4 Assessment Delivery

Chapter 4 of the Dynamic Learning Maps^® (DLM^®) Alternate Assessment System 2021–2022 Technical Manual—Year-End Model (Dynamic Learning Maps Consortium, 2022) describes general test administration and monitoring procedures. This chapter describes updated procedures and data collected in 2024–2025, including a summary of adaptive delivery, administration incidents, accessibility support selections, test administration observations, and test administrator survey responses regarding user experience and opportunity to learn, including new longitudinal analyses of response trends over time.

Overall, intended administration features remained consistent with the 2023–2024 implementation, including the availability of instructionally embedded testlets, spring operational administration of testlets, the use of adaptive delivery during the spring window, and the availability of accessibility supports.

For a complete description of test administration for DLM assessments—including information on the Kite^® Suite used to assign and deliver assessments, testlet formats, accessibility features, the First Contact Survey used to recommend testlet linkage level, available administration resources and materials, and information on monitoring assessment administration—see the 2021–2022 Technical Manual—Year-End Model (Dynamic Learning Maps Consortium, 2022).

4.1 Overview of Key Features of the Year-End Assessment Model

As briefly described in Chapter 1, the DLM assessment system has two available models. This manual describes the Year-End assessment model. Consistent with the DLM Theory of Action described in Chapter 1, the DLM assessment administration features reflect multidimensional, nonlinear, and diverse ways that students learn and demonstrate their learning. Test administration procedures therefore use multiple sources of information to assign testlets, including student characteristics and prior performance.

In the Year-End model, the DLM system is designed to assess student learning at the end of the year. All testlets are administered in the spring assessment window; however, optional instructionally embedded testlets are available throughout the fall and winter. The instructionally embedded assessments, if administered, do not contribute to summative scoring. This assessment model yields summative results based only on testlets completed during the spring assessment window.

With the exception of English language arts (ELA) writing testlets, each testlet contains items measuring one Essential Element (EE) and one linkage level. In reading and mathematics, items in a testlet are aligned to nodes at one of five linkage levels for a single EE. Writing testlets measure multiple EEs and are delivered at one of two levels: emergent (which corresponds with Initial Precursor and Distal Precursor linkage levels) or conventional (which corresponds with Proximal Precursor, Target, and Successor linkage levels).

For a complete description of key administration features, including information on assessment delivery, the Kite Suite, the Instruction and Assessment Planner, and linkage level assignment, see Chapter 4 of the 2021–2022 Technical Manual—Year-End Model (Dynamic Learning Maps Consortium, 2022). Additional information about changes in administration can also be found in the Test Administration Manual (Dynamic Learning Maps Consortium, 2025d) and the Educator Portal User Guide (Dynamic Learning Maps Consortium, 2025c).

4.1.1 Assessment Administration Windows

Assessments are administered in the spring assessment window for operational reporting. Optional assessments are available during the instructionally embedded assessment window for educators to administer for formative information.

4.1.1.1 Instructionally Embedded Assessment Window

During the instructionally embedded assessment window, testlets are optionally available for test administrators to assign to their students. When choosing to administer the optional testlets during the instructionally embedded assessment window, educators decide which EEs and linkage levels to assess for each student using the Instruction and Assessment Planner in Educator Portal. The assessment delivery system recommends a linkage level for each EE based on the educator’s responses to the student’s First Contact Survey, but educators can choose a different linkage level based on their own professional judgment. In 2024–2025, the instructionally embedded assessment window occurred between September 9, 2024, and February 21, 2025. States were given the option of using the entire window or setting their own dates within the larger window. Across all states, the instructionally embedded assessment window ranged from 15 to 24 weeks.

4.1.1.2 Spring Assessment Window

During the spring assessment window, students are assessed on all of the EEs on the assessment blueprint in ELA and mathematics. The linkage level for each EE is determined by the system. In 2024–2025, the spring assessment window occurred between March 10, 2025, and June 6, 2025. States were given the option of using the entire window or setting their own dates within the larger window. Across all states, the spring assessment window ranged from 3 to 13 weeks.

4.2 Evidence From the DLM System

This section describes evidence collected by the DLM system during the 2024–2025 operational administration of the DLM alternate assessment. The categories of evidence include adaptive delivery, administration incidents, accessibility support selections, and participation by nonsymbolic communicators.

4.2.1 Adaptive Delivery

The ELA and mathematics assessments are adaptive between testlets. In spring 2025, the same routing rules were applied as in prior years. That is, the linkage level associated with the next testlet a student received was based on the student’s performance on the most recently administered testlet, with the specific goal of maximizing the match of student knowledge and skill to the appropriate linkage level content.

