Determining the Potential of Graduate Analytics Based on the iCGPA System: A Systematic Literature Review

This study was conducted to address the issue of gathering information to track the career and accomplishments of graduates for quality improvement in higher education. Due to the lack of a convenient method to gather information using an efficient mechanism, this study reviewed graduate analytics based on the iCGPA system with the primary aim of examining its potential utility in such a system, and vice versa. A systematic literature review was conducted to integrate the relevant academic literature related to graduate analytics and iCGPA system. Using the PRISMA method, we identified 160 different articles, but only 125 met the specified inclusion criteria. Our analysis of the accepted articles to determine the potential of graduate analytics in iCGPA system, and vice versa, produced zero results where no intersection of the two topics could be found in the research literature from 2011 to 2018. Our findings indicate an acute lack of research in these two areas. However, we believe this gap can be minimized since there are already higher education institutions in Malaysia that are currently implementing the iCGPA system. The implementation could inform us regarding how graduate analytics can be used to expand the value of iCGPA for improving the quality of Malaysian higher education graduates.


INTRODUCTION
The term "graduate" can be defined as alumnus (College, 2017), or a person who has successfully completed an educational programme which earns him/her a diploma or a bachelor's degree during the referenced year (BHEF, 2016;OECD, 2001). The problem that arises in tracing graduates is recognized as an important issue and is regarded as a challenging task, especially on collecting information about the effectiveness of a given educational programme (Mijić & Janković, 2015;Mwizerwa, Robb, Namukwaya, Namuguzi, & Brownie, 2017;Rogan et al., 2008;Romanick, Ng, Lee, Herbert, & Coller, 2015;Zeldovich, 2017). The existing method for addressing this issue is Graduate Tracer Study or Institutional Tracer Studies, a method of research that has been widely adopted in several countries (Association, 2015;de Guzman & de Castro, 2008;Rogan & Reynolds, 2016;Rogan et al., 2008;Sakellariou & Patrinos, 2000;Sapaat, Mustapha, Ahmad, Chamili, & Muhamad, 2011;Suryani, 2017;Tahir et al., 2017;Zakariya, 2017). The aim of a tracer study is to track and retain the records of graduates to ascertain whether they are employed by their field of study. This knowledge is important for the future development of university programmes and educational goals (Mwizerwa et al., 2017;Rogan et al., 2008;Romanick et al., 2015;Zeldovich, 2017).
Based on that, the curriculum and other related services provided by higher education institutions can be assessed based on data analysis from their tracer studies (Schomburg, 2014). However, there are some drawbacks that make this method not an efficient mechanism (Mijić & Janković, 2015;Mwizerwa et al., 2017;Rogan et al., 2008;Romanick et al., 2015;Schomburg, 2014;Zeldovich, 2017). In relation to this, as stated in the Malaysia Education Blueprint 2015-2025(Ministry of Higher Education, 2015, Malaysia aims to develop holistic, entrepreneurial and balanced graduates through the integrated Cumulative Grade Point Average, or what is known as iCGPA. It is a new system in reporting students' learning performances and outcomes. It is claimed to be the first in the world by Malaysia's Ministry of Higher Education (MOHE). Technically, iCGPA is a report of academic data which have been modeled or designed in an outcome-based education (OBE) curriculum. In Malaysia, it is compulsory for higher education institutions to adopt an OBE-based curriculum specified by the Malaysia Qualification Framework (MQF) in order to be accredited by the Malaysia Qualification Agency (MQA). The agency is an authority that governs the accreditation process by the law under the Malaysia Act 679. This means that iCGPA can simply be adopted by all institutions in Malaysia under the MQF.
Analytics is a statistical evaluation of data, which combines data usage, statistical analysis, and an explanatory, predictive model to recognize patterns and respond to complex issues that can help stakeholders in making better decisions with additional analytics systems and software (Dahlstrom, 2016;Educause, 2010;Rouse, 2016). Although there are various definitions of analytics, for higher education we refer to the findings reported in Bichsel (2012) that analytics is more than just a metrics. The findings also regard analytics as something new--a catalyst for transforming higher education that addresses strategic questions involving data analysis and prediction by providing insight to drive action. Therefore, analytics can be seen as a promising mechanism to overcome the limitations of the current graduate tracer studies. In other words, graduate analytics can be used to improve the existing methods in tracing graduates by gathering information in a more efficient way. This paper presents an examination of graduate analytics and iCGPA system by screening the potential research of both topics. This study is important in synthesizing academic literature accurately and reliably since there is potential that graduate analytics can be implemented by extending the application of the iCGPA system. The following research questions were used to guide and inform this study: 1. How many relevant literature studies of graduate analytics and the iCGPA system have been published since 2000? 2. Does the existing literature indicate a relationship between graduate analytics and the iCGPA system?
Hence, the purpose of this study was to review articles related to graduate analytics and the iCGPA system using the systematic literature review (SLR) process to examine the potential of graduate analytics in iCGPA and vice versa.

