Computer Graphics Skills Required for Effective Entrepreneurial Development
Bibliographic record
Abstract
This study identified lucrative business ideas in the use of computer graphics skills that could boost entrepreneurial development. The descriptive survey research design was adopted for the study. Five specific purposes and five research questions were formulated to guide the study. The population for the study was eight graphics design/printing press firms comprising of 1,024 graphics design/printing press personnel in Nsukka metropolis, Enugu State, Nigeria. A Structured questionnaire was used as an instrument for data collection and data collected were analyzed using mean. Major findings of the study showed that ability to think creatively and create a vision or imagery off heart, ability to utilize the hardware and software rights of graphics designing jobs, ability to use the function/impact of design and the role of the design profession appropriately in our society, ability to organize files in terms of formats/size for easy use, ability to use computer software to execute designs, meeting with clients and adjusting designs to fit their needs or taste, and using the various print and layout techniques were among the artistic, technical, communication, organizational and problem solving skills required in computer graphics for effective entrepreneurial development. Based on the findings of this study, it was recommended that the curriculum of institutions of higher learning in computer graphics should be reviewed to incorporate present needs of the society. The government should also ensure that adequate funds are allocated to procure necessary facilities that will facilitate teaching and learning of computer graphics in schools.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".