflection x a → −x a , i.e., a parity inversion plus a time-reversal, PT.
In the story above, we had a torsion that didn’t preserve tangent vectors. In three or more dimensions, however, it is possible to have torsion that does preserve tangent vectors. For example, transporting a vector along the x axis could cause only a rotation in the y-z plane. This relates to the symmetries of the torsion tensor, which for convenience we’ll write in an x-y-z coordinate system and in the fully covariant form \(\tau_{\lambda \mu \nu}\). The definition of the torsion tensor implies \(\tau_{\lambda (\mu \nu)} = 0\), i.e., that the torsion tensor is antisymmetric in its two final indices. Torsion that does not preserve tangent vectors will have nonvanishing elements such as \(\tau_{xxy}\), meaning that parallel-transporting a vector along the x axis can change its x component. Torsion that preserves tangent vectors will have vanishing \(\tau_{\lambda \mu \nu}\) unless \(\lambda, \mu\), and \(\nu\) are all distinct. This is an example of the type of antisymmetry that is familiar from the vector cross product, in which the cross products of the basis vectors behave as x × y = z , y × z = x , y × z = x . Generalizing the notation for symmetrization and antisymmetrization of tensors from earlier , we have
\[\begin{align} T_{(abc)} &= \frac{1}{3!} \Sigma T_{abc} \\ T_{[abc]} &= \frac{1}{3!} \Sigma \epsilon^{abc} T_{abc}, \end{align}\]
where the sums are over all permutations of the indices, and in the second line we have used the Levi-Civita symbol. In this notation, a totally antisymmetric torsion tensor is one with \(\tau_{\lambda \mu \nu} = \tau_{[\lambda \mu \nu]}\), and torsion of this type preserves tangent vectors under translation.
In two dimensions, there are no totally antisymmetric objects with three indices, because we can’t write three indices without repeating one. In three dimensions, an antisymmetric object with three indices is simply a multiple of the Levi-Civita tensor, so a totally antisymmetric torsion, if it exists, is represented by a single number; under translation, vectors rotate like either right-handed or left-handed screws, and this number tells us the rate of rotation. In four dimensions, we have four independently variable quantities, \(\tau_{xyz}, \tau_{tyz}, \tau_{txz}\), and \(\tau_{txy}\). In other words, an antisymmetric torsion of 3+1 spacetime can be represented by a four-vector, \(\tau^{a} = \epsilon^{abcd} \tau_{bcd}\).
Experimental Searches for Torsion
One way of stating the equivalence principle (see section 4.4 ) is that it forbids spacetime from coming equipped with a vector field that could be measured by free-falling observers, i.e., observers in local Lorentz frames. A variety of high-precision tests of the equivalence principle have been carried out. From the point of view of an experimenter doing this kind of test, it is important to distinguish between fields that are “built in” to spacetime and those that live in spacetime. For example, the existence of the earth’s magnetic field does not violate the equivalence principle, but if an experiment was sensitive to the earth’s field, and the experimenter didn’t know about it, there would appear to be a violation. Antisymmetric torsion in four dimensions acts like a vector. If it constitutes a universal background effect built into spacetime, then it violates the equivalence principle. If it instead arises from specific material sources, then it may still show up as a measurable effect in experimental tests designed to detect Lorentz-invariance. Let’s consider the latter possibility.
Since curvature in general relativity comes from mass and energy, as represented by the stress-energy tensor T ab , we could ask what would be the sources of torsion, if it exists in our universe. The source can’t be the rank-2 stress-energy tensor. It would have to be an odd-rank tensor, i.e., a quantity that is odd under PT, and in theories that include torsion it is commonly assumed that the source is the quantum-mechanical angular momentum of subatomic particles. If this is the case, then torsion effects are expected to be proportional to \(\hbar\)G, the product of Planck’s constant and the gravitational constant, and they should therefore be extremely small and hard to measure. String theory, for example, includes torsion, but nobody has found a way to test string theory empirically because it essentially makes predictions about phenomena at the Planck scale, \(\sqrt{\frac{\hbar G}{c^{3}}}\) ∼ 10 −35 m, where both gravity and quantum mechanics are strong effects.
There are, however, some high-precision experiments that have a reasonable chance of detecting whether our universe has torsion. Torsion violates the equivalence principle, and by the turn of the century tests of the equivalence principle had reached a level of precision sufficient to rule out some models that include torsion. Figure 5.8.4 shows a torsion pendulum used in an experiment by the Eöt-Wash group at the University of Washington. 11 If torsion exists, then the intrinsic spin \(\boldsymbol{\sigma}\) of an electron should have an energy \(\boldsymbol{\sigma} \cdot \boldsymbol{\tau}\), where \(\boldsymbol{\tau}\) is the spacelike part of the torsion vector. The torsion could be generated by the earth, the sun, or some other object at a greater distance. The interaction \(\boldsymbol{\sigma} \cdot \boldsymbol{\tau}\) will modify the behavior of a torsion pendulum if the spins of the electrons in the pendulum are polarized nonrandomly, as in a magnetic material. The pendulum will tend to precess around the axis defined by \(\boldsymbol{\tau}\).