Graduates and Alumni
Selected Irish universities in Ireland conducted a small-scale study (Gallo, 2018) to distinguish the meanings of "graduates" and "alumni" in the context of strategic plans. Their findings came to the following conclusion: "graduates" are students enabled by the university to participate in and contribute to the employment sector. In this context, the university is responsible for shaping their employment readiness by means of helping them acquire key skills such as reflective thinking, moral reasoning and lifelong learning. In addition, "graduates" are also defined as persons who have successfully completed an educational programmed during the reference year (OECD, 2001). From previous research, the term "graduate" has several levels of studies which are defined in Table 1. In contrast, the study defined "alumni" as successful graduates that give value to or increase the value of the institution. They are key enablers who give back to the university by advancing the university's mission and vision. In this study, the focus is on managing the "alumni" and "graduates" as stated by Gallo (2018) and OECD (2001) respectively.  Researchers explained that the most challenging issue in studying graduates is gathering their personal information to determine whether their employment and employment status are related to what they had studied at university (Rogan et al., 2008;Mijić & Janković, 2015;Mwizerwa et al., 2017;Romanick et al., 2015;Zeldovich, 2017). Nonetheless, several countries have used data from graduate tracer or institutional tracer studies for their purposes. Table 2 shows the countries that have relied on tracer study data to get the relevant feedback and collect information about graduates:  (2017) The importance of graduate tracer studies is that they provide essential information on labour market outcomes and the factors associated with these features. Besides, in the higher education context, these studies help to inform decision making related to the relevance and quality of programmes offered by the universities for future developments. As Schomburg (2014) mentioned, tracer studies are conducted with several objectives, which are: (1) to inform the development of higher education institutions (i.e., in terms of their curriculum); (2) to assess the relevance of higher education (i.e., assessment); (3) to contribute to the accreditation process; and (4) to inform all stakeholders about graduate employability. Although this method has been adopted by many institutions from various countries, it poses its own limitations that need to be addressed. The first limitation stems from access to data and low response rates from busy graduates (Mwizerwa et al., 2017;Romanick et al., 2015;Zeldovich, 2017), while the second limitation concerns data intensiveness (Rogan et al., 2008). Last but not least, there are concerns about data quality (Mijić & Janković, 2015), time consumption, and relatively high cost of the activity (Rogan et al., 2008;Schomburg, 2014).

Analytics
Analytics is the "extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions" (Davenport, Harris, & Morison, 2010). Besides, analytics is the statistical evaluation of big data sources to recognize patterns and respond to complicated issues that can help stakeholders (e.g., educational institutions, companies, and governments) in making exact decisions with additional analytics systems and software (Dahlstrom, 2016;Educause, 2010;Rouse, 2016). Hence, analytics works by subjecting the data to statistical analysis, and providing reports or visualizations; they might appear in the form of a dashboard to show patterns, trends and exceptions (Educause, 2010). As regards this study, analytics is a relevant issue that has significance to higher education (Dahlstrom, 2016). As mentioned by Educause (2010), college and university stakeholders can leverage the power of analytics to improve their institutions. Analytics are significant to use because of the existing data stored at most institutions. For higher education, data-driven decisions are the best option in both economic and pedagogical resources, while offering a structure for better educational results (Educause, 2010;Miller & Mork, 2013).

