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Keser, Sinem Bozkurt; Aghalarova, Sevda – Education and Information Technologies, 2022
Education plays a major role in the development of the consciousness of the whole society. Education has been improved by analyzing educational data related to student academic performance. By using data mining techniques and algorithms on data from the educational environment, students' performances can be predicted. In this study, a novel Hybrid…
Descriptors: Grade Prediction, Academic Achievement, Data Analysis, Data Collection
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Narjes Rohani; Behnam Rohani; Areti Manataki – Journal of Educational Data Mining, 2024
The prediction of student performance and the analysis of students' learning behaviour play an important role in enhancing online courses. By analysing a massive amount of clickstream data that captures student behaviour, educators can gain valuable insights into the factors that influence students' academic outcomes and identify areas of…
Descriptors: Mathematics Education, Models, Prediction, Knowledge Level
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Yanzheng Li; Zorka Karanxha – Educational Management Administration & Leadership, 2024
This systematic literature review critically evaluates 14 empirical studies published over a 14 years span (2006-2019) to answer questions about the models and the effects of transformational school leadership on student academic achievement. The analysis of the related literature utilized vote counting and narrative synthesis to delineate the…
Descriptors: Transformational Leadership, Instructional Leadership, Academic Achievement, Models
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Shoaib, Muhammad; Sayed, Nasir; Amara, Nedra; Latif, Abdul; Azam, Sikandar; Muhammad, Sajjad – Education and Information Technologies, 2022
Technology and data analysis have evolved into a resource-rich tool for collecting, researching and comparing student achievement levels in the classroom. There are sufficient resources to discover student success through data analysis by routinely collecting extensive data on student behaviour and curriculum structure. Educational Data Mining…
Descriptors: Prediction, Artificial Intelligence, Student Behavior, Academic Achievement
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Umer, Rahila; Susnjak, Teo; Mathrani, Anuradha; Suriadi, Lim – Interactive Learning Environments, 2023
Predictive models on students' academic performance can be built by using historical data for modelling students' learning behaviour. Such models can be employed in educational settings to determine how new students will perform and in predicting whether these students should be classed as at-risk of failing a course. Stakeholders can use…
Descriptors: Prediction, Student Behavior, Models, Academic Achievement
Leone, Elizabeth L. – ProQuest LLC, 2023
Data collection and analyzation practices for English language development services are scarcely found in research, but needed in the subgroup of minority students commonly known as English language learners (Wiseman & Bell, 2021). Wiseman and Bell (2021) identified ELLs as one of the most under-documented student subgroups in the American…
Descriptors: Data Collection, Data Analysis, Second Language Learning, English Language Learners
Complete College America, 2023
Measurement systems give colleges a structure for collecting, sharing, and acting on data. The guidebook and tools presented here help faculty, staff, college leadership, and policymakers understand and use measurement systems--and specifically use data to improve completion rates, close institutional performance gaps, and facilitate economic…
Descriptors: Measurement, Guides, College Faculty, College Administration
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Butuner, Resul; Calp, M. Hanefi – International Journal of Assessment Tools in Education, 2022
Many institutions in the field of education have been involved in distance education with the learning management system. In this context, there has been a rapid increase in data in the e-learning process as a result of the development of technology and the widespread use of the internet. This increase is in the size of large data. Today, big data…
Descriptors: Distance Education, Academic Achievement, Data Collection, Data Analysis
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Gray, Cameron C.; Perkins, Dave; Ritsos, Panagiotis D. – Assessment & Evaluation in Higher Education, 2020
The field of learning analytics is progressing at a rapid rate. New tools, with ever-increasing number of features and a plethora of datasets that are increasingly utilized demonstrate the evolution and multifaceted nature of the field. In particular, the depth and scope of insight that can be gleaned from analysing related datasets can have a…
Descriptors: Educational Research, Data Collection, Data Analysis, Visual Aids
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Alturki, Sarah; Alturki, Nazik; Stuckenschmidt, Heiner – Journal of Information Technology Education: Innovations in Practice, 2021
Aim/Purpose: One of the main objectives of higher education institutions is to provide a high-quality education to their students and reduce dropout rates. This can be achieved by predicting students' academic achievement early using Educational Data Mining (EDM). This study aims to predict students' final grades and identify honorary students at…
Descriptors: Data Collection, Data Analysis, Grade Prediction, Academic Achievement
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Knight, Jim; Faggella-Luby, Michael – Learning Professional, 2022
Data is so deeply woven into the fabric of people's lives that it is next to impossible to imagine what a data-free life would be like. But despite the centrality of data in everyone's personal lives, when people talk about data in schools, their comments are often negative. The authors of this article believe "data" should not be a…
Descriptors: Coaching (Performance), Teacher Effectiveness, Instructional Effectiveness, Data Use
Knight, Jim – ASCD, 2021
Even under ideal conditions, teaching is tough work. Facing unrelenting pressure from administrators and parents and caught in a race against time to improve student outcomes, educators can easily become discouraged (or worse, burn out completely) without a robust coaching system in place to support them. For more than 20 years, perfecting such a…
Descriptors: Coaching (Performance), Academic Achievement, Success, Teaching