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 2022–2023, including a summary of administration time, device use, adaptive routing, accessibility support selections, test administration observations, data forensics reports, and test administrator survey responses regarding user experience.

Overall, intended administration features remained consistent with the 2021–2022 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, 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, 2023d) and the Educator Portal User Guide (Dynamic Learning Maps Consortium, 2023c).

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 2022–2023, the instructionally embedded assessment window occurred between September 12, 2022, and February 22, 2023. 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 23 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 2022–2023, the spring assessment window occurred between March 13, 2023, and June 9, 2023. 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 6 to 13 weeks.

4.2 Evidence From the DLM System

This section describes evidence collected by the DLM system during the 2022–2023 operational administration of the DLM alternate assessment. The categories of evidence include administration time, device use, adaptive routing, administration incidents, and accessibility support selections.

4.2.1 Administration Time

Estimated testlet administration time varies by student and subject. Testlets can be administered separately across multiple testing sessions as long as they are all completed within the testing window.

The published estimated total testing time per testlet is around 5–10 minutes in mathematics, 10–15 minutes in reading, and 10–20 minutes for writing (Dynamic Learning Maps Consortium, 2023d). The estimated total testing time is 60–75 minutes per student in ELA and 35–50 minutes in mathematics in the spring assessment window. Published estimates are slightly longer than anticipated real testing times where students are interacting with the assessment because of the assumption that test administrators need time for setup. The actual amount of testing time per testlet for a student varies depending on each student’s unique characteristics.

Kite Student Portal captured start dates, end dates, and time stamps for every testlet. The differences between these start and end times were calculated for each completed testlet. Table 4.1 summarizes the distribution of test times per testlet. The distribution of test times in Table 4.1 is consistent with the distribution observed in prior years. Most testlets took around 7 minutes or less to complete, with mathematics testlets generally taking less time than ELA testlets. Time per testlet may have been affected by student breaks during the assessment or use of accessibility supports. Testlets with shorter than expected administration times are included in an extract made available to each state education agency. State agency staff can use this information to monitor assessment administration and address as necessary. Testlets time out after 90 minutes.

Table 4.1: Distribution of Response Times per Testlet in Minutes
Grade Min Median Mean Max 25Q 75Q
English language arts
3 0.1 3.9 4.9 89.2 2.5 6.0
4 0.2 4.1 5.1 89.5 2.7 6.3
5 0.1 4.1 5.1 89.0 2.7 6.4
6 0.1 4.2 5.1 89.8 2.7 6.3
7 0.1 4.9 5.9 89.4 3.1 7.4
8 0.1 4.2 5.2 89.9 2.8 6.4
9 0.2 4.6 5.8 89.8 2.8 7.2
10 0.2 4.5 5.6 83.9 2.8 6.9
11 0.2 4.9 6.3 89.4 3.0 7.8
12 0.2 4.8 6.3 77.3 2.8 7.8
Mathematics
3 0.1 1.8 2.6 88.8 1.1 3.2
4 0.0 1.5 2.1 88.2 0.9 2.4
5 0.1 1.6 2.3 88.1 1.0 2.7
6 0.1 1.6 2.4 87.8 1.0 2.8
7 0.1 1.6 2.3 89.3 1.0 2.7
8 0.1 1.6 2.3 89.3 0.9 2.7
9 0.1 1.7 2.4 89.1 0.9 2.9
10 0.1 1.6 2.3 89.7 0.9 2.7
11 0.1 1.8 2.5 89.3 1.1 3.0
12 0.1 1.8 2.7 81.0 1.0 3.0
Note. Min = minimum; Max = maximum; 25Q = lower quartile; 75Q = upper quartile.

4.2.2 Device Use

Testlets may be administered on a variety of devices. Kite Student Portal captured the operating system used for each testlet completed. Although these data do not capture specific devices used to complete each testlet (e.g., SMART Board, switch system, etc.), they provide high-level information about how students access assessment content. For example, we can identify how often an iPad is used relative to a Chromebook or traditional personal computer. Figure 4.1 shows the number of testlets completed on each operating system by subject and linkage level for 2022–2023. Overall, 48% of testlets were completed on a Chromebook, 25% were completed on an iPad, 20% were completed on a personal computer, and 6% were completed on a Mac.

