@inproceedings{5315c86699bb40f1b25fe1b47c4505d9,
title = "Top concept networks of professional education reflections",
abstract = "This study explores the application of computational techniques to extract information about dental students' developing conceptions of their profession from digital reflective journal entries. Top concept networks were created for two cohorts of students at the beginning and end of their four-year program. A shift from a collection of general notions about becoming a professional to a more integrated, patient-centered conceptualization was found for both cohorts. The two groups initially differed in their perception of dental school (a mechanism for being able to work as a dentist versus a place to learn the skills to serve patients well) and subsequently in the extent of attention they paid to the feelings of their patients and themselves, as well as the continual growth of skill after graduation. Several useful linguistic markers were identified for examining these same issues in other cohorts. The results suggest that top concept networks can offer a useful window into students' developing conceptions of their profession. This kind of information can support student success on a macro level by offering feedback on existing curricula / informing learning designs to cultivate desired conceptions, and on a micro level through identifying particular ways individuals align with and diverge from the common trajectories.",
keywords = "Concept network, Professional education, Reflection",
author = "Wise, {Alyssa Friend} and Yi Cui",
note = "Publisher Copyright: {\textcopyright} 2019 Copyright is held by the owner/author(s).; 9th International Conference on Learning Analytics and Knowledge, LAK 2019 ; Conference date: 04-03-2019 Through 08-03-2019",
year = "2019",
month = mar,
day = "4",
doi = "10.1145/3303772.3303840",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "260--264",
booktitle = "Proceedings of the 9th International Conference on Learning Analytics and Knowledge",
}