Classroom Implementation of Instructional Strategies and Techniques that are Based on Universal Instructional Design Principles and Support Diversity
Bibliographic record
Abstract
Aim/Purpose: This paper describes foundational principles of universal instructional design (UID), which is also known as universal design for learning, that support accessibility and inclusivity for a diverse population of students and discusses how these design principles and instructional strategies are being implemented in courses we instruct. Background: The goal of any instructor should be to ensure all students have their learning needs met. Unfortunately, this is complex. Each student is unique and can have individual learning needs and preferences. Consequently, it would likely be impossible to create instructional materials that address the specific learning needs and preferences of every individual. Principles of UID help to minimize this challenge. UID strategies should support deaf and hard of hearing individuals, students with a vision loss, learners who have difficulties staying focussed, weak readers, academically-weak students, students with low confidence, learners with high anxiety, individual learning preferences, and cultural minorities. UID principles should also lead to the creation of instructional materials that support cognitively-gifted students. The principles applied in our classroom, based on the principles of UID, helped to address these challenges that students have and foster a classroom environment that was conducive to supporting the diversity in our student population. Methodology: This is not applicable because this is a practical paper, not a research paper. Contribution This paper provides practical instructional strategies and techniques that can presumably help students with disabilities learn more effectively while also fostering a culture of inclusivity. Findings: There are no formal findings for this paper. Recommendations for Practitioners: Readers should consider applying the discussed instructional strategies and techniques to support their own students that have disabilities. Recommendations for Researchers: Researchers should create instructional interventions for students with specific disabilities and assess whether those interventions help students with that disability learn more effectively. Impact on Society: Although not proven by research on populations of individuals with disabilities, the presented instructional strategies and techniques are presumed to help students with a disability learn more effectively. The aim is for other instructors to create instructional materials with similar instructional strategies and techniques to enable accessibility and promote inclusivity for their diverse population of students. Future Research From a practical perspective, instructors should apply the presented instructional strategies and techniques in their classrooms for their diverse population of students. In-class research could be done afterwards.
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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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".