Figure 4.1: Distribution of Devices Used for Completed Testlets

A bar graph showing the number of testlets completed on each device, by subject and linkage level.

Note. PC = personal computer.

4.2.3 Adaptive Delivery

The ELA and mathematics assessments are adaptive between testlets. In spring 2023, 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. See Chapter 4 of the 2021–2022 Technical Manual—Year-End Model (Dynamic Learning Maps Consortium, 2022) for more details. The correspondence between the First Contact complexity bands and first assigned linkage levels are shown in Table 4.2.

Table 4.2: 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 2023 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. The aggregated results can be seen in Table 4.3 and Table 4.4 for ELA and mathematics, respectively.

For the majority of students across all grades who were 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 60% to 94% across both subjects). Consistent patterns were not as apparent for students who were assigned to Band 1, Band 2, or Band 3. Distributions across the three categories 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 of more variability in the adaptation patterns in the higher complexity bands is consistent with prior years. Several factors may help explain these results, including more variability in student characteristics within this group and content-based differences across grades and subjects. Further exploration is needed in this area.

Table 4.3: Adaptation of Linkage Levels Between First and Second English Language Arts Testlets (N = 89,523)
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 14.9 85.1 58.6 21.7 19.6 76.5 14.8   8.7 79.3 18.2   2.5
Grade 4 32.8 67.2 17.3 29.3 53.3 61.7 25.9 12.4 52.5 18.5 29.0
Grade 5 29.0 71.0 25.1 30.4 44.5 60.0 32.7   7.4 92.3   6.5   1.3
Grade 6 28.9 71.1 12.5 22.2 65.3 25.0 38.4 36.6 45.6 37.4 17.0
Grade 7 28.6 71.4 29.7 25.4 44.9 52.0 35.3 12.8 66.6 27.2   6.2
Grade 8 40.4 59.6 34.2 28.8 37.0 71.7 20.7   7.6 85.5 10.6   3.9
Grade 9 12.5 87.5 32.0 35.1 32.9 19.9 31.1 49.0 63.6 25.3 11.1
Grade 10   6.2 93.8 27.2 34.9 37.8 15.2 31.3 53.5 63.3 24.4 12.3
Grade 11 26.4 73.6 13.5 37.5 49.1 62.5 24.8 12.7 65.0 23.0 12.0
Grade 12 * * 16.9 35.1 48.1 72.1 14.8 13.1 * * *
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 4.4: Adaptation of Linkage Levels Between First and Second Mathematics Testlets (N = 89,406)
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 12.6 87.4 12.1 31.1 56.8 19.4 54.5 26.0 64.5 19.3 16.2
Grade 4 14.9 85.1 19.5 33.0 47.5 66.5 25.5   8.1 73.2 23.7   3.2
Grade 5 16.1 83.9 14.5 30.9 54.6 41.9 25.9 32.2 70.8 21.2   8.0
Grade 6 17.2 82.8 15.4 42.8 41.8 30.0 36.0 34.0 47.5 46.0   6.6
Grade 7 15.3 84.7 13.7 26.0 60.3 20.9 19.5 59.6 73.4 19.0   7.6
Grade 8 15.0 85.0 16.7 47.6 35.7 30.2 55.3 14.5 49.0 22.7 28.4
Grade 9 14.2 85.8 20.7 49.2 30.0 52.9 38.9   8.2 56.3 36.0   7.7
Grade 10 14.0 86.0 22.2 30.4 47.4 33.8 17.0 49.2   4.9 20.3 74.8
Grade 11 25.7 74.3 11.9 27.0 61.2 26.0 41.3 32.7 15.2 12.1 72.7
Grade 12 * * 15.7 27.1 57.1 29.7 41.9 28.4 * * *
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 4.5 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 4.5. 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 4.5: Distribution of Linkage Levels Assigned for Assessment
Linkage level n %
English language arts
Initial Precursor 178,944 25.3
Distal Precursor 149,533 21.2
Proximal Precursor 136,566 19.3
Target 100,040 14.2
Successor 141,465 20.0
Mathematics
Initial Precursor 227,054 34.5
Distal Precursor 158,058 24.0
Proximal Precursor 132,412 20.1
Target   76,872 11.7
Successor   63,942   9.7

4.2.4 Administration Incidents

DLM staff annually evaluate testlet assignment to promote correct assignment of students to testlets. 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 2022–2023 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.

