A proposed educational design model for digital empowerment in light of the degree of use of machine learning systems tools among faculty members in Saudi universities

Abstract

The study aimed to develop an instructional design model that supports digital empowerment, based on the extent of use by faculty members at Saudi universities of machine learning tools available on the Blackboard platform. A questionnaire was administered to 108 faculty members across five Saudi universities to collect and analyze data. The study employed the descriptive methodology. The use of ten machine learning tools available on the Blackboard platform was identified and evaluated, namely: "Blackboard Predict", "Collaborate Ultra", "Discussion Boards", "Test Analytics", "Rubrics", "Adaptive Release", "Intelligent Agents", "Retention Center", "Performance Dashboard", and "Learning Analytics Module". The Statistical Package for the Social Sciences (SPSSv27) was used to perform the necessary statistical analyses for the study. These analyses included frequencies and percentages to calculate the relative distribution of the data, as well as calculating means and standard deviations to measure data dispersion and determine performance levels. The "Independent Samples T-test" was used to compare the different study groups. To analyze the strength of the relationship between variables, Pearson's coefficient was utilized. Additionally, the "Alpha Cronbach's" coefficient was calculated to estimate the reliability of the study instrument. The results showed that the tools "Blackboard Predict", "Collaborate Ultra", "Discussion Boards", "Test Analytics", and "Rubrics" achieved a medium level of use, while the usage of other tools was low. Furthermore, it was found that there were no statistically significant differences in the use of these tools based on gender or years of experience, but there were notable differences based on academic specialization. The results indicated that members of the humanities disciplines used the tools at higher rates compared to others.