Exploring gender differences in sustainable project management competencies and awareness of the sustainable development goals (SDGs)
Bibliographic record
Abstract
This study investigates whether gender differences exist in the levels of sustainable project management competencies and awareness of the Sustainable Development Goals (SDGs), specifically SDG 9 (Resilient Infrastructure) and SDG 11 (Sustainable Cities and Communities), among College of Business students at Prince Sattam bin Abdulaziz University. A questionnaire was employed to assess six key sustainable competencies: communication, leadership, management, cognitive ability, effectiveness, and professionalism. The sample consisted of 63 students from diverse business disciplines, including accounting, finance, management information systems, and human resources. The questionnaire was developed based on an extensive review of the literature and validated by experienced educators. Data analysis included descriptive statistics and the Mann-Whitney U test to examine gender differences in competency levels and SDG awareness. The findings reveal significant gender differences, with female students demonstrating higher mean ranks across all competencies and SDG awareness compared to their male counterparts. These results suggest that gender may play a significant role in the development of sustainable project management competencies and the understanding of global sustainability challenges. This study contributes to the literature by offering valuable insights into how gender influences students’ potential to engage with SDGs, particularly SDG 9 and SDG 11. The findings emphasize the importance of incorporating sustainable project management competencies into academic curricula to enhance students' awareness of SDGs, and they highlight the need for gender-sensitive educational strategies that promote inclusive sustainability education.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".