Using Generative Text Models to Create Qualitative Codebooks for Student Evaluations of Teaching
Feedback is a critical aspect of improvement. Unfortunately, when there is a lot of feedback
from multiple sources, it can be difficult to distill the information into actionable insights …
from multiple sources, it can be difficult to distill the information into actionable insights …
Assessing Student Conceptual Understanding: Supplementing Deductive Coding with Natural Language Processing Techniques
C Arbogast - 2016 - ir.library.oregonstate.edu
Assessing student conceptual understanding is a valuable method for gauging specific
student learning outcomes but can be difficult and time consuming to measure. This …
student learning outcomes but can be difficult and time consuming to measure. This …
[PDF][PDF] Pilot study on applying natural language processing techniques to classify student responses to open-ended problems to improve peer review assignments
M Verleger - ASEE Annual Conference, 2015 - coed.asee.org
As an educational tool, peer review can be a valuable way to provide students feedback
without a significant increase in instructor workload. Despite all that is currently known about …
without a significant increase in instructor workload. Despite all that is currently known about …
[引用][C] Using natural language processing to facilitate student feedback analysis
What the Heck is that?! Adaptation of evidence-based instructional practices
JJ Pembridge, M Verleger… - 2015 IEEE Frontiers in …, 2015 - ieeexplore.ieee.org
Numerous avenues exist for faculty to learn about new pedagogical techniques, but these
techniques rarely make it into practice, even by experienced and motivated engineering …
techniques rarely make it into practice, even by experienced and motivated engineering …
[引用][C] Applying natural language processing techniques to an assessment of student conceptual understanding
CA Arbogast, D Montfort - 2016 ASEE Annual Conference & Exposition, 2016
[引用][C] Board# 147: Go With Your Gut!–Using Low-Time-Investment Evaluations of Student Work for Identifying High versus Low Quality Responses
MA Verleger - 2017 ASEE Annual Conference & Exposition, 2017