# Systematic Literature Review of Predictive Analysis Tools in Higher Education +
## 2 Methodology
### Search Procedure  
The search process was performed with the purpose of finding relevant scientific papers that present applications of predictors and EWS in higher education scenarios.  
The search was limited to the following types of documents: journal articles, conference proceedings, and book extracts. The election of these document types was made under the assumption that they would be likely to present a good variety of unique approaches to build and test predictive applications, thus allowing for more interesting comparisons. Additionally, to focus on relatively new applications and technologies, no documents with a publication date older than 2012 were considered, as this year marked the point when learning analytics as a whole really started to bloom [9]. Regarding language, only documents written in English were eligible.  
The following online databases were used in the document retrieval process: IEEE Xplore Digital Library, ACM Digital Library, Elsevier (ScienceDirect), Wiley Online Library, Springer (SpringerLink), Emerald, and Taylor & Francis. These were selected according to the reason of them being the most important online scientific libraries that we had full access to. Additionally, queries were run on Google Scholar, Scopus, and Web of Science in order to complement the search results from the aforementioned libraries.  
The document search process started in March 2019. The latest search-related tasks were performed in June of the same year, therefore, papers published after this date were not contemplated in this review. The following search procedure was applied:  
1. early warning system
2. predictive analy*
3. predictive algorithm
4. OR 2 OR 3
5. education
6. university
7. 4 AND 5 AND 6
8. disaster
9. medical
10. health
11. 7 AND NOT 8 AND NOT 9 AND NOT 10  
The reasoning behind this strategy was to obtain documents that focus on higher education contexts while also filtering out papers that deal with the use of EWS in the medical or natural disaster prevention fields, since these are areas where predictive algorithms and EWS are very prominent, and thus have a significant amount of related literature.  
Table 1 shows the number of results that were retrieved in each of the online libraries that were searched.  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Source** & **Results** \\ \hline IEEE Xplore Digital Library & 36 \\ ACM Digital Library & 45 \\ Elsevier (ScienceDirect) & 412 \\ Wiley Online Library & 255 \\ Springer (SpringerLink) & 91 \\ Emerald & 36 \\ Taylor \& Francis & 165 \\ Google Scholar & \(\sim\)13,800 \\ Scopus & 956 \\ Web of Science & 97 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Search results per database.  
It is worth noting that the search on Springer was limited to the \"Education\" discipline. Additionally, the lists of results obtained from both Google Scholar and Scopus were ordered by relevance using the built-in sorting options that these searchers provide, and only the first 200 results in each case were considered. This was done because documents further down the list of results were not observed to be related to the educational field.  
Together with the search results obtained from the online libraries, the total number of retrieved documents was 1537. However, some of the results that were obtained using Google Scholar, Scopus, and Web of Science were duplicates of documents already yielded by searches on the other library databases. Disregarding these duplicates, the final number of documents that were retrieved in the search process was 1382.