The Grouping Model

During its initial meetings and training in May, 2013, the AcTF was introduced to the so-called Dickeson Model for Program Prioritization. The model described in Dickeson’s book is deliberately vague, allowing each institution fairly free rein to implement it as it sees fit. However, the suggestions from the facilitator at the training sessions were rather more definite.

The AcTF was asked to determine weights for the various criteria against which programs were to be assessed. These weights were designed to sum to 1.0 (or 100%), and the suggestion was that these would be used to support a linear combination of scores for each criterion. The subsequent weighted score would then allow easy grouping of programs into quintiles. The quintiles would then be a linear ranking approach, albeit clustered into five equally sized groups.

The facilitator assured us that this approach was the easiest way to undertake placing programs into quintiles, and that this approach also allowed quick grouping. This suggested grouping model was more definite than that in the book, and was apparently based on implementation experience elsewhere.

Recalling that the Dickeson Model is primarily designed for a triage situation, these attributes of speed and simplicity are indeed an asset. An institution in financial crisis must move quickly to resolve its issues, and a quick resolution of the question of how to reallocate resources to ensure survival for the largest part of the institution is critical. Whether this is the best way is another question and, as it turns out, is not relevant to UAA’s situation.

The AcTF recognized very early the very non-linear nature of the problem of determining the grouping model. This militated against a simple linear combination, supported by predetermined weights, as this was incompatible with the situation as we saw it. This was a significant factor in the AcTF moving away from the Dickeson Model and its suggested grouping model.

Why does the grouping process (how we go from an assessment of a program against the criteria to a program’s placement in a category, as set out in what we are calling the grouping model) have this non-linearity? Perhaps this is easier to show with some examples.

Suppose we have a program that scores very well against nine of the ten criteria. It is well aligned with UAA’s mission, is efficient and effective, does all the right things within and outside the university, and is clearly important to the state and region. In a strictly linear scoring system, such a program will rank at or very close to the top, and so would qualify for additional funding. But what if the one criterion where it scored poorly was concerned with its opportunity for development with additional funds? This program could be doing everything right, but be at capacity, either internally (faculty, space, equipment), or in terms of capturing the potential student pool. If the program would require major additional funding in order to increase its numbers by, say, 10%, because it needed to build new facilities or attract significant numbers from out of state, it would not benefit from the smaller amounts of incremental funding available through reallocation via PBAC. So it should not be placed in the ‘top category,’ even though the numbers would require that outcome in a strictly linear grouping model.

Program Prioritization is supposed to deal with resources that PBAC can manage. This means relatively small amounts. Whatever the merits of the case, Program Prioritization cannot deal with situations where funding has to come from major capital allocations or grants. A recent example has been the School of Engineering. Program Prioritization would not have been able to be used to support funding for the new Engineering Building, other than being able to be used as supporting information; gaining such funding would necessarily be a very different process.

Similarly, consider a program in dire straights. Its finances and management are in a mess, for whatever reason, and it scores poorly across the board in all criteria, except one. That one criterion is essentiality, as this program is critically important for the state. While a strictly linear model would probably place it squarely in the ‘bottom’ category, it really belongs in the Transform category, and would probably benefit significantly from reorganization and some additional resources.

It can be seen that the linear approach has very limited flexibility as a grouping model. If the outcomes have to be modified based on a more realistic assessment of the situation, clearly the grouping model is of limited utility, and probably should not be used. (In Geomatics-speak, there are systematic errors introduced by a model that does not match reality in some important way(s).) This was the conclusion of the AcTF, reached after much consideration, discussion and soul-searching. One of the consequences of this conclusion is that the original weights were changed to be guides to the relative importance of criteria, not the basis of linear combinations.

Similarly, the non-linearity extended to the categories in which programs are placed. We have been at pains to convey the idea that the categories are not linear, and that there is not a ‘top’ and a ‘bottom.’ This is a significant departure from the Dickeson Model, which has a very definite ordering to the categories, and matching placement methodologies. It is also important to realize that what the AcTF does is not able to be converted into any kind of action without a subsequent process. PBAC determines additional funding, not the AcTF. There is a lot of input to the processes for programs in the Further Review category, in which the AcTF will play no part. AcTF is at least as much about information creation and dissemination as it is about program assessment and categorization.

