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Title:Crafting an innovative model for developing an online data curriculum
Author(s):Murillop, Angela P.
Subject(s):Library and information science
Data science
Undergraduate education
Online education
Program development
Abstract:This poster presents the preliminary findings and observations of developing the undergraduate Applied Data and Information Science (ADIS) Bachelor of Science program. The ADIS program incorporates competencies and skillsets from Library and Information Science and Data Science and is an interdisciplinary collaboration between an LIS Department and a Human-Centered Computing department. The LIS courses in this program are online asynchronous courses. This poster presents the preliminary findings and observations regarding program development, curriculum development, course development, and online course delivery to undergraduates. This poster will present the LIS and data science models and frameworks that were utilized to develop the program learning outcomes from the program development perspective. This poster will discuss the specific LIS and data science competencies embedded into the curriculum from the curriculum development perspective. This poster will present examples of how specific data skill sets and competencies are incorporated into the course from the course development perspective. Lastly, this course will discuss best practices for delivering hands-on data-related curriculum to undergraduates in an online environment from an online course delivery perspective. Although this poster focuses on undergraduate program development, similar models can be used for the creation of masters-level data-related program development, as well as the lessons learned from the delivery of online asynchronous hands-on data-related courses. Strategic partnerships, data-related curriculum, and online course delivery are highly relevant for all levels of current and future LIS education and program development.
Issue Date:2021-09-20
Series/Report:Education of information professionals
Education programs/schools
Data science
Data management
Genre:Conference Poster
Date Available in IDEALS:2021-09-17

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