Vocabulary Assessment Techniques: Perspectives of School-Based Speech-Language Pathologists

Standardized assessments

Previous survey research has focused on standardized assessment techniques for general eligibility purposes; standardized tests are typically not used for monitoring progress. Comprehensive spoken language tests are the most commonly used standardized assessments for eligibility decisions; however, the use of single-word vocabulary tests has also been reported (Betz et al., 2013; Caesar & Kohler, 2009). It is unknown whether SLPs use different tests when investigating specific areas of language, such as vocabulary.

Options for standardized assessment of vocabulary include omnibus language assessments or stand-alone vocabulary assessments, with expressive or receptive response types. Omnibus language tests (e.g., Clinical Evaluation of Language Fundamentals; Semel et al., 2013) and comprehensive vocabulary tests (e.g., Test of Semantic Skills; Huisingh et al., 2004) use multiple subtests to measure semantic/lexical skills. Other vocabulary-specific tests use a single response type to measure one aspect of vocabulary, for example, receptive knowledge of single words (e.g., Peabody Picture Vocabulary Test; Dunn, 2018). With the exception of the Diagnostic Evaluation of Language Variation (Seymour et al., 2005), which includes two subtests to measure how a child learns a new word, currently available standardized assessments measure vocabulary knowledge. “Show me X” is the most common receptive format, wherein the examiner provides a word or phrase and the child points to the matching picture from a choice of three or four. Labeling a picture and providing a synonym are common expressive formats. Other expressive tasks include providing definitions, explaining word relationships, and stating categories, attributes, or functions.

Standardized tests are integral to comprehensive language evaluations; however, problems and limitations have also been documented. Standardized tests may have inadequate or inappropriate norming samples, may lack adequate information regarding sensitivity and specificity, and may lack validity for assessing real-life communicative competence (Caesar & Kohler, 2009; Spaulding et al., 2006). Also, standardized tests often do not distinguish two types of poor performers: those with underlying language impairment and those with home language learning experiences that differ from the normative sample (Horton-Ikard & Ellis Weismer, 2007). Next, some standardized vocabulary tests are limited in the information that they provide, for example, labeling or identifying pictures assesses only superficial word knowledge. Finally, because standardized tests cannot be repeatedly administered within a short time frame, they cannot be used for progress monitoring.

Informal assessment techniques

Clinicians should assess vocabulary using a variety of techniques to obtain the clearest understanding of the degree and nature of their client’s vocabulary ability (Watkins & DeThorne, 2000). Furthermore, different techniques may be needed for eligibility decisions than are needed for progress monitoring. Such techniques may include parent/caregiver or teacher report, language sample analysis, dynamic assessment, curricular-based measures, and clinician-created tasks.

Parent/caregiver report measures are commonly used for young children for whom independently administered standardized language tests may not be appropriate. Although not specific to vocabulary, parent report measures of young children’s language have high reliability and validity, are useful for identifying language delay, help to identify areas of strengths and needs, and can be used for monitoring progress (Gilkerson et al., 2017; Watkins & DeThorne, 2000). In comparison with standardized tests alone, the addition of parent report provides essential information that increases the diagnostic accuracy of language impairment in young children (Bishop & McDonald, 2009). It should be noted that parent report of language skills in the school-age years is less consistently correlated with standardized test performance (Hauerwas & Stone, 2000). Furthermore, although empirical support exists for parent report, the accuracy of teacher report for identifying language weaknesses in children is less clear (Gregory & Oetting, 2018). Caution should be used with teacher report in the assessment process, as teachers may confuse nonmainstream dialect use with low language ability (Hendricks & Jimenez, 2021).

Another assessment technique is language sample analysis. Many states require language sample analysis as part of the eligibility protocol, although survey data indicate that this technique is only sometimes used (Caesar & Kohler, 2009). Because language sample analysis can be conducted repeatedly, this technique is especially useful for monitoring progress (Miller et al., 2011). Number of different words is indicative of vocabulary diversity and helps to identify children with language impairment (Watkins et al., 1995). Language samples may also be coded for semantic errors and generic word use, which provide a fuller account of a child’s vocabulary expression (Miller et al., 2011). In addition to spoken language samples, written language samples are an academically relevant way of identifying students’ vocabulary diversity and word-level errors (Nelson, 2014). When standard protocols are used, language sample measures can be compared with normative databases, which is beneficial for identifying vocabulary deficits, as well as students’ strengths and weaknesses (Miller et al., 2011). However, SLPs often use self-designed language sampling methods that would not allow for accurate database comparisons (Pavelko et al., 2016).

