Title: Impact of Scanning and Optical Character Recognition on the Digital Transformation of Research Publications in Bayero University Library, Kano, Nigeria
Author(s): Moruf Hawwau A.; Enang Uduak U.; Umoren Eboro E.
Publication Year: 2024; Volume 19, Issue 1, pages 30-39

Scanning is a fundamental step in the digitization workflow, allowing physical documents to be transformed into a format that can be stored, manipulated, and accessed electronically. This study was carried out to investigate the impact of document scanning and Optical Character Recognition (OCR) on the visibility of research publications at Bayero University, Kano. The study was guided by four specific objectives with their matching research questions. The design employed in this study was survey research design. Data were collected using structured questionnaire with Four point Likert Scale. The data were analyzed using descriptive statistics of mean and standard deviation, while Student-t-test was used to test the hypotheses at 0.05 level of significance. The results revealed that the mean range for document scanning was 1.86 - 1.99, with a standard deviation range of 1.29 - 1.34, indicating close clustering around the weighted mean. Notably, all mean values were below 2.0, suggesting a relatively limited impact. The use of scanning software and Photoshop Elements for batch processing also showed mean and standard deviation values of 1.97 and 1.34, contributing to a pooled mean of 1.93, indicating a lesser extent of impact. For OCR, the mean range was 1.63 - 1.95, with a standard deviation range of 1.17 - 1.38. The mean responses were closely grouped below 2.0, and the pooled mean is 1.85, indicating consensus among respondents that OCR has a positive impact on visibility, albeit to a lesser extent. Statistical analyses support these findings, with the t-test for document scanning yielding a t-value of 25.71 and a probability value of .0001 at the .05 alpha level, indicating statistical significance. The null hypothesis was rejected, confirming a significant impact of document scanning on visibility. Similarly, the t-test for OCR produces a t-value of 26.93, with a probability value of .001, reinforcing the statistical significance and rejecting the null hypothesis. In conclusion, both document scanning and OCR contributes to the visibility of research publications at Bayero University, Kano, the impact is observed to be moderate. The paper recommends that institutions should take advantage of cloud services (Softwae As A Service, SAAS) for document scanning, as there are off-the shelf and cloud services that can help institutions scan and prepare documents.