Looking at a more complex combination-type approach, such as that used in the Analytic Hierarchy Process (AHP), pairwise comparisons of criteria are used to derive what is still a set of weights for linear combination. While such an approach has the potential to provide finer discrimination, especially when based on non-expert assessment of weights, the combination is still linear.

An alternative, rather different, approach is that adopted in expert systems. Here we arrange a number of “IF … THEN … ELSE” combinations to provide the grouping model. The problem with this is twofold. First is that it is necessary to define ahead of time all possible combinations and their outcomes, and this can be very difficult if qualitative assessment is used for each criterion. The second problem is that we are doing this for the first time at UAA, and we have no experts from whom to extract the knowledge of how it should be done. All we have are faculty with experience of academic programs at UAA, who are going to have to assess these combinations as they arise. As it is difficult to create an expert system before there are any experts in that particular field, the expert system style of approach has serious implementation problems in our current circumstances.

Our best approach to creating the grouping model for the UAA Program Prioritization Process is to rely on the expertise we have, and allow the AcTF faculty to develop (in effect) the ‘expert system’ as we work our way through the process. Here we rely on Professional Judgment, and after many months of considering this problem, it looks to be the best solution available. While it may not have the superficial certainty of a more mathematical approach, it has flexibility and a capacity for rapid learning. It also has the ability to self-assess its own processes as they are being developed. These are major advantages.

The primary advantage to this approach is that it is based on humans and their wetware, rather than being based in deterministic machine software. The main disadvantage of this approach is that it is based on humans and their wetware. Because we are dealing with humans, a great deal comes down to trust.

The AcTF is currently wrestling with the problem of ensuring that this trust is maintained and assured to the university community. What would constitute a conflict of interest, and when does it move from being merely potential to being real? When should members recuse themselves, and does it really matter in a group of 18 voting members that has to achieve an 80% majority of votes cast for all decisions? How effective is any ‘code of conduct’ likely to be, and how much of it would be symbolic only, rather than really deal with actual conflicts of interest?

Self-assessment and self-monitoring are potential solutions, but they rely on trust. A comprehensive process of exclusion for potential conflicts may render the process unworkable, as if this is a competition for finite resources (a zero-sum game), then all members can potentially be biased against all programs but their own.

The AcTF brings a wide range of viewpoints to this issue, and is very aware of concerns across the university community. Our discussions on the subject are wide-ranging, varied and informative, but we have not yet reached consensus on a workable solution, despite devoting a lot of time to this issue.

This is a very difficult problem, and we are trying to apply Professional Judgment to its resolution. It has to be resolved for a reliable and acceptable outcome to be achieved.