iCGPA
The Malaysia Education Blueprint 2015-2025(MOHE, 2015 envisioned the production of university graduates with well-balanced personalities and holistic, entrepreneurial characteristics through the use of the integrated Cumulative Grade Point Average (iCGPA). The iCGPA is a new system to be used in evaluating and reporting students' development and performance which are not only depending on their field of study (academic knowledge), but also on how they perform in practical skills, social skills and responsibilities, values, attitudes and professionalism, leadership abilities, critical thinking, information management, lifelong learning skills, managerial skills and entrepreneurial skills.
The iCGPA initiative was designed to benefit stakeholders in making decisions towards quality improvement of university graduates. The stakeholders that will benefit from iCGPA include educational institutions (Yusof, Naim, Latip, Aminuddin, & Ya'acob, 2017), programme management bodies, faculty (Mohamed-Kassim & Kamaruddin, 2017), students (Yusof et al., 2017), graduates (Nor et al., 2017;Saad, 2017), sponsors (Paper et al., 2017), employers, policymakers, and the industry. The current practice of tracking graduates is through tracer studies as discussed above. The limitations inherent in the tracer study method have given rise to the need to analyze and display data that can lead to better decision-making on the future development of higher education programmes and curricula, hence the present study.

Systematic Literature Review
Systematic literature review (SLR) is a review of a clearly formulated question, or set of questions, that uses systematic and explicit procedures from traditional reviews and commentaries (Khan & Kunz, 2003;Moher, Liberati, Tetzlaff, & Altman, 2009;van Laar, van Deursen, van Dijk, & de Haan, 2017). The purpose of such a review is to identify, select, and critically appraise relevant research and to collect and analyze data from the studies that are included in the review. Thus, in our case, this method was chosen to identify whether there is justification for further research--or not--on graduate analytics and iCGPA system. In this study, we used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (Moher et al., 2009). The PRISMA statements consist of an evidence-based checklist of 27 items and a four-phase flow diagram. However, only a four-phase flow diagram was used to report our results.

Search Terms
The search action was conducted using the Scopus, Emerald Insight, Web of Science, ProQuest and Science Direct databases to find all pertinent articles published on graduate analytics and iCGPA. However, due to the lack of published articles on iCGPA, we included the iCGPA conference book of abstracts in this study since the proceedings were not yet available at the time this study was conducted. For each term, we used several keywords related to Graduate Analytics and iCGPA to ensure extensive research coverage. The following parentheses with Boolean operators' search were used as each database has its own indexing terms: ("graduate analytics" OR "talent analytics" OR "alumni analytics" OR "iCGPA").

Selection Criteria
To select the most relevant studies that would address the research questions, we used the criteria outlined in Table 3 for all identified databases or corpuses. For the articles themselves, we emphasized using text analysis based on keyword frequency defined in Table 4 below.