This type of experiment is extremely difficult, because the pendulum tends to act as an ultra-sensitive magnetic compass, resulting in a measurement of the ambient magnetic field rather than the hypothetical torsion field \(\boldsymbol{\tau}\). To eliminate this source of systematic error, the UW group first eliminated the ambient magnetic field as well as possible, using mu-metal shielding and Helmholtz coils. They also constructed the pendulum out of a combination of two magnetic materials, Alnico 5 and SmCo 5 , in such a way that the magnetic dipole moment vanished, but the spin dipole moment did not; Alnico 5’s magnetic field is due almost entirely to electron spin, whereas the magnetic field of SmCo 5 contains significant contributions from orbital motion. The result was a nonmagnetic object whose spins were polarized. After four years of data collection, they found \(|\boldsymbol{\tau}| \lesssim 10^{−21}\) eV. Models that include torsion typically predict such effects to be of the order of \(\frac{m^{2}_{e}}{m_{P}} ∼ 10^{−17}\) eV, where m e is the mass of the electron and \(m_{P} = \sqrt{\frac{\hbar c}{G}}\) ≈ 10 19 GeV ≈ 20 \(\mu\)g is the Planck mass. A wide class of these models is therefore ruled out by these experiments.
Since there appears to be no experimental evidence for the existence of gravitational torsion in our universe, we will assume from now on that it vanishes identically. Einstein made the same assumption when he originally created general relativity, although he and Cartan later tinkered with non-torsion-free theories in a failed attempt to unify gravity with electromagnetism. Some models that include torsion remain viable. For example, it has been argued that the torsion tensor should fall off quickly with distance from the source. 12
References
11 http://arxiv.org/abs/hep-ph/0606218
12 Carroll and Field, http://arxiv.org/abs/gr-qc/9403058


8.5: Exercises
- Three players are dividing a business. The assets are divided into three shares, S1, S2, and S3. The following table shows how each player sees each share. For each player, list the shares that the player considers a fair share.
| S1 | S2 | S3 | |
|---|---|---|---|
| Doug | 40% | 30% | 30% |
| Eddie | 33 1/3% | 33 1/3% | 33 1/3% |
| Fred | 35% | 30% | 35% |
- Four cousins are dividing a pizza. The pizza has been divided into four pieces, S1, S2, S3, and S4. The following table shows how each cousin sees each piece. For each cousin, list the pieces that the cousin considers a fair share.
| S1 | S2 | S3 | S4 | |
|---|---|---|---|---|
| Anne | 0% | 0% | 50% | 50% |
| Bob | 30% | 30% | 30% | 10% |
| Cathy | 20% | 30% | 20% | 30% |
| Don | 25% | 25% | 25% | 25% |
- A three-flavored cake is one-third chocolate, one-third vanilla, and one-third strawberry. If the chocolate part is worth $4, the vanilla part is worth $6 and the strawberry part is worth $12 to Francis, find the value of each of the following slices.
- A three-flavored cake is one-third chocolate, one-third vanilla, and one-third strawberry. If the chocolate part is worth $6, the vanilla part is worth $8 and the strawberry part is worth $10 to George, find the value of each of the following slices.
- A 12-inch sandwich worth $6 is half turkey and half meatball. To Jack, the turkey half is worth $4 and the meatball half is worth $2. Find the value of the following slices of the sandwich.
- A 12-inch sandwich worth $9 is half turkey and half meatball. To Jack, the turkey half is worth $3 and the meatball half is worth $6. Find the value of the following slices of the sandwich.
- Alice wants to divide a half-strawberry half-vanilla cake worth $12 into two pieces of equal value. She likes strawberry three times as much as vanilla. How should she cut the cake so that each piece is a fair share to her?
- Sam has a pizza that is one-third pepperoni, one-third mushrooms, and one-third sausage. He likes both pepperoni and mushrooms twice as much as sausage. He wants to split the pizza into two pieces to share with his roommate. How should Sam cut the pizza so that each piece is a fair share to him?
- Luke wants to split a twelve-inch half turkey and half veggie sub sandwich worth $12 with a friend. Luke likes turkey twice as much as veggies. How should he cut the sandwich so that each piece is a fair share to him?
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Alice and Betty want to divide a half-strawberry half-vanilla cake worth $12 by the divider/chooser method. Alice likes strawberry three times as much as vanilla and Betty likes vanilla twice as much as strawberry. A coin is tossed and Alice is the divider.
- How should Alice cut the cake?
- Which piece should Betty choose and what is its value to her?
