# Patent

## Title
Test pallet assembly and family assignment

## Abstract

An optimization engine builds a set of test forms, called a pallet for use in a qualification test setting. The pallet is generated using a optimization engine programmed with constraints and goals for each test form in the pallet and for the pallet in general. A test information floor is set at the cut point of the test which causes test items to be focused at the area of the test where the pass/fail decision is made. The test items may be separated into families by assigning test items selected for a test form in each test generation cycle to one of several families. Because each family has unique test items compared to other families, a person re-taking a qualification test from a particular pallet may be given a test form from another family, ensuring that no item from the first administration will appear on the subsequent test.

## Background
CROSS-REFERENCE TO RELATED APPLICATIONS
This patent claims priority to U.S. Provisional Application No. 61/638,461 filed Aug. 15, 2012, entitled “Test Pallet Assembly and Family Assignment,” U.S. Provisional Patent Application No. 61/602,752, filed Feb. 24, 2012, entitled, “Test Pallet Assembly,” and U.S. Provisional Patent Application No. 61/602,882, filed Feb. 24, 2012, entitled “Outlier Detection Tool,” all which are hereby incorporated by reference for all purposes.


TECHNICAL FIELD
This patent is directed to test generation and more specifically to an automatically generated set of test forms meeting defined psychometric requirements.
BACKGROUND
Testing to determine competence in a particular field has long been of interest. Testing is used in virtually all areas of commercial enterprise and government to evaluate candidates seeking certification in certain professional capacities, including real estate brokers, attorneys, medical doctors, etc. As opposed to student/classroom testing, where the goal is to give the test taker an absolute score on a continuum, often the goal of tests used for licensing is to place a candidate above or below a cut point or pass/fail level of latent ability.
Licensure tests attempt to maintain consistency over a period of time, while reflecting changes in laws, rules, or advances in the field that affect its particular subject matter. Additionally, the use of such standardized tests, potentially over a period of time, creates security risks associated with multiple administrations of the test. These risks include hacking test host computer systems, test item harvesting and subsequent answer distribution, etc. To address some of these issues, multiple versions of tests may be generated for a given round of testing where each test instance, or form, is assembled from a pool of test items.
Linear on-the-fly (“LOFT”) or computer adaptive tests (“CAT”) have become popular alternatives for optimizing educational and psychological measurement for specific purposes while minimizing certain risks, such as test item harvesting. Linear on-the-fly exams construct test forms out of a pool of items or item sets either just prior to or while the test taker responds to the test items. LOFT forms are usually constructed to optimized measurement precision in certain regions of the score scale for all test takers, as in the case of certification or licensure exams where precision is maximized near the pass/fail or “cut” point. Adaptive tests present test items selected from a pool of test items by using responses to previous test items to estimate the test taker's latent ability. Adaptive tests seek to either minimize test time or maximize score precision for each individual test taker by selecting items that are most appropriate for the individual based on his or her apparent competence. In addition to maximizing measurement, both of these methods seek to present unique exam forms to each individual, thus minimizing the opportunity for one individual to share items with another. However, both of these methods have well-known liabilities. Neither method offers the opportunity for pre-delivery review of the test as presented by subject matter experts because the test is assembled during the actual test session. Without the benefit of specific review, the LOFT or CAT forms may be subject to previously unidentified interactions, such as test item enemies. Further while most LOFT and CAT algorithms seek to minimize departures from targeted psychometric and content constraints for the forms they assemble, they often cannot guarantee constraint compliance for individual test takers. In the case of both LOFT and CAT the aggregate psychometric and content properties of all the forms produced cannot be known ahead of time, only simulated. Existing LOFT and CAT algorithms do not track aggregate item exposure in real time for items in their pools and usually cannot guarantee that certain items will not be over-exposed or under-utilized. Current LOFT and CAT forms are assembled individually and in isolation and may underuse or overexpose portions of the item pool. Finally, both LOFT and CAT testing can sometimes require a significant amount of processing power at a testing facility that increases the cost and overhead of administering the test and may limit the number of facilities capable of delivering a specific test.
SUMMARY
The use of linear programming or similar techniques in an optimization engine for solving multiply constrained problems can be used to generate test forms for use in testing applications. Test forms are comprised of test items. Test items can either be operational (contribute towards a candidate's score) or pretest (do not contribute towards a candidate's score). A specifically engineered set of test forms, referred to here as a “pallet of test forms” or simply, a “pallet”, draws on a pool of test items with identified characteristics as an input to the optimization engine. These characteristics may include one or more subject matter areas to which the test item refers, the difficulty, discrimination, and pseudo-guessing properties of the test item, whether a use of a particular test item affects use of other test items, as well as other content or cognitive attributes. These characteristics are typically captured as metadata associated with each test item.
The development of the pallet has both goals, such as the maximization of measurement precision near the cut score, and constraints, such as a number of test forms to be generated for a particular pallet, a number of test items in each form, a length of the test, etc. One constraint of particular interest is the use, or exposure, of individual test items. Overuse of a test item can, among other things, make it easier to harvest and divulge the test item to future test takers. Underuse of some test items goes hand-in-hand with overuse of others and represents a waste of costly intellectual assets since each operational test item costs many hundreds of dollars to develop, refine, evaluate, and publish. Therefore, an important goal for pallet preparation can be to minimize exposure of individual items by maximizing the uniformity of item exposures across the source item pool while simultaneously complying with all content constraints for the form and pallet. One way to do this is to minimize the number of aggregate exposures in the items selected for each form. Alternatively, in the case where each item has a maximum number of availabilities allotted, one may maximize the aggregate availabilities of the selected items. In either case, the goal in assembling the pallet is to maximize test item diversity among test forms.
Another area of particular interest in pallet assembly is the score precision of an exam across the ability continuum. Under item response theory the sensitivity of a set of items to differences in ability at each point along the continuum is captured by a quantity know as “measurement information”, “test information”, or simply “information”. The greater the information value for a test form in a particular score region, the more precise the scores occurring in that region will be. There is an obvious need to assure that each test form meets specific precision criteria in specific regions of the ability continuum. For a certification or licensure exam the region of greatest interest is that surrounding the cut score. As discussed in more detail below, assuring a minimum level of measurement information or “information floor” near the cut is at odds with the desire to uniformly spread item exposures across the pool.
When the objectives and constraints for a pallet are identified, as well as a pool of test items from which to draw, a program for an optimization engine may be written to capture the objectives and constraints for each form, including those outlined above. Executing the program on the optimization engine generates a pallet of tests meeting the programmed assembly objectives and constraints including having a set information floor at the cut point of a form while maximizing item use. The pallet so generated also has a specified number of forms, promotes content validity by ensuring precise compliance with all content specifications, promotes fairness by minimizing variability in test information near the cut point, and allows post-generation expert review of forms.



BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 illustrates a representative testing cycle;
FIG. 2 is a block diagram illustrating a pallet test generation process;
FIG. 3 is a block diagram of an exemplary test delivery system;
FIG. 4 is a block diagram of a second exemplary test delivery system;
FIG. 5 is a graph showing sample target and actual test information distribution for a pallet;
FIG. 6 is an exemplary method of generating a pallet of tests;
FIG. 7 is a supplement to the method illustrated in FIG. 6; and
FIG. 8 is a block diagram showing an exemplary electronic device in the form of a computer supporting a pallet assembly process.



DETAILED DESCRIPTION
Although the following text sets forth a detailed description of numerous different embodiments, it should be understood that the legal scope of the description is defined by the words of the claims set forth at the end of this disclosure. The detailed description is to be construed as exemplary only and does not describe every possible embodiment since describing every possible embodiment would be impractical, if not impossible. Numerous alternative embodiments could be implemented, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims.
It should also be understood that, unless a term is expressly defined in this patent using the sentence “As used herein, the term ‘——————’ is hereby defined to mean . . . ” or a similar sentence, there is no intent to limit the meaning of that term, either expressly or by implication, beyond its plain or ordinary meaning, and such term should not be interpreted to be limited in scope based on any statement made in any section of this patent (other than the language of the claims). To the extent that any term recited in the claims at the end of this patent is referred to in this patent in a manner consistent with a single meaning, that is done for sake of clarity only so as to not confuse the reader, and it is not intended that such claim term by limited, by implication or otherwise, to that single meaning. Finally, unless a claim element is defined by reciting the word “means” and a function without the recital of any structure, it is not intended that the scope of any claim element be interpreted based on the application of 35 U.S.C. §112, sixth paragraph.
FIG. 1 illustrates a representative testing cycle 10. The testing cycle 10 involves development of test items (block 12), that is, individual questions or other items requiring a response from a test subject. Using the test items, a test may be designed to meet certain requirements of the test client (block 14). As discussed above, some tests may be targeted at ascertaining a test subject's ability level against a certain metric, such as grade level in reading. Other tests may be targeted at estimating a test subject's latent ability at a given pass/fail test cut point. Tests are usually generated according specific objectives while complying with constraints articulated in the test specification and embodied in a particular assembly model (block 14). Some tests may be presented in a fixed order, such as in a paper test, or test items may be presented to a test subject in an order determined during the administration of the test, as in an adaptive or linear on-the-fly test. After the test is administered (block 18), an analysis and scoring process is performed to evaluate the operational and pretest items, calibrate items moving from pretest to operational status, identify and take action on any anomalies found in the test administration, and generate, evaluate and report scores to test consumers (block 20). The exemplary embodiments described here are, for the sake of simplicity but without limitation, directed to pass/fail testing, such as a board test for professional licensing.
FIG. 2 is a block diagram 200 illustrating a pallet test generation process, generally covering elements of blocks 14 and 16 of FIG. 1. A database 202 stores test items 204a-204n and associated metadata 206a-206n. While an individual test item 204 may be associated with more than a category of a test, for example, a state qualifying examination and also a college-level aptitude test, generally each test item is directed to a single purpose, such as veterinarian licensing, pharmacist licensing, etc. There is generally a one-to-one correspondence between a test item 204a and its associated metadata 206a. While this one-to-one relationship is not essential, it is desirable for some embodiments of test assembly, as described below.
Psychometric models may be stored in either a second database or, as depicted in FIG. 2, a data store 208. A psychometric model may be a collection of constraints used to bound the nature of a particular pallet. The psychometric model may carry over to other tests covering the same qualification, such as a particular license. In this manner, tests given over a number of years may be kept relatively consistent while accommodating the changing needs of the subject area to which the testing applies.
For example, a pharmacology licensing test may include some of the following constraints or goals directed at both individual forms and the overall pallet, although the list is representative and is not intended to be comprehensive:

    
    
