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Therapy Goal Bank

Pre-written, fillable goal templates in SMART format across every domain, free to copy into your documentation. Replace the blanks with your own client, target, cue level and criterion.

Goals
116
Domains
8
Login
None
Cost
Free

The format every goal follows

[Client] will <do the thing>, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

The behavior
What the client will actually do, and at what level - isolation, word, phrase, sentence, conversation.
The support
How many cues and of what type: verbal, visual, tactile, gestural, or a model. "No more than 2 verbal cues" is more useful than "minimal cues".
The criterion
The accuracy percentage. Pick it off the baseline, not off a template.
The timeframe
How many consecutive sessions, so a single good day does not close the goal.
The measurement
How you will know. SLP data collection for most; a log, self-rating or partner report where that fits better.

How to use these

  • Every goal is a template. The blanks - written ___ - are yours to fill: the target, the number and type of cues, the accuracy, the number of sessions.
  • The cue slot takes two things, a number and a type: "no more than 2 verbal cues", "minimal tactile cues", "a model only". A bare "minimal cues" is hard to score and harder to defend.
  • "[Client]" is there so a name or "the student" drops straight in. Swap the pronoun to whatever the client uses.
  • Accuracy percentages and session counts are deliberately left blank. A number that is right for a 4-year-old establishing /k/ is wrong for a 10-year-old generalizing /r/ into conversation, and a bank cannot make that call for you.
  • Delete any slot that does not apply in your setting rather than leaving a blank in it. A goal with an unfilled blank reads as an unfinished goal.

These are templates, not clinical advice

These are documentation templates, not clinical recommendations. Choosing a target, a baseline, a cue level and a criterion is a clinical judgment that depends on assessment data, the setting, and eligibility rules that vary by state and district. Nothing here substitutes for your own evaluation, and nothing here has been reviewed against any particular district or payer requirements.

116 goals across 8 domains

Articulation and Phonology

Speech sound production, from isolation through conversation, plus pattern-based phonological targets.

Word lists for every sound and blend The practice ladder on each sound page matches the levels these goals step through.

  1. 1

    [Client] will produce /___/ in isolation, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  2. 2

    [Client] will produce /___/ in ___ syllable shapes (CV, VC, CVC), given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  3. 3

    [Client] will produce /___/ in the ___ position of single words, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  4. 4

    [Client] will produce /___/ in all word positions at the single-word level, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  5. 5

    [Client] will produce /___/ in two- to three-word phrases, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  6. 6

    [Client] will produce /___/ in self-generated sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  7. 7

    [Client] will produce /___/ during structured reading or picture description for ___ minutes, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  8. 8

    [Client] will produce /___/ during ___ minutes of conversational speech, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  9. 9

    [Client] will produce the ___ consonant cluster in single words, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  10. 10

    [Client] will produce vocalic /r/ in the ___ variation (AIR, AR, EAR, IRE, OR, ER) at the word level, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  11. 11

    [Client] will suppress ___ by producing the contrasting sound in minimal pairs, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  12. 12

    [Client] will produce all syllables in ___-syllable words, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  13. 13

    [Client] will produce final consonants in CVC words, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  14. 14

    [Client] will identify their own error productions of /___/ when presented with a recorded sample, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  15. 15

    [Client] will self-correct error productions of /___/ during structured conversation, independently, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  16. 16

    [Client] will be judged ___% intelligible by an unfamiliar listener during a ___-minute conversational sample, across ___ consecutive sessions, as measured by SLP data collection.

Grammar and Syntax

Morphology and sentence structure: tense, number, agreement, pronouns, helping verbs and sentence expansion.

Grammar topics with printable worksheets Each topic page carries an explainer, expected ages and a worksheet with an answer key.

  1. 1

    [Client] will produce regular past tense -ed verbs in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  2. 2

    [Client] will produce ___ irregular past tense verbs in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  3. 3

    [Client] will produce the present progressive form (is/are + verb-ing) in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  4. 4

    [Client] will produce regular plural -s in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  5. 5

    [Client] will produce ___ irregular plural forms in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  6. 6

    [Client] will produce third person singular -s on verbs in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  7. 7

    [Client] will produce subject pronouns (he, she, they) with correct case in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  8. 8

    [Client] will produce object pronouns (him, her, them) with correct case in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  9. 9

    [Client] will produce possessive pronouns in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  10. 10

    [Client] will produce reflexive pronouns (himself, herself, themselves) in sentences, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  11. 11

    [Client] will produce the copula "be" (is, am, are) in ___ contexts, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  12. 12

    [Client] will produce the auxiliary "be" preceding present progressive verbs, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  13. 13

    [Client] will form yes/no questions using an auxiliary verb, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  14. 14

    [Client] will produce grammatically complete negative sentences using do/does/did + not, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  15. 15

    [Client] will produce modal and semi-modal verbs (can, will, should, have to) and request verbs (want, need) to request or refuse, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  16. 16

    [Client] will produce spatial prepositions in sentences describing a pictured scene, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  17. 17

    [Client] will combine two ideas into one compound sentence using a conjunction, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  18. 18

    [Client] will expand a ___-word utterance into a grammatically complete sentence of at least ___ words, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  19. 19

    [Client] will identify and correct a grammatical error in a clinician-produced sentence, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

Expressive Language

Labeling, describing, categorizing, answering questions and telling a connected story.

