Comparative Life Cycle Assessment of Paper and Computer Based Exams
Bibliographic record
Abstract
Universities around the globe consume large number of papers every year for educational and administrative purposes. A major portion of these papers are consumed for exam purpose only. Post Covid -19, several universities have moved to computer-based exams because of health and safety concerns. The purpose of this article is to compare paper and computer-based exams primarily from the perspective of their impact on the environment. Our main aim is to perform Life Cycle Assessment (LCA) for three scenarios and find out which one of them is better from the environmental perspective. The three scenarios that have been considered for LCA modelling are as follows: (1) consumed papers go to landfill, (2) consumed papers are recycled, and (3) switching to computer-based exams. The procedure of conducting the LCA follows the ISO 14040 standard method which consists of four steps: (1) goal and scope definition, (2) inventory analysis, (3) impact assessment and (4) interpretation. This research uses GaBi educational software tool for LCA modeling and considers Global Warming Potential (GWP) as the impact category for comparison purpose. A further comparison from student performance point of view has also been made at the end of the article. The result of this research shows that computer-based exams have least impact on the environment based on the selected GWP impact category as compared to paper-based exams. Furthermore, it has been found that there is no significant student performance difference in either type of these exams
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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 | 0.000 | 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".