Helping Students Use Their Own Data and Set Learning Goals

Recommendation 2: Students as Participants in Data Use

Recommendation 2 shifts the focus of data use from educators analyzing student performance to students learning how to participate in that process. The guide recommends explicit instruction in using achievement information to monitor performance and establish learning goals.

This recommendation treats students as active participants rather than passive recipients of scores. The same basic logic used by teachers—clarify the target, examine evidence, identify a need, set a goal, take action, and review new evidence—can be taught to students in developmentally appropriate ways.

The Four Action Steps

Evidence Calibration: Recommendation 2 Is Rated Low Evidence

The guide rates Recommendation 2 as supported by a low level of evidence. The panel identified two randomized experiments that met WWC standards, one with reservations, alongside other noncausal and descriptive studies. Some studies reported statistically significant achievement gains when students used assessment information and feedback, but the overall research base was not strong or broad enough for a higher evidence rating.

This is an important professional distinction. The recommendation is not presented as unsupported opinion, but neither should it be described as conclusively proven across populations, grades, subjects, and implementation conditions.

Students Need Clear Expectations Before They Can Interpret Data

A score is difficult to interpret when the learner does not understand what successful performance was supposed to look like. For this reason, the first action step is to make learning expectations and assessment criteria explicit.

The guide uses rubrics as one way to communicate quality. A rubric can break a complex product into dimensions and describe performance across levels. When students understand the criteria in advance, later feedback becomes more interpretable because the learner can connect comments or scores to specific aspects of the task.

This also reduces the risk that students interpret a grade as a global judgment about ability. Instead of receiving “72%” as an undifferentiated message, the student can see, for example, that organization was strong while use of evidence and conventions require additional work.

What Makes Feedback Useful?

The guide describes several characteristics of feedback that help students learn from assessment information. Feedback should not merely communicate evaluation; it should help the student identify what to do next.

Feedback Should Describe Performance, Not Define the Student

One of the guide's explicit roadblocks is that students may view feedback as a reflection of fixed ability rather than an opportunity for focused improvement. The suggested response is to make feedback explanatory and to give students opportunities to improve.

Teachers should emphasize performance on the task in relation to learning goals and avoid broad statements about a student's ability. This distinction matters psychologically because feedback such as “You are bad at writing” collapses a specific performance problem into an identity judgment. In contrast, “Your introduction states the topic but does not yet include a clear central argument” identifies something concrete that can be changed.

Tools Help Students Learn From Feedback

The guide recommends giving students structured tools that help them analyze performance over time. Examples include teacher-generated graphs that track progress and grids in which students record baseline and interim scores on specific dimensions.

These tools externalize patterns that may otherwise be difficult for students to detect. A graph can show steady growth even when the student remains below benchmark. A rubric grid can show that one writing dimension has improved while another remains weak. An error-analysis form can help a student identify recurring mistakes across assignments.

Goal Setting Should Follow Analysis

The guide's examples emphasize having students identify strengths and weaknesses before selecting improvement goals. This sequencing matters. Goals should emerge from evidence rather than from a generic request to “do better.”

A useful goal identifies a specific area for improvement, establishes a realistic target, and is connected to actions that the learner can take. The goal should also be monitored so that the student can determine whether the strategy is working.

Students Can Analyze Item-Level Performance

The guide describes students reviewing individual test items, identifying correct answers, reconstructing solution steps, recording why an item was missed, and deciding whether a concept needs additional review. This moves the student beyond a total score toward an analysis of the knowledge or process that produced the score.

Item-level analysis is particularly useful when several errors arise for different reasons. A mathematics student may miss one item because of order of operations, another because of dividing by a fraction, and another because of misunderstanding square roots. Treating all three errors as “math weakness” loses the instructional information embedded in the response pattern.

Use Student Goals to Inform Instruction

Recommendation 2 is not only about student motivation or self-reflection. The fourth action step asks teachers to use student analyses to guide instructional changes.

The guide suggests that teachers can organize small-group instruction around subsets of goals students identify for themselves. Teachers can also tally concepts that multiple students identify as weaknesses and use that information to plan whole-class review.

This creates a reciprocal relationship between student self-analysis and teacher decision making. Students learn to identify needs, while teachers gain another source of information about which skills may require additional instruction.

Roadblock: Students May See Feedback as Ability Judgment

If students interpret feedback as proof that they are “smart,” “bad at math,” or “not a writer,” data use can become discouraging rather than productive. The guide recommends explanatory feedback and opportunities to improve, combined with goal setting that focuses attention on the gap between current performance and a reachable target.

For psychologists, this is a useful consultation point. The emotional meaning of feedback can affect whether students engage with it. A technically accurate score can still be instructionally ineffective if the learner experiences it only as a fixed judgment.

Roadblock: Student Data Analysis Takes Time

The guide recognizes that class time is limited. Its suggested approach is not to treat student analysis as an optional add-on, but to integrate understanding assessment tools and feedback into routine instruction.

This matters because students cannot become independent users of data if they only encounter graphs, rubrics, and goal sheets during isolated special activities. Repeated practice helps data interpretation become part of how students approach learning.

The Extended Example: All Four Action Steps Working Together

The guide's extended example illustrates how the four action steps can be integrated. Students first need clear criteria for successful work. They then receive feedback tied to those criteria, use structured tools to identify strengths and weaknesses, and set goals based on their analyses. The teacher then uses the resulting student information to make instructional decisions.

The strength of this sequence is coherence. Expectations, feedback, student analysis, goal setting, and teacher response all refer to the same learning targets. When these components are disconnected, students may complete goal sheets without understanding the criteria, receive comments that do not match the goals, or track numbers that do not influence instruction.

What the Appendix D Reading Adds

Appendix D provides technical information about studies cited for Recommendation 2. The panel identified two randomized experiments that met WWC standards, one with reservations, along with additional studies that informed implementation examples.

The appendix is important because it separates an appealing instructional model from the strength of evidence supporting it. Some studies reported positive achievement effects when students used curriculum-based measurement, peer tutoring, feedback, or related student data practices. However, the overall evidence base was limited in size, population, and design.

Implications for School Psychologists

Psychologists can support student data use at several levels: helping teams clarify learning targets, designing understandable progress displays, improving feedback language, teaching students to analyze patterns, and ensuring goals are specific enough to guide action.

Psychologists can also help teams distinguish productive self-monitoring from simple score surveillance. The purpose is not to make students responsible for fixing every learning problem. Adults remain responsible for providing effective instruction and appropriate supports. Student data use should add agency and clarity, not shift responsibility away from instruction.