4.2.5 Accessibility Support Selections

Accessibility supports provided in 2022–2023 were the same as those available in previous years. The DLM Accessibility Manual (Dynamic Learning Maps Consortium, 2023b) distinguishes accessibility supports that are provided in Kite Student Portal via the Personal Needs and Preferences Profile, require additional tools or materials, or are provided by the test administrator outside the system. Table 4.6 shows selection rates for the three categories of accessibility supports. Overall, 87,974 students (>99%) had at least one support selected. The most commonly selected supports in 2022–2023 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 4.6: Accessibility Supports Selected for Students (N = 87,974)
Support n %
Supports provided in Kite Student Portal
Spoken audio 54,431 61.9
Magnification 13,081 14.9
Color contrast   7,767   8.8
Overlay color   3,278   3.7
Invert color choice   2,245   2.6
Supports requiring additional tools/materials
Individualized manipulatives 42,475 48.3
Calculator 28,108 31.9
Single-switch system   3,692   4.2
Alternate form–visual impairment   2,086   2.4
Two-switch system   1,135   1.3
Uncontracted braille      103   0.1
Supports provided outside the system
Human read aloud 78,496 89.2
Test administrator enters responses for student 55,705 63.3
Partner-assisted scanning   9,033 10.3
Language translation of text   1,700   1.9
Sign interpretation of text   1,193   1.4

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. Project staff also reviewed Service Desk requests and hosted regular check-in calls with state education 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, engagement, and barriers to engagement. 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 2022–2023, there were 265 assessment administration observations collected in eight states. Table 4.7 shows the number of observations collected by state. Of the 265 total observations, 164 (62%) were of computer-delivered assessments and 101 (38%) were of educator-administered testlets. The observations consisted of 131 (49%) ELA reading testlets, 20 (8%) ELA writing testlets, and 114 (43%) mathematics testlets.

Table 4.7: Educator Observations by State (N = 265)
State n %
Arkansas 64 24.2
Iowa 27 10.2
Kansas 46 17.4
Missouri 52 19.6
New Jersey   5   1.9
New York 31 11.7
North Dakota   3   1.1
West Virginia 37 14.0

Observations for computer-delivered testlets are summarized in Table 4.8; behaviors on the test administration observation protocol were identified as supporting, neutral, or nonsupporting. For example, clarifying directions (found in 42.7% 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, 55% of observed behaviors were classified as supporting, with 1% of observed behaviors reflecting nonsupporting actions.

Table 4.8: Test Administrator Actions During Computer-Delivered Testlets (n = 164)
Action n %
Supporting
Read one or more screens aloud to the student 99 60.4
Navigated one or more screens for the student 78 47.6
Clarified directions or expectations for the student 70 42.7
Repeated question(s) before student responded 51 31.1
Neutral
Used verbal prompts to direct the student’s attention or engagement (e.g., “look at this.”) 57 34.8
Used pointing or gestures to direct student attention or engagement 56 34.1
Entered one or more responses for the student 43 26.2
Asked the student to clarify or confirm one or more responses 29 17.7
Used materials or manipulatives during the administration process 23 14.0
Repeated question(s) after student responded (gave a second trial at the same item) 13   7.9
Allowed student to take a break during the testlet 11   6.7
Nonsupporting
Physically guided the student to a response   6   3.7
Reduced the number of answer choices available to the student   2   1.2
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 48% 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 4.9. Independent response selection was observed in 59% 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 7% 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 4.9: Student Actions During Computer-Delivered Testlets (n = 164)
Action n %
Selected answers independently 97 59.1
Navigated screens independently 59 36.0
Selected answers after verbal prompts 48 29.3
Navigated screens after verbal prompts 25 15.2
Navigated screens after test administrator pointed or gestured 24 14.6
Asked the test administrator a question 13   7.9
Used materials outside of Kite Student Portal to indicate responses to testlet items 12   7.3
Revisited one or more questions after verbal prompt(s)   4   2.4
Skipped one or more items   2   1.2
Independently revisited a question after answering it   1   0.6
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 101 observations of educator-administered testlets, observers noted difficulty in four cases (4%). For computer-delivered testlets, observers noted students who indicated responses to items using varied response modes such as gesturing (24%) and using manipulatives or materials outside of the Kite system (7%). Of the 265 test administration observations collected, students completed the full testlet in 162 cases (61%). In all instances where the testlet was not completed, no reason was provided by the observer.