• The system adapted up one linkage level if the student responded correctly to at least 80% of the items measuring the previously tested EE. If the previous testlet was at the highest linkage level (i.e., Successor), the student remained at that level.
• The system adapted down one linkage level if the student responded correctly to less than 35% of the items measuring the previously tested EE. If the previous testlet was at the lowest linkage level (i.e., Initial Precursor), the student remained at that level.
• Testlets remained at the same linkage level if the student responded correctly to between 35% and 80% of the items on the previously tested EE.

The linkage level of the first testlet assigned to a student was based on First Contact Survey responses.⁷ See Chapter 4 of the 2021–2022 Technical Manual—Year-End Model (Dynamic Learning Maps Consortium, 2022) for more details. Table 4.1 shows the correspondence between the First Contact complexity bands and first assigned linkage levels.

Table 4.1: Correspondence of Complexity Bands and Linkage Levels

First Contact complexity band	Linkage level
Foundational	Initial Precursor
Band 1	Distal Precursor
Band 2	Proximal Precursor
Band 3	Target

Following the spring 2025 administration, analyses were conducted to determine the mean percentage of testlets that were adapted by the system from the first to second testlet administered for students within a grade, subject, and complexity band. Table 4.2 and Table 4.3 show the aggregated results for ELA and mathematics, respectively.

For the majority of students across all grades assigned to the Foundational Complexity Band by the First Contact Survey, the system did not adapt testlets to a higher linkage level after the first assigned testlet (ranging from 57% to 85% across both subjects). Consistent patterns were not as apparent for students who were assigned to Band 1, Band 2, or Band 3. Adaptation distributions across the three categories (adapted up, did not adapt, adapted down) were more variable across grades and subjects. Results indicate that linkage levels of students assigned to higher complexity bands are more variable with respect to the direction in which students move between the first and second testlets. However, this finding is consistent with prior years. Several factors may help explain these results, including more variability in student characteristics within this group of students assigned to higher complexity bands and content-based differences across grades and subjects. Further exploration is needed in this area.

Table 4.2: Adaptation of Linkage Levels Between First and Second English Language Arts Testlets (N = 89,424)

	Foundational		Band 1			Band 2			Band 3
Grade	Adapted up (%)	Did not adapt (%)	Adapted up (%)	Did not adapt (%)	Adapted down (%)	Adapted up (%)	Did not adapt (%)	Adapted down (%)	Adapted up (%)	Did not adapt (%)	Adapted down (%)
Grade 3	18.2	81.8	61.0	23.6	15.4	69.7	19.6	10.7	84.4	12.9	2.7
Grade 4	28.6	71.4	16.3	30.3	53.5	54.7	29.6	15.7	37.5	20.6	42.0
Grade 5	28.5	71.5	21.9	33.3	44.8	62.7	31.1	6.2	87.1	8.9	4.0
Grade 6	33.9	66.1	15.9	37.2	46.9	22.5	37.8	39.8	42.4	37.2	20.4
Grade 7	41.8	58.2	26.2	26.6	47.2	46.6	35.4	18.0	62.1	30.5	7.4
Grade 8	43.3	56.7	35.8	40.8	23.4	64.1	25.5	10.4	80.2	14.4	5.5
Grade 9	18.0	82.0	28.5	35.6	35.9	17.4	30.9	51.7	59.7	23.9	16.5
Grade 10	15.0	85.0	27.8	37.0	35.2	13.9	31.5	54.6	57.1	26.6	16.2
Grade 11	27.0	73.0	10.9	44.5	44.6	55.4	27.3	17.3	56.6	25.7	17.6
Grade 12	*	*	*	*	*	*	*	*	56.9	31.4	11.8
Note. Foundational is the lowest complexity band, so the system could not adapt testlets down a linkage level.
* These data were suppressed because n < 50.