        To the extent each test item is in a category, such as legal requirements, drug interactions, pediatric considerations, etc., the minimum and maximum number of items for each category.
        A target test information floor at the test cut point. As discussed in more detail with respect to FIG. 5, each test item is associated with an item information function, that is, the measure of the sensitivity of that item to changes in latent test-taker ability as a function of latent ability. The item information function is generally bell-shaped, but its shape, height and position along the latent ability scale are idiosyncratic to each item. The sum of the item information functions in a particular test form is known as the test information function. Of particular interest for a credentialing exam is the test information value at the cut point. In constructing a credentialing exam it is desirable to select items so that a minimum test information value, or information floor, is obtained at the cut point.
        Zero or more references to a particular medication, and conversely a maximum number of items directed to any one particular medication.
        A minimum and maximum number of pediatric questions per form. Similarly, requirements may be included for a min/max range of items covering disease states, requirements for clinical data, symptoms, etc.
        Identification of related items as a set or testlet, where the number and size of testlets is between a minimum and maximum number of items presented Test item metadata, testlet information, or both, may specify the exact test items in the set and an appearance sequence, if any, for a particular testlet. Alternatively, testlet information may simply specify that for any testlet sampled, the number of cohort items to appear on a single form from that testlet must fall between a minimum and maximum value.
        A directive to maximize item diversity across the pallet, as discussed more below.
        A maximum allowable exposure rate for any one item across a pallet. However, the above directive to maximize exposure will attempt to use test items equally, so the maximum exposure rate is more or less a backstop on form generation across a pallet.
        A total of items belonging to testlets vs. a number of free standing items.
        A number of questions per form and/or a targeted test time per form, where each test item metadata specifies an average response time.
        Enemy item pairs, that is, pairs of test items such that if one member of the pair is used on a test form the second item should be excluded from the form because it may divulge or allude to the answer to the first item or may be too redundant in intent.
        A number of pretest and/or operational items. Each test item has a “state” metadatum that specifies whether the item will be scored (operational) or left unscored (pretest). Pretest items are included for evaluation and possible use in future tests. Pretest items do not have psychometric parameters by definition, since they are only in the process of being evaluated and do not contribute to scoring. However they have all the other features of operational items and must be assembled independently of but in coordination with the assembly of operational items according to their own specifications per test form.
        A number of test items may be designated as preferred items, for example, test items having value over a long period. Such items may have particular exposure goals so that they are not overused and become common knowledge to the community.
    
    


The data store 208 may also include a number of forms to be generated for a particular pallet. The data store 208 or a similar computer-readable memory may also include test generation parameters used during the pallet generation process for tracking item usage, testlet usage, etc.
The data store 208 may also store a computer-executable program that is used to codify the above and any other constraints and goals for the pallet. An optimization engine 210 may be used to execute the program. Execution of the program on the optimization engine 210 generates a pallet description 212 representing the final forms in the pallet. The optimization engine may be any of several known optimization engines, for example, linear programming solution engines used to optimize a solution over a given set of constraints. Such programs are used in a number of fields from product marketing to airline scheduling. One exemplary program is the IBM® ILOG® CPLEX® optimizer that uses a programming language known as OPL. Other equivalent products are known in the industry, such as the Analytica Optimizer from Lumina Decision Systems.
In an embodiment, an OPL program incorporating the relevant constraints may be developed by a psychometrician or other programmer and executed on the optimization engine 210. Using test item metadata 206a-206n, the optimization engine 210 generates the pallet description 212, including a list of test items for each form.
During the generation of the forms for the pallet, test generation parameters may be set to initial values prior to execution and then updated at the end of each form generation cycle. In an embodiment, each test item may be assigned an eligibility weighting that is used for distribution of test items across a form. After an item is selected, its eligibility weighting may be reduced and subsequently increased after generation of a form in which the item is not selected. However, other mechanisms for item distribution may be used, based on the optimization engine and the programmer. For example, usage vs. a maximum availability count may be another way of controlling item exposure, where each item's availability parameter may be reduced by one if that item is used on a particular form.
Additionally, some items may be designated as preferred items. Preferred items may include high value test items that may be used over a long period, as well as others, such as those covering particularly narrow subject matter. To avoid the item becoming overused and reducing its long term value, preferred items may be separately metered for inclusion in forms. For example, after inclusion in a form, a probability for next use, such an eligibility weighting may be set to a low value and increased incrementally after each form in which the item is not used, thereby increasing its statistical odds of being selected. Alternatively, the program may set an exclusion parameter for the item that prevents use of the item in subsequent forms, up to a value of the setting, after which the item is again eligible for selection.
Instructions and coding information 214 may be stored in a computer memory and used to analyze and arrange the test items for each form. That is, specific test instructions for a proctor/test administrator and for the test subject may be added to the pallet and the individual test items may be arranged according to certain criteria, for example, sequencing items in a testlet.
An optional expert review 218 may be performed to review the content of each form, with the goal of identifying additional item enemies, test items requiring change due to recent changes in law or the corresponding practice being tested, under-coded test items resulting in test anomalies, etc. One advantage of the current technique is that if one or more test items are identified during expert review as requiring change or replacement, the optimization engine can redevelop changed forms without regenerating each form from scratch.
When expert review 218, if any, is complete and any changes are made to the pallet description 212, the actual pallet may be generated 220 with each of the forms assembled with test item text, images, charts, etc., being drawn from the database 202 and assembled into a pallet of test forms ready for delivery either via the web or a testing facility. The final assembly may include translating the test items and instructions into a format and/or protocol associated with a particular test delivery architecture, such as one associated with a given testing facility and its specialized test delivery requirements. The completed and assembled forms may be stored in a second data store 222.
FIG. 3 illustrates a system 300 for delivery of a test via a test center 302. In such centers 302 the pallet of test forms 304 are delivered in a secure fashion either manually (not depicted) or via a network 306. The pallet 304 is stored in a server 308 and delivered to test subjects via test stations 310 and 312 in accordance with the instructions accompanying the pallet 304. Certain advantages of monitored tests include candidate identity verification and monitored test environments. However, transfer of the test to an outside facility incurs a small but real risk of a comprise of the test forms or results tampering.
FIG. 4 illustrates a system 400 for delivery of a test via a network 408, such as the Internet. The pallet of test forms 404 may be stored on a server 406 at the test generation facility 402 and delivered via test subject stations 410 and 412. In most cases, the stations 410 and 412 would still be located at a testing facility to help ensure candidate identity verification, etc. Delivering the test from the test generation facility 402 reduces the risk of compromised tests and results tampering.
FIG. 5 is a graph 500 of a standard error function using the current technique. “Standard error of theta” is measure of the precision of ability or “theta” estimates resulting from a test across the ability continuum, where ability increases from low to high across the horizontal access. As test information increases (not shown) the standard error of theta decreases, so the lowest values indicate the most accurate measurements. The labeled vertical 502 line shows the position of the cut score. The solid curve 504 represents the mean standard error function resulting from a pallet of forms assembled with the current technique, while the dotted curves represent maximum values 506 and minimum values 508. Superimposed over these curves is a cloud 510 representing the final standard errors of over 6000 CAT exams constructed from the same item pool. Because the goal of testing in the exemplary embodiment is to arrive at a pass/fail decision for a test subject, focusing test information (and minimizing the standard error) around the cut point allows a finer evaluation of test subjects near the pass/fail mark (cut point) rather than focusing on those who pass easily (right side) or fail miserably (left side).
Corresponding to FIG. 5, Table 1 shows a comparison of item exposure for a series of actual computer adaptive tests (CAT) vs. a pallet of tests generated in accordance with the current disclosure (Pallet Assembly). The table shows the percentage of forms on which a particular test item occurs (item exposure) and the frequency of such occurrence under CAT and Pallet Assembly. In practice, items with exposure greater than 0.30 are considered to be at risk for item harvesting.










