The Pace approach to teaching with TABE is a focus on the specific skills that are measured in each individual learner, as opposed to a focus on “levels of mastery” demonstrated by specific test levels, Scale Score ranges, or Scale Score improvements. An individualized approach and a focus on specific skills, especially when communicating progress with the learner, provides the best results.

The TABE Test Translation provides a wealth of additional information on TABE test 11/12 content, beyond what is provided by TABE diagnostic reports, including:

  • Connections between TABE Skills and CCR Anchor Standards
  • Identification of TABE Skills tested on each test item (Levels E, M, and D)
  • Alternative descriptions for each TABE Skill and test item, describing the skill performed in plain terms

Use this resource to see emphasis of sub-skills on a particular test and level, to compare sub-skills tested on Form 11 and Form 12, and even to help build a more accurate, efficient study schedule from a given TABE Diagnostic result.

Register free as a Pace Online Community Member, and gain access to this resource and other member benefits.

If you are an existing user, sign in and access the Test Translation here:

Pace has designed learning systems with TABE at their core since the beginning days of the TABE assessments. In fact, the original Pace Learning System was designed with TABE Forms 1&2 as its diagnostic tool. With each new generation of TABE assessments, since the 1960’s, Pace systems have evolved to meet new TABE targets. If you are testing with TABE, you should be teaching with Pace. 

Pace offers truly self-paced tutorials designed specifically for the TABE test taker. Pace lessons target discrete skills which are highly-referenced on the TABE tests, to provide an efficient, easy-to-use method of remediation for ABE programs.

To learn more about TABE-correlated Pace curricula, go here.

PACE/TABE 11/12 Correlation (PDF)

PACE/TABE 9/10 Correlation (PDF)

The TABE® name and TABE materials are Copyright 2019 by Data Recognition Corporation (DRC).