Table 4.3: Adaptation of Linkage Levels Between First and Second Mathematics Testlets (N = 89,309)

	Foundational		Band 1			Band 2			Band 3
Grade	Adapted up (%)	Did not adapt (%)	Adapted up (%)	Did not adapt (%)	Adapted down (%)	Adapted up (%)	Did not adapt (%)	Adapted down (%)	Adapted up (%)	Did not adapt (%)	Adapted down (%)
Grade 3	19.9	80.1	31.6	48.9	19.6	20.5	53.8	25.6	60.7	18.9	20.5
Grade 4	25.3	74.7	33.9	46.5	19.6	67.2	23.9	9.0	73.1	20.4	6.5
Grade 5	24.8	75.2	18.7	39.5	41.8	41.8	25.7	32.5	74.5	13.0	12.5
Grade 6	20.4	79.6	16.3	43.2	40.5	29.4	35.5	35.1	43.4	48.1	8.5
Grade 7	31.1	68.9	21.3	38.0	40.7	20.7	21.1	58.2	75.3	17.3	7.4
Grade 8	18.2	81.8	17.6	47.7	34.7	30.3	53.8	16.0	46.3	24.9	28.8
Grade 9	34.8	65.2	20.8	51.4	27.8	55.1	36.9	8.0	55.8	36.5	7.8
Grade 10	38.3	61.7	31.6	25.9	42.5	33.5	19.2	47.3	7.3	14.5	78.2
Grade 11	29.3	70.7	30.2	44.2	25.6	28.6	42.0	29.3	13.8	14.2	72.0
Grade 12	*	*	38.8	41.8	19.4	*	*	*	*	*	*
Note. Foundational is the lowest complexity band, so the system could not adapt testlets down a linkage level.
* These data were suppressed because n < 50.

After the second testlet is administered, the system continues to adapt testlets based on the same routing rules. Table 4.4 shows the total number and percentage of testlets that were assigned at each linkage level during the spring assessment window. Because writing testlets are not assigned at a specific linkage level, those testlets are not included in Table 4.4. In ELA, testlets were fairly evenly distributed across the five linkage levels, with slightly fewer assignments at the Target linkage level. In mathematics, there were slightly more assignments at the Initial Precursor linkage level and fewer assignments at the Target and Successor levels.

Table 4.4: Distribution of Linkage Levels Assigned for Assessment

Linkage level	n	%
English language arts
Initial Precursor	194,968	27.6
Distal Precursor	147,473	20.9
Proximal Precursor	128,694	18.2
Target	99,493	14.1
Successor	134,993	19.1
Mathematics
Initial Precursor	223,554	34.0
Distal Precursor	176,812	26.9
Proximal Precursor	129,783	19.7
Target	71,740	10.9
Successor	56,211	8.5

4.2.2 Administration Incidents

DLM staff annually evaluate testlet assignment to promote correct assignment of testlets to students. Administration incidents that have the potential to affect scoring are reported to state education agencies in a supplemental Incident File. No incidents were observed during the 2024–2025 operational assessment windows. Assignment of testlets will continue to be monitored in subsequent years to track any potential incidents and report them to state education agencies.

4.2.3 Accessibility Support Selections

Accessibility supports provided in 2024–2025 were the same as those available in previous years. The DLM Accessibility Manual (Dynamic Learning Maps Consortium, 2025b) distinguishes accessibility supports that are provided in Kite Student Portal via the Personal Needs and Preferences Profile, those that require additional tools or materials, and those that are provided by the test administrator outside the system. Table 4.5 shows selection rates for the three categories of accessibility supports. Multiple supports can be selected for each student. Overall, 89,572 students enrolled in the DLM system (93%) had at least one support selected. The most selected supports in 2024–2025 were human read aloud, test administrator enters responses for student, and spoken audio. For a complete description of the available accessibility supports, see Chapter 4 of the 2021–2022 Technical Manual—Year-End Model (Dynamic Learning Maps Consortium, 2022).

Table 4.5: Accessibility Supports Selected for Students (N = 89,572)

Support	n	%
Supports provided in Kite Student Portal
Spoken audio	58,373	60.5
Magnification	13,841	14.3
Color contrast	8,726	9.0
Overlay color	2,953	3.1
Invert color choice	2,035	2.1
Supports requiring additional tools/materials
Individualized manipulatives	45,695	47.3
Calculator	28,116	29.1
Single-switch system	3,618	3.7
Alternate form–visual impairment	2,244	2.3
Two-switch system	1,128	1.2
Uncontracted braille	97	0.1
Supports provided outside the system
Human read aloud	80,397	83.3
Test administrator enters responses for student	60,332	62.5
Partner-assisted scanning	9,819	10.2
Language translation of text	1,909	2.0
Sign interpretation of text	1,178	1.2

