Acquisition vs. proficiency data: How using both positively affects student interventions and learning outcomes

The key to understanding student interventions and promoting positive student outcomes lies in understanding the whole child. That means diving deeper than data that only speaks to one aspect of the student’s experience.

Attempting to juxtapose acquisition data and proficiency data can lead educators astray, overlooking the most effective intervention for a particular student.

In this blog, I’ll explore students’ complete educational journey through the lens of acquisition and proficiency data. I’ll also explain how discerning educators can harness both sets of insights to identify the best intervention for a particular student.

What is the difference between acquisition vs. proficiency data?

Learning anything new involves a continuum of activities that includes:

1. Acquisition
2. Fluency
3. Generalization
4. Adaptation

Acquisition of new knowledge or skills is an educator-led process of organizing information and activities and then facilitating student engagement for the purpose of learning. In other words, acquisition is the introductory stage of learning, where the teacher’s expertise allows modeling for the student.

The second stage, fluency, is when the student practices in order to reach mastery.

Proficiency, however, requires two additional instructional stages—generalization and adaptation—that are often student-led. These stages involve using learning in new settings and contexts and document the student’s ability to apply learning to specific situations. 

Learning requires enough time engaged in each stage of the hierarchy for the student to become the expert.

Why are both acquisition and proficiency data important?

Acquisition and proficiency data are both used by schools to measure a student’s performance. Multiple data points are key to:

• Understanding the whole child
• Tracking skill progress
• Predicting future performance

Acquisition and proficiency data are important because each provides insight into students’ current level of competency and serves as a predictor of how students will perform in a variety of subjects in the future.

Assessing the student by acknowledging the bigger picture, as well as the individual parts that contribute to the learning curve, allows educators who use a multi-tiered system of support (MTSS) to best determine what will be the most effective intervention.

Using acquisition data for student intervention

From the moment a student first encounters a learning objective, acquisition of that skill begins. Thus, data should track the student’s progress as they move through deliberate skills practice to reach proficiency.

Acquisition data typically include information about the student’s accuracy and automaticity with the target skill. Acquisition data are individualized and based on the student’s unique ability to acquire the knowledge or skill and will also indicate where the student may be struggling.

Gathering acquisition data

Information regarding a student’s level of knowledge and skill acquisition can be determined by more than just nominal data. Acquisition data can be gathered for many different subjects and will reflect the accuracy of the student in the particular skill being tested.

For example: For students who score low on a classroom or state reading assessment, a curriculum-based measure (CBM) can be administered to assess the rate at which the student reads, as well as how accurate the student is when reading.

Importance of acquisition data

Key indicators in acquisition data can inform the educator if a student needs support in acquiring a new skill. The choice of which type of intervention and tier to use is usually based on how far behind the student is, and the resources necessary to help the student catch up.

Students who are near a grade-level goal can often be supported in Tier 1. Those who are farther behind will likely need the combination of Tier 1 and Tier 2 or 3. Importantly, Tier 1 core instruction must be the foundation for all students, with Tiers 2 or 3 added for those whose data indicate larger and more significant deficits.

Acquisition data can help educators identify what type of intervention and level of intensity is needed to support a student.

How are acquisition data used?

Each student has different needs, and some will need more one-on-one instruction than others. When a student’s acquisition data reflects low performance with many errors, that insight helps the educator to understand which intervention might best meet the student’s needs.

Determining if an acquisition intervention is necessary ensures the educator can quickly and easily understand the student’s needs and respond appropriately with extended instruction.

Let’s return to our example of acquisition data obtained from a CBM reading assessment. We might ask ourselves: Does the student’s acquisition data reflect slow reading with many errors? A slow reading rate coupled with low accuracy scores indicates the student has not yet acquired the target skills. Therefore, an acquisition intervention will be the most effective for that student.

When selecting an acquisition intervention, it is important to determine whether the focus needs to be on accuracy or automaticity. Importantly, accuracy must always come before automaticity. A student needs to be 95% accurate with the target skill before moving on to improving automaticity.

Once a student reaches 95% or better accuracy, an automaticity intervention is best. There are many progress measures and norms that educators can use to monitor students’ accuracy and automaticity to reach acquisition.

Using proficiency data for student intervention

Proficiency data reflect the student’s current level of skill or mastery in a subject. For example, proficiency can be identified by comparing a student’s current reading level to grade-level expectations. Proficiency data will influence the educator’s assessment of the student’s competency level, as well as the tier and type of intervention most likely to improve student outcomes.

Gathering proficiency data

Proficiency data are typically composed of student scores from a range of tasks representing grade-level skills. Computer-adaptive tests (CATs) are widely used proficiency assessments because they adapt the items each student completes in relation to their performance on prior items. In this way, CAT scores reflect the student’s current skills and level of proficiency.

Proficiency data can be gathered through a variety of assessments in different subjects where application of basic skills can be measured, including:

• Math
• Reading
• Language
• And more

Importance of proficiency data

Proficiency data are important because they can inform:

• Instruction
• Assessment
• Intervention

Proficiency data provide a deeper look into the student’s comprehension of the curriculum because they measure:

1. If the student can grasp the skill; and
2. The student’s level of command of the skill

How are proficiency data used?

Proficiency data are used to determine if the student can apply the learned skill or if a proficiency intervention is needed.

Proficiency data document whether the student recognizes what knowledge or skill is required for a specific question, and the depth of their understanding in a variety of learning domains. In relation to the instructional hierarchy, proficiency includes generalization and adaptation, which are the indicators of mastery, as mentioned earlier.

Acquisition vs. proficiency interventions: How do they affect student outcomes?

To sum up, acquisition interventions are intended to help students learn new material more easily. In contrast, proficiency interventions focus on helping students improve their application of material they’ve already learned. Let’s explore each point.

#1: Helping students to acquire learning objectives

Acquisition interventions are designed to improve a student’s basic skills and understanding of a subject, and to increase accuracy and automaticity. These interventions may include:

• Direct instruction with student practice
• Immediate feedback
• A progression of learning that leads to specific skills

Educators implement acquisition interventions with the goal of teaching the basic knowledge and skills from the beginning, and with ample opportunities for the student to practice.

#2: Helping students to master learning objectives

Proficiency interventions are designed to increase a student’s ability to recall a learned skill and to apply it with ease, elevating their competency in the subject. Some examples of proficiency interventions might include:

• Problem-solving
• Applying skills in new situations
• Adapting skills to meet new needs

With proficiency interventions, the educator aims to elevate the student’s mastery of the material, such that the student can use the knowledge and skills across any and all new situations.

Implement effective interventions with Renaissance

With MTSS collaboration and management tools from Renaissance, you can enter both academic and social-emotional behavior (SEB) interventions, allowing you to track…

• Fidelity
• Participation
• Engagement

…as well as monitor on-track status, in real-time.

Whether you need to complement your current system with real-time dashboards or comprehensive assessments, Renaissance can help your educators respond effectively and efficiently using in-depth acquisition and proficiency data.