Dynamic assessment is an informal measure that is used to measure a student’s modifiability and is especially helpful for appropriately diagnosing children from culturally and linguistically diverse backgrounds (Gutiérrez-Clellen & Peña, 2001). Dynamic assessment has been found to be an appropriate measure of vocabulary ability for English Language Learners (Camilleri & Botting, 2013; Peña et al., 2001) and for children who speak nonmainstream dialects (Peña & Quinn, 1997). Rather than measuring a child’s independent performance as in a static assessment, the examiner interacts dynamically with a child to evaluate their performance with and without assistance. This adult assistance includes prompts, explanations, or questions that help to determine how a student is understanding the task, what type of scaffolding may be helpful, and what treatment targets may be most appropriate (Gutiérrez-Clellen & Peña, 2001). Adult assistance may also involve a short period of teaching in a test–teach–retest design. Thus, progress monitoring is built into the dynamic assessment technique. Progress is realized when a student can complete a task independently or when they require less directive adult assistance for success. Despite its benefits, results of previous surveys have indicated that SLPs rarely or never use dynamic assessment (Caesar & Kohler, 2009).

Curricular-based measures may be used to identify how children perform in relation to educational standards and are typically administered to plan instruction and monitor progress (Yell & Stecker, 2003). In the Common Core State Standards (National Governors Association Center for Best Practices, 2010), vocabulary skills are explicitly included in every academic standard. For example, students need to determine the meanings of words and phrases used in the text, use precise language and vocabulary, and understand and apply domain- or subject-specific vocabulary. Separate standards for vocabulary acquisition and use are in the English Language Arts section and include unknown words, multiple meaning words, figurative language word relationships, and nuances. Vocabulary may be included as a component of computerized curricular-based assessments for reading. For example, the i-Ready assessment for reading includes a vocabulary section that measures academic- and domain-specific vocabulary, word relationships, word-learning strategies, affixes and word roots, and use of reference materials (Curriculum Associates, 2015). These computerized assessments are typically purchased by the school district and administered by the classroom teacher. However, SLPs may create their own curricular-based measures using educational standards to determine the impact of vocabulary delays on a student’s academic achievement and to measure progress with these standards.

Clinicians may use other informal tasks to more fully understand the abilities of children on their caseload and/or to monitor progress. Informal tasks may be self-designed by clinicians or may be sourced from academic journals. Little has been reported about the informal tasks that SLPs create on their own to identify vocabulary deficits and monitor progress. Examples of informal task formats identified in the literature include completing sentences, categorizing/sorting words or pictures, selecting words or word sequences, expressing words or word sequences, and answering yes/no or wh- questions. These tasks can be used to assess depth of vocabulary learning and knowledge (McKeown et al., 2017), as well as the issues that are known to impact children with language impairment (Brackenbury & Pye, 2005). To gain a more complete understanding of their students’ vocabulary knowledge, SLPs are encouraged to use the following recommendations:

Survey Instrument

The complete survey included questions about vocabulary assessment and intervention. Two SLPs served as consultants on the survey content. They were certified and licensed SLPs with 19 and 20 years of experience working in educational settings. Both SLPs had broad backgrounds in all aspects of language development and disorders. Working within a large school district, they held administrative positions with the primary responsibility of supporting best practice for more than 100 SLPs in each of their regions. They used their knowledge of current and best practice to provide feedback on questions and response options.

This article reports on the results of the assessment section, including these topics: (a) standardized assessments, (b) informal assessments, and (c) clinician-created tasks for identifying vocabulary deficits and for monitoring progress. Multiple-choice and multiple-answer formats were used. Response options were created from the literature review and the SLP consultants’ knowledge and experience. Respondents had the option to write in an “other” response for every question and they could skip any question they did not wish to answer. The survey is available in Supplementary Material.

Participants

Invitations were sent to 400 SLPs working in a large public school district in a Midwestern U.S. state. Reminder notices were not sent and participants were not compensated. One hundred sixty-one respondents completed the survey (40.25% response rate).

Caseload ages were primarily children of elementary (62.1%), middle (13.0%), and high school (12.4%) age. Other responses indicated combined elementary and middle school (2.5%) and combined middle and high school (3.1%), as well as all ages (5.0%). Respondents who worked in elementary (n = 100) and middle and high (n = 42) schools were included in the final analysis so that comparisons across ages could be made.

