Instructional Strategies and Educational Outcomes for Students with Developmental Disabilities in Inclusive “Multiple Intelligences” and Typical Inclusive Classrooms
Bibliographic record
Abstract
Pedagogical practices based on Gardner's (1983) theory of multiple intelligences (MI) are often cited as potentially facilitative of inclusion of students with developmental disabilities (Armstrong, 1994; Eichinger & Downing, 1996; Falvey, Givner, & Kimm, 1996). However, no research to date has examined this relationship. The purpose of this study was to examine the engaged behavior and social interactions of 10 students with developmental disabilities in two types of inclusive classrooms–those that ascribed to MI pedagogy, instruction, and assessment, and those that used no specific educational theory or approach to instruction. The study was intended to be exploratory in nature to generate hypotheses for future investigations. Data were collected using MS-CISSAR (Greenwood, Carta, Kamps, & Delquadri, 1997), a software program for gathering and analyzing observational data in classrooms. Results suggested that the experiences of the participants in both typical and MI-inclusive classrooms were more alike than different. Participants in both types of classrooms were engaged primarily in whole-class, independent seatwork, and traditional classroom activities, and were engaged less frequently in small groups or multiple response activities. However, participants were observed more frequently to be engaged in multiple response activities in MI classrooms, and in both noninstructional time and individual seatwork activities that were different from those of peers in typical classrooms. The participants in MI classrooms spent more time interacting with their typical peers, whereas those in typical classrooms spent more time interacting with adults during 1:1 activities that were different from those of their peers. The results are discussed in terms of their educational and research implications, limitations, and suggestions for further research.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".