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Beyond Borders, Beneath Words: Using Natural Language Processing to Map Student Reflections on International Service
Alexandra L Borstad1,2,3,4,5, Susan A Appling1,2,3,4,5, Anne D Kloos1,2,3,4,5
1Alexandra L. BorstadE is a clinical professor in the Department of Physical Therapy at Oregon State University - Cascades, 1500 SW Chandler Ave, Bend, OR 97702 ( alexandra.borstad@osucascades.edu ). Please address all correspondence to Alexandra L. Borstad.
Introduction:
Advances in artificial intelligence (AI) offer physical therapy educators opportunities to improve student learning. We applied AI to identify themes and determine the extent to which physical therapy professional values were reflected upon by students during a high-impact international service learning (ISL) course in México.
Review Of Literature:
Natural language processing (NLP), a subfield of AI, organizes and interprets language nuances, efficiently providing insight into the meaning expressed in written work. Efficient methods to measure written work are needed.
Subjects:
Reflection statements (n = 802) from 21 third-year, Doctor of Physical Therapy students were analyzed.
Methods:
Natural language processing methods executed in the R statistical software were K-means clustering to parse reflections by theme, and the semantic distance metric, cosine similarity (cos θ), to quantify the similarity of meaning between reflections and 7 physical therapy professional values.
Results:
Using NLP, 3 themes emerged in the reflections: educating patients and caregivers, providing new treatment ideas, and learning about a different culture. Eighty-four percent of reflections were highly similar (cos θ = 0.59) to the value excellence. Reflections were also highly similar to integrity (cos θ = 0.61) and compassion and caring (cos θ = 0.51) and least similar to professional duty (cos θ = 0.24). Reflections on the theme of learning about a different culture were most similar to 5 of the 7 values compared with other themes.
Discussion And Conclusion:
Natural language processing enabled a detailed understanding of the values woven throughout students' written reflections on ISL. The experience implicitly promoted the development of physical therapy core values, in particular excellence, affirming it as a high-impact educational practice for professional development. Natural language processing's automated, quantitative, and debiased outcomes advance reflection analytics, an example of one of the new and powerful approaches AI offers educators and researchers that will transform our field.
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