Background
A Computerized Adaptive Test (CAT) dynamically adjusts item difficulty, selecting subsequent items based on prior performance. Compared with traditional paper-and-pencil tests, CATs are considerably more efficient, saving time and improving accuracy. Moreover, they provide a more engaging and less fatiguing testing experience, which is significant for Generations Z and Alpha, who often demonstrate lower tolerance for lengthy questionnaires. These characteristics have meaningful implications for assessing multidimensional career-related constructs measured through word-based instruments.
Purpose
To develop a systematic procedure and algorithm for Computerized Adaptive Questionnaires (CAQs) and empirically examine their feasibility using three multidimensional, career-related questionnaires:
1. The Career Decision-Making Difficulties Questionnaire (CDDQ; 10 dimensions and 32 items);
2. The Higher Education Orientation (HEO) questionnaire (5 dimensions and 25 items); and
3. The Work Orientation Questionnaire (WOQ) (5 dimensions and 25 items).
Method
We analysed data from three samples:
1,212 first-year university students who completed the HEO;
605 first-year students who completed the WOQ;
1,484 career-undecided individuals, who completed the CDDQ via the Making Better Career Decisions website.
For each questionnaire, we developed an adaptive algorithm that selected a subset of items for presentation, based on each participant's prior responses.


Results
The median (and interquartile range) of within-participant Pearson correlations between the original and adaptive scores across dimensions were .98 (.95-.99), .97 (.94-.99), and .98 (.97-.99), for the HEO, WOQ, and CDDQ, respectively. Dimension-level results will be provided during the presentation.




Items Retention Overview
Questionnaire Total items Items Removed Retained (%)
HEO 25 13.63 54.53
WOQ 25 12.85 51.42
CDDQ 32 5.83 18.21
Conclusion
Findings demonstrate that adaptive, shorter versions of multidimensional questionnaires are feasible. By improving efficiency and engagement, adaptive methodologies offer strong potential to enhance the quality and accessibility of multidimensional career assessment in both research and applied settings.