Department of Information Science, Haramaya University,
Dire Dawa, Oromia, Ethiopia
Guidelines for Submission
Manuscripts can be submitted until the expiry of the deadline. Submissions must be previously unpublished and may not be under consideration elsewhere.
Papers should be formatted according to the guidelines for authors (see: http://www.sciencepublishinggroup.com/journal/guideforauthors?journalid=390). By submitting your manuscripts to the special issue, you are acknowledging that you accept the rules established for publication of manuscripts, including agreement to pay the Article Processing Charges for the manuscripts. Manuscripts should be submitted electronically through the online manuscript submission system at http://www.sciencepublishinggroup.com/login. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal and will be listed together on the special issue website.
The special issue currently is open for paper submission. Potential authors are humbly requested to submit an electronic copy of their complete manuscript by clicking here.
There is a growing interest by higher education institution (HEI) to take advantage of Big Data to improve student performance and raise teacher/professor effectiveness, while reducing administrative workload. Student performance data is increasingly being captured as part of software-based and online classroom exercises and testing. This data can be augmented with behavioral data captured from sources such as social media, student-professor meeting notes, blogs, student surveys, and so forth. This special issue is to investigate and explore that importance of how analytics will be of great advantage to higher educational institution. Analytics play a critical role in performing a thorough analysis of student and learning data to make an informed decision on future course offerings and their mix to cater to the potential and existing students. Predictive analytics / forecasting models in a Big Data environment enable institutions to make right investment decisions for higher institutional impact. A Big Data based architecture enables the inclusion of a greater variety of data sources so that many different types of data can be analyzed.
Aims and Scope:
1. Predictive Analytics in HEI 2. Big Data Analytics in HEI 3. Decision Support System in HEI 4. Business Intelligence in HEI 5. Competitive Intelligence in HEI 6. Data Warehousing in HEI