Answer Patterns Research Articles

Changing Disadvantaged Children's Learning Tempos through Automated Techniques

Abstract Nineteen disadvantaged sixth-grade underachievers were exposed to an automated technique which included an answering time delay, audio-visual tutoring, and extrinsic reinforcement for accuracy. These Ss, having shown impulsive cognitive patterns on pretesting, averaged progressive reductions in errors coupled with parallel increases in time spent per lesson as they progressed through 65 instructional sessions. Confirmation of the influence of the automated technique upon cognitive tempo shifts was shown by across-program comparisons of the experimental group's standardized reading test performance with that of a control group. Experimental Ss averaged a significantly greater movement toward reflective answering patterns than did control students, with 53 percent of the experimental group and no control Ss showing shifts toward reflection.

The use of configural analysis for the evaluation of test scoring methods

A method based on configural analysis has been given whereby test scoring techniques can be evaluated to see if they have optimal validity. Configural analysis has also been used to show how three well known item scoring techniques, multiple regression, total score, and multiple cut-off, imply (for optimal validity) certain conditions on the answer pattern means. The method is illustrated by a worked example.

Identical Errors and Deception

Some years ago deception by college and high school students dis rupted completely the construction of a Group Rational Learning Test. It was necessary to abandon the test construction until a technique was devised for the elimination of deception errors. Students had to be seated compactly for test purposes, and some would invariably peek at neighbors' answers. Individualizing the administration of the test, through unique patterns for each subject, solved that problem. 2It amounted, figuratively, to placing each subject in an individual booth by surrounding him with students hav ing unknown answer patterns. The control and experimental groups set up proved valuable in shed ding light on the relative number of identical errors for control and experi mental groups. This experimenting with patterns, likewise, revealed the necessity for a particular identical errors percentage range for each sep arate test item type. Here, Identical Errors, refers to the percentage obtained by dividing the number of like errors by one's total errors. Table I was derived by first determining the actual number of differ ent ways two students may answer different items. Take a dual-choice item for example, two subjects (1 & 2) may answer in any of the following ways: (Tx F2), (Tt T2), (Fx T2) and (Fx F2). Here a two-choice item has four possible response combinations. Two of these (T j T2) and (Fx F2) are identical responses. One is the answer to the test item, the other is an identical error for each student.