Bibliographic record
Abstract
Vancouver, Wash., resident earns master in early childhood education with UND Online at the same time maintaining successful work and home life Growing up in Vancouver, Wash., Shawn Sears loved playing hockey. It was his devotion to North Dakota hockey that led him to consider the University of North Dakota when deciding to further his education. Sears decided to pursue his Master’s in Early Childhood Education (ECE) from UND, a program named a Top-25 Smart Choice by SuperScholar.com. “I researched the best online programs for this type of degree and was very impressed with UND’s classes, online tools and the flexibility of the program,” Sears said. “It was an ideal fit, I needed to maintain the right work/life balance for the sake of my family and full-time job, as well as my education. My connection to hockey certainly peaked my interest in the University as well.” Sears received his undergraduate degree at the City University of Seattle and now teaches students in kindergarten through second grade. He currently resides in his hometown of Vancouver, along with his wife, Allison, and three children, Caleb, 10; Madelyn, 2; and Mackenzie, 6 months. Sears explained his love of teaching young elementary students: “I believe it is a critical time of development for students, and I enjoy helping them reach their educational goals of developing strong cognitive and social emotional skills.” Sears long had a goal of obtaining a Master’s degree in ECE, and he believes will enhance his experience and knowledge. Sears enjoys online learning because it provides the flexibility to work at his own pace and time. He recommends online learning to anyone furthering his or her education. “I desired an online program so I could further my education while also working full-time and being a husband and father,” Sears said. “It is an ideal way to further your education while balancing life.” For students considering online courses, Sears recommends open and regular communication with advisors and professors. “Read the syllabus and create a schedule that holds you accountable to assignments,” Sears explained. “Know when assignments are due, especially with different time zones.” When not working on his degree or teaching, Sears engages in an active Washington lifestyle by spending time outdoors, playing sports and being with his family. About the degree: The online Master’s in Early Childhood Education is 32 credits with semester-based courses. Students are required to complete a 2-credit practicum at an approved site. The program was named a top 25 smart choice for online ECE degrees by Super Scholar. Students pursuing this degree pay in-state tuition, regardless of residency.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.007 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.116 | 0.040 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".