An Undergraduate Design Experience in Digital Logic Design Course of Special Purpose Arithmetic Logic Unit Using Multisim, Ultiboard and Print Circuit Board
Bibliographic record
Abstract
Project-Based Curriculum (PBC) is considered one of the most powerful methods in the engineering education where each course or courses-cluster is assigned a design project which considers a series of inter-related concepts that have been shown theoretically for the students. Using this approach, the student will gain the required knowledge in an atmosphere of groups of teams where students can experience and learn the most needed inquiry, research tools and skills, teamwork skills, leadership skills, accountability, communication skills, interdisciplinary experience, curiosity, planning skills, critical thinking, and problem-solving skills. In this article, an undergraduate design experience in digital logic design course of special purpose arithmetic logic unit using Multisim, Y-0010/0020 Experiment Sets and Ulti-Board Kit is presented as an integral part of several electrical engineering courses throughout the curriculum at King Faisal University. The project was very beneficial in assessing the student outcomes a, c, d, e and k which introduced by ABET accreditation criteria.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".