Assessment of Language in Children and Adolescents in Clinical and Educational Contexts (Speech-Language Pathology)

Team members

Felipe Torres-Morales and Marcela Vega from Universidad de Chile, Santiago, Chile.

Programs/courses

Assessment of Language in Children and Adolescents in Clinical and Educational Contexts (Speech-Language Pathology)

How have you used Clinical Mind AI in your teaching or research?

We used Clinical Mind AI as part of the course Assessment of Language in Children and Adolescents in Clinical and Educational Contexts, taught to 37 third-year Speech-Language Pathology students at Universidad de Chile.

Clinical Mind AI was incorporated as a formative learning activity designed to prepare students to conduct a clinical interview. We developed a virtual case in which students interacted individually with an AI-simulated mother of a child with a language disorder associated with intellectual disability.

During the activity, students were required to conduct the interview by asking the virtual mother relevant clinical questions, simulating an authentic interaction with a caregiver. The case included a set of key interview items that students were expected to address.

We also incorporated an assessment rubric into Clinical Mind AI. For each expected interview item, the platform automatically identified whether the student had addressed it (0 = not addressed; 1 = addressed). At the end of the interaction, each student received automated individualized feedback based on their performance.

Importantly, this activity was embedded within a broader sequence of progressively more authentic clinical learning experiences. The Clinical Mind AI activity served as preparation for a subsequent assessed clinical interview with a standardized patient in the Clinical Skills Center. This was followed by practical learning experiences in real educational and clinical settings. In this way, the AI-based simulation provided students with an initial, low-stakes opportunity to practice clinical interviewing before progressing to interactions with standardized and real patients.

What impact or benefits have you observed for your students or teaching practice?

The activity helped students develop core clinical interviewing skills, particularly their ability to identify and formulate relevant questions according to the patient's reason for consultation and the specific characteristics of the case.

One of the main benefits was the opportunity to practice and progressively automate the more structured components of a clinical interview. Through the interaction with the AI-simulated caregiver and the immediate feedback provided by the platform, students could recognize which areas they had adequately explored and which relevant questions they had omitted.

Students also reported feeling more confident and less exposed during this initial practice because the activity was completed individually in a low-stakes environment. They could make mistakes, reconsider their questions, and learn from the feedback without the pressure of being observed by peers, instructors, or a standardized patient.

We recognize that an AI-based interaction does not fully reproduce the socioemotional and interpersonal dimensions of a clinical interview, which are essential in Speech-Language Pathology practice. However, this was precisely why we integrated Clinical Mind AI as an initial step within a broader learning sequence. By first strengthening and automating the content and structure of clinical questioning, students could subsequently focus more attention on communication, empathy, responsiveness, and other interpersonal skills when interacting with standardized patients and, later, with real patients in clinical and educational settings.

From a teaching perspective, Clinical Mind AI therefore provided a useful bridge between classroom-based preparation and progressively more authentic clinical experiences.