  1. 1

    [Client] will label ___ items from ___ categories, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  2. 2

    [Client] will name ___ items in a given category within ___ seconds, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  3. 3

    [Client] will describe a familiar object using at least ___ attributes (category, function, size, color, parts), given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  4. 4

    [Client] will state the function of ___ common objects, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  5. 5

    [Client] will state how two items are similar and how they differ, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  6. 6

    [Client] will answer ___ WH-question types about a short passage, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  7. 7

    [Client] will request an object or action using at least ___ words, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  8. 8

    [Client] will retell a familiar story including character, setting and at least ___ events in sequence, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  9. 9

    [Client] will narrate a personal experience with a clear beginning, middle and end, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  10. 10

    [Client] will give step-by-step instructions for a familiar activity in the correct order, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  11. 11

    [Client] will produce a mean length of utterance of at least ___ morphemes across a ___-utterance language sample, across ___ consecutive sessions, as measured by SLP data collection.

  12. 12

    [Client] will define ___ grade-level vocabulary words using category plus at least one attribute, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  13. 13

    [Client] will use a repair strategy (restating, adding detail, rephrasing) when a listener signals confusion, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  14. 14

    [Client] will predict a plausible outcome for a described situation and give a reason, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

Receptive Language

Following directions, identifying concepts and vocabulary, and comprehending what is heard.

Language concepts, with worksheets Spatial, temporal, quantitative and descriptive concepts, and following directions.

  1. 1

    [Client] will follow ___-step directions without embedded concepts, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  2. 2

    [Client] will follow ___-step directions containing ___ embedded concepts, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  3. 3

    [Client] will identify ___ spatial concepts on request, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  4. 4

    [Client] will identify ___ quantitative concepts (all, some, none, more, few) on request, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  5. 5

    [Client] will identify ___ temporal concepts (before, after, first, last) on request, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  6. 6

    [Client] will identify ___ descriptive concepts (color, size, shape, texture) on request, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  7. 7

    [Client] will point to the named item from a field of ___, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  8. 8

    [Client] will identify the correct answer to ___ WH-question types about a short passage, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  9. 9

    [Client] will indicate whether a question asks about a person, a place, a time or a reason, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  10. 10

    [Client] will identify the item that does not belong in a set of ___ and state why, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  11. 11

    [Client] will demonstrate comprehension of ___ grade-level vocabulary words by matching each to a picture or definition, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  12. 12

    [Client] will indicate non-comprehension by asking for repetition or clarification, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  13. 13

    [Client] will answer inferential questions about a short narrative, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

Social and Pragmatic Language

Turn-taking, topic maintenance, perspective-taking, conversational repair and register.

  1. 1

    [Client] will initiate an interaction with a peer or adult, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  2. 2

    [Client] will take at least ___ conversational turns on a partner-selected topic, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  3. 3

    [Client] will maintain a topic across at least ___ exchanges before introducing a new one, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  4. 4

    [Client] will ask a follow-up question related to a partner's comment, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  5. 5

    [Client] will signal a topic change with an appropriate transition phrase, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  6. 6

    [Client] will identify how another person is likely feeling in a described situation and state one reason, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  7. 7

    [Client] will identify a speaker's intent when the words and tone conflict (teasing, sarcasm, reluctance), given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  8. 8

    [Client] will repair a communication breakdown by rephrasing or adding information when asked to clarify, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  9. 9

    [Client] will request help or clarification using a complete sentence, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  10. 10

    [Client] will use a greeting and a closing appropriate to the listener and setting, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  11. 11

    [Client] will adjust volume, wording or formality for a stated audience (teacher, friend, younger child), given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  12. 12

    [Client] will join an activity already in progress using an appropriate entry strategy, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  13. 13

    [Client] will state their own position and acknowledge a differing one during a structured disagreement, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  14. 14

    [Client] will wait for a natural pause before speaking, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

Fluency

Stuttering management: strategy use, self-monitoring, and the attitudes and avoidance that come with it.