TABLE 1





Exposure
CAT
PA



















1.00
0
0



0.95
0
0



0.90
0
0



0.85
1
0



0.80
4
0



0.75
3
0



0.70
4
0



0.65
3
0



0.60
3
0



0.55
6
0



0.50
11
0



0.45
32
0



0.40
19
0



0.35
19
0



0.30
50
0



0.25
61
197
Max usage = 0.221


0.20
113
166



0.15
115
232



0.10
48
85



0.09
86
90



0.08
118
97



0.07
114
117



0.06
117
62



0.05
45
137



0.04
43
129



0.03
21
107



0.02
161
77



0.01
138
18



0.00
183
4



Total
1518
1518









As can be seen, the pallet assembly-generated forms use more items overall compared to the prior art CAT test. Note that 183 items under CAT are completely ignored (delivered less than 1% of the time) versus only 4 such items under Pallet Assembly. Further, no test items appear on more than 22.1% of the forms under Pallet Assembly vs. 178 items that appear on more than 22.1% or test instances under CAT. In addition to optimal measurement at the cut point and good item utilization, pallet assembly has other positive impacts on test administration. Many CAT implementations allow small departures from the test content specifications in order to meet the psychometric demand of an accurate test for each individual. Pallet assembly using an optimization engine 210 helps ensure compliance with all content and psychometric constraints in the final pallet compared to other test delivery methods so that no candidate receives a form that is “out of spec”. Under CAT, each test taker gets a test that is tailored to his or her ability, a condition that promotes score precision but may be disconcerting psychologically, given that all test takers get about half the presented items correct. Under pallet assembly each test taker gets a test that is substantially the same as every other test in terms of content, difficulty, and measurement precision at the cut point, a condition that promotes fairness and standardization. While every candidate does not get a unique test, when pallets of, say 180-200 forms are constructed and randomly assigned to several thousand test takers, the chances of any two test takers getting the same test are small. Even though small groups of test takers may be randomly assigned to the same form, the overall average pairwise item overlap between forms is substantially less than with many alternative test delivery methods, such as CAT.
Under CAT many items may be under-utilized, as discussed above. As shown in the Table 1 illustration, 503 out of 1518 pool items are used 3% of the time or less under CAT. Under Pallet Assembly, 181 test forms are constructed with only 206 items used 3% of the time or less. In contrast, by comparison the unused information under CAT peaks near the cut point where it is most valuable for pass-fail decision making, whereas the unused information under Pallet Assembly occurs at the extreme high end of the score distribution where information isn't as valuable.
FIG. 6 illustrates a method 600 of assembling a set of test forms or a “pallet” where each test form in the pallet complies with given psychometric and content constraints. A plurality of test items may be generated, including collecting pre-test items and operational items from previous administration of tests (block 602). The test items may be stored in a database (block 604), such as database 202 of FIG. 2.
For each test item, metadata may be developed through an analysis of the test item response data (block 606). The metadata may describe psychometric characteristics of each test item, such as item difficulty, discrimination, and pseudo-guessing characteristics (quantities from which test information is derived). The metadata may include subject matter or cognitive classifications, tags for mentioned content such as specific drugs or medical conditions. The metadata may include item interaction information that describes, for example, whether the item is part of a testlet. Interaction data may also include enemy data describing two or more test items that should not appear in the same test form. The metadata may be stored (block 608) in the database, such as database 202.
Psychometric and content requirements for a particular pallet may be developed (block 610) that describe a “blueprint” for all test forms in the pallet, including minimum and maximum items to be delivered in different content categories and other constraints or goals as outlined above. In particular, developing the psychometric requirement may include setting a psychometric requirement maximizing item diversity across the pallet and setting a test information floor at the test cut point. That is, the optimization engine will attempt to maximize the spread of test item uses across the item pool while simultaneously meeting the information constraint at the cut point as well as all other content constraints.
In some implementations, a user interface at a computing device initiates the development of metadata for each test item. The user interface may be, for example, a web interface executed by one or more processors of a computing device. The user may select one or more test items stored in a database (block 604), such as database 202 of FIG. 2, via the user interface and initiate the development of metadata, for the selected test items, “on-the-fly.” Further, the user interface may present visualizations of the generated metadata, such as tables and graphs, to the user and/or export the metadata in any appropriate format, such as a spreadsheet, for example.
After the psychometric requirements are defined, these requirements may be coded into a program to create a computer model of the psychometric requirements (block 612), for example, in the form of a program. In one embodiment the OPL programming language may be used.
Test parameters may be specified (block 614) for the pallet, including, but not limited to, a number of forms (individual test instances) to include in the pallet and test item generation parameters including item usage maximums, preferred item settings, etc.
The test generation parameters may be set to initial values (block 616) and a form may be generated and saved (block 618) using the optimization engine to execute the program in view of the test generation parameters. A test may be performed to determine if the required number of forms has been generated (block 620). If more forms are needed, the “no” branch may be followed and the test generation parameters may be updated (block 622). In some embodiments, each item used in a form will have its corresponding maximum usage parameter reduced by one. This may be used to statistically change the item's probability of being selected again so as to maximize item usage.
When the required number of forms has been generated, the “yes” branch may be followed and the pallet description may be saved, optionally including statistical data about the forms and the pallet as a whole (block 624). The completed pallet, including test administration information may be delivered to a testing facility (block 626) where individual tests from the pallet may be administered to individual test takers.