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 4.10 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 4.10: Primary Response Mode for Educator-Administered Testlets (n = 101)
Response mode n %
Gestured to indicate response to test administrator who selected answers 63 62.4
Verbally indicated response to test administrator who selected answers 59 58.4
Eye gaze system indication to test administrator who selected answers   4   4.0
No observable response mode   1   1.0
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 43 of 164 (26%) observations of computer-delivered testlets, the test administrator entered responses on the student’s behalf. In 37 (86%) of those cases, observers indicated that the entered response matched the student’s response, while the remaining six observers either responded that they could not tell if the entered response matched the student’s response, or they left the item blank.

4.4 Evidence From Test Administrators

This section describes evidence collected from the spring 2023 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, and 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 were asked about one of the following topics per survey: relationship of the assessment to ELA, mathematics, or science instruction.

4.4.1 User Experience With the DLM System

A total of 16,613 test administrators responded to the survey (68%) about 50,847 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 65 students, with a median of 2 students. Test administrators reported having an average of 12 years of experience in ELA, 11 years in mathematics, and 10 years teaching students with significant cognitive disabilities.

The following sections summarize responses regarding both educator and student experience with the 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. Responses are summarized in Table 4.11.

Nearly all test administrators (97%) agreed or strongly agreed that they were confident administering DLM testlets. Most respondents (93%) agreed or strongly agreed that the 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 (92%).

Table 4.11: 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. 141 1.0 247 1.8 5,478 40.6 7,641 56.6 13,119 97.2
Required Test Administrator Training prepared me for the responsibilities of a test administrator. 270 2.0 653 4.8 6,257 46.4 6,308 46.8 12,565 93.2
I have access to curriculum aligned with the content measured by DLM assessments. 370 2.7 1,236 9.2 6,361 47.2 5,514 40.9 11,875 88.1
I used manuals and/or the DLM Educator Resource Page materials. 284 2.1 844 6.3 6,880 51.0 5,492 40.7 12,372 91.7
Note. SD = strongly disagree; D = disagree; A = agree; SA = strongly agree; A+SA = agree and strongly agree.

4.4.1.2 Student Experience

The spring 2023 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. Results are presented in Table 4.12. The majority of 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 4.12: 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 his/her knowledge, skills, and understanding. 1,657 3.6 3,369 7.4 24,422 53.6 16,083 35.3 40,505 88.9
Student was able to respond regardless of his/her disability, behavior, or health concerns. 2,570 5.6 3,916 8.6 23,766 52.1 15,373 33.7 39,139 85.8
Student had access to all necessary supports to participate. 1,374 3.0 2,283 5.0 24,280 53.4 17,565 38.6 41,845 92.0
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. In spring 2020, DLM staff conducted educator focus groups with educators who disagreed with one or more of these survey items to learn about potential accessibility gaps in the DLM system (Kobrin et al., 2022). A total of 18 educators from 11 states participated in six focus groups. The findings revealed that many of the challenges educators described were documented in existing materials (e.g., wanting clarification about allowable practices that are described in the Test Administration Manual, such as substituting materials; desired use of not-allowed practices like hand-over-hand that are used during instruction). DLM staff are using the focus group findings to review existing materials and develop new resources that better communicate information about allowable practices to educators.

4.4.2 Opportunity to Learn

The spring 2023 test administrator survey also included items about students’ opportunity to learn. Table 4.13 reports the opportunity to learn results.

Approximately 70% of responses (n = 32,142) reported that most or all ELA testlets matched instruction, compared to 62% (n = 28,247) for mathematics.

