The OAKTrust Digital Repository
The OAKTrust digital repository at Texas A&M is a digital service that collects, preserves, and distributes the scholarly output of the University. The repository facilitates open access scholarly communication while preserving the scholarly legacy of the Texas A&M community.
Recent Submissions
DATA: Household clusters of SARS-CoV-2 Omicron subvariants contemporaneously sequenced from dogs and their owners
(2024) Ferreira, Francisco; Hamer, Gabriel; Hamer, Sarah
Household clusters of SARS-CoV-2 Omicron subvariants contemporaneously sequenced from dogs and their owners
(2024) Ferreira, Francisco; Hamer, Gabriel; Hamer, Sarah
Zenji: Heuristic Algorithms to Identify and Correct Common Japanese Kanji Handwriting Mitakes
(Texas A&M University. Undergraduate Research. Department of Computer Science and Engineering., 2024-12) Broberg, Cole; Taele, Paul
The kanji writing system—tens of thousands of logographic Japanese characters originating from China—is by far the most complex of the three Japanese scripts. Kanji present a unique challenge for English-speaking Japanese learners, as they lack an equivalent in western tongues. Whether studying in a classroom or independently, Japanese language learners are often exposed to mnemonics or other techniques to aid in the memorization of these symbols. However, the classroom setting presently provides a unique opportunity for learners to hand-write the characters and receive feedback on their writing. The difficulty and lack of feedback on handwriting for independent learners discourages the practice of hand-writing kanji, which can stunt the learning process. This paper introduces Zenji, a system of heuristic algorithms to analyze student handwriting of kanji. Zenji provides a lightweight solution that may easily be run on students’ personal computing devices and naturally integrated into existing mobile spaced-repetition solutions for kanji learning. The Zenji system provides users overall and per-stroke numeric, visual, and written feedback on various metrics, focusing on common mistakes. In validation testing, Zenji’s feedback proved to be highly accurate across the categories that it assesses, highlighting user errors and combining a classroom-like learning experience with the flexibility of independent study.
GSIS Newsletter | Number 164 | February 1997
(Geoscience Information Society, 1997) GSIS
Fueling the mind, feeding the world: Decision making – Thinking abstractly about problems (DM07)
(Texas A&M University. Department of Agricultural Leadership, Education, and Communications, 2024) Esquivel, Christi; Murphrey, Theresa Pesl; Richburg, Audra; Leggette, Holli R.
This packet contains instructional materials and online modules prepared for Fueling the mind, feeding the world: Decision making – Thinking abstractly about problems (DM07). It includes curriculum, PowerPoint slides, activities, handouts, grading considerations, and notes for instructors. These materials were created as part of the USDA Grant entitled "Fueling the Mind, Feeding the World: Enhancing Communication and Decision-Making Skills of Secondary Agricultural Education Students."
MODULE OVERVIEW: The problems that society will face in the future—those that do not exist now and that we have never seen before—will require abstract thinking.