FIG. 7 continues the method of FIG. 6 and illustrates a supplementary method 700 that provides a protection against duplicate item exposure to repeat test-takers. When a test taker repeats a test, administration of a test that has repeated questions already seen by the test taker in a previous test administration may give the test taker an unfair advantage. In general, the method 700 divides test items into a set of families during test form generation. Therefore, forms using test items found in different families will all meet the same psychometric and content requirements but will have no duplicated test items. A repeat test taker may simply be given a test form from another family with an assurance that no repeated test items will be presented.
Test items are provided in a pool of test items and a number of families of items is selected by a test designer (block 702). For the sake of illustration, three families will be used, but any number of families can be generated by setting the number of families at this point. The number of families may be influenced by a projected number of times a test taker may be expected to re-take a test and a rate at which test items are updated. Some test-takers will pass and some will fail so miserably that they may not re-attempt the test. However, those just below a cut point may re-take a test several times more. If the test cycle is every 6 months, some percentage will take the test two more times the subsequent year. Selecting three as the number of families will guarantee that this test taker will not see any repeat items until a fourth retest one and a half years down the road. If the test item pool has a significant item turn over for each test cycle, the test administered to the test taker the fourth time may have a number of repeat items, but at a rate statistically determined by the original number of items in the pool, and therefore in each original family, as well as a rate at which items are turned over in the pool.
A first form is generated from the pool of test items (block 704). If the number of families has not been reached (block 706), items from the first form are assigned to a first family (block 708).
The test generation cycle is repeated using only items from the test item pool that have not already been assigned to a family. In this first pass through the loop, all items except those in the first form, now assigned to the first family, are available. Because our illustrative case is using three families, the no branch is taken (block 706) and those items in the second form are assigned to a second family (block 708). At a third pass, those test items in the third form, selected from the items not already in the first or second families, are assigned to a third family (block 708).
When the next form is generated (block 704) and the number of families (three) has been reached, the yes branch is taken (block 706). If there are still unassigned items in the pool of test items (block 710) the no branch is taken. Items from the fourth form are assigned to the first family. Items for each subsequent pass will be assigned to the next family in the sequence until enough forms have been created to cause all the test items to be assigned to one of the three families, per the exemplary embodiment. For example, items from test forms 1, 4 and 7 will be assigned to the first family. Items from forms 2, 5, and 8 will be assigned to the second family, etc. In practice, a hundred or more test forms may be generated from a pool of questions of a thousand or more. At some point, the pool of unselected and unassigned items may not be enough to populate another test form and still meet all the psychometric and content requirements. In that case, the remaining items may be ignored and further test form generation can proceed with only items assigned to a family, or the remaining test items may be assigned to families in a round-robin approach, although other assignment techniques may be used.
Assuming additional forms are to be generated, a family of test items is selected (block 712), for example, the first family, and a form is generated using only items from that family. Note that the application of psychometric and content requirements, as described above with respect to FIG. 6, for each form being generated are still adhered to. If more forms are to be generated, the next family in the sequence is selected (block 718) and the next form is generated (block 714). Each family may be selected in sequence so that an equal, or nearly equal, number of forms are generated from each family.
When the required number of forms has been generated, the yes branch from block 716 may be followed. Each form generated is stored with its respective family identifier (block 720). When administering tests, each test taker's information will include the family from which his or her test form was selected. Should that individual be required to re-take the test, a form from another family may be selected, ensuring that no duplicate test items will be given to the test taker. Thus, the repeat test taker does not benefit from item harvesting questions presented during his or her previous attempt.
Alternatively, the form generation process could be applied to the entire pool of questions and used in a separate process to divide the pool of test items first into families and then re-run to generate specific forms. The method of FIG. 7, however, is efficiently accomplished in a single pass through the form generation process.
Either technique avoids an inevitable form of item harvesting when repeat items are administered to the same person, given the assumption that a test taker will remember at least a few test items and can later study in the hope of seeing that one or more of those test items again. Either technique also avoids a more complicated process of repeat test selection using an item-by-item screening to compare every item presented in a previous test with every item in a proposed subsequent test to determine that no overlapping items exist, if two such tests exist. Such a process is even more unwieldy if a third re-test is involved. By simply selecting a test form from another family, the test administrator is guaranteed that no repeat test items will appear on a subsequent test. In qualification testing, where ultimately one more correct answer can be the difference between passing and failing, the impact is significant.
With reference to FIG. 8, an exemplary system for implementing the claimed method and apparatus includes a general purpose computing device in the form of a computer 110. Components shown in dashed outline are not technically part of the computer 110, but are used to illustrate the exemplary embodiment of FIG. 8. Components of computer 110 may include, but are not limited to, a processor 120, a system memory 130, a memory/graphics interface 121 and an I/O interface 122. The system memory 130 and a graphics processor 190 may be coupled to the memory/graphics interface 121. A monitor 191 or other graphic output device may be coupled to the graphics processor 190.
A series of system busses may couple various system components including a high speed system bus 123 between the processor 120, the memory/graphics interface 121 and the I/O interface 122, a front-side bus 124 between the memory/graphics interface 121 and the system memory 130, and an advanced graphics processing (AGP) bus 125 between the memory/graphics interface 121 and the graphics processor 190. The system bus 123 may be any of several types of bus structures including, by way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MCA) bus and Enhanced ISA (EISA) bus. As system architectures evolve, other bus architectures and chip sets may be used but often generally follow this pattern. For example, companies such as Intel and AMD support the Intel Hub Architecture (IHA) and the HypertransportTM architecture, respectively.