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Sam and Ted have a pizza that is one-third pepperoni, one-third mushrooms, and one-third sausage. Sam likes pepperoni and sausage equally well but does not like mushrooms. Ted likes pepperoni twice as much as sausage and likes mushrooms twice as much as pepperoni. They want to split the pizza by the divider/chooser method. After drawing straws, Sam is the divider.
- How should Sam cut the pizza?
- Which piece should Ted choose and what is its value to him?
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Luke and Mark want to use the divider/chooser method to split a twelve-inch half turkey and half veggie sub sandwich worth $12. Luke likes turkey three times as much as veggies and Mark like veggies twice as much as turkey. They draw cards and Mark is the divider.
- How should Mark cut the sandwich?
- Which piece should Luke choose and what is its value to him?
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Two brothers want to divide up a piece of land their grandfather left them. The piece of land, valued at $300,000 is made up of two distinct parts as shown in the following figure. Joseph likes the woods twice as much as the fields. Kevin likes the fields but does not like the woods at all. The brothers decide to use the divider/chooser method to divide the land. They toss a coin and Joseph is the divider.
- How should Joseph divide the land if he makes one horizontal cut on the map: Which piece of land should Kevin choose: What is its value to him?
- How should Joseph divide the land if he makes one vertical cut on the map: Which piece of land should Kevin choose: What is its value to him?
- If Joseph can make more than one cut (i.e. cut out a rectangle or a triangle) how should he cut the piece of land: Hint: there is more than one answer.
- Amy, Becky, Charles and Doug want to use the lone divider method to split a piece of land they inherited from their father. They draw cards to determine that Doug is the divider. After Doug divides the land, Amy bids {S2, S3}, Becky bids {S1, S2}, and Charles bids {S3}. Describe the fair division.
- Edward, Frank, George, and Harold want to use the lone divider method to split a piece of land they inherited from their Grandfather. They draw cards to determine that George is the divider. After George divides the land, Edward bids {S3, S4}, Frank bids {S2}, and Harold bids {S3, S4}. Describe the fair division.
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Inez, Jackie, Kelly, and Louise want to use the lone divider method to split a piece of land they inherited from their father. They draw cards to determine that Jackie is the divider.
- If Inez bids {S2}, Kelly bids {S1, S2}, and Louise bids {S2, S4} describe the fair division.
- At the last minute Louise changes her bid to {S2}. If Inez and Kelly do not change their bids, describe the fair division.
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Frank, Greg, and Harriet want to divide a cake worth $24 that is half chocolate and half strawberry. Frank likes all cake equally well. Greg likes chocolate twice as much as strawberry and Harriet like strawberry three times as much as chocolate. They decide to use the lone chooser method and draw cards to determine that Greg will cut the cake first and Harriet will be the chooser.
- How should Greg cut the cake?
- Which piece will Frank choose and what is its value to him?
- How will Greg subdivide his piece of the cake?
- How will Frank subdivide his piece of the cake?
- Which pieces of cake will Harriet choose?
- Describe the final division of the cake. Which pieces does each player receive and what are their values?
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Paul, Rachel and Sally want to divide a four-topping pizza using the lone chooser method. The draw straws to determine that Rachel is the chooser and Paul will make the first cut. Paul likes pepperoni twice as much as mushrooms, likes sausage three times as much as mushrooms and does not like pineapple. Rachel likes mushrooms and pineapple equally well but does not like pepperoni or sausage. Sally likes all pizza equally well.
- How should Paul cut the pizza?
- Which piece should Sally choose and what is its value to her?
- How will Paul subdivide his piece of pizza?
- How will Sally subdivide her piece of pizza?
- Which pieces of pizza will Rachel choose?
- Describe the final division of the pizza. Which pieces does each player receive and what are their values?
 They decide to use the last diminisher method to divide the property. They draw straws to choose an order. Assume the order of the players is P1, P2, P3, P4, P5, P6, P7, and P8. In round one, P3, P4 and P7 are the only diminishers. In round two, no one diminishes the piece. In round three, P3 and P4 are the only diminishers. No one diminishes the piece in rounds four and five. Every player diminishes the piece in round 6.
- Who keeps the piece at the end of round one?
- Who cuts the piece at the beginning of round three?
- In round six, who cuts the piece and who keeps the piece?
- Which players are left after round six and how do they finish the division?
 They decide to use the last diminisher method to divide the property. They draw straws to choose an order. Assume the order of the players is P1, P2, P3, P4, P5, P6, and P7. In round one, P3, P4 and P7 are the only diminishers. In round two, every player diminishes the piece. In round three, P3 and P4 are the only diminishers. No one diminishes the piece in rounds four or five. Every player diminishes the piece in round 6.
- Who keeps the piece at the end of round two?
- In round three, who cuts the piece and who keeps the piece?
- Who cuts the piece at the beginning of round five?
- Which players are left after round five and how do they finish the division?
