Data-Informed Educational Decision Making to Improve Teaching and Learning Outcomes of EFL

For many justifications, the collection, analysis, and use of educational data are central to the evaluation and improvement of students’ progress and learning outcomes. The use of data in educational evaluation and decision making are expected to span all layers—from the institution, teachers, students, and classroom levels, providing a longitudinal record of each student’s performance over time. Such records/data can play a crucial role by giving students, teachers, parents, and stakeholders a scalable and efficient platform that track performance and lead to informed valid enhancement decisions. This paper provides a description of a proposed tracking system. Developed by an English Language institute. It has multiple key features and processes that can monitor the progress of students from day 1 till completing their study. It is a comprehensive integration of student data management and a monitoring system. Such data makes it possible to see if students are achieving their academic goals and administrator could see, as soon as possible, if a student is not progressing. The system is also useful in helping the institute to plan their educational activities every semester and improve data communication between administrator, teachers, and students.


Introduction
For a long time, many educational institutions have been generating data about student performance and storing them manually. Without a proper plan on how to use such information for in the advancement of educational outcomes, some teachers have failed to acquire the requisite knowledge needed to explain how such data can be used to improve decision-making skills in the learning setting (Warschauer, 2020). This problem stems from the reliance on traditional/manual data management methods, which failed to provide a framework for teachers to integrate available data in their decision-making processes. Additionally, the lack of fluidity in the management of manually stored data has made it difficult to track a student's educational progress. This problem cuts across different types of educational services because tracking and monitoring a student's progress is an imperative process in learning (Prinsloo, 2017). To address it, data-driven evaluation techniques have been introduced to help education stakeholders make better and informed decisions regarding their teaching practice.
In this paper, the role of data-informed decision-making in improving the learning outcomes of students who study English as a Foreign Language (EFL) is explored. The discussion is presented in two parts. In the first one, the theoretical background of the study is explored with three issues discussed: understanding the role of Information Technology (IT) in EFL, evaluating the importance of acquiring data-driven decision-making skills in education, and evaluating the extent that information systems have been used to improve the outcomes of EFL teaching and learning. In the second stage of analysis, a context of the overall discussion will be provided using the English Language Institute as a case study for the implementation of IT tools in decision-making. A comprehensive description of the system adopted in EFL will be provided in the same section and discussions/thoughts on its reliability outlined in a new section of the study. In the last section of the study, the information highlighted above will be collated, analyzed, and used to justify recommendations to improve the institution's evaluation information system.

IT in Teaching and Learning English as a Foreign Language
The use of data in decision-making is not a new phenomenon in the education sector because instructors have always used traditional tools of assessment, such as conducting physical tests and using the findings to develop instruction practices. These traditional tools of assessment used data derived from a teacher's educational experiences, intuition, and teaching philosophy to make critical decisions about a learner's educational progress and development (Savitz-Romer et al., 2018). The use of IT-enabled tools for data assessment is regarded as a new approach to making decisions in the education setting because it emphasizes the need to use data-driven information to formulate and implement educational policies. These tools of assessment encourage educators to use empirical knowledge to make decisions about the teaching practice (Mertler, 2020). They are a superior way of managing information because they could lead to better decision-making based on their reliance on quality and actionable data.
Over the past few decades, there has been an increase in the pace of technological adoption in the education sector. Many activities and processes in the field have benefitted from this development and the study of English as a foreign language is no exception (Sampson, 2019;Fenwick & Edwards, 2016). However, differences between traditional and IT-enabled data analysis tools have created differences in their impact on EFL learning. For example, old data assessment tools have had a lower effect on EFL learning compared to the use of IT-enabled assessment procedures because they have failed to create systematic processes for monitoring and evaluating data. Comparatively, IT-enabled tools have allowed educators to enjoy these advantages and much more by providing a standardized way of collecting, analyzing, and evaluating information (Piety, 2019). In this regard, IT is a revolutionary tool for data management and evaluation within the EFL space.
Based on the superior role played by IT in facilitating data evaluation processes in EFL learning, it has become increasingly clear to educators that traditional methods of information assessment are vulnerable to human errors, which may affect students' learning outcomes (Fischer et al., 2016). This is because the unstandardized nature of manual evaluation systems makes it difficult to determine which strategy to use in an education setting and the measurement criteria to use in monitoring progress. In other words, traditional data assessment tools do not provide a framework for evaluating information holistically because experiences vary across groups of teachers and institutional settings. IT-enabled tools have helped to address this problem by providing a platform for educational institutions to use their resources to develop a standardized software or system that appeals to their specific needs and dynamics (Nieminen & Hyytinen, 2015). Therefore, IT has created flexibility in the evaluation of educational data. However, the integration of IT tools in teaching English as a foreign language has been adopted using the e-learning framework.
The e-learning model involves the use of computer-enabled teaching methods to facilitate EFL learning. In most research studies, this concept has been associated with the use of the internet as a mode of teaching English as a foreign language (Mutambik, 2018;Yıldırım & İspinar, 2019). Stated differently the internet is regarded as a principal or supplementary education resource for EFL learning. The case for the use of IT in learning English as a foreign language has been made by highlighting the power of technology in eliminating traditional barriers to education, such as geographical and time differences. Researchers have also pointed out that the use of IT tools in learning English as a foreign language is also rooted in its ability to eliminate spatial and temporal challenges to learning (Ellison & Aloe, 2019;Zhang et al., 2016). Other researchers have pointed out that the use of IT in EFL learning has helped to provide students with an increased array of language resources needed to communicate more effectively with their teacher and colleagues (Hartong, 2016;Williamson, 2016aWilliamson, , 2016bSouto-Otero & Beneito-Montagut, 2016). These competencies have been captured by technology integration theories used in the education sector, such as the intentional use of technology model, which explains how IT tools can be used to assess and monitor students' learning outcomes. It suggests that three categories of technology are used in helping teachers to make sound judgments about students' learning outcomes: service, engagement, and learning (Steele, 2015). IT enhances these areas of evaluation in EFL learning and highlight the importance of data-driven decision making in education.

