Bennett Mechanical Comprehension Test® – II
The leading selection tool for industrial and repair jobs just got better!
Bennett Mechanical Comprehension Test – II is the successor to one of the most widely used and extensively validated assessments of mechanical aptitude. For more than 60 years, this instrument has helped organizations select the best candidates for mechanical, repair, and industrial occupations. It is also used to predict performance on mechanical skills training courses.
BMCT-II assesses individuals for their:
- Mechanical reasoning abilities
- Aptitude for learning mechanical processes and tasks
- Spatial Awareness and Visualization
- Application of basic mechanical and physical concepts
- Deduction of “how machinery works”
|At A Glance|
BMCT-II (2017) – Suitable for screening applicants in unsupervised or supervised testing scenarios. Highlights of the BMCT-II:
- 55 items help decrease administration time (25 minutes)
- Item-banked making it suitable for supervised and unsupervised testing scenarios. Questions are drawn from a large bank of items.
- Online version available in US and UK English, Spanish, Latin American Spanish, Dutch, French and French Canadian
- Paper version available in US English
- Items presented in color
BMCT- I (2006) the previous test version has been retired (effective January 2017) and is no longer available for purchase in the Pearson catalog. For the differences between BMCT-II and BMCT-I see the Frequently Asked Questions document
Hire With Confidence
Bennett Mechanical was developed in accordance with legal and professional guidelines embodied in the Uniform Guidelines for Employee Selection Procedures and the Principles for the Validation and Use of Personnel Selection Procedures.
Click below to download the 2016 Bennett Mechanical Comprehension Test® (BMCT) Case Study to see how BMCT scores can have a strong impact on both revenue and turnover rates in your organization.
An individual who scores well on BMCT demonstrates an aptitude for learning mechanical skills. The test is also shown to predict training performance (r = .52) and job performance (r = .31) across many jobs and industries.