- Three heirs are dividing an estate consisting of a house, a lakeside cabin, and a small business using the method of sealed bids. The bids are listed in the following table.
| Mary | Nancy | Olivia | |
| House | $350,000 | $380,000 | $362,000 |
| Cabin | $280,000 | $257,000 | $270,000 |
| Business | $537,000 | $500,000 | $520,000 |
Describe the final settlement including who gets each item and how much money they pay or receive.
- Five heirs are dividing an estate using the method of sealed bids. The bids are listed in the following table.
| A | B | C | D | E | |
| Item 1 | $352 | $295 | $395 | $368 | $324 |
| Item 2 | $98 | $102 | $98 | $95 | $105 |
| Item 3 | $460 | $449 | $510 | $501 | $476 |
| Item 4 | $852 | $825 | $832 | $817 | $843 |
| Item 5 | $513 | $501 | $505 | $505 | $491 |
| Item 6 | $725 | $738 | $750 | $744 | $761 |
Describe the final settlement including who gets each item and how much money they pay or receive.
- Albert, Brett and Carl own a hot dog stand together. Unfortunately, circumstances are forcing them to dissolve the partnership. They decide to use the method of sealed bids with the understanding that one of them will get the hot dog stand and the other two will get cash. Albert bids $81,000, Brett bids $78,000, and Carl bids $87,000. Who gets the hot dog stand and how much does he pay each of the other two partners?
- The method of sealed bids can be used to divide up negative items like a list of chores that must be done. The main difference in the method is that the item or chore is given to the lowest bidder rather than the highest. You also need to be careful in the “owes to estate”/”estate owes” step. Three roommates need to divide up four chores in order to get their security deposit back. They use the method of sealed bids to divide the chores. The bids are summarized in the following table.
| Harry | Ingrid | Jeff | |
| Clean Bathrooms | $65 | $70 | $55 |
| Patch and Paint Wall | $100 | $85 | $95 |
| Scrub Baseboards | $60 | $50 | $45 |
| Wash Windows | $75 | $80 | $90 |
Describe the final outcome of the division. State which chores each roommate does and how much money each roommate gets or pays.
- Albert, Bernard, and Charles want to divide up a collection of 17 small objects using the method of markers. The objects are laid out in a straight line and the players place their markers as shown in the following figure. Describe the final division, including which objects each player gets and how they deal with any leftover objects.
- Alex, Bobby, Carrie, and Doug want to divide a collection of 25 small objects using the method of markers. The objects are laid out in a straight line and the players place their markers as shown in the following figure. Describe the final division, including which objects each player gets and how they deal with any leftover objects.
- Jack, Kelly, and Larry want to divide a collection of 25 small objects using the method of markers. The objects are laid out in a straight line as shown in the following figure. Jack values each red object at $2, each blue object at $1, each green object at $0.50, and each yellow object at $0. Kelly values each red object at $0, each blue object at $1.50, each green object at $1, and each yellow object at $2. Larry values each red object at $1.50, each blue object at $1.50, each green object at $2, and each yellow object at $0.50. Determine where each player should place his markers. Draw the figure placing each player’s markers in the correct places. Do not determine the division of objects.
Note: The numbers do not come out evenly so you might have to round off a bit.


2.4: Significant Figures in Calculations
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Learning Objectives
- Use significant figures correctly in arithmetical operations.
Rounding
Before dealing with the specifics of the rules for determining the significant figures in a calculated result, we need to be able to round numbers correctly. To round a number, first decide how many significant figures the number should have. Once you know that, round to that many digits, starting from the left. If the number immediately to the right of the last significant digit is less than 5, it is dropped and the value of the last significant digit remains the same. If the number immediately to the right of the last significant digit is greater than or equal to 5, the last significant digit is increased by 1.
Consider the measurement \(207.518 \: \text{m}\). Right now, the measurement contains six significant figures. How would we successively round it to fewer and fewer significant figures? Follow the process as outlined in Table \(\PageIndex{1}\).
| Number of Significant Figures | Rounded Value | Reasoning |
|---|---|---|
| 6 | 207.518 | All digits are significant |
| 5 | 207.52 | 8 rounds the 1 up to 2 |
| 4 | 207.5 | 2 is dropped |
| 3 | 208 | 5 rounds the 7 up to 8 |
| 2 | 210 | 8 is replaced by a 0 and rounds the 0 up to 1 |
| 1 | 200 | 1 is replaced by a 0 |
Notice that the more rounding that is done, the less reliable the figure is. An approximate value may be sufficient for some purposes, but scientific work requires a much higher level of detail.
It is important to be aware of significant figures when you are mathematically manipulating numbers. For example, dividing 125 by 307 on a calculator gives 0.4071661238… to an infinite number of digits. But do the digits in this answer have any practical meaning, especially when you are starting with numbers that have only three significant figures each? When performing mathematical operations, there are two rules for limiting the number of significant figures in an answer—one rule is for addition and subtraction, and one rule is for multiplication and division.