Importance of Data-Driven Decision Making in Education
Empirically informed decisions emanate from the use of IT-enabled tools in information gathering and assessment. Consequently, data-driven decision-making has been at the center of educational reforms. Example on this is the adoption of the No Child Left behind Program conceptualized in the US (Jung & Young, 2019). Since the inception of the program in 2001, it has become routine for children across all grade levels to complete standardized tests and the same practice has been borrowed in EFL teaching (Dunn, 2016). As teachers measure the yearly progress of all children involved in associated educational programs, educators must embrace data-driven decision-making processes to understand what students know and what they are yet to master (Williamson, 2017). Doing so will help them to understand the learning gaps that exist and how to fill them.
As its name suggests, data-driven decision-making is focused on using empirical information to make important decisions affecting a student's educational progress. The data used are instrumental in choosing what to teach and when to teach it. Therefore, instead of looking at teaching as a form of art that requires a teacher's intuition to make instructional choices in learning, it is presented as a process that uses empirical data to minimize the negative effects of trial-and-error approaches in educational decision making.
The formalization of education has seen a long-term trend where teachers and educators have strived to use data to inform their decisions. Those who have succeeded in this regard use information from different sources to come up with their educational plans. However, recently, the development of IT tools and their integration in EFL learning have broadened the scope of information available for review through the rapid generation of data (Conaway et al., 2015). Indeed, these tools allow educators to generate data in real-time and assess them in the same fashion. In this regard, it is beneficial to teachers and educators alike because it simplifies their data assessment needs and requirements.
Data-driven decision-making is an important process in the improvement of student learning outcomes. For example, it has been used to evaluate educational progress among students and keep track of changes that have occurred during a student's educational journey (Prinsloo, 2020). Additionally, teachers have used it to better plan their educational curricula and identify areas requiring improvement by monitoring and integrating information relating to a student's educational progress. To have the maximum possible effect on their educational outcomes, the use of data-driven decision-making tools in EFL learning has spanned several cadres of educational assessment (Prinsloo, 2020). They also involve different players, including students, non-teaching staff, and teachers.
Overall, the use of data-driven techniques in EFL learning provides educational stakeholders with a basis they can use to track changes in a student's educational journey and provide a longitudinal record of information needed to understand their educational experiences and how to improve them in the future. Overall, data-driven decision-making processes are beneficial in EFL learning because it helps them to make informed decisions about the teaching practice, based on empirical evidence. These decisions can be used to improve EFL learning outcomes using information system assessment tools.

Improving Outcomes of EFL Teaching and Learning Through Information Systems
Data can be used to improve teaching and learning outcomes if implemented correctly in EFL learning. The process of data assessment and integration is often characterized by a cycle that involves activities centered on reviewing past practices, devising a plan of action to address important areas of attention involving the past practices, implementing the plan of action, assessing, and measuring outcomes, and transforming data into actionable information. These strategies of data assessment and analysis are often closely linked with one another and may overlap at different stages of analysis.
The cycle is commonly used to explain processes surrounding data treatment and evaluation geared towards improving outcomes of EFL teaching and learning through the adoption of information systems assessment techniques. Relative to this assertion, EFL teaching processes have been affected by concerns regarding the methodologies chosen to assess learning outcomes (Huang, Teo, & Zhou, 2019). For example, some researchers have expressed concern regarding the overreliance on academic rewards mechanism to improve educational outcomes because there is enough evidence to suggest that using academic success as the main metric of evaluation does not necessarily improve educational outcomes (Fischer et al., 2016;Nagy, 2016). To address this problem, educational stakeholders need to make a concerted effort to provide a holistic framework for evaluating educational outcomes. It should not be biased against students who do not have "academic buoyancy"; instead, it should reward those who make incremental achievements.
The holistic framework of evaluation should create a space for nurturing students to develop different competencies in language development by outlining a set of key performance indicators to be used to evaluate educational outcomes. However, to realize the above-mentioned outcomes, there should be an individualized culture of evaluating student outcomes in EFL learning over a long period of assessment. Studies have shown that parents hold a more favorable view of this type of review because it helps them to understand the unique learning needs and requirements of each student, as opposed to one that measures their performance using a generalized framework or standard of assessment (Hobsons, 2014). This statement is further supported by the fact that most parents prefer to hear the educational progress of their children before understanding how it  Vol. 10,No. 5; gress from the anding of stud data and analy taken with a ca g to the conte t of evaluation to help institu ome universiti y enroll studen ational career.
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