The computer 110 typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 110 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer executable instructions, data structures, program modules or other data. Computer storage media includes RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, data stores, or other physical storage elements that physically embody electronic data and excludes any propagated media such as radio waves or modulated carrier signals.
The system memory 130 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 131 and random access memory (RAM) 132. The system ROM 131 may contain permanent system data 143, such as computer-specific data that may be used as a seed for generating random numbers or nonces, for example, for use in item selection and statistical calculations. RAM 132 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processor 120. By way of example, and not limitation, FIG. 8 illustrates operating system 134, application programs 135, other program modules 136, and program data 137.
The I/O interface 122 may couple the system bus 123 with a number of other busses 126, 127 and 128 that couple a variety of internal and external devices to the computer 110. A serial peripheral interface (SPI) bus 126 may connect to a basic input/output system (BIOS) memory 133 containing the basic routines that help to transfer information between elements within computer 110, such as during start-up.
A super input/output chip 160 may be used to connect to a number of ‘legacy’ peripherals, such as floppy disk 152, keyboard/mouse 162, and printer 196, as examples. The super I/O chip 160 may be connected to the I/O interface 122 with a bus 127, such as a low pin count (LPC) bus, in some embodiments. Various embodiments of the super I/O chip 160 are widely available in the commercial marketplace. In one embodiment, bus 128 may be a Peripheral Component Interconnect (PCI) bus.
The computer 110 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only, FIG. 8 illustrates a hard disk drive 140 that reads from or writes to non-removable, nonvolatile magnetic media. The hard disk drive 140 may be a conventional hard disk drive.
Removable media, such as a universal serial bus (USB) memory 153, firewire (IEEE 1394), or CD/DVD drive 156 may be connected to the PCI bus 128 directly or through an interface 150. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like.
The drives and their associated computer storage media discussed above and illustrated in FIG. 8, provide storage of computer readable instructions, data structures, program modules and other data for the computer 110. In FIG. 8, for example, hard disk drive 140 is illustrated as storing operating system 144, application programs 145, other program modules 146, and program data 147. Note that these components can either be the same as or different from operating system 134, application programs 135, other program modules 136, and program data 137. Operating system 144, application programs 145, other program modules 146, and program data 147 are given different numbers here to illustrate that, at a minimum, they are different copies. A user may enter commands and information into the computer 110 through input devices such as a mouse/keyboard 162 or other input device combination. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processor 120 through one of the I/O interface busses, such as the SPI 126, the LPC 127, or the PCI 128, but other busses may be used. In some embodiments, other devices may be coupled to parallel ports, infrared interfaces, game ports, and the like (not depicted), via the super I/O chip 160.
The computer 110 may operate in a networked environment using logical communication ports to one or more remote computers, such as a remote computer 180 via a network interface controller (NIC) 170. The remote computer 180 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 110. The logical connection between the NIC 170 and the remote computer 180 depicted in FIG. 8 may include a local area network (LAN), a wide area network (WAN), or both, but may also include other networks. Such networking environments are commonplace in offices, enterprise-wide computer networks, intranets, and the Internet.
In summary, the pallet assembly system and process enables delivery of a large number of parallel test forms with precise control over global item exposure and better utilization of existing items. The pallet thus generated has forms that are optimized for pass-fail decision making but that are very similar in terms of content and psychometric characteristics. The use of pre-assembled fixed forms eliminates unnecessary computational overhead associated with CAT and LOFT and allows subject matter expert and psychometric expert review of test forms before publication. The pallet assembly system centralizes control of all pre-publication processing but retains the ability for continued use of rigorously proctored testing centers and established test delivery architectures.
In further summary, various aspects of the disclosed embodiments include:
1. A first aspect includes method (700) of separating test items into non-overlapping families of test items using a computer (110) executing a test generation algorithm, the computer (110) coupled to a database of test items in a pool of test items, the method comprising:
setting, with the computer, a number of families of test items;
executing, with the computer using the test generation algorithm, a test generation cycle that generates a first test form using test items selected from the pool of test items, each test form meeting a psychometric and content requirement;
assigning, with the computer, all test items selected for use in the first test form to a first family;
repeating, with the computer using the test generation algorithm, the test generation cycle including:
i) generating a next test form using only test items not assigned to a family;
ii) assigning all test items selected for the next test form to a next family;
repeating i) and ii) until the selected number of families is reached;
after the selected number of families is reached, repeating i) and assigning test items from the next test form to an existing family in a sequential family order;
when all test items are assigned to a family, iii) selecting a family in a sequential order;
iv) generating a next test form using only test items found in the sequentially selected family;
repeating iii) and iv) until a number of test forms required is reached or no more test forms meeting the psychometric and content requirements can be generated from any family of test items; and
assigning, with the computer, a family identifier to each test form generated corresponding to the family in which a respective test form's test items are found, the family identifier for use in test administration of test forms to repeat test-takers.
2. The aspect of aspect 1, further comprising:
assigning a remainder of test items in the pool of test items that are not assignable to an individual test form across all the families.
3. The aspect of aspects 1-2, further comprising:
receiving a selection of the number of test forms to be generated.
4. The aspect of aspects 1-3, further comprising:
developing a psychometric and content requirement for a set of test forms;
