Phan, A. M., & Metera, J., & Fereidooni, S., & Yang, C., & Kim, M., & Sandoval, C. L., & Truong, P. (2024, June), WIP: A Novel Learning Log Application for Classifying Learning Events Using Bloom’s Taxonomy  Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. https://peer.asee.org/48285

\bibitem{asee_peer_48285}
  Phan, A. M., \& Metera, J., \& Fereidooni, S., \& Yang, C., \& Kim, M., \& Sandoval, C. L., \& Truong, P. (2024, June), \emph{WIP: A Novel Learning Log Application for Classifying Learning Events Using Bloom’s Taxonomy}
  Paper presented at 2024 ASEE Annual Conference \& Exposition, Portland, Oregon.
  https://peer.asee.org/48285

Alex M. Phan, Jenna Metera, Sonia Fereidooni, Cham Yang, Minju Kim, Carolyn L. Sandoval, and Phuong Truong.  "WIP: A Novel Learning Log Application for Classifying Learning Events Using Bloom’s Taxonomy".  2024 ASEE Annual Conference & Exposition, Portland, Oregon, 2024, June.  ASEE Conferences, 2024.  https://peer.asee.org/48285 Internet.  30 Jul, 2024

\bibitem{asee_peer_48285}
  Alex M. Phan, Jenna Metera, Sonia Fereidooni, Cham Yang, Minju Kim, Carolyn L. Sandoval, and Phuong Truong.
  "WIP: A Novel Learning Log Application for Classifying Learning Events Using Bloom’s Taxonomy".
  \emph{2024 ASEE Annual Conference \& Exposition, Portland, Oregon, 2024, June}.
  ASEE Conferences, 2024.
  https://peer.asee.org/48285 Internet.  30 Jul, 2024

@INPROCEEDINGS{asee_peer_48285
author = "Alex M. Phan, Jenna Metera, Sonia Fereidooni, Cham Yang, Minju Kim, Carolyn L. Sandoval, and Phuong Truong"
title = "WIP: A Novel Learning Log Application for Classifying Learning Events Using Bloom’s Taxonomy"
booktitle = "2024 ASEE Annual Conference \& Exposition"
year = "2024"
month = "June"
address = "Portland, Oregon"
publisher = "ASEE Conferences"
note = {https://peer.asee.org/48285}
}

TY  - CPAPER
AB  - Learning can be a daunting and challenging process, particularly in engineering.  While cognitive models for learning such as Bloom's taxonomy have been developed since the 1950s and evidenced to be useful in designing engineering courses, these models are not commonly explicitly taught in classrooms to help students manage and regulate their own learning. In highly demanding curriculum such as engineering, ineffective strategies can lead to poor academic performance that cascades throughout a student’s academic career. Feedback from traditional examinations often do not provide personalized and actionable changes to study habits (i.e., with suboptimal scores, students may know they need to study more, but whether “more” is effective is often unclear). There is a pressing need to bridge the gap between study practices and learning outcomes that enable students to regulate and improve their own learning strategies in engineering. This work in progress paper presents initial data from a novel “learning log” application that allows students to enter their studying activity (e.g., timed practice exam, redoing homework, reading the textbook, practice problems), and labels the cognition level (using Bloom's taxonomy: remember, understand, apply, analyze, evaluate, create). In this work in progress, we present initial data from students’ logged studying activities using the application. The logging allows students to track their cognition distribution over time, providing data about how they engaged with course content. 
AU  - Alex M. Phan
AU  - Jenna Metera
AU  - Sonia Fereidooni
AU  - Cham Yang
AU  - Minju Kim
AU  - Carolyn L. Sandoval
AU  - Phuong Truong
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - WIP: A Novel Learning Log Application for Classifying Learning Events Using Bloom’s Taxonomy
UR  - https://peer.asee.org/48285
ER  -