In operations involving significant figures, the answer is reported in such a way that it reflects the reliability of the least precise operation. An answer is no more precise than the least precise number used to get the answer.
Multiplication and Division
For multiplication or division, the rule is to count the number of significant figures in each number being multiplied or divided and then limit the significant figures in the answer to the lowest count. An example is as follows:
The final answer, limited to four significant figures, is 4,094. The first digit dropped is 1, so we do not round up.
Scientific notation provides a way of communicating significant figures without ambiguity. You simply include all the significant figures in the leading number. For example, the number 450 has two significant figures and would be written in scientific notation as 4.5 × 10 2 , whereas 450.0 has four significant figures and would be written as 4.500 × 10 2 . In scientific notation, all significant figures are listed explicitly.
Example \(\PageIndex{1}\)
Write the answer for each expression using scientific notation with the appropriate number of significant figures.
- 23.096 × 90.300
- 125 × 9.000
Solution
a
| Explanation | Answer |
|---|---|
| The calculator answer is 2,085.5688, but we need to round it to five significant figures. Because the first digit to be dropped (in the tenths place) is greater than 5, we round up to 2,085.6. | \(2.0856 \times 10^3\) |
b
| Explanation | Answer |
|---|---|
| The calculator gives 1,125 as the answer, but we limit it to three significant figures. | \(1.13 \times 10^3\) |
Addition and Subtraction
How are significant figures handled in calculations? It depends on what type of calculation is being performed. If the calculation is an addition or a subtraction, the rule is as follows: limit the reported answer to the rightmost column that all numbers have significant figures in common. For example, if you were to add 1.2 and 4.71, we note that the first number stops its significant figures in the tenths column, while the second number stops its significant figures in the hundredths column. We therefore limit our answer to the tenths column.
We drop the last digit—the 1—because it is not significant to the final answer.
The dropping of positions in sums and differences brings up the topic of rounding. Although there are several conventions, in this text we will adopt the following rule: the final answer should be rounded up if the first dropped digit is 5 or greater, and rounded down if the first dropped digit is less than 5.
Example \(\PageIndex{2}\)
- 13.77 + 908.226
- 1,027 + 611 + 363.06
Solution
a
| Explanation | Answer |
|---|---|
| The calculator answer is 921.996, but because 13.77 has its farthest-right significant figure in the hundredths place, we need to round the final answer to the hundredths position. Because the first digit to be dropped (in the thousandths place) is greater than 5, we round up to 922.00 | \(922.00 = 9.2200 \times 10^2\) |
b
| Explanation | Answer |
|---|---|
| The calculator gives 2,001.06 as the answer, but because 611 and 1027 has its farthest-right significant figure in the ones place, the final answer must be limited to the ones position. | \(2,001.06 = 2.001 \times 10^3\) |
Exercise \(\PageIndex{2}\)
Write the answer for each expression using scientific notation with the appropriate number of significant figures.
- 217 ÷ 903
- 13.77 + 908.226 + 515
- 255.0 − 99
- 0.00666 × 321
- Answer a:
- \(0.240 = 2.40 \times 10^{-1}\)
- Answer b:
- \(1,437 = 1.437 \times 10^3\)
- Answer c:
- \(156 = 1.56 \times 10^2\)
- Answer d:
- \(2.14 = 2.14 \times 10^0\)
Remember that calculators do not understand significant figures. You are the one who must apply the rules of significant figures to a result from your calculator.
Calculations Involving Multiplication/Division and Addition/Subtraction
In practice, chemists generally work with a calculator and carry all digits forward through subsequent calculations. When working on paper, however, we often want to minimize the number of digits we have to write out. Because successive rounding can compound inaccuracies, intermediate rounding needs to be handled correctly. When working on paper, always round an intermediate result so as to retain at least one more digit than can be justified and carry this number into the next step in the calculation. The final answer is then rounded to the correct number of significant figures at the very end.
In the worked examples in this text, we will often show the results of intermediate steps in a calculation. In doing so, we will show the results to only the correct number of significant figures allowed for that step, in effect treating each step as a separate calculation. This procedure is intended to reinforce the rules for determining the number of significant figures, but in some cases it may give a final answer that differs in the last digit from that obtained using a calculator, where all digits are carried through to the last step.