creating, using a computer, a computer model of the psychometric and content requirement;
specifying test generation parameters;
setting, on the computer, the test generation parameters to initial values;
5. The aspect of aspects 1-4, wherein the test generation cycle comprises:
a) using an optimization engine, creating a test form assembled from the plurality of test items that meets the psychometric and content requirement, wherein the optimization engine uses the computer model and test generation parameters to select test items;
b) adjusting, using the optimization engine, the test generation parameters based on the items selected for the test form.
6. The aspect of aspects 1-5, wherein setting the number of test families comprises:
receiving a selection of the number of test families via a user interface of the computer.
7. The aspect of aspects 1-6, further comprising:
during a test administration, associating a family identifier with each test taker;
during a subsequent test administration, retrieving the family identifier for a particular test taker; and
assigning the particular test taker to a test form having another family identifier so that the particular test taker uses a form from another family during the subsequent test administration.
8. A aspect of a computer-readable storage media having computer executable instructions that when executed on a processor of a computer cause the computer to implement a method of generating a pallet of test forms segregated by family, the method comprising:
developing a psychometric and content requirement for the pallet of test forms;
creating, using a computer, a computer model of the psychometric and content requirement;
specifying test generation parameters;
setting the test generation parameters to initial values;
executing a test generation cycle that generates a first test form using test items selected from a pool of test items, each test form meeting the psychometric and content requirement;
assigning all test items selected for use in the first test form to a first family;
repeating the test generation cycle including:
i) generating a next test form using only test items not assigned to a family;
ii) assigning all test items selected for the next test form to a next family;
repeating i) and ii) until a selected number of families is reached;
after the selected number of families is reached, repeating i) and assigning test items from the next test form to an existing family in a sequential family order;
when all test items are assigned to a family, iii) selecting a family in a sequential order;
iv) generating a next test form using only test items found in the sequentially selected family;
repeating iii) and iv) until a number of test forms required is reached or no more forms meeting the psychometric and content requirements can be generated from any family of test items; and
assigning, with the computer, a family identifier to each test form generated in the pallet corresponding to the family in which a respective test form's test items are found, the family identifier for use in test administration of test forms to repeat test-takers.
9. The computer-readable storage media of aspect 8, having further instructions for implementing the method comprising:
assigning a remainder of test items not assignable to an individual test form to a selected family in a rotating basis until all test items are assigned to a family.
10. The computer-readable storage media of aspects 8-9, having further instructions for implementing the method comprising:
receiving a selection the number of test forms to be generated in the pallet of test forms.
11. The computer-readable storage media of aspects 8-10, wherein executing the test generation cycle comprises:
a) using an optimization engine, creating a test form assembled from the plurality of test items that meets the psychometric and content requirement, wherein the optimization engine uses the computer model and test generation parameters to select test items;
b) adjusting, using the optimization engine, the test generation parameters based on the items selected for the test form.
12. The computer-readable storage media of aspects 8-11, wherein the selected number of families is specified via computer executable instructions implementing a user interface on the computer.
13. Another aspect includes a method of test administration comprising:
receiving, at a test administration computer, a pallet of test forms, each test form in the pallet of test forms having a family identifier such that no test item in any test form with a first family identifier is found in another test form having another family identifier;
associating each test taker with a particular test form;
administering the test via the test administration computer;
determining a score for each test taker; and
notifying each test taker of the score.
14. The aspect of aspect 13, further comprising:
during a subsequent administration of the pallet of test forms via a test administration computer, determining that a test taker has appeared at a previous administration of the test pallet;
determining the particular test form used by the test taker at the previous administration of the test pallet;
determining a family identifier associated with the particular test form;
assigning, to the test taker, a second test form having a different family identifier than that of the particular test form used by the test taker at the previous administration of the test pallet;
administering to the test taker, via the test administration computer, the test using the second test form;
determining a score for the test taker; and
notifying the test taker of the score of the test administered using the second test form.
15. The aspect of aspects 13-14, wherein receiving the pallet of test forms, each test form in the pallet of test forms having a family identifier comprises receiving the pallet of test forms with each test form having one of three family identifiers.
16. The aspect of aspects 13-15, wherein receiving, at the test administration computer, the pallet of test forms comprises receiving the pallet of test forms at the test administration computer via a web server.
17. The aspect of aspects 13-16, wherein administering the test via the test administration computer comprises administering the test via a web session and delivered over a network.
Although the foregoing text sets forth a detailed description of numerous different embodiments of the invention, it should be understood that the scope of the invention is defined by the words of the claims set forth at the end of this patent. The detailed description is to be construed as exemplary only and does not describe every possibly embodiment of the invention because describing every possible embodiment would be impractical, if not impossible. Numerous alternative embodiments could be implemented, using either current technology or technology developed after the filing date of this patent, which would still fall within the scope of the claims defining the invention.
Thus, many modifications and variations may be made in the techniques and structures described and illustrated herein without departing from the spirit and scope of the present invention. Accordingly, it should be understood that the methods and apparatus described herein are illustrative only and are not limiting upon the scope of the invention.