4.2.4 Participation by Nonsymbolic Communicators

A subset of students who take DLM assessments communicate only through non-symbolic means such as unique gestures, movements, and expressions. Representing about 7%–9% of students with the most significant cognitive disabilities, these students are often excluded or prematurely stopped in other assessments requiring symbolic responses. The DLM system prioritizes their inclusion, using an expanded cognitive process taxonomy (Bechard et al., 2021) and universal design for learning principles. Testlets at the Initial Precursor level are designed to capture a range of intentional and pre-intentional responses, enabling educators to detect progress toward grade-level expectations. To evaluate the DLM approach to assessment design for this subpopulation of students, we examined student data from 2022–-2023 (Erickson & Karvonen, 2025). Around 7% of students taking DLM assessments communicated in only nonsymbolic ways. Of these students, 93% responded to at least one assessment item correctly and many demonstrated mastery of at least one linkage level (75% in ELA and 67% in mathematics). Only 0.17% of these students did not make an observable response to any items. We also found that the percentage of nonsymbolic communicators decreased across grade bands, suggesting students are making progress in symbolic communication over time.

4.3 Evidence From Monitoring Assessment Administration

DLM staff monitor assessment administration using various materials and strategies. As in prior years, DLM staff made available an assessment administration observation protocol for use by DLM staff, state education agency staff, and local education agency staff. DLM staff also reviewed Service Desk requests and hosted regular check-in calls with state education agency staff to monitor common issues and concerns during the assessment window. This section provides an overview of the assessment administration observation protocol and its use.

4.3.1 Test Administration Observations

Consistent with previous years, the DLM Consortium used a test administration observation protocol to gather information about how educators in the consortium states deliver testlets to students with the most significant cognitive disabilities. This protocol gave observers, regardless of their role or experience with DLM assessments, a standardized way to describe how DLM testlets were administered. The test administration observation protocol captured data about student actions (e.g., navigation, responding), educator assistance, variations from standard administration, student engagement, and barriers to engagement. Because the protocol does not differ by administration model (i.e., Instructionally Embedded or Year-End), we report all results here. For a full description of the test administration observation protocol, see Chapter 4 of the 2021–2022 Technical Manual—Year-End Model (Dynamic Learning Maps Consortium, 2022).

During 2024–2025, there were 390 assessment administration observations collected in six states. Table 4.6 shows the number of observations collected by state. Of the 390 total observations, 258 (66%) were of computer-delivered assessments and 132 (34%) were of educator-administered testlets. The observations were for 228 (58%) ELA reading testlets, 15 (4%) ELA writing testlets, and 147 (38%) mathematics testlets.

Table 4.6: Educator Observations by State (N = 390)

State	n	%
Arkansas	69	17.7
Colorado	6	1.5
Iowa	96	24.6
Kansas	24	6.2
Missouri	95	24.4
West Virginia	100	25.6

Table 4.7 summarizes observations for computer-delivered testlets; behaviors on the test administration observation protocol were identified as supporting, neutral, or nonsupporting. For example, clarifying directions (found in 36% of observations) removes student confusion about the task demands as a source of construct-irrelevant variance and supports the student’s meaningful, construct-related engagement with the item. In contrast, using physical prompts (e.g., hand-over-hand guidance) indicates that the test administrator directly influenced the student’s answer choice. Overall, 54% of observed behaviors were classified as supporting, with 1% of observed behaviors reflecting nonsupporting actions.

Table 4.7: Test Administrator Actions During Computer-Delivered Testlets (n = 258)

Action	n	%
Supporting
Read one or more screens aloud to the student	187	47.9
Clarified directions or expectations for the student	139	35.6
Navigated one or more screens for the student	117	30.0
Repeated question(s) before student responded	79	20.3
Neutral
Used verbal prompts to direct the student’s attention or engagement (e.g., “look at this.”)	125	32.1
Used pointing or gestures to direct student attention or engagement	103	26.4
Entered one or more responses for the student	61	15.6
Used materials or manipulatives during the administration process	45	11.5
Asked the student to clarify or confirm one or more responses	44	11.3
Allowed student to take a break during the testlet	31	7.9
Repeated question(s) after student responded (gave a second trial at the same item)	23	5.9
Nonsupporting
Physically guided the student to a response	5	1.3
Reduced the number of answer choices available to the student	5	1.3
Note. Respondents could select multiple responses to this question.

For DLM assessments, interaction with the system includes interaction with the assessment content as well as physical access to the testing device and platform. The fact that educators navigated one or more screens in 30% of the observations does not necessarily indicate the student was prevented from engaging with the assessment content as independently as possible. Depending on the student, test administrator navigation may either support or minimize students’ independent, physical interaction with the assessment system. While not the same as interfering with students’ interaction with the content of the assessment, navigating for students who are able to do so independently conflicts with the assumption that students are able to interact with the system as intended. The observation protocol did not capture why the test administrator chose to navigate, and the reason was not always obvious.