Example \(\PageIndex{3}\)
- 2(1.008 g) + 15.99 g
- 137.3 s + 2(35.45 s)
- \( {118.7 g \over 2} - 35.5 g \)
Solution
a.
| Explanation | Answer |
|---|---|
|
2(1.008 g) + 15.99 g = Perform multiplication first.2 (1.008 g 4 sig figs ) = 2.01 6 g 4 sig figs The number with the least number of significant figures is 1.008 g; the number 2 is an exact number and therefore has an infinite number of significant figures . Then, perform the addition.2.01 6 g thousandths place + 15.9 9 g hundredths place (least precise) = 18.006 g Round the final answer.Round the final answer to the hundredths place since 15.99 has its farthest right significant figure in the hundredths place (least precise). |
18.01 g (rounding up) |
b.
| Explanation | Answer |
|---|---|
|
137.3 s + 2(35.45 s) = Perform multiplication first.2(35.45 s 4 sig figs ) = 70.90 s 4 sig figs The number with the least number of significant figures is 35.45; the number 2 is an exact number and therefore has an infinite number of significant figures. Then, perform the addition.137.3 s tenths place (least precise) + 70.90 s hundredths place = 208.20 s Round the final answer.Round the final answer to the tenths place based on 137.3 s. |
208.2 s |
c.
| Explanation | Answer |
|---|---|
|
\( {118.7 g \over 2} - 35.5 g \) = Perform division first.\( {118.7 g \over 2} \) 4 sig figs = 59.35 g 4 sig figs The number with the least number of significant figures is 118.7 g; the number 2 is an exact number and therefore has an infinite number of significant figures. Perform subtraction next.59.35 g hundredths place − 35.5 g tenths place (least precise) = 23.85 g Round the final answer.Round the final answer to the tenths place based on 35.5 g. |
23.9 g (rounding up) |
Exercise \(\PageIndex{3}\)
Complete the calculations and report your answers using the correct number of significant figures.
- 5(1.008s) - 10.66 s
- 99.0 cm+ 2(5.56 cm)
- Answer a
- -5.62 s
- Answer b
- 110.2 cm
Summary
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Rounding
- If the number to be dropped is greater than or equal to 5, increase the number to its left by 1 (e.g. 2.9699 rounded to three significant figures is 2.97).
- If the number to be dropped is less than 5, there is no change (e.g. 4.00443 rounded to four significant figures is 4.004).
- The rule in multiplication and division is that the final answer should have the same number of significant figures as there are in the number with the fewest significant figures.
- The rule in addition and subtraction is that the answer is given the same number of decimal places as the term with the fewest decimal places.


9.2: Quality in E-learning
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The Problem of Quality
Certain e-learning and pedagogical innovations have not succeeded in meeting a number of promises (Salmon, 2005), and have created confusion between the mere supply of information and actual knowledge-building and training (Barbera, 2004). Projects aiming at supporting e-learning environments such as UK eUniversity, NYU Online, Scottish Knowledge, Universitas 21, Global University Alliance (Garret, 2004), as well as a number of European corporate learning projects (e.g., StarScience, Dunes, Adapt-IT, Teachers-in-Europe, POLE STAR) have failed to realize many of their goals. However, the collapse of such initiatives does not indicate the failure of the e-learning concept per se, but rather the lack of quality. For example, lack of planning and marketing were the major reasons for the UKeU failure (Garrett, 2004.) The questions that arise include: What constitutes quality in e-learning? Why is it important? Are there ways we can ensure e-learning quality?
In general, quality refers to fitness of purpose. In e-learning, quality refers to learning (Stephenson, 2005), something excellent in performance (EFQUEL, 2005). In particular, quality in e-learning means providing the right content at the right time, enabling learners to acquire knowledge and skills and apply their learning to improve their performance, whether as an individual or within an organizational framework (ASTD & NGA, 2001). Stephenson (2005) proposed that quality depends on its interdisciplinary nature, and the identification of quality factors for a given environment depends on the chosen perspective. As there are two essential levels—the pedagogical and the operational—the target for return of investment must therefore be viewed as long term.
National bodies and international organizations have now developed principles, guidelines, and benchmarks to describe quality based on the international developments in the field (QAA, 1998; CHEA, 2001; USNEI, 2001; ISO-9000, the Benjamin Franklin Institute, 2001; EFQUEL, 2006). Furthermore, importance is also attached to national standards resulting from the globalization and universal access of learners as customers and taxpayers. For example, in Europe, there were efforts for regionally harmonized systems (see Bologna Declaration, European Ministers of Education, 1999) and Quality Assurance (QA) and accreditation systems developments. Brajnik (2001) proposed that a quality model seeks ‘quality’ by:
- understanding, controlling, and improving a product or a process;
- identifying problems or performance bottlenecks, base-lines, and timescales, and,
- comparing these for progress assessment, as well as for distinguishing certain attributes from others.
This method for developing and documenting a quality model suggests the production of a complete and consistent set of quality requirements (Firesmith, 2003). Attempts to provide such quality frameworks were conducted by European organizations but they have yet to be fully tested.