  1. 1

    [Client] will identify moments of stuttering in their own speech during a ___-minute sample, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  2. 2

    [Client] will identify moments of stuttering in a recorded or clinician-produced sample, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  3. 3

    [Client] will describe what their speech mechanism is doing during a moment of stuttering, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  4. 4

    [Client] will use ___ (easy onset, light articulatory contact, prolonged speech) at the ___ level, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  5. 5

    [Client] will use a pull-out or cancellation on a moment of stuttering, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  6. 6

    [Client] will use ___ strategy during structured conversation with the clinician for ___ minutes, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  7. 7

    [Client] will use ___ strategy during conversation with an unfamiliar listener, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  8. 8

    [Client] will speak in a ___ situation (classroom, telephone, ordering) while using ___ strategy, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  9. 9

    [Client] will identify one avoidance behavior and substitute an approach behavior, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  10. 10

    [Client] will explain stuttering to a listener in their own words, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  11. 11

    [Client] will self-advocate by stating what a listener can do to help, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  12. 12

    [Client] will rate their own speech comfort and strategy use after a speaking task, with self-ratings agreeing within ___ points of clinician ratings across ___ consecutive sessions, as measured by SLP data collection.

  13. 13

    [Client] will participate in ___ speaking situations previously reported as avoided, across ___ consecutive weeks, as measured by a daily log and SLP report.

Voice

Vocal hygiene, healthy production, resonance and carryover of a target voice into conversation.

  1. 1

    [Client] will identify ___ phonotraumatic behaviors (shouting, throat clearing, hard glottal onsets) and a healthier substitute for each, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  2. 2

    [Client] will follow the agreed vocal hygiene plan, across ___ consecutive weeks, as measured by a daily log and SLP report.

  3. 3

    [Client] will produce ___ (resonant voice, easy onset, forward focus) at the word level, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  4. 4

    [Client] will produce the target voice quality in phrases, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  5. 5

    [Client] will produce the target voice quality in sentences and structured reading, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  6. 6

    [Client] will carry the target voice quality into ___ minutes of conversation, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  7. 7

    [Client] will maintain appropriate loudness for the listening environment, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  8. 8

    [Client] will maintain pitch within their target range during ___ tasks, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  9. 9

    [Client] will discriminate between a healthy and an effortful production in a paired sample, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  10. 10

    [Client] will identify early signs of vocal fatigue and apply a compensatory strategy, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  11. 11

    [Client] will use ___ breath support pattern during connected speech, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  12. 12

    [Client] will self-rate vocal effort after a speaking task, with self-ratings agreeing within ___ points of clinician ratings across ___ consecutive sessions, as measured by SLP data collection.

AAC

Core vocabulary, combining words, communicative functions, device navigation and partner-supported use.

Helping verbs and modals as core vocabulary The helping-verb and modal pages flag which targets are preloaded core vocabulary on most systems.

  1. 1

    [Client] will use their AAC system to produce ___ core vocabulary words, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  2. 2

    [Client] will combine ___ symbols or words on their AAC system to produce a message, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  3. 3

    [Client] will use their AAC system to request a desired item or action, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  4. 4

    [Client] will use their AAC system to protest or refuse using a symbolic message rather than a behavior, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  5. 5

    [Client] will use their AAC system to comment on an activity or object, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  6. 6

    [Client] will use their AAC system to ask a question, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  7. 7

    [Client] will use their AAC system to greet and to close an interaction, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  8. 8

    [Client] will navigate to a target vocabulary page and produce the intended message within ___ seconds, given ___ ___ cues, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  9. 9

    [Client] will use their AAC system across ___ different activities or settings within the day, across ___ consecutive weeks, as measured by a daily log and SLP report.

  10. 10

    [Client] will use their AAC system with ___ different communication partners, across ___ opportunities per session, as measured by SLP observation and communication partner report.

  11. 11

    [Client] will repair a breakdown on their AAC system by reselecting, adding a word or navigating to another page, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  12. 12

    [Client] will use their AAC system to direct a partner's action (stop, go, more, help, my turn), given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  13. 13

    [Client] will retrieve and power on their AAC system at the start of ___ activities, independently, with ___% accuracy across ___ consecutive sessions, as measured by SLP data collection.

  14. 14

    [Client] will indicate when a needed word is missing from their AAC system, given ___ ___ cues, across ___ opportunities per session with ___% accuracy, as measured by SLP data collection.

  15. 15

    Communication partners will model aided language on [Client]'s AAC system, across ___ opportunities per session, as measured by SLP observation and communication partner report.

Original wording

Every goal here was written for this site. The category names are standard clinical terminology, but no goal is adapted from another goal bank. If you spot one that reads awkwardly or asks for something unmeasurable, tell me and it gets fixed.