Observations of student actions taken during computer-delivered testlets are summarized in Table 4.8. Independent response selection was observed in 74% of the cases. Nonindependent response selection may include allowable practices, such as test administrators entering responses for the student. The use of materials outside of Kite Student Portal was seen in 9% of the observations. Verbal prompts for navigation and response selection are strategies within the realm of allowable flexibility during test administration. These strategies, which are commonly used during direct instruction for students with the most significant cognitive disabilities, are used to maximize student engagement with the system and promote the type of student-item interaction needed for a construct-relevant response. However, they also indicate that students were not able to sustain independent interaction with the system throughout the entire testlet.

Table 4.8: Student Actions During Computer-Delivered Testlets (n = 258)

Action	n	%
Selected answers independently	191	74.0
Navigated screens independently	146	56.6
Navigated screens after verbal prompts	85	32.9
Selected answers after verbal prompts	71	27.5
Navigated screens after test administrator pointed or gestured	63	24.4
Used materials outside of Kite Student Portal to indicate responses to testlet items	24	9.3
Asked the test administrator a question	17	6.6
Revisited one or more questions after verbal prompt(s)	10	3.9
Independently revisited a question after answering it	9	3.5
Skipped one or more items	7	2.7
Note. Respondents could select multiple responses to this question.

Observers noted whether there was difficulty with accessibility supports (including lack of appropriate available supports) during observations of educator-administered testlets. Of the 132 observations of educator-administered testlets, observers noted difficulty in seven cases (5%). For computer-delivered testlets, observers noted students who indicated responses to items using varied response modes such as gesturing (17%) and using manipulatives or materials outside of the Kite system (9%). Of the 258 observations of computer-delivered testlets, 256 (99%) indicated the student completed the full testlet. Similarly, of the 132 observations of educator-administered testlets, 130 (98%) indicated the student completed the full testlet.

Finally, DLM assessment administration observation intends for test administrators to enter student responses with fidelity, including across multiple modes of communication, such as verbal, gesture, and eye gaze. Table 4.9 summarizes students’ response modes for educator-administered testlets. The most frequently observed behavior was gestured to indicate response to test administrator who selected answers.

Table 4.9: Primary Response Mode for Educator-Administered Testlets (n = 132)

Response mode	n	%
Gestured to indicate response to test administrator who selected answers	79	59.8
Verbally indicated response to test administrator who selected answers	54	40.9
No observable response mode	14	10.6
Eye gaze system indication to test administrator who selected answers	5	3.8
Note. Respondents could select multiple responses to this question.

Observations of computer-delivered testlets when test administrators entered responses on behalf of students provided another opportunity to confirm fidelity of response entry. This support is recorded on the Personal Needs and Preferences Profile and is recommended for a variety of situations (e.g., students who have limited motor skills and cannot interact directly with the testing device even though they can cognitively interact with the onscreen content). Observers recorded whether the response entered by the test administrator matched the student’s response. In 61 of 258 (24%) observations of computer-delivered testlets, the test administrator entered responses on the student’s behalf. In 58 (95%) of those cases, observers indicated that the entered response matched the student’s response, while the remaining observers responded that they could not tell if the entered response matched the student’s response.

4.4 Evidence From Test Administrators

This section describes evidence collected from the spring 2025 test administrator survey. Test administrators receive one survey per rostered DLM student, which annually collects information about that student’s assessment experience. As in previous years, the survey was distributed to test administrators in Kite Student Portal, where students completed assessments. Instructions indicated the test administrator should complete the survey after administration of the spring assessment; however, users can complete the survey at any time. The survey consisted of three blocks. Blocks 1 and 3 were administered in every survey. Block 1 included questions about the test administrator’s perceptions of the assessments and the student’s interaction with the content. Block 3 included questions about the test administrator’s background, to be completed once per administrator. Block 2 was spiraled, so test administrators received one randomly assigned section. In these sections, test administrators responded to questions about a single topic (e.g., relationship of the assessment to ELA, mathematics, or science instruction).

4.4.1 User Experience With the DLM System

A total of 16,289 test administrators (67%) responded to the survey about 51,831 students’ experiences. Test administrators are instructed to respond to the survey separately for each of their students. Participating test administrators responded to surveys for between 1 and 60 students, with a median of 2 students. Test administrators most commonly reported having 11–20 years of experience in ELA, 11–20 years in mathematics, and 2–5 years teaching students with significant cognitive disabilities. Most of the survey respondents (71%) were the student’s primary teacher in the subject assessed, while other respondents included case managers (16%), other teachers (9%), and others (6%).

