Purpose There has been increased interest in using telepractice for involving more diverse children in research and clinical services, as well as when in-person assessment is challenging, such as during COVID-19. Little is known, however, about the feasibility, reliability, and validity of language samples when conducted via telepractice. Method Child language samples from parent–child play were recorded either in person in the laboratory or via video chat at home, using parents' preferred commercially available software on their own device. Samples were transcribed and analyzed using Systematic Analysis of Language Transcripts software. Analyses compared measures between-subjects for 46 dyads who completed video chat language samples versus 16 who completed in-person samples; within-subjects analyses were conducted for a subset of 13 dyads who completed both types. Groups did not differ significantly on child age, sex, or socioeconomic status. Results The number of usable samples and percent of utterances with intelligible audio signal did not differ significantly for in-person versus video chat language samples. Child speech and language characteristics (including mean length of utterance, type–token ratio, number of different words, grammatical errors/omissions, and child speech intelligibility) did not differ significantly between in-person and video chat methods. This was the case for between-group analyses and within-child comparisons. Furthermore, transcription reliability (conducted on a subset of samples) was high and did not differ between in-person and video chat methods. Conclusions This study demonstrates that child language samples collected via video chat are largely comparable to in-person samples in terms of key speech and language measures. Best practices for maximizing data quality for using video chat language samples are provided.

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Despite increasing emphasis on emergent brain‐behavior patterns supporting language, cognitive, and socioemotional development in toddlerhood, methodologic challenges impede their characterization. Toddlers are notoriously difficult to engage in brain research, leaving a developmental window in which neural processes are understudied. Further, electroencephalography (EEG) and event‐related potential paradigms at this age typically employ structured, experimental tasks that rarely reflect formative naturalistic interactions with caregivers. Here, we introduce and provide proof of concept for a new “Social EEG” paradigm, in which parent–toddler dyads interact naturally during EEG recording. Parents and toddlers sit at a table together and engage in different activities, such as book sharing or watching a movie. EEG is time locked to the video recording of their interaction. Offline, behavioral data are microcoded with mutually exclusive engagement state codes. From 216 sessions to date with 2‐ and 3‐year‐old toddlers and their parents, 72% of dyads successfully completed the full Social EEG paradigm, suggesting that it is possible to collect dual EEG from parents and toddlers during naturalistic interactions. In addition to providing naturalistic information about child neural development within the caregiving context, this paradigm holds promise for examination of emerging constructs such as brain‐to‐brain synchrony in parents and children.

The COVID-19 pandemic has impacted data collection for longitudinal studies in developmental sciences to an immeasurable extent. Restrictions on conducting in-person standardized assessments have led to disruptive innovation, in which novel methods are applied to increase participant engagement. Here, we focus on remote administration of behavioral assessment. We argue that these innovations in remote assessment should become part of the new standard protocol in developmental sciences to facilitate data collection in populations that may be hard to reach or engage due to burdensome requirements (e.g., multiple in-person assessments). We present a series of adaptations to developmental assessments (e.g., Mullen) and a detailed discussion of data analytic approaches to be applied in the less-than-ideal circumstances encountered during the pandemic-related shutdown (i.e., missing or messy data). Ultimately, these remote approaches actually strengthen the ability to gain insight into developmental populations and foster pragmatic innovation that should result in enduring change.

Although language samples are child-friendly and well-suited for obtaining global measures of language production, structured protocols have the potential to elicit many different exemplars of language structures in a shorter amount of time. We created a structured elicitation protocol, the Sentence Diversity Priming Task (SDPT), to efficiently assess sentence diversity in toddlers via video chat platforms. Sentence diversity is operationalized as the number of different subjectverb combinations in active declarative sentences. The task is presented as an animated picture book, with parents serving as the child's primary partner during administration. In this article, we provide the rationale for assessing sentence diversity, describe the task, and present preliminary analyses of compliance and developmental associations for 32 typically developing toddlers, 30-35 months old, with average language abilities. The preliminary findings suggest that the SDPT is an engaging task that holds toddlers' attention, reveals robust individual differences in their ability to produce sentences, is positively correlated with parent-reported language measures, and has the potential for assessing children's language growth over time. Finally, recommendations and tips for developing and remotely administering the protocol are provided, with an emphasis on encouraging parent involvement and increasing toddler compliance.