The European Foundation for Quality in E-learning (EFQUEL) was established in June 2005 in order to provide a coherent framework of quality factors for all European organizations. Its mission is “to enhance the Quality of eLearning in Europe by providing services and support for all stakeholders” (Nascimbeni, 2005, EFQUEL). This means that the quality factors are explicitly connected to the provision of services and support for all stakeholders from different fields. EFQUEL has attempted to map a quality model by incorporating stakeholders’ perspective for policy makers, researchers, e-learning quality related organizations, decision-makers, e-learning users, and learners. EFQUEL conducted a European survey between 15 August 2004 and 15 November 2004 (Panorama Report, Ehlers, Hildebrandt, Görtz & Pawlowski, 2005). Of the 5,023 responses, 28 percent completed it, and only seven percent finished the two basic sections on quality of e-learning. (The low response rate may have been due to inherent difficulties of understanding and defining what e-learning quality is. It is perhaps easier to described what quality is than to define it (Stephenson, 2005).) According to the results, quality relates to obtaining the best learning achievements (50 percent) and “something that is excellent in performance” (19 percent). In detail, the Panorama Report revealed the following:
- the importance of e-learning quality: Quality is, and will be of great importance for e-learning.
- the need for specific frameworks: Although numerous quality strategies and concepts were used, the understanding of quality is lacking—this being conceived as an abstract rather than a concrete form. The respondents believed that they knew about quality but they showed a general lack of information on quality measures, and that deceived them.
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quality requirements in design: Learners are both users and customers, and are seldom involved in design in public and business sectors, but design for quality needs to consider the following issues:
- their recommendations for successful quality development. This will prevent the low level of acceptance of designs that lack user quality.
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the inclusion of organizations’ own checklists for quality found in web resources, discussion forums and fairs;
The above shows that designers of quality must have experience of quality and ability to meet challenges; to change and adapt, to incorporate quality strategies, and being open to creativity for entirely new forms of quality development.
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critical awareness: Analysis and criticism of quality demands:
- a high degree of critical awareness;
- quality systems that reconcile the objectives of all the individuals involved;
- quality must be seen as a dynamic process of adaptation to users’ needs, primarily those of learners.
The researchers produced a framework of processes for describing quality approaches. This framework refers to general conditions of e-learning that comprise analysis of the external context; design and production involving testing, adaptation, and release of learning resources; implementation, evaluation, and optimization; and lastly, establishment of requirements such as initiation, identification of stakeholders, definition of objectives, and analysis of needs. They stressed that “learners must play a key part in determining the quality of e-learning services”, and insisted on the integration of all stakeholders in the process. The outcome of the European efforts was the white paper ISO/IEC 19796-1 entitled How to Use the New Quality Framework for Learning, Education, and Training (Pawlowski, 2006)— yet to be fully tested.
In the UK the Government’s University for Industry has embraced a learner-centred approach, learning to be determined by the learner, for its ICT programmes. This is to be done by transforming traditional methods of learning (University for Industry, 2003). The Quality Assurance Agency for Higher Education (QAA, 2004) described quality assurance as a code of practice with conditions in place for students to achieve, as set by the institution (QAA, 1998). QAA evaluation is based on teams of academics conducting audits and processing learner reviews. (For detailed QA efforts and comparison see Parker, 2003.) The quality assurance seems to be a description of quality factors for a planned and systematic review of an institution or a program. This description determines the acceptable standards of learner-centred education, scholarship, pedagogic culture and expertise, infrastructure, and organizational strategy and vision, and ensures that these are being maintained and enhanced (Pond, 2002). In the business sector, quality of e-learning in organizations is associated with guidelines for finding and choosing quality in e-learning courses, services, and providers in the e-learning marketplace (WR Hambrecht + Co, 2000).
Because of its intangible dimensions, e-learning quality control creates challenges to contemporary research. Overall, e-learning quality appears to derive from interdisciplinary approaches on learner-centred frameworks and depends on the organization’s’ infrastructure, organizational strategy, and vision. However, working on a meta-study on e-learning, Pinelle and Cutwin (2000) reported that in real world settings only one-quarter of the articles included evaluations. Thus researchers missed the current transition from the Industrial to the Information and Collaboration Age as the Tavistock Institute had predicted in 1949 (Mumford, 1983; Dolence & Norris, 1995, cited in Parker, 2003). In fact, these changes are apparent in the ways people work, learn, and entertain themselves, which shows the need of multiple skills within an organization. Therefore, although QA processes are necessary, it is difficult to set specific QA standards in a transitional period. In this connection, a European survey on e-learning quality revealed the problem of reflecting reality, and directly associated it with e-learning instructional design (Massy, 2002).
In order to ensure quality education without empirical and systematic assessment, Pond (2002) provided a set of universal attributes (criteria). He referred to the most widely used definitions of quality, quality assurance, and accreditation, with the learner at the centre of the evaluation process. According to Pond, accreditation is the process used in education to ensure that schools, post-secondary institutions, and other education providers meet and maintain the minimum standards of quality and integrity. This would include academics, administration, and related services (USNEI, 2001). He called on the Council for Higher Education Accreditation to define quality. In its glossary for International Quality Review, quality is defined as “fitness of purpose—meeting or conforming to generally accepted standards … [Quality assurance is] … planned and systematic review … of an institution or program to determine that acceptable standards of education, scholarship, and infrastructure are being maintained and enhanced” (CHEA, 2001). That is to say, learners’ expectations have to be met or exceeded. In other words, they must acquire knowledge and skills that they did not possess before the learning experience took place. Wallace (1999) and Smulders (2002) saw the learner in e-learning as both a learner and a user, and then quality standards need to be defined in practical terms on both pedagogical and operational levels.