The following sections summarize responses regarding both educator and student experiences with the DLM system.

4.4.1.1 Educator Experience

Test administrators were asked to reflect on their own experience with the assessments as well as their comfort level and knowledge administering them. Most of the questions required test administrators to respond on a 4-point scale: strongly disagree, disagree, agree, or strongly agree. Table 4.10 summarizes responses.

Nearly all test administrators (97%) agreed or strongly agreed that they were confident administering DLM testlets. Most respondents (93%) agreed or strongly agreed that Required Test Administrator Training prepared them for their responsibilities as test administrators. Most test administrators agreed or strongly agreed that they had access to curriculum aligned with the content that was measured by the assessments (88%) and that they used the manuals and the Educator Resource Page (91%).

Table 4.10: Test Administrator Responses Regarding Test Administration

	SD		D		A		SA		A+SA
Statement	n	%	n	%	n	%	n	%	n	%
I was confident in my ability to deliver DLM testlets.	163	1.2	280	2.0	5,951	42.2	7,718	54.7	13,669	96.9
Required Test Administrator Training prepared me for the responsibilities of a test administrator.	268	1.9	702	5.0	6,716	47.6	6,414	45.5	13,130	93.1
I have access to curriculum aligned with the content measured by DLM assessments.	393	2.8	1,220	8.7	6,878	48.8	5,594	39.7	12,472	88.5
I used manuals and/or the DLM Educator Resource Page materials.	314	2.2	998	7.1	7,246	51.3	5,558	39.4	12,804	90.7
Note. SD = strongly disagree; D = disagree; A = agree; SA = strongly agree; A+SA = agree and strongly agree.

We evaluated longitudinal trends for a subset of educator experience items using an ordered logistic regression model (See Section 3.3.2.1 for the analytical methods). Figure 4.1 presents longitudinal trends in educator experience by showing the raw percentage of each response category (triangles) and the predicted probability of selecting each category (circles) across years, separately by item. The results show that educators consistently reported high agreement with each statement, which remained stable or improved over time. The agreement with the statement, “I was confident in my ability to deliver DLM testlets,” remained consistently high over time without significant change (odds ratio = 0.998, 95% CI [0.992, 1.003]). The percentage of test administrators strongly agreeing with the statement, “Required test administrator training prepared them for their responsibilities as test administrators,” increased toward 2025. The odds of selecting a higher level of agreement with the statement increased by 5.6% per year (odds ratio = 1.056, 95% CI [1.05, 1.062]). In each year, more than 80% of educators agreed with the statement, “I have access to curriculum aligned with the content measured by DLM assessment,” and the percentage of educators who strongly agreed with it increased toward 2025. The odds of selecting a higher level of agreement with the statement increased by 3.5% per year (odds ratio = 1.035, 95% CI [1.028, 1.042]). Overall, test administrators’ experiences remained positive and showed a gradual improvement over time. However, it is important to note that the sample of teachers who respond to the survey each year is different, and the student population they are referencing when answering these questions has also changed over time.

Figure 4.1: Longitudinal Trends in Educator Experience

4.4.1.2 Student Experience

The spring 2025 test administrator survey included three items about how students responded to test items. Test administrators were asked to rate statements from strongly disagree to strongly agree. Table 4.11 presents the results. For the majority of students, test administrators agreed or strongly agreed that their students responded to items to the best of their knowledge, skills, and understandings; were able to respond regardless of disability, behavior, or health concerns; and had access to all necessary supports to participate.

Table 4.11: Test Administrator Perceptions of Student Experience with Testlets

	SD		D		A		SA		A+SA
Statement	n	%	n	%	n	%	n	%	n	%
Student responded to items to the best of their knowledge, skills, and understanding.	1,715	3.7	3,422	7.4	24,871	53.8	16,230	35.1	41,101	88.9
Student was able to respond regardless of their disability, behavior, or health concerns.	2,778	6.0	4,157	9.0	23,879	51.5	15,554	33.5	39,433	85.0
Student had access to all necessary supports to participate.	1,541	3.3	2,239	4.9	24,553	53.2	17,815	38.6	42,368	91.8
Note. SD = strongly disagree; D = disagree; A = agree; SA = strongly agree; A+SA = agree and strongly agree.

Annual survey results show that a small percentage of test administrators disagree that their student was able to respond regardless of disability, behavior, or health concerns; had access to all necessary supports; and was able to effectively use supports.

