Vulnerable Decision Point 3: Collecting Additional Information

Table of Contents

Introduction

In addition to confirmation bias that may occur at the start and planning of an evaluation, during referral and the review of existing data, attribution bias may arise when implementing the evaluation plan. During the implementation step, IEP team participants should be mindful of attribution bias at this vulnerable decision point, especially once they begin gathering any additional data or other information about the student.. Attributions are the ways we explain human behavior. Attribution bias occurs when we take information and inappropriately use it to explain behavior (Turner & Hewstone 2010). Researchers have found that when participants of the same group (such as white educators and white students) are trying to explain each other’s behavior, they are more likely to explain negative performance as being the result of external factors; but the opposite occurs when you have participants of different groups assessing each other (Turner & Hewstone 2010).

For example, when white educators are trying to explain the behavior of Black students, they are more likely to attribute negative behaviors or performance (e.g., reading difficulties) to internal characteristics (e.g., low IQ), but when assessing this same performance for white students, they are more likely to attribute the performance to external characteristics (e.g., instruction).

Untrue, Unalterable, and Unfounded Attribution Bias

Attribution bias refers to when IEP team participants take some data and use it to inaccurately explain (interpret) the student’s behavior or performance. Attribution bias can take many forms, but three forms commonly observed on school teams are: untrue attributions, unfounded attributions, and unalterable attributions.

Untrue Attributions
 

Untrue attributions are made when IEP team participants take information that is not accurate and use it to explain the student’s performance. For example, a school staff IEP team participant might note that the student lives in poverty and conclude that the student is exhibiting behavioral difficulties because of poverty. This is an untrue attribution because there is no evidence that indicates living in poverty causes behavioral difficulties. Nevertheless, if the others on the team accepts this conclusion, then their selection of existing data as well as identification of new data to collect might be biased because the team could overly focus on collecting information related to the family’s living conditions and ignore important ecological factors in the classroom (e.g., classroom management, instruction, curriculum) that could be contributing or causing the behavior. Taken together, when teams accept untrue attributions they are more likely to ignore other important, relevant factors.

Unfounded Attributions
 

Unfounded attributions are made when team participants take information for which there is no evidence and use it to explain student performance. For example, upon review of the initial referral information for a student who is significantly underperforming in reading, a school staff IEP team participant might note that there might be something genetic going on with the student because they worked with the two older siblings who also received special education services. If the team accepts this attribution, then the team might only seek out data to analyze within-child deficit factors to explain the performance and ignore collecting data on factors in the learning ecology (e.g., curriculum, instruction, tasks). Another example of an unfounded attribution is when school staff who is also a participant of the IEP team says outside of the IEP meeting that the parent or guardian “does not care about the child’s education” and this lack of care is “contributing to the student’s difficulties.” When there is no data gathered or evidence to indicate a statement is true, then this is an unfounded attribution.

Unalterable Attributions
 

Unalterable attributions are made when IEP team participants take information that educators cannot change and use it to explain performance. For example, upon review of an initial special education referral for a student who is exhibiting behavioral difficulties, a school staff IEP team participant notes that one of the student’s parents is incarcerated. This is a factor that cannot be changed. If IEP team participants accept this attribution, then the team might feel powerless to improve the student’s behavior because they cannot change the parent’s incarceration. The result might be that the team has reduced effort in seeking out the information to identify a student’s disability-related needs to support college and career ready services that can improve the student’s performance.

Even more common is the belief that because a student lives in poverty, school personnel cannot do anything to improve the student’s performance, due to the belief that poverty is the reason for the student’s difficulties. The student may live in poverty and school personnel cannot change that fact, but it does not absolve educators of their responsibility to ensure the student is receiving a high-quality education. Another example is that a team may have a student who has been homeless and highly mobile, which has resulted in missed instruction. The team cannot change the fact that the student has been homeless and missed learning opportunities, but the team is still responsible for determining if the student is eligible to receive special education and how to best support the student.

In sum, the identification of potential areas of academic and functional need during the referral and review of existing data represents a vulnerable decision point when bias can be identified and addressed for special education evaluation teams. This decision point within the evaluation process can allow bias to manifest and lead to inaccurate decisions.

Two types of bias were discussed in relation to the review and collection of data:

1. confirmation bias and,
2. attribution bias.