Quality Assurance (QA)
Quality assurance (QA) is a planned and systematic review process of an institution or program to determine that acceptable standards for learner-centred education, scholarship, pedagogic culture and expertise, infrastructure, and organizational strategy and vision, are being maintained and enhanced. This would include expectations that mechanisms of quality control for benchmarking are in place and effective. QA provides the means through which an institution ensures that conditions are such that students can achieve the standards set by that institution or other awarding body. Benchmarking provides signposts against which outcomes can be measured. Subject benchmark statements allow the academic community to describe the nature and characteristics of programs in a specific subject. They also represent general expectations about the standards for qualifications at a given level; they articulate the attributes and capabilities that those possessing such qualifications should be able to demonstrate. Benchmarking is therefore a prerequisite for quality assessment.
Quality assessment is a diagnostic review and evaluation of teaching, learning, and outcomes based on detailed examination of curricula, structure, and effectiveness. It is designed to determine whether or not the institution or program meets generally accepted standards of excellence, and to suggest further quality improvements.
Quality improvement refers to expectations that an institution will have to plan, monitor and improve the quality of its programs. In most cases, the quality assurance of an accrediting agency requires established procedures to ensure an ongoing process (CHEA, 2001). According to Pond (2002), the new educational online paradigms are learner-centred, tailored, open, collaborative, qualitative, and flexible. They may also be locally differentiated. These criteria meet a universal set of quality e-learning criteria. Online education should therefore provide:
- continuity between advertising and reality
- continuity between purpose and practice
- preparation for external credentialing/further study
- personal/professional/academic growth for the learner
- relevant
- rich, multidirectional interaction
- functional, user-friendly interface
- adequate resources for: instructors, learners, curriculum
- appropriate assessment methods/opportunities
Pond’s criteria seem to be eminently constructive for a learner’s development.
In conclusion, quality assurance, assessment, and improvement require sets of performance, benchmarks, and indicators based on evaluation tools and techniques. The latter need specific criteria anchored in quality factors. E-learning quality factors describe these systematic reviews and evaluation of principles, guidelines, and benchmarks. However, there is a problem related to labour-management issues during collective bargaining vis-à-vis quality education. It is important that to be in alignment with the international, national and organizational targets need to be in alignment. This is the major challenge.
Quality Factors
It is evident that ‘quality is easier to describe and illustrate than to define’ (Stephenson, 2005:1). Ensuring e-learning design for cognitive engagement in practice associated with outcomes is exactly what constitutes e-learning (Kalantzis & Cope, 2004; Oliver, 2005). Systems design has to ensure factors for quality at different levels and fields, micro or macro (Hedberg et al., 2002). Recent studies aim to identify quality factors. These studies are guides to good practice (Grahan et al, 2002); indicators for online teaching (Corich et al., 2004); pedagogical dimensions for computer-based education evaluation (Reeves, 1997); quality management (López et al., 2003); learners’ perspective (Ehlers, 2004); pillars for quality assurance and accreditation (Pond, 2002); and evaluation frameworks and tools (Muir et al., 2003). These studies referred to specific institutions’ QA standards, defining all stakeholders’ goals based on international, national, and organizational frameworks.
According to the International Standard Organization ISO/IEC 19796-1, QA can be ensured by:
- identifying the main quality objective for a process;
- identifying the responsible actors;
- identifying methods or instruments that can be used to assure quality; and
- designing to measure the success of the quality objective.
For example, if an organization provides short-term programming courses for groups of 20 students learning C++ in two weeks, the online teaching and learning style is quite different than it would be if the objective were to learn Greek. The system needs to meet the learner’s objectives. Another example is proposed by Parker, as four QA principles (2003):
- guaranteeing consistency in the product’s results based on long-term values;
- guaranteeing consistency in governmental and corporate education;
- guaranteeing learner-centred education;
- guaranteeing collaboration between internal and external stakeholders).
Parker believes that in order to maintain continuity and consistency it is important to define values. As mentioned earlier, collaboration between the stakeholders for a learner-centred education is the key to success. Institutions need to have a proper understanding of their monitoring operations if they are to improve decision-making and performance. This being done, they will satisfy both themselves and external agencies that they are effective in achieving aims and objectives, as well as being cost-effective and cost-efficient (Rumble, 1986).
To sum up, specific frameworks are necessary to specify quality factors and requirements fit for purpose. Collaboration between all stakeholders is critical: involvement of all stakeholders in the process of design is important: good evaluation tools and techniques ensure quality. E-learning is valuable as an added learning environment to enhance human capabilities further.