Caseload disability categories included speech and language impairment as the most frequent (78.9%), followed by autism spectrum disorder (9.9%) and intellectual disability (5.6%). Other responses (4.3%) included deaf/hard of hearing, physical disability, multiple severe disabilities, and other health impairment. A minority of participants (2.5%) worked primarily with students who speak a primary language other than English.

Most participants (98.8%) had a master’s degree as their highest degree earned; one participant had a bachelor’s degree, and one had a doctorate. The mean years’ experience was 16.42, with a range of 1 to 40.

Data Analysis

Frequency counts ( f ) and percentages were calculated for all available data, including partially complete surveys. Percentages were calculated using the number of respondents in the denominator.

Assessments for Identifying Vocabulary Deficits

Respondents indicated which standardized tests they used to identify whether a student has a vocabulary deficit. The tests were grouped by type: (a) omnibus language test, (b) comprehensive vocabulary test, and (c) single response vocabulary test. A comprehensive vocabulary test was defined as one that used multiple subtests to assess vocabulary skills (e.g., synonyms, antonyms, definitions) other than a single response type, such as word labeling or picture identification. Table 1 displays the number and percentage of respondents who selected each test. As a post hoc analysis, data were coded to determine how SLPs combined tests to identify vocabulary deficits. Fifty-four (36.5%) respondents selected only omnibus language tests, four (2.7%) selected only vocabulary-specific tests, and 86 (58.1%) selected at least one omnibus language test and at least one vocabulary-specific test.

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Table 1.

Standardized Tests for Identifying Vocabulary Deficits.

Test name	Elementary		Middle-high
	%	Frequency	%	Frequency
Omnibus Language Tests
CELF	89.00	89	85.42	41
TOLD	68.00	68	33.33	16
CASL	62.00	62	60.42	29
PLS	10.00	10	2.08	1
DELV	2.00	2	0	0
OWLS	0	0	2.08	1
Comprehensive Vocabulary Tests
LPT	20.00	20	4.17	2
CREVT	15.00	15	18.75	9
TOSS	9.00	9	0	0
ASSET	9.00	9	0	0
TOWK	1.00	1	8.33	4
Single-Word Vocabulary Tests
EOWPVT	30.00	30	20.83	10
ROWPVT	24.00	24	22.92	11
PPVT	7.00	7	4.17	2
EVT	6.00	6	6.25	3
TACL	8.00	8	4.17	2
Boehm	4.00	4	0	0
Bracken	48.00	48	0	0
Other
TOPS	21.00	21	18.75	9
Other	4.00	4	6.25	3

Note. Elementary refers to SLPs who work with elementary school-age children; middle-high refers to SLPs who work with middle school and high school students. CELF = Clinical Evaluation of Language Functions (Semel et al., 2013); TOLD = Test of Language Development (includes both primary and intermediate; Newcomer & Hammill, 2008); CASL = Comprehensive Assessment of Spoken Language (Carrow-Woolfolk, 2017); PLS = Preschool Language Scale (Zimmerman et al., 2011); DELV = Diagnostic Evaluation of Language Variation (Seymour et al., 2005); OWLS = Oral and Written Language Skills (Carrow-Woolfolk, 2011); LPT = Language Processing Test (Richard & Hanner, 2005); CREVT = Comprehensive Receptive and Expressive Vocabulary Test (Wallace & Hammill, 2013); TOSS = Test of Semantic Skills (Huisingh et al., 2004); ASSET = Assessing Semantic Skills through Everyday Themes (Barrett et al., 1988); TOWK = Test of Word Knowledge (Wiig & Secord, 1992); EOWPVT = Expressive One Word Picture Vocabulary Test (Martin & Brownell, 2011a); ROWPVT = Receptive One Word Picture Vocabulary Test (Martin & Brownell, 2011b); PPVT = Peabody Picture Vocabulary Test (Dunn, 2018); EVT = Expressive Vocabulary Test (Williams, 2018); TACL = Test of Auditory Comprehension of Language (Carrow-Woolfolk, 2014); Boehm = Boehm Test of Basic Concepts (Boehm, 2000); Bracken = Bracken Basic Concept Scale (Bracken, 2006); TOPS = Test of Problem Solving (Bowers et al., 2005); SLPs = speech-language pathologists.

Next, respondents indicated which informal assessments they felt were the most helpful for identifying vocabulary deficits. Multiple selections were allowed, as well as write-in responses. As shown in Table 2, a variety of tasks was selected, with minor differences depending on whether the SLPs worked with younger or older children. Spoken language samples (for both groups) and curricular-based measures (for the middle-high school group) were the most frequently identified tasks.

