The impact of computer aided drafting technology on industrial education curriculum in British Columbia secondary schools
Bibliographic record
Abstract
The purpose of this study was to identify the prerequisite skills most appropriate to training and/or employment in computer aided drafting... Specific objectives of the study were concerned with: 1. The prevalence of CAD in specific industries. 2. The relationship between the size and/or type of CAD system and the training required to operate it. 3. The background and training of individuals operating CAD systems. A. The preferences of employers as to the education of their CAD operators. 5. The preferences of CAD training institutions as to the education of CAD training candidates. 6. The methods by which individuals in industry received CAD training. 7. The methods of CAD training preferred by employers. 8. The importance of certain skills relative to CAD employment or training. 9. The importance of certain secondary school drafting curriculum items relative to CAD training or employment. 10. The identification of secondary school curriculum areas to be modified to suit the needs of industry and CAD training institutions PROCEDURES The survey questionnaire method was used to obtain data for this study. Two parallel, closed-form questionnaires were developed from a review of related literature and an analysis of current drafting standards and techniques. One questionnaire was sent to all training institutions in British Columbia offering courses in CAD. The other questionnaire was sent to sixty-five businesses in British Columbia identified as users of CAD technology. The responses were analysed to provide information on the impact of CAD technology on secondary school curriculum. The importance of particular items was determined through calculation of mean priority or ranking levels. FINDINGS The businesses surveyed were primarily involved in mechanical and electronics drafting followed by structural, architectural, and cartographic. Training institutions were concerned with architectural and civil drafting followed by mechanical and structural. Data indicated that CAD was being used in all areas of drafting. CAD system descriptions indicated that a large number of businesses and training institutions were using personal computer based CAD systems that were less expensive and easier to operate than larger mainframe or dedicated systems. Educational institutions indicated that the majority of their CAD training candidates were upgrading themselves and that they preferred candidates with a good drafting background. Businesses indicated that most of their CAD operators were draftspersons retrained for CAD. Few CAD operators had received formal CAD training although employers indicated a hiring preference for draftspersons with formal training in CAD. Both businesses and training institutions involved with CAD considered manual drafting skills and good problem solving ability to be the most important prerequisites for CAD training or employment. With respect to specific drafting skills, there was consensus on the importance of individual items. Dimensioning to CSA standards was considered most important followed by the three dimensional representations typified in sketching, pictorial, drawing, auxiliary views, and developments. Both surveys indicated that curricular change to reflect the changing technology was necessary and should include the introduction of computer aided drafting at the secondary level as well as more drafting course time and more emphasis on computational and communication skills. CONCLUSIONS 1. Drafting, especially computer aided drafting, should be approached as a necessary skill for a wide variety of occupations and not as a vocation in itself. This would require a conscious effort to open secondary school drafting programs to all students, not just those in industrial programs. 2. Drafting educators should acquaint themselves with the changing technology of drafting including contact with post secondary training institutions and representative industry. 3. Secondary school drafting programs should introduce students to computer aided drafting. 4. More emphasis should be placed on dimensioning to CSA standards and on areas of drafting that involve viewing an object in three dimensions. 5. Secondary school curriculum should be modified to include more drafting time and place more emphasis on computational and communication skills.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".