As described in Vulnerable Decision Point 4: Interpreting Data and Information, confirmation bias can occur when IEP team participants review referral information and seek out data to confirm only the information presented in the referral. Attribution bias occurs when IEP team participants take pieces of information about the student and use it to over-explain or under-explain their performance, which can also influence the data teams review and collect. IEP team participants must be able to identify these forms of bias when they occur and interrupt them.

Strategy 1: Use ICEL Framework to Collect Multidimensional Data

To help teams collect data beyond the referring concern and based on the hypotheses, teams can use the ICEL framework (Christ & Arañas 2008) to structure the assessment process. As explained in the Guide for Problem-Solving Teams (Newell 2017), the ICEL framework is an approach designed to ensure teams are collecting multidimensional data, which means that teams are collecting data from multiple domains, sources, and settings as well as using multiple methods. ICEL domains include:

• Instruction (refers to how the teacher teaches the content)

• Curriculum (refers to the curriculum and tasks students complete)

• Environment (refers to the settings that can impact the student’s learning)

• Learner (refers to skills, characteristics and traits of the student)

By using this framework, IEP team participants can create a map to identify existing and any newly collected data in each of the domains as they relate to understanding the academic and functional needs of the student. For example, the team can ask the following educationally relevant guiding questions:

• What do we know about classroom instruction and how the student is responding to the instruction?
• What do we know about the curriculum and how the student is responding to the curriculum?
• What do we know about the learning environment and is it conducive to this student learning?
• What do we know about the student (e.g., academic skills, social and emotional needs, mental health) and how do these factors relate to learning?

To help structure each of these aforementioned questions, teams can use Margolis’ Instructionally Relevant Question (2018) framework as a guide. More specifically, the educationally-relevant questions can be mapped into these broad questions so that teams have more specific sub-questions within each domain that can ensure teams focus on the elements of the student’s environment that are most relevant to their learning. As can be seen, all of these questions focus on the learning ecology and how that ecology is meeting (or not meeting) the needs of the student. Special education is about adapting the learning ecology to meet the learner needs; not changing the student to meeting the needs of the learning ecology.

By answering these questions through existing and newly collected data, teams can clarify concerns, strengths, and needs that will help them design effective instruction, curriculum, and ecology the student needs to access, engage, and make progress in age or grade level general education curriculum, instruction, environments, and activities. It is important to remember that the purpose of special education is to create the learning ecologies that students need so they can access, engage and make progress in age and grade level instruction and, as a result, be college and career ready; answering these questions through data will help lead teams to identify and create those conditions.

Reflection and Application Activities

The following reflection and application activities were developed to build the knowledge, skills, and systems of adults so they can develop better systems for conducting comprehensive special education evaluations.

1. Think of students with differences in racial, ethnic, gender, socio-economic status, ability, disability label, or other factors but have similar difficulties in their educational program.

   • How may bias show up when thinking about the difficulties these students have in their education?

   • What assumptions are made? Is information used to over-explain or under-explain the student’s difficulties?

   • Are there assumptions that are unfounded, untrue, or unalterable?

2. What processes does the IEP team have to address untrue, unalterable, and unfounded attributions if they are made during a team meeting?

   • Discuss why it may be important to include protocols (e.g. IEP team meeting norms or agreements) and training for staff on how to address untrue, unfounded, and unalterable attributions in a direct and professional manner.

   • Think of an untrue, unalterable, or unfounded assumption you have heard about a student. How might you interrupt or redirect a comment about such an attribution in the future?

   • Develop sentence stems might help an IEP team participant redirect an untrue, unalterable, or unfounded statement? (e.g. “you mentioned students living in poverty have more behavioral problems, what evidence do you have to support that assumption).

3. Discuss the benefits the ICEL framework provides when implementing a special education evaluation.

   • What types of information does the ICEL framework help teams provide that may have been otherwise “missed”?

   • How might information gathering using the ICEL framework be useful in determining if a student is a student with a disability and requires specially designed instruction to access, engage, and make progress in age or grade level curriculum, instruction, activities, and environments?

   • How does utilizing the ICEL framework when conducting a special education evaluation assist the IEP team with meeting other required special education evaluation requirements?

   • How does using developmentally and educationally relevant questions and the ICEL framework help address potential attribution bias that may show up during a special education evaluation?