Table 4.13: 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 2,715 5.9 10,198 22.3 18,612 40.6 13,530 29.5 753 1.6
Mathematics 3,082 6.8 13,263 29.2 17,371 38.2 10,876 23.9 873 1.9

A subset of test administrators was asked to indicate the approximate number of hours spent instructing students on each of the conceptual areas by subject (i.e., ELA, mathematics). 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 4.14 and Table 4.15 indicate the amount of instructional time spent on conceptual areas for ELA and mathematics, respectively. Around 51% of the test administrators provided at least 11 hours of instruction per conceptual area to their students in ELA, compared to 42% in mathematics.

Table 4.14: 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 3,287 17.4 3,502 18.5 2,700 14.3 2,257 11.9 2,497 13.2 4,661 24.7
Construct understandings of text 11–15 2,602 13.8 3,277 17.4 2,735 14.5 2,259 12.0 2,639 14.0 5,346 28.3
Integrate ideas and information from text 11–15 3,145 16.7 3,387 18.0 2,777 14.8 2,426 12.9 2,669 14.2 4,397 23.4
Use writing to communicate 11–15 2,993 15.9 3,466 18.4 2,675 14.2 2,261 12.0 2,595 13.8 4,863 25.8
Integrate ideas and information in writing 6–10 4,042 21.6 3,468 18.5 2,664 14.2 2,321 12.4 2,523 13.5 3,733 19.9
Use language to communicate with others 16–20 1,372   7.3 2,204 11.7 2,127 11.3 1,938 10.3 2,601 13.8 8,618 45.7
Clarify and contribute in discussion 11–15 2,741 14.6 2,909 15.5 2,627 14.0 2,264 12.0 2,703 14.4 5,574 29.6
Use sources and information 6–10 4,897 26.0 3,770 20.0 2,816 14.9 2,236 11.9 2,127 11.3 3,002 15.9
Collaborate and present ideas 6–10 4,472 23.7 3,847 20.4 2,804 14.9 2,211 11.7 2,276 12.1 3,248 17.2
Table 4.15: 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) 16–20 1,456   7.8 2,762 14.7 2,437 13.0 2,222 11.8 2,847 15.2 7,048 37.5
Compare, compose, and decompose numbers and steps 11–15 3,232 17.3 3,044 16.3 2,739 14.7 2,399 12.9 2,853 15.3 4,374 23.5
Calculate accurately and efficiently using simple arithmetic operations 11–15 3,146 16.9 2,571 13.8 2,288 12.3 2,116 11.3 2,694 14.4 5,835 31.3
Understand and use geometric properties of two- and three-dimensional shapes 6–10 4,339 23.3 4,001 21.5 3,279 17.6 2,726 14.6 2,254 12.1 2,041 10.9
Solve problems involving area, perimeter, and volume 1–5 8,236 44.2 3,455 18.5 2,435 13.1 1,869 10.0 1,399   7.5 1,244   6.7
Understand and use measurement principles and units of measure 1–5 5,554 29.8 4,161 22.3 3,276 17.6 2,282 12.2 1,723   9.2 1,640   8.8
Represent and interpret data displays 1–5 5,776 31.1 3,749 20.2 3,131 16.8 2,373 12.8 1,835   9.9 1,730   9.3
Use operations and models to solve problems 6–10 5,030 27.0 3,174 17.0 2,777 14.9 2,384 12.8 2,231 12.0 3,029 16.3
Understand patterns and functional thinking 6–10 3,842 20.6 3,805 20.4 3,342 17.9 2,700 14.5 2,321 12.4 2,651 14.2

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 4.16 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 86% of students demonstrate fleeting or sustained attention to educator-directed instruction.

Table 4.16: 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 = 84,275) 11,179 13.3 47,324 56.2 25,772 30.6
Educator-directed (n = 91,397) 13,251 14.5 57,347 62.7 20,799 22.8

4.5 Conclusion

Delivery of the DLM system was designed to align with instructional practice and be responsive to individual student needs. Assessment delivery options allow for necessary flexibility to reflect student needs while also including constraints to maximize comparability and support valid interpretation of results. The dynamic nature of DLM assessment administration is reflected in adaptive routing between testlets. Evidence collected from the DLM system, test administration monitoring, and test administrators indicates that students are able to successfully interact with the system to demonstrate their knowledge, skills, and understandings.