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PhD Supervision: STAKEHOLDER IDENTIFICATION MODEL FOR SYNCHRONOUS AND ASYNCHRONOUS E-LEARNING SYSTEM

PhD Supervision: STAKEHOLDER IDENTIFICATION MODEL FOR SYNCHRONOUS AND ASYNCHRONOUS E-LEARNING SYSTEM

πŸ—“οΈ Timeline

January 2019 – January 2024


πŸ‘₯ Contributors

  • DUHA AWAD HAMED ELNEEL ELMUBARAK β€” PhD Candidate
  • Mansoor Abdulhak β€” Co-Supervisor

πŸ“Œ Abstract

The system’s effective development depends mainly on successfully defining the requirements. The right requirements rely on accurate stakeholder identification (SI) from early stages of the system lifecycle. SI is an essential part of the requirements engineering process and it is a challenging and critical aspect that requires a delicate study to categorize and classify the right project stakeholders. The e-learning system is considered a significant platform that has diverse stakeholders which need to be identified. The high growth of e-learning systems in the last years and the sudden shift from classroom to online education especially during the covid-19 pandemic made this system become indispensable. Consequently, this research focuses on identifying the key stakeholders of the e-learning system based on communication modes (Synchronous, Asynchronous). The problems that arise sequentially after the launch of the e-learning system and threaten the continuity of the system are one of the motivators of this research, in addition to the different types of e-learning modes and diversity e-learning organizations that produce different unknown stakeholders need to be identified. On the other hand, the limitations of the existing methods of SI specially in the e-learning system domain and the shortage of the existing applied processes for requirements elicitation to cooperate with the recent technologies also stimulated the work of this research. Subsequently, stakeholder identification model for e-learning system (SIMe) is proposed in order to improve the e- learning system requirements engineering process and thus build a sustainable and continuous system. The SIMe has been constructed based on the e-learning system modes (Synchronous and Asynchronous) platform that helps to determine various activities and roles accordingly, different types of stakeholders can be identified and categorized. Moreover, The SIMe used the power/interest grid for more stakeholder identification and categorization in addition to an Oracle application for the implementation. Three operative methods are used to evaluate the efficiency of the proposed SIMe. First, implementing the SIMe to a selected e-learning system, then comparing the SIMe with the existing SI methodologies in terms of the performance and the fulfilment, and finally presenting the proposed model to specialists to evaluate its actual performance. The experiment declares that SIMe can generate the required stakeholder lists with accurate result which is better than other alternative SI methods. On the other hand, the findings approve that the SIMe can generate the key stakeholder report, respectively with clear classification and is more effective compared with other existing techniques. Additionally, the results of the experts’ opinions review indicate that they were satisfied with the SIMe contribution in e-learning system sustainability. In future work, new prospects can be added for more improvement such as personal considerations, organizational considerations, emerging technologies and some regulations.


πŸ“š Publication

  1. Elneel, D. A., Fakharudin, A. S., Ahmed, E. M., Kahtan, H., & Abdullateef, M. (2022, January). Stakeholder identification overview and challenges in requirements engineering prospective. In 2022 2nd International Conference on Computing and Information Technology (ICCIT) (pp. 314-319). IEEE.
  2. Elneel, D. A. H., Kahtan, H., Fakharudin, A. S., Abdulhak, M., Al-Ahmad, A. S., & Alzoubi, Y. I. (2023). The factors influenced by stakeholder identification in E-learning systems: A survey. Journal of King Saud University-Science, 35(3), 102566.
  3. Elneel, A. H., Al-Ani, H. K., Sahli Fakharudin, A., Abdulhak, M., Salah Al-Ahmad, A., & Ibrahim Alzoubi, Y. (2023). Investigating Internet of Things impact on e-learning system: an overview.

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