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Table 2.

Informal Assessments for Identifying Vocabulary Deficits and Monitoring Progress.

Assessment	Identifying deficits				Monitoring progress
	Elementary SLPs		Middle-high SLPs		Elementary SLPs		Middle-high SLPs
	%	Frequency	%	Frequency	%	Frequency	%	Frequency
Clinician-Created Task	42.00	42	41.67	20	75.00	75	68.75	33
Curricular-Based Measures	44.00	44	68.75	33	38.00	38	62.50	30
Dynamic Assessment	28.00	28	20.83	10	12.00	12	6.25	3
Observation	39.00	39	39.58	19	15.00	15	22.92	11
Parent Interview	15.00	15	14.58	7	2.00	2	0.00	0
Portfolio	NA	NA	NA	NA	9.00	9	12.50	6
Response to Intervention	19.00	19	8.33	4	5.00	5	8.33	4
Spoken Language Sample	77.00	77	62.5	30	24.00	24	22.92	11
Standardized Tests a	NA	NA	NA	NA	5.00	5	2.08	1
Student Interview	29.00	29	41.67	20	5.00	5	14.58	7
Teacher Interview	42.00	42	31.25	15	8.00	8	6.25	3
Written Language Sample	15.00	15	39.58	19	12.00	12	20.83	10
Other	2.00	2	10.41	5	4.00	4	2.08	1

Note. SLPs = speech-language pathologists.

a

See Table 1 for information about standardized tests for identifying deficits.

When respondents selected a clinician-created task as one of their informal assessments, a follow-up question was displayed asking respondents to specify their tasks. Results in Table 3 highlight the variety of tasks that clinicians felt were helpful for identifying vocabulary deficits. As a post hoc analysis, these tasks were categorized as simple if they did not tap into depth of word knowledge (i.e., identifying or producing definitions, matching synonyms, identifying pictures) or complex if they could measure multiple aspects of word knowledge, such as semantic, syntactic, and morphological knowledge (i.e., answering questions, judging sentences, producing sentences). The number of simple and complex tasks selected by each respondent was tallied. Of the SLPs who selected “clinician created task” for identifying deficits, 37 (88.10%) elementary SLPs selected at least one simple task (M = 2.26), and 39 (92.86%) selected at least one complex task (M = 1.90). All 20 middle-high SLP respondents (100.00%) selected at least one simple task (M = 2.40) and at least one complex task (M = 2.05).

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Table 3.

Clinician-Created Tasks for Identifying Vocabulary Deficits and Monitoring Progress.

Task	Identifying deficits				Monitoring progress
	Elementary SLPs		Middle-high SLPs		Elementary SLPs		Middle-high SLPs
	%	Frequency	%	Frequency	%	Frequency	%	Frequency
Simple Tasks
Identifying Correct Definitions	50.00	21	65.00	13	62.67	47	48.48	16
Identifying Pictures	59.52	25	30.00	6	38.67	29	18.18	6
Matching Synonyms	57.14	24	80.00	16	57.33	43	51.52	17
Providing Oral Definitions	59.52	25	65.00	13	68.00	51	51.52	17
Complex Tasks
Answering Multiple Choice Questions	28.57	12	45.00	9	37.33	28	24.24	8
Answering Wh- Questions	69.04	29	65.00	13	65.00	45	51.52	17
Judging Sentences as Correct/Incorrect	28.57	12	20.00	4	24.00	18	24.24	8
Using Target Words in Sentences	64.29	27	78.25	15	76.00	57	72.73	24
Other	2.38	1	15.00	3	12.00	9	15.15	5

Note. For identifying vocabulary deficits, percentages were calculated from 42 elementary and 20 middle-high SLP respondents who selected “clinician-created task” as a helpful technique. For monitoring progress, percentages were calculated from elementary (n = 75) and middle-high (n = 33) SLP respondents who selected “clinician-created task” as a helpful technique. SLPs = speech-language pathologists.

Assessments for Monitoring Progress

The remaining questions related to assessment techniques for monitoring progress with vocabulary goals. The options were similar to those for identifying deficits. As with previous questions, multiple selections were allowed along with write-in options. Table 2 shows the percentage and number of endorsements for each assessment type. The most frequently selected technique for monitoring progress was clinician-created tasks, which was preferred by elementary SLPs. Middle-high SLPs identified both clinician-created tasks and curricular-based measures.