We evaluated longitudinal trends in student experience with an ordered logistic regression model (See Section 3.3.2.1 for the analytical methods). Figure 4.2 presents longitudinal trends in educators’ perceptions of student experience with testlets by showing the raw percentage of each response category (triangles) and the predicted probability of selecting each category (circles) across years, separately by item. Overall, educators reported consistently high agreement across items. The percentages of agreement with the statement, “Students responded to the items on the assessment to the best of their knowledge, skills, and understanding,” were consistently higher than those of disagreement with the statement. However, the overall trend decreased slightly across years, as the odds of selecting a higher level of agreement declined slightly by 0.8% per year (odds ratio = 0.992, 95% CI [0.99, 0.994]). Educators also showed consistently high agreement with the statement, “Student was able to respond to items regardless of their disability, behavior, or health concerns.” More than 80% of them agreed with the statement across years, and the overall trend increased slightly, as the odds of selecting a higher level of agreement with the statement increased by 1.1% per year (odds ratio = 1.011, 95% CI [1.009, 1.013]). The percentages of educators agreeing with the statement, “Students had access to all necessary support in order to participate in the assessment,” were approximately 90% across years. Due to the decrease in the percentage of educators strongly agreeing with the statement toward 2025, the odds of selecting a higher level of agreement with the statement decreased by 3.4% per year (odds ratio = 0.966, 95% CI [0.964, 0.969]). Overall, teachers’ perspectives about student experience with testlets remained largely stable, with some mixed trends over time. However, it is important to note that the sample of teachers who respond to the survey each year is different, and the student population they are referencing when answering these questions has also changed over time.

Figure 4.2: Longitudinal Trends in Educators’ Agreement on Student Experience with Testlets

4.4.2 Opportunity to Learn

The spring 2025 test administrator survey also included items about students’ opportunity to learn academic content measured by DLM assessments. Table 4.12 reports the opportunity to learn results.

Approximately 71% of responses (n = 33,141) for ELA and 65% (n = 29,912) for mathematics reported that most or all testlets matched instruction.

Table 4.12: Educator Ratings of Portion of Testlets That Matched Instruction

	None		Some (<half)		Most (>half)		All		Not applicable
Subject	n	%	n	%	n	%	n	%	n	%
English language arts	2,393	5.2	10,166	21.9	17,972	38.7	15,169	32.7	747	1.6
Mathematics	2,630	5.7	12,749	27.6	17,217	37.3	12,695	27.5	888	1.9

We evaluated longitudinal trends in educator ratings of the portion of testlets that matched instruction using an ordered logistic regression model (See Section 3.3.2.1 for the analytical methods). Figure 4.3 presents the results by showing the raw percentage of each response category (triangles) and the predicted probability of selecting each category (circles) across years, separately by item. Overall, test administrators were increasingly likely over time to report that a greater proportion of testlets aligned with instruction. Specifically, the odds of rating a higher proportion of English language arts testlets as matching instruction increased by 3.4% per year (odds ratio = 1.034, 95% CI [1.032, 1.036], p < 0.001). Similarly, the odds for mathematics testlets increased by a higher percentage 6.7% (odds ratio = 1.067, 95% CI [1.065, 1.07], p < 0.001). Overall, these results indicate a consistent upward trend in test administrators’ perceptions of testlet alignment with instruction over time.

Figure 4.3: Longitudinal Trends in Educator Ratings of Portion of Testlets That Matched Instruction

In addition to the fixed questions answered by all participants, the survey included spiraled content, where test administrators responded to different blocks of items to provide feedback across a broad range of topics. On these blocks, a subset of test administrators was asked to indicate the approximate number of hours in total spent instructing students on each of the conceptual areas by subject (i.e., ELA, mathematics) during the 2024–2025 year. Test administrators responded using a 6-point scale: 0 hours, 1–5 hours, 6–10 hours, 11–15 hours, 16–20 hours, or more than 20 hours. Table 4.13 and Table 4.14 indicate the amount of instructional time spent on conceptual areas for ELA and mathematics, respectively. On average, 41% of the test administrators provided at least 11 hours of instruction per conceptual area to their students in ELA, compared to 39% in mathematics.

