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Although electronic records management system (ERMS) is important in bringing about the productivity of organizations, majority of them refuse to implement it, while a few embark on implementing it blindly, without guidance, which often results in failure. This paper, therefore, proposed a model for the ERMS adoption to support the productivity and performance of higher professional education (HPE) institutions in the Yemeni context. This paper used the unified theory of acceptance and use of technology (UTAUT) and a mixed explanatory approach to gather quantitative and qualitative data. Data were then analyzed through the use of SPSS 21, with SEM and Smart PLS V3 software used to test the proposed model. The model was also confirmed by five experts who were interviewed to obtain qualitative data. Based on the analysis results, all the fit indices met the recommended values range that assumed the acceptability of the developed model. The model was found to be of a good fit, and the theory upon which the model was developed was stable. The quantitative findings showed that performance expectancy, effort expectancy, social influence, facilitating conditions, policy, and training have a significant relationship with the ERMS adoption, which in return has a significant relationship with HPE organizations’ productivity. This was supported by the qualitative results, confirming the theoretical study and contributing to the understanding of the ERMS adoption among HPEs. Such adoption ensures educational institutions’ productivity.

Sustainability is a concern that has been raised in many domains especially in institutions of higher learning such as universities. Hence, universities are implementing Green practices to promote sustainability. Similarly Green practice implementation in universities for attaining sustainability has been the priority for most universities across the world, mainly in ensuring the effectiveness and efficiency of Information Technology (IT) related service. Over the years, a few approaches have been developed to facilitate Green practice in institutions of higher learning, however these approaches are not autonomous and do not provide adequate information on Green implementation initiatives. Moreover, institutions of higher learning utilize manual checklist assessment questionnaire to evaluate their current Green practice. Therefore, this study proposes a system model that integrates hybrid multi-agent and Case Based Reasoning (CBR). The CBR technique facilitates Green implementation by providing information on how institution of higher learning can adopt Green practices initiative, whereas software agents autonomously assess the current Green practice initiative implemented in institutions of higher learning. Findings from this paper show how the hybrid multi-agent and CBR aid universities implement Green practice for sustainability attainment in institutions of higher learning.

The study was conducted to identify characteristics that are associated with successful transfer to institutions of higher learning from 3 Phi Theta Kappa chapters at a large multi-campus Mississippi community college. The study examined participation rates and transfer rates of Phi Theta Kappa students. The current study also identified student characteristics that predict the successful transfer of Phi Theta Kappa members. A correlational methodological approach was employed. The Phi Theta Kappa chapters in this study have significant differences in membership, yet the factors that predict transfer to a 4-year university or college are few. The factors include age at transfer, cumulative grade point average, type of major, and associate degree completion. The analysis resulted in a model that may be used to predict the probability that a Phi Theta Kappa student will be a successful transfer. The model was able to predict the transfer of these students with significantly higher probabilities than the baseline model.

Data mining has been integrated into application systems to enhance the quality of the decision-making process. This study aims to focus on the integration of data mining technology and Knowledge Management System (KMS), due to the ability of data mining technology to create useful knowledge from large volumes of data. Meanwhile, KMS vitally support the creation and use of knowledge. The integration of data mining technology and KMS are popularly used in business for enhancing and sustaining organizational performance. However, there is a lack of studies that applied data mining technology and KMS in the education sector; particularly students- academic performance since this could reflect the IHL performance. Realizing its importance, this study seeks to integrate data mining technology and KMS to promote an effective management of knowledge within IHLs. 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Letter concerning a position in horticulture and botany at Utah Agricultural College, copies given to J. C. Blair, J. L. Snyder, and L. H. Bailey.