Lewis R. Aiken

Activation and Behavior: II. Visually Evoked Cortical Potentials in Man as Indicants of Activation Level

The effects of variations in behavioral arousal and neural activation or excitation on averaged evoked occipital-cortical potentials to a repetitive flashing light stimulus were studied, using the Mnemotron computer of average transients (CAT). Degree of behavioral arousal and neural activation was manipulated by having Ss perform physical and “mental” tasks of varying degrees of difficulty. Records obtained under these conditions were compared with those obtained during periods of physical and mental quiescence wherein activation level was assumed to be at a relatively low level. The evoked potential patterns were found to increase in amplitude and/or to change in wave form with increases in level of activation or arousal. A number of techniques for quantifying differences in evoked cortical potential patterns were described. It was concluded that the evoked potential measure may be added to the repertory of physiological measures (EEG, EMG, heart rate, skin conductance, etc.) currently considered to constitute reliable and valid indices of activation level.

LEARNING AND RETENTION IN THE ESTIMATION OF SHORT TIME INTERVALS: A CIRCUIT AND A STUDY.

An investigation of the temporal course of learning and retention in the estimation of short time intervals is reported. In addition, a versatile response feedback circuit used in this investigation and appropriate for other studies concerned with time estimation or delayed responding is described. The experimental design was a 6 time intervals (1½, 3, 4½, 6, 7½, and 9 sec.) by 6 Ss balanced Latin square in which 6 adult female Ss made 10 pre-feedback, 25 feedback, and 15 post-feedback time estimates by terminating a 500-cps stimulus tone when they judged it to have been on for a certain time interval. Feedback consisted of informing S if she had responded too soon, too late, or at the correct time. Analysis of the 1800 absolute differences in milliseconds between real and estimated interval gave the following results. (1) During the pre-feedback phase, there was a moderate negative relationship between accuracy of time estimation and duration of interval estimated. (2) Accuracy of estimation improved on the trial following the first feedback trial, but little further improvement during the feedback phase was noted. (3) Amount of improvement in accuracy of estimation with feedback had a moderate negative relationship to duration of interval estimated. (4) Accuracy of estimation declined rather rapidly during the post-feedback phase. Some implications of these findings and suggestions for further research are presented.

Reaction Times to Regularly Recurring Visual Stimuli

In this experiment, which was concerned with reaction times to regularly recurring visual stimuli, four experienced Ss made 21 serial responses at eight interstimulus intervals with eight replications each. The experiment was designed to provide answers to the following questions. With regularly recurring visual stimuli, (a) what is the relationship between foreperiod length and mean reaction time to light at the asymptote of the reaction time practice curve, and (b) what are the differences, for various foreperiod lengths, in the effects of practice on mean reaction time to light? The predicted answers to both questions (a) and (b) were confirmed. First, the relationship between interstimulus time interval and reaction time to regularly recurring visual stimuli is best depicted as an increasing function which reaches an asymptote at a different time interval for each S. In addition, practice results in a greater decrease in reaction time for the 1- and 2-sec. interstimulus intervals, and especially for the former, than for longer intervals; this effect is most pronounced after one experience with the given interstimulus interval.

Reaction Time and the Expectancy Hypothesis

The measurement and meaning of the term expectancy and equivalent concepts as used in areas such as learning and vigilance are discussed briefly, and some experiments designed to measure the temporal course of expectancy are reviewed. A visual reaction time experiment is reported in which the effects of 1, 2, 3, or 4 recurrences of 2-, 3-, 4-, or 5-sec. “training” intervals on reaction time to a single “test” stimulus appearing 2, 3, 4, or 5 sec. after the last training stimulus were investigated. The results showed an insignificant effect of number of training intervals, but both the training and test interval effects and the interaction between the two were statistically significant. The general features of the curves plotted from the 16 training × test interval reaction time means illustrate that, under the conditions employed in the present experiment, mean reaction time is minimum when the training and test intervals are equal and increases as the absolute difference in duration of training and test intervals increases. Since expectancy in this investigation was operationally defined as the reciprocal of reaction time, the results obtained here are consistent with those of several previous investigations of the temporal course of expectancy.

Interstimulus and inter-response time variables in reaction times to regularly recurring visual stimuli

As an addendum to a previous study, it is demonstrated that having Ss react to either every fourth, every second, or every stimulus in a series of regularly recurring flashes of light results in three nearly identical positive linear relationships between reaction time and interstimulus time interval. This similarity of functions is interpreted as being due to covert reacting by S to the stimulus flashes to which no overt reaction is required. As a consequence of such covert responding, readiness to react becomes synchronized with the interstimulus time interval and does not vary appreciably with the inter-response time interval.

Interdepartmental Variability and Student Expectations of College Grades

areas (Bass, 1951; Morris, 1953), and even among instructors and departments combined across years (Webb, 1959; Aiken, 1963). There are many possible reasons for such variations and changes in grading. Morris (1953) discussed nine suggested causes for differences in grading practices among college departments or schools, but only the factor of class standing of students (lower versus upper division) was studied empirically. This factor was found to have a significant effect upon the grading practices of several schools and departments, viz., higher average grades being assigned to upper division students.

Some Nomographs for Academic Prediction Work

DURING the past few years, the demand for greater precision in academic prediction has resulted in more extensive use of multiple regression procedures by college admissions officers and registrars. After the appropriate equation is determined, however, there are a number of tasks which confront the user of these procedures. One of these is the necessity of computing a predicted score for each applicant. This need not be disconcerting if a digital computer is available and if decisions concerning all applicants are made simultaneously. The difficulty arises when only a desk calculator, or less, is available and/or decisions concerning a large number of applicants are made at different time periods, e.g., applications are acted upon as they are received. In these cases, the number of &dquo;on-

College Dropouts and Difference Scores

It is shown that not only will the usual predictors of college grades such as the Scholastic Aptitude Tests-Verbal and Mathematical (SAT-V & SAT-M) and rank in high school graduating class (HSR) differentiate significantly between college dropouts and non-dropouts but that scores obtained by converting SAT-V, SAT-M, and HSR to normalized T scores and computing the differences between HSR and the other two variables will also distinguish dropouts from non-dropouts. It is felt that such difference scores may be useful indicators of academic achievement motivation.

A Program for Constructing and Scoring Several Types of Ratings Scales and Checklists

This article describes a set of 11 menu-driven procedures, written in BASICA for MS-DOS-based microcomputers, for constructing several types of rating scales, attitude scales, and checklists, as well as for scoring responses to the constructed instruments. The program can facilitate the construction and scoring of bipolar, forced-choice, graphic, numerical, semantic differential, and standard rating scales, as well as Likert-type attitude scales, questionnaires for comparing and ranking persons, and checklists of behaviors and characteristics.

Sixteen Computer Programs for Selecting, Assigning, and Evaluating Samples

This article describes a set of 16 menu-driven programs, written in BASICA for DOS-based microcomputers, for selecting, assigning, and evaluating samples in survey, correlational, or experimental research. Programs for selecting simple random, stratified random, and cluster samples are described. Procedures for matching samples, testing for independence, and estimating confidence intervals and power for procedures involving proportions and means are included. The problems of sample size, nonresponse or missing values, and order effects are also considered.