A Model Based on Data Science for Analysis and Improving Accreditation Processes at the Higher Education Authority

Abstract

The study was conducted to establish the factors influencing the adoption and acceptability of implementing accreditation processes through the HEA-IMIS. The research study assessed the factors in order to establish and identify whether adoption and acceptability of implementing accreditation processes through the HEA-IMIS were affected by the five constructs/predictors of the UTAUT model. The research used a mixed method research design and data captured was qualitatively and quantitatively through a questionnaire. The study was conducted in Lusaka, the capital city of Zambia, and the sample size of 126 is all the current active users of the HEA-IMIS. The target population was the registered, recognized and proposed HEIs. The questionnaire used was generated based on the UTAUT conceptual model and took into account the five predictors: PE, SI, EE, FC, and BI, to determine the adoption and acceptability of implementing accreditation processes through the HEA-IMIS. The response rate was 88% of 112 respondents through the survey questionnaires, with 76 (67.8%) being male and 36 (32.2%) being female. The findings were eventually analysed by SPSS and the Chi-Square test to determine the relationship between variables. Two out of the five (5) hypotheses were accepted as they showed a statistically significant relationship between the variable for actual usage. The measure of the p-value was at 0.05. The research implications suggest how the findings may be important for improving the implementation of the accreditation processes through the HEA-IMIS.