Posted in Models
14 comments on “The Grouping Model
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    -Phenylalanine: 4,5%, giúp bổ não, tăng trí nhớ -Histidine: 2,09%, giúp cơ thể phát triển và tăng liên kết mô cơ bắp -Lysine: 1,75% tăng khả năng hấp thụ Ca, giúp xương chắc khỏe, chống lão hóa cột sống. -tryptophan: 0,7% có tác dụng ngăn ngừa ung thư -L-arginine:11,4% giúp cải thiện vấn đề sinh lý. Thành phần yến sào còn chứa 31 nguyên tố vi lượng như: sắt(Fe), nhôm (Al), silic, kẽm (Zn), magie (Mg).. có hàm lượng cao. Những nguyên tố này có vai trò quan trọng trong việc tạo máu, hoạt động thần kinh (Mg), tác động hoạt hóa cho nhiều enzyme trao đổi chất dinh dưỡng, tăng cường sự phát triển tuyến sinh dục (Zn). Một số cách nấu món ăn bổ dưỡng từ như sau: Yến thả: Sợi yến hấp cách thủy cho chín (không nấu trực tiếp với nước vì dễ bị nát và mất chất bổ) được xếp vào bát con, rải thịt gà xé lên trên, rồi chan nước luộc gà thật nóng. Thêm gia vị cho đủ ngọt, ăn làm một lần. Hình. Món yến sào gà xé Yến tần: Sợi yến nhồi vào bụng chim bồ câu đã làm thịt sạch cùng với ít gạo nếp, đậu xanh, mộc nhĩ hoặc nấm hương, gia vị. Hầm cách thủy cho chín nhừ. Ăn trong ngày. Yến sào bồ câu non Chè yến: Sợi yến đã hấp cách thủy cho vào bát con. Đường kính nấu với nước đến sôi, bắc ra, cho lòng trắng trứng và vỏ trứng tán vụn để quyện lấy tạp chất. Lọc thật trong, rồi dội vào bát yến. Có thể nấu chung với hạt sen, táo đỏ, hoặc hạnh nhân. Ăn khi chè còn ấm hoặc để lạnh cũng rất ngon. Quý khách đọc thêm chuyên mục “món ăn yến sào” để biết thêm nhiều món ăn khác. Tóm lại, chim yến dùng nước miếng để làm thành yến sào, rất giàu chất đạm và khoáng chất, glucosamin thiên nhiên rất bổ dưỡng và là nguồn dược liệu qu‎ý của việt Nam. Chè yến chưng đường phèn là món ăn phổ biến của người sành ăn yến sào. Các bạn có thể làm theo cách sau để có được món yến chưng đường phèn ngon nhất và dinh dưỡng cao nhất. 1. Nguyên liệu: – 5g (1/2 tổ) tổ yến sào đã tinh chế. – 50g đường phèn – 4 ly nước lọc – 1 củ gừng 2. Cách làm yến chưng đường phèn -Sơ chế Yến sào. -Gọt vỏ gừng, rửa sạch để ráo, thái sợi nhỏ. -Giã nhuyễn đường phèn, cho vào nước lọc nấu sôi đến khi tan đều. Sau đó, cho nước đường, gừng, và yến sào ra thố, bắc lên bếp chưng cách thủy khoảng 30-40 phút. Chè Yến chưng đường phèn Hình. Chè Yến chưng đường phèn 3. Thưởng thức món chè yến đường phèn – Lấy chè yến đường phèn ra bát. Món này dùng nóng hay lạnh đều rất ngon. Theo những đầu bếp có kinh nghiệm nấu các món yến thì mỗi tuần chúng ta ăn ba bát chè yến đường phèn là vừa, tốt nhất là ăn trước khi đi ngủ để cơ thể có thể hấp thu trọn vẹn chất dinh dưỡng từ tổ yến sào. Đặc biệt đối với sản phụ, người già, người bị suy nhược cơ thể hoặc mới ốm dậy, ăn một bát chè tổ yến sẽ giúp cơ thể sảng khoái, thèm ăn, chống mệt mỏi. Cũng với cách làm tương tự, có thể nấu món chè yến hạt sen . Chúc quý khách ngon miệng.

  8. Swiftlets are insectivores; hymenopterans and dipterans being the most abundant prey (Lourie & Tompkins, 2000). Typically, they leave the cave during the day to forage and return to their roost at night. Males and females look similar; as usual in such cases, these birds are monogamous and both partners take part in caring for the nestlings. Males perform aerial displays to attract females and mating occurs at the nest. The breeding season overlaps the wet season, which corresponds to an increased insect population. Clutch size depends on the location and the food source, but it is generally not large; Aerodramus swiftlets lay 1 to 2 eggs. The eggs are a dull white color and are laid every other day. Many if not all species are colonial nesters; some build their nests in high, dark corners on cave walls. Swiftlets in temperate zones do migrate, but most Aerodramus swiftlets live in the tropical Indo-Pacific region and do not migrate. These birds usually remain in one cave or other roosting/nesting site. Some examples of caves include the Niah Caves at Niah National Park & Gunung Mulu National Park which are all located in Sarawak, Malaysian Borneo.

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  10. I totally agree with you . Full article quite convince me , the evidence is authentic , I like this post.
    The AcTF really recognized and very usefull.
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  11. The AcTF really recognized and very usefull. thanks for your information

  12. asharel.com says:

    Self-assessment and self-monitoring are not potential solutions

  13. So is this model working? Have you try to apply it?

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AcTF Open Dialogue

This is a community forum for people to share their perceptions and experiences with UAA’s process of prioritizing of academic programs. Members of the AcTF will post to share their experiences of task force deliberations and dialogues with the UAA community. We encourage well-informed and open dialogue about this process. Anyone is welcome to comment on posts. Find more information on UAA's Prioritization Process Website.
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