Table 4.13: Instructional Time Spent on English Language Arts Conceptual Areas

	Number of hours
		0		1–5		6–10		11–15		16–20		>20
Conceptual area	Median	n	%	n	%	n	%	n	%	n	%	n	%
Determine critical elements of text	6–10	1,054	10.2	2,368	23.0	1,830	17.8	1,396	13.5	1,357	13.2	2,300	22.3
Construct understandings of text	6–10	1,627	15.9	2,511	24.5	1,846	18.0	1,348	13.2	1,249	12.2	1,667	16.3
Integrate ideas and information from text	6–10	1,921	18.8	2,556	25.0	1,816	17.8	1,400	13.7	1,209	11.8	1,324	12.9
Use writing to communicate	6–10	1,673	16.4	2,514	24.7	1,748	17.1	1,366	13.4	1,207	11.8	1,690	16.6
Integrate ideas and information in writing	6–10	2,249	22.1	2,461	24.2	1,701	16.7	1,314	12.9	1,112	10.9	1,351	13.3
Use language to communicate with others	11–15	995	9.8	2,238	21.9	1,828	17.9	1,460	14.3	1,399	13.7	2,277	22.3
Clarify and contribute in discussion	6–10	1,511	14.8	2,376	23.3	1,764	17.3	1,406	13.8	1,331	13.1	1,788	17.6
Use sources and information	1–5	2,802	27.5	2,553	25.0	1,643	16.1	1,185	11.6	938	9.2	1,086	10.6
Collaborate and present ideas	1–5	2,675	26.1	2,555	24.9	1,683	16.4	1,194	11.6	986	9.6	1,159	11.3

Table 4.14: Instructional Time Spent on Mathematics Conceptual Areas

	Number of hours
		0		1–5		6–10		11–15		16–20		>20
Conceptual area	Median	n	%	n	%	n	%	n	%	n	%	n	%
Understand number structures (counting, place value, fraction)	11–15	1,573	7.7	4,289	20.9	3,437	16.8	2,625	12.8	2,935	14.3	5,647	27.5
Compare, compose, and decompose numbers and steps	6–10	3,490	17.2	4,720	23.2	3,586	17.6	2,622	12.9	2,707	13.3	3,218	15.8
Calculate accurately and efficiently using simple arithmetic operations	6–10	3,062	15.1	4,161	20.5	3,363	16.5	2,660	13.1	2,755	13.6	4,331	21.3
Understand and use geometric properties of two- and three-dimensional shapes	6–10	4,171	20.5	5,374	26.4	3,810	18.8	2,764	13.6	2,245	11.0	1,954	9.6
Solve problems involving area, perimeter, and volume	1–5	7,043	34.8	4,807	23.8	3,042	15.0	2,071	10.2	1,694	8.4	1,570	7.8
Understand and use measurement principles and units of measure	1–5	4,748	23.5	5,641	27.9	3,722	18.4	2,379	11.8	1,928	9.6	1,770	8.8
Represent and interpret data displays	6–10	4,660	23.1	5,317	26.3	3,659	18.1	2,574	12.7	2,024	10.0	1,977	9.8
Use operations and models to solve problems	6–10	3,623	17.9	4,474	22.1	3,498	17.3	2,705	13.3	2,627	13.0	3,351	16.5
Understand patterns and functional thinking	6–10	2,748	13.5	5,643	27.7	4,077	20.0	2,861	14.0	2,549	12.5	2,503	12.3

Another dimension of opportunity to learn is student engagement during instruction. The First Contact Survey contains two questions that ask educators to rate student engagement during computer- and educator-directed instruction. Table 4.15 shows the percentage of students who were rated as demonstrating different levels of attention by instruction type. Overall, 87% of students demonstrate fleeting or sustained attention to computer-directed instruction and 84% of students demonstrate fleeting or sustained attention to educator-directed instruction, supporting their opportunity to learn the academic content measured by DLM assessments. These high levels of engagement across both computer-delivered and educator-administered instruction also suggest that students are likely to demonstrate similar engagement during DLM computer-delivered and educator-administered assessments.

Table 4.15: Student Attention Levels During Instruction

	Demonstrates little or no attention		Demonstrates fleeting attention		Generally sustains attention
Type of instruction	n	%	n	%	n	%
Computer-directed (n = 90,591)	11,808	13.0	46,437	51.3	32,346	35.7
Educator-directed (n = 93,754)	14,748	15.7	56,250	60.0	22,756	24.3

4.5 Conclusion

Delivery of DLM assessments was designed to align with instructional practice and be responsive to individual student needs. Assessment delivery options allow for flexibility to reflect student needs while also including constraints to maximize comparability and support valid interpretation of results. The flexible nature of DLM assessment administration is reflected in adaptive delivery between testlets. Evidence collected from the DLM system, test administration monitoring, and test administrator survey indicates that test administrators are prepared and confident administering DLM assessments, that students are able to successfully interact with the system to demonstrate their knowledge, skills, and understandings, and that students have opportunity to learn the academic content measured by DLM assessments.