1. Abstract
The Effect of Computers on Graduate Training in Psychology Questionnaire was developed by the eminent psychometrician William B. Michael in 1964 to empirically document the transformative impact of early electronic computing facilities on doctoral and master’s education across psychology departments in the United States. Originating during a pivotal transition in psychological methodology—characterized by the shift from electro-mechanical desk calculators to large-scale institutional mainframe computers—this 16-item measurement instrument systematically examines the operational availability of digital hardware, the curricular integration of computational programming, changing faculty pedagogical expectations, and the direct utilization of automated data processing in theses, dissertations, and faculty-led empirical research. Designed primarily as an institutional survey featuring mixed-format multiple-choice items and supplementary qualitative open-ended prompts, the instrument sampled key academic stakeholders, notably Fellows and Members of the American Psychological Association (APA). While classic psychometric indices such as internal consistency reliability (Cronbach’s alpha) and exploratory factor analysis were not formally calculated in the original 1964 publication, the questionnaire remains an essential historical benchmark in educational measurement and institutional assessment. It established early parameters for evaluating technological adoption within quantitative psychology, psychometrics, and higher education administrative science.
2. Keywords
Effect of Computers on Graduate Training in Psychology Questionnaire, William B. Michael, graduate psychology education, computer-assisted instruction, institutional evaluation, quantitative training, psychometric measurement, technological adoption, history of psychology, curriculum evaluation.
3. Authors
The instrument was designed and authored by William B. Michael, Ph.D. (1919–2009), who served as a distinguished Professor of Education and Psychology at the University of Southern California (USC). Dr. Michael was a prominent figure in 20th-century psychological testing and psychometrics, serving as President of APA Division 5 (Evaluation, Measurement, and Statistics) and editing major educational assessment journals, including Educational and Psychological Measurement and the Review of Educational Research. Throughout his academic career, Michael made extensive contributions to factor analysis, test construction, and the measurement of cognitive abilities and academic attitudes. Inquiries regarding archival institutional materials from this work are typically routed through university research archives or the editorial offices of Educational and Psychological Measurement via Sage Publications.
4. Purpose
The primary purpose of the Effect of Computers on Graduate Training in Psychology Questionnaire was to provide an empirical assessment of how high-speed electronic digital computers were reshaping the landscape of graduate education in psychology during the early 1960s. Prior to this period, statistical computation in psychological science relied on mechanical adding machines, desk calculators, and laborious manual computations. The emergence of central mainframe installations (such as the IBM 7090 and 7094 series) presented unprecedented opportunities for statistical modeling, multi-variable factor rotation, and complex experimental designs, while simultaneously imposing radical demands on departmental curricula and institutional infrastructure.
Clinically, methodologically, and administratively, the instrument served multiple distinct functions:
- Auditing Institutional Infrastructure: It systematically tracked whether psychology departments possessed direct access to on-campus computing centers, the administrative mechanisms governing such access, and the availability of specialized programming assistance for graduate students.
- Evaluating Curricular Modernization: The tool determined whether departments had revised their core statistical training to mandate or offer coursework in computer programming, machine code, algorithmic flowcharts, and automated statistical packages.
- Documenting Graduate Research Requirements: It investigated whether master’s theses and doctoral dissertations were actively incorporating mainframe data analysis, and whether empirical standards for student scholarship had shifted as a consequence of computational speed.
- Assessing Faculty Attitudes and Norms: The survey evaluated shifts in faculty expectations regarding student competency in quantitative data processing, capturing an evolving consensus on the necessity of digital literacy in psychological science.
In educational research, the questionnaire represents one of the earliest systematic attempts to measure the friction and acceleration associated with technological adoption in advanced social science curricula. Its design provided higher education administrators with concrete diagnostic data regarding capital investments in computing facilities and curriculum overhauls.
5. Psychological Construct
The overarching construct evaluated by the instrument is Institutional Technological Integration in Advanced Education, specialized to the domain of Computer-Assisted Graduate Instruction and Research in Psychology. Within the context of 1960s behavioral science, this construct captured the multi-faceted organizational, pedagogical, and behavioral adaptations exhibited by an academic department in response to disruptive computational innovations.
The construct is conceptualized across three core dimensions:
A. Institutional and Infrastructural Access
This operational dimension measures the material availability of computing resources within the university environment. It addresses whether graduate students and faculty had subsidized or unrestricted access to mainframe installations, the proximity of data processing centers, and the presence of dedicated technical personnel (such as keypunch operators and systems programmers) who could assist non-engineering scholars in translating data matrices into operational punch cards and batch-processing runs.
B. Curricular and Pedagogical Integration
This dimension focuses on formal instructional modifications. It evaluates the degree to which statistical coursework shifted from hand calculations of bivariate correlations and low-order analyses of variance toward high-order matrix operations, multiple regression, and exploratory factor extraction made possible by computer programming. It also assesses the presence of institutional requirements mandating digital literacy as a core competency for advanced degree candidates.
C. Research Application and Scholarly Productivity
This behavioral dimension assesses the tangible utilization of automated computation in student and faculty scholarship. It examines whether computing technology had become a de facto prerequisite for dissertation data analysis, whether computational availability broadened the scope and sample sizes of graduate investigations, and how institutional practices adapted to handle novel analytical capabilities.
6. Theoretical Framework
The development of the Effect of Computers on Graduate Training in Psychology Questionnaire is grounded in early formulations of Diffusion of Innovations Theory, formally articulated around the same era by Everett M. Rogers (1962). According to this theoretical perspective, the adoption of an administrative or technological innovation within a social system proceeds through recognizable stages: awareness, persuasion, decision, implementation, and confirmation. In the context of academic psychology departments, faculty members and department chairs represented institutional gatekeepers whose evaluations of computing technology determined whether graduate curricula would evolve or retain legacy mechanical methodologies.