## Claims

1. A method of separating test items into non-overlapping families of test items by using a computer executing a test generation algorithm, the computer coupled to a database storing a pool of test items, the method comprising:
receiving, by the computer, a selection of a number of families of test items, wherein each family includes a respective, non-overlapping set of test items from the pool of test items;
until no more unique test forms can be generated meeting a psychometric and content requirement, executing, by the computer, a test generation algorithm, the test generation algorithm including:
i) sequentially incrementing a family identifier such that when the incremented family identifier equals the selected number of families, the computer sets the family identifier to an initial family identifier,
ii) generating a test form using test items from the pool of test items not assigned to a family, the test form meeting the psychometric and content requirement, and
iii) assigning all test items from the test form to a family corresponding to the family identifier;

after the test generation algorithm is executed:
determining, by the computer, a number of required test forms; and
until (1) the number of required test forms is met or (2) no more unique test forms can be generated meeting the psychometric and content requirement, executing, by the computer, another test generation algorithm to generate a pallet of test forms, the other test generation algorithm including:
i) selecting a next sequential family of the generated families,
ii) generating a new test form using test items assigned to the sequentially selected family, the new test form meeting the psychometric and content requirement, and
iii) assigning, by the computer and to the new test form, the family identifier corresponding to the sequentially selected family, the family identifier for use in test administration of the output test forms to repeat test-takers.

2. The method of claim 1, further comprising:
after executing the test generation algorithm, assigning a remainder of test items in the pool of test items that are not assigned to a family to one of the families.

3. A non-transitory computer-readable storage media having computer executable instructions that, when executed on a processor of a computer, cause the computer to implement a method of generating a pallet of test forms segregated by family, the method comprising:
developing, by the computer, a psychometric and content requirement for the pallet of test forms segregated by family, each family including a respective, non-overlapping set of test items from a pool of test items;
creating, using the computer, a computer model of the psychometric and content requirement;
until no more unique test forms can be generated meeting the psychometric and content requirement, executing a test generation cycle, the test generation cycle including:
i) sequentially incrementing a family identifier such that when the incremented family identifier equals a selected number of families, the computer sets the family identifier to an initial family identifier,
ii) generating a test form using test items from the pool of test items not assigned to a family, the test form meeting the psychometric and content requirement, and
iii) assigning all test items from the test form to a family corresponding to the family identifier;

after the test generation algorithm is executed:
determining, by the computer, a number of required test forms for the pallet of test forms; and
until (1) the number of required test forms is met or (2) no more unique test forms can be generated meeting the psychometric and content requirement, executing, by the computer, another test generation algorithm to generate the pallet of test forms, the other test generation algorithm including:
i) selecting a next sequential family of the generated families of test items,
ii) generating a new test form using test items assigned to the sequentially selected family, the new test form meeting the psychometric and content requirement, and
iii) assigning, by the computer and to the new test form, the family identifier corresponding to the sequentially selected family, the family identifier for use in test administration of test forms to repeat test-takers.

4. The non-transitory computer-readable storage media of claim 3, having further instructions for implementing the method, the method further comprising:
after executing the test generation algorithm, assigning a remainder of test items not assigned to a family to a family in a rotating basis until all test items in the pool of test items are assigned to a family.

5. The non-transitory computer-readable storage media of claim 3, having further instructions for implementing the method, the method further comprising:
receiving a selection of the number of test forms to be generated in the pallet of test forms.

6. A method of test administration comprising:
receiving, at a test administration computer, a pallet of test forms, each test form in the pallet of test forms having a family identifier such that no test item in any test form having a first family identifier is found in another test form having another family identifier;
associating a test taker with a particular test form;
administering the particular test form via the test administration computer; and
during a subsequent administration of the pallet of test forms:
determining that the test taker has been previously administered the particular test form of the pallet of test forms,
determining a family identifier associated with the particular test form,
assigning, to the test taker, a second test form of the pallet of test forms having a family identifier other than the determined family identifier associated with the particular test form, and
administering to the test taker, via a subsequent test administration computer, the second test form using the subsequent test administration computer.

7. The method of claim 6, wherein receiving the pallet of test forms further comprises:
receiving the pallet of test forms with each test form having one of three family identifiers.

8. The method of claim 6, wherein receiving, at the test administration computer, the pallet of test forms comprises:
receiving the pallet of test forms at the test administration computer via a web server.

9. The method of claim 6, wherein administering the test via the test administration computer comprises:
administering the particular test form via a web session facilitated by a network.