Using AI and Cognitive Apprenticeship to Improve the Writing Capacity of Nursing Students

Audience Level: 
All
Session Time Slot(s): 
Institutional Level: 
Higher Ed
Streamed: 
Streamed
Special Session: 
Research
Diversity & Inclusion
Abstract: 

Discover how to use artificial intelligence to assess college students’ scholarly writing performance. Learn how to apply the cognitive apprenticeship model to instructional design to improve students’ writing success in one semester. Mixed methods from a quasi-experimental research study will also be shared and recommendations for improving educational equity in higher ed.

Extended Abstract: 

Dr. Red Wolf will share the results from her Ed.D. dissertation, “Exploring the Scholarly Writing Development of Master’s Nursing Students.” Rebecca evaluated the effectiveness of a Writing Workshop course in developing students’ writing capacity and self-efficacy and found significant gains in both with large effect sizes. The interviewed students discussed transformations in their scholarly writing, critical thinking, professional communication skills, and confidence after participating in the course. Several of these students identified as non-native English speakers. Artificial intelligence was used to assess students’ pre- and post-course writing performance. The instructional design of the writing course and self-efficacy survey will be shared. Handouts on the instructional design and cognitive apprenticeship model will also be provided. Attendees will learn about brand new research results with recommendations on how to improve students’ writing success through AI assessment, instructional design, and a cognitive apprenticeship approach. (If I am allowed to present in a more interactive format, I would love to share samples of students’ writing and have attendee’s review the samples in small groups so they can learn how to use formative feedback to improve writing instruction!)

 

 

Conference Track: 
Research, Evaluation, and Learning Analytics
Session Type: 
Discovery Session Asynchronous
Intended Audience: 
Administrators
Faculty
Instructional Support
Students
Training Professionals
All Attendees
Researchers