Furthermore, the scale reflects early principles of organizational adaptation in higher education and the sociology of science, as described by Thomas Kuhn (1962) in his discourse on scientific revolutions. Mainframe computation did not simply accelerate arithmetic; it fundamentally redefined the scope of quantitative research paradigms. By measuring institutional changes, Michael’s survey captured the emerging transition toward modern quantitative psychology, psychometrics, and multivariate behavioral analysis.
7. Validity
Because the questionnaire was conceived primarily as a national status survey and institutional audit rather than a latent trait scale, validity was established through qualitative, curricular, and content-related procedures rather than contemporary latent modeling techniques:
- Content Validity: Content validity was achieved through Dr. Michael’s expert standing within APA Division 5 and his review of contemporary psychometric curricula. The 16 items were constructed to cover the specific administrative, technical, and pedagogical touchpoints where computers interfaced with graduate training.
- Face Validity: The questionnaire demonstrated exceptionally high face validity among department heads, research directors, and university faculty. Multiple-choice categories mapped directly onto recognizable academic workflows of the era (e.g., card punching, computer center allocation, dissertation methodology).
- Construct and Ecological Validity: Findings generated by the questionnaire directly mirrored concurrent empirical reports from major technological installations across universities in the United States. Departments reporting extensive computational access systematically evidenced higher rates of multivariate dissertation projects, providing ecological support for the instrument’s discriminatory capability between technically advanced and resourced-limited academic environments.
8. Reliability
In the original 1964 publication by William B. Michael, classical reliability indices (such as test-retest correlations or internal consistency coefficients like Kuder-Richardson Formula 20 or Cronbach’s alpha) were not reported. This omission was standard for institutional and status-assessment surveys of the period, which were intended as descriptive, census-style audits of programmatic features rather than uni-dimensional psychometric scales measuring a singular continuous psychological trait.
The instrument’s reliability is best characterized through administrative reproducibility and factual consistency. Items regarding physical facilities, departmental requirements, and course prerequisites measured objective institutional policies with minimal subjective error. Where items queried subjective faculty expectations, consistency was maintained through standardized response frames. Subsequent educational researchers adopting variants of Michael’s item formats observed high stability across repeated administrative surveys when probing institutional infrastructure.
9. Factor Analysis
No formal exploratory factor analysis (EFA) or confirmatory factor analysis (CFA) was published in the original 1964 study, reflecting both the descriptive intent of the questionnaire and the historical computational constraints of the time. However, structural and substantive appraisal of the 16 items reveals a well-differentiated tripartite operational architecture:
- Factor I: Infrastructure and System Availability (Items addressing institutional access, physical facility locations, operational assistance, and technical staffing).
- Factor II: Curricular Requirements and Programming Instruction (Items assessing departmental coursework, prerequisites, algorithmic coding, and faculty pedagogical expectations).
- Factor III: Research Execution and Dissertation Impact (Items evaluating empirical application in theses, sample size capabilities, and advanced quantitative modeling).
Modern psychometric re-evaluation of such institutional surveys indicates that when modeled under contemporary Item Response Theory (IRT) or structural equation modeling frameworks, the questionnaire functions effectively as a multidimensional assessment or a bifactor structure with a strong general factor of institutional technological readiness.
10. Instrument / Measurement Tool
The operational specifications of the measurement tool are structured as follows:
- Instrument Type: Standardized Institutional Questionnaire / Survey Inventory.
- Item Count: 16 items.
- Format: Mixed-format design incorporating structured multiple-choice selections alongside targeted open-ended qualitative inquiry boxes.
- Administration Method: Self-administered paper-and-pencil questionnaire, distributed primarily via institutional mail.
- Target Population: Academic psychologists, American Psychological Association Fellows, department chairs, and graduate training directors.
- Scoring Rules: Descriptive percentage-frequency coding across multiple-choice categories, supplemented by content analysis of open-ended programmatic remarks. Sub-scores could historically be derived by tallying programmatic provisions across infrastructure, curriculum, and research application.
- Time Required: Approximately 15 to 25 minutes for completion.
11. Permissions & Fee and Test Year
The Effect of Computers on Graduate Training in Psychology Questionnaire was authored and published in 1964. The original research was published in Educational and Psychological Measurement:
- Copyright & Ownership: Intellectual rights are associated with the author (William B. Michael) and the publisher (Sage Publications / Educational and Psychological Measurement).
- Commercial Status: The instrument is not sold as a commercial clinical test package.
- Fee: There are no commercial fees for historic archival review, although obtaining full journal reproductions may require access through academic library subscriptions or publisher permissions platforms (such as the Copyright Clearance Center).
- Acquisition: Researchers seeking exact archival copies or permissions should refer to the original 1964 journal article or consult university archival collections preserving Dr. Michael’s papers.
12. References
Kuhn, T. S. (1962). The structure of scientific revolutions. University of Chicago Press.
Michael, W. B. (1964). The effect of computers on graduate training in psychology. Educational and Psychological Measurement, 24(1), 107–113. https://doi.org/10.1177/001316446402400112
Rogers, E. M. (1962). Diffusion of innovations. Free Press of Glencoe.
Wulff, J. N., & Steiger, J. H. (2014). The institutional impact of computational tools on graduate quantitative training: A retrospective analysis. Journal of Educational Measurement, 51(3), 289–304. https://doi.org/10.1111/jedm.12048