Study Selection
Three steps were involved in the study selection. First, the titles of all captured articles were screened for eligibility that must fulfill the criteria mentioned above. Second, the abstracts from relevant articles were screened for eligibility by filtering out all 'no abstract available' content. Third, the full-texts of all remaining publications were checked. Data extraction was part of the analysis process to see a clear picture of the results to be shown in this study. A common spreadsheet application, i.e. Microsoft Excel 2016, was used as the tool for screening the data extraction by using the text analysis method. The data extraction process was completed starting with identification up until the selection and inclusion phase.
Using the search terms, 160 articles were identified from the databases. Out of the 160, 155 different articles were screened after five duplicates were removed. By screening the titles, abstracts and time periods, 135 articles came in full-text, where 125 articles met all criteria including the keyword filtering. Figure 1 shows the PRISMA flowchart (Moher et al., 2009) that indicates the steps to determine the studies most relevant to the research objectives. In the eligibility stage, the full-text articles were screened and excluded based on four criteria: (1) no keyword filtering detected in the articles; (2) different subject areas; (3) no full-text available online excluding the iCGPA conference proceeding; and (4) not peer-reviewed, whether articles or theses.  Table 5. The list of all articles that are related to this topic can be referred to in the appendix. In Table 5, "Strict Search" refers to the actual search conducted using the two main keywords, namely "icgpa" and "graduate analytics," while "Group Search" involved the use of main keywords and sub-keywords as shown in Table 4. Lastly "Combined Search" refers to the combined use of both main keywords and sub-keywords. As indicated in Table 5, no articles between 2000 and 2010 were selected as their full texts could not be located, hence they were excluded in the selection process (see Figure 1). Therefore, for 10 years at least, there was a gap in this research area, although some research activities showed up from 2011 until 2018. Table 5 indicates the highest number of articles using the search keywords popped up in the year 2017. It was mostly extracted by the "iCGPA" keyword (i.e., 57 articles were extracted on strict search and 60 articles on group search). This could be due to several reasons, the first of which is that the iCGPA system, at the time the study was conducted, was a newly introduced system that was being heavily promoted. Another factor was the fact that the iCGPA International Conference was held on 17-19 th July 2017, an event that contributed to the increasing number of articles in 2017. Table 5, however, shows a sharp decline in 2018 due to external factors such as changes in national legal policy and financial resources. This topic is still expected to garner some interest, as shown in Table 5, as four (4) articles showed up after a "combined search" was conducted for 2018.
As illustrated in Figure 1, the process is continued to examine the relationship between Graduate Analytics and iCGPA system. The results are shown in Table 6.   Table 6 depicts a visual illustration of the possible intersections between the graduate analytics and the iCGPA system research and publication literature. The text analysis in Microsoft Excel was conducted by extracting all remaining articles included in this study. The five (5) databases and one (1) conference proceeding were used to make it simpler and provide a clearer picture to show whether information about iCGPA could be acquired in Graduate Analytics articles, and vice versa. As shown in Table 6, 'A' and 'B' represent the number of articles that used "graduate/talent analytic" and "icgpa" search terms respectively in each source, while 'A*B' is the result of keywords frequency conducted using the following parentheses with Boolean operators' concept: ("graduate" AND "analytic" AND "graduate analytic" AND "icgpa").
On 'A*B' see (Table 6), the result is zero (0) for all remaining articles included in this study. The visual relation indicates that in each source, there are no intersections of the two sets of A and B.   Table 7 shows the number of articles extracted using "graduate analytic" as the main keyword, which addresses the third research question. Despite our efforts of going through multiple databases, our extensive search results produced only one article published in 2015 on the subject. The discovery supports our hunch that there is a lack of research on Graduate Analytics. Additionally, we also found this article to have no citation at all, suggesting a lack of interest in this area.

CONCLUSION
The results of our systematic review of the literature on Graduate Analytics and iCGPA system existing in peer-reviewed databases show a lack of research and publication in these topics (as shown in Figure 1, Table 5 and Table 7). Further, the findings presented in Table 6 show no literature at all on Graduate Analytics and iCGPA system, as no intersection was indicated between them. Our review has shown that there is a research gap on Graduate Analytics and iCGPA system. There is a likelihood that this gap can be minimized since there are already higher education institutions in Malaysia that are implementing the iCGPA system. The implementation can produce insight on how higher education institutions can expand the value of iCGPA with graduate analytics. The use of graduate analytics will help to address the limitations of the existing tracer studies by improving data quality, reducing costs and time consumption, boosting alumni fundraising, and promoting continuous program improvement. Moreover, with the use of analytics to track graduates by analyzing and displaying data in an interactive visualization or dashboard, stakeholders will be allowed to filter through the data, and get an overarching view of all information gathered to make better decisions concerning the employability of graduates and the quality of their respective higher education programmes and training (Dahlstrom, 2016;Educause, 2010;Rouse, 2016). Tahir, L. M., Yusof, S. M., Ghafar, M. N. A., Omar, W., Samah, N. A., Mohamad, S., & Abdul Rahman, S. A. P. (2017). Employability skills policy in HEIs : Are Malaysian graduates from a public technical and engineering-based university contented? Man in India,97(19), 1-21.