Respondents who selected a clinician-created task were presented a follow-up question asking them to specify the tasks they felt were most helpful for monitoring progress. Responses are shown in Table 3. For both SLP groups, producing sentences was the most commonly selected task. Other helpful tasks were simple (such as providing and identifying oral definitions and matching synonyms) and complex (answering wh-questions), and these were selected by both SLPs groups.

Standardized Assessments

To identify vocabulary deficits, SLPs most frequently selected omnibus language tests. The Clinical Evaluation of Language Fundamentals (Semel et al., 2013), the Test of Language Development (Newcomer & Hammill, 2008), and the Comprehensive Assessment of Spoken Language (Carrow-Woolfolk, 2017) received more endorsements than any of the vocabulary-specific tests. Speech-language pathologists were most likely to use both an omnibus language test and a vocabulary-specific test to identify vocabulary deficits in children. However, many respondents reported using only language tests. These results suggested that SLPs assess vocabulary as one component of an overall evaluation for language impairment.

Each of these omnibus language tests uses multiple subtests to measure lexical skill, which is aligned with guidelines for assessing semantic relations and attributes, in addition to simple tasks such as identifying or producing labels (McKeown et al., 2017). However, it should also be noted that omnibus language tests do not measure all aspects of vocabulary knowledge. For example, none assesses knowledge of derivational morphology, which is an important factor underlying vocabulary growth during the school-age years (Anglin, 1993). Furthermore, the only standardized test to measure the process of word learning via fast mapping subtests, the Diagnostic Evaluation of Language Variation (Seymour et al., 2005), was selected by only 2.0% of elementary SLP respondents. Assessment of fast mapping allows SLPs to distinguish children who have word learning problems from children who lack exposure to the words on the tests. Thus, the language tests selected by SLPs more comprehensively measure vocabulary knowledge beyond knowing the label for a referent. Yet, additional informal assessments, such as dynamic assessment, morphological assessment, or language sample analysis, are still needed to gain a full understanding of the process of vocabulary learning and depth of word knowledge.

Single-response picture vocabulary tests, such as the Receptive One-Word Picture Vocabulary Test (Martin & Brownell, 2011b) and Expressive One-Word Picture Vocabulary Test (Martin & Brownell, 2011a), also received many endorsements. These results mirror previous survey studies that found SLPs use single-response vocabulary tests for general language impairment eligibility purposes (Betz et al., 2013; Caesar & Kohler, 2009). Single-response vocabulary tests are fast and easy to administer; however, they are limited in the information they provide about a child’s vocabulary knowledge. Comprehensive vocabulary-specific tests (those that use multiple subtests to measure vocabulary) were seldom chosen by participants, although the present survey was specifically focused on vocabulary deficits and not general eligibility. It is worth noting that the Test of Problem Solving (Bowers et al., 2005), which does not measure vocabulary, was selected more frequently than any of the comprehensive vocabulary tests. These results may reflect the reality of tests that are available to SLPs, limited time available for evaluations, as well as familiarity with single-response vocabulary tests (Caesar & Kohler, 2009). At the same time, SLPs are discouraged from choosing a test simply because it is fast, familiar, and available. Rather, SLPs should consider whether the test properties will provide the most accurate information about a student’s vocabulary knowledge.

Informal Assessments

Language sample analysis was indicated as a helpful way to identify vocabulary deficits, although it was selected much less frequently for monitoring progress. Regardless of age of students, SLPs favored spoken language samples over written language samples. Middle-high school SLPs were more likely to use written language samples compared with elementary SLPs. Language sample analysis is an evidence-based assessment technique that may be required by state educational agencies. One important point, which was not included in the current survey, is the method that SLPs used in their language sample analysis. SLPs are not likely to use the standardized protocols that are needed to identify vocabulary deficits in children (Pavelko et al., 2016). Thus, SLPs must be diligent in using standard methods for gathering, transcribing, and interpreting the language samples, if they are to be used for eligibility decisions. Time and lack of training are common reasons why SLPs do not use formal language sample analysis (Pavelko et al., 2016). These reasons may also explain why SLPs were less likely to select language sample analysis for progress monitoring purposes, despite the benefit that language samples can be repeatedly administered.

Curricular-based measures were another technique frequently selected as helpful for identifying vocabulary deficits. Middle-high school SLPs favored curricular-based measures for monitoring progress more so than elementary SLPs. It is unknown whether SLPs are using results from curricular-based measures administered by the classroom teacher or whether they are creating their own assessments. One positive implication is that curricular standards cover a wide range of vocabulary skills across academic domains. For example, Common Core English Language Arts vocabulary standards include (a) to determine or clarify the meaning of unknown and multiple-meaning words and phrases; (b) to demonstrate understanding of figurative language, word relationships, and nuances in word meanings; and (c) to acquire and use accurately a range of general academic and domain-specific words and phrases. Thus, a robust curricular-based measure may provide in-depth information about vocabulary knowledge when used in conjunction with standardized assessments of vocabulary. However, a remaining question is how curricular-based measures are used to identify disorders, as they are most typically used to measure progress (Halls-Mills, 2018). This finding could reflect federal and state requirements that to qualify for special education services, the disability must negatively impact the child’s educational performance.

Respondents also found it helpful to make their own tasks to identify vocabulary deficits and to monitor progress. These clinician-created tasks include simple pointing and labeling, as well as more complex tasks such as using words in sentences, categorizing, defining, and answering questions. These results are in line with recommendations that SLPs assess word knowledge in multiple ways and consider multiple components of word knowledge. However, the results also call into question what words SLPs are choosing when they make their own tasks: how appropriate, how difficult, and how common. For example, contrary to best practice guidelines, SLPs tend to select basic, conversational words to target, rather than more advanced general academic vocabulary (Justice et al., 2014).

Interestingly, although SLPs appear comfortable in creating their own tasks, they do not tend to use dynamic assessment as a preferred strategy. In fact, dynamic assessment was among the least frequently selected technique for identification of deficits for both groups of SLPs. A similar finding was reported over a decade ago (Caesar & Kohler, 2009). Both curricular-based measures and clinician-created tasks, which SLPs frequently selected, would be ideal for a dynamic assessment procedure. SLPs may benefit from additional training on how to use dynamic assessment protocols, such as graduated prompting or test–teach–retest, to differentiate children who have vocabulary learning deficits from those who are unfamiliar with standardized testing procedures or who lack exposure to test words. This training may also show SLPs how the dynamic assessment procedure offers a more nuanced indication of progress compared with static assessments.

Techniques Without Empirical Support

The survey results also pointed to techniques that lack strong empirical support, specifically, use of observation, student interview, and therapy data. Although observation is a general strategy that SLPs use throughout an assessment, this technique was not found in the research literature. Observation may provide important insight into how treatment impacts a student’s overall communication effectiveness. Questions about observation include what settings and linguistic contexts are being observed? How is observation different than a poorly executed language sample? How does observation assess depth of knowledge, such as syntactic role, semantic features, relations, attributes, or connotations? Questions also remain regarding use of therapy data. What data are being collected? What cues are used? Is generalization included? What standard is used for mastery? Student interview also received a surprising number of endorsements for identifying deficits by middle-high school SLPs. Although teacher and parent report have some research base, student interview does not. Questions include whether student interview is a kind of language sampling procedure, whether SLPs are taking note of vocabulary used during the interview, or whether SLPs are seeking student insight into their vocabulary difficulty.

Limitations and Future Directions

As with any survey design, a major limitation is response bias. SLPs who have an interest in vocabulary may have been more likely to respond, raising questions about how well the responses generalize to other school-based SLPs. In addition, because requirements for educational assessment vary by state, it is possible that geographical location would impact how other SLPs would respond to the survey questions. Additional research is needed to identify how practice patterns may differ by years of experience, caseload, setting, and location.

The survey results provide important information about the clinical expertise component of evidence-based practice by highlighting not what SLPs currently do, but by asking what they think is most helpful. The results showcase areas that would benefit from additional research. For example, future work should identify how SLPs combine standardized and informal assessment results to identify vocabulary deficits and to write therapy goals. Also important to understand is how assessment practices may vary based on a student’s age, English language skills, and dialect. Finally, the use of therapy data, observation, and student interview in both eligibility and progress monitoring should be further investigated, as these were frequently identified techniques that do not currently have an evidence base.

Conclusion

The current survey study was undertaken to identify SLPs’ perspectives regarding vocabulary assessment techniques. For standardized tests, SLPs were most likely to identify omnibus language tests and vocabulary-specific single-word tests. Among the least commonly selected tests were comprehensive vocabulary-specific tests and one that assessed fast mapping. For identifying vocabulary deficits, language sample analysis and curricular-based measures were the most frequently selected. For monitoring progress toward vocabulary goals, clinician-created tasks and curricular-based measures were most frequently selected. The vocabulary assessment preferences of elementary and middle-high school SLPs tended to be similar, with minor differences noted with middle-high SLPs favoring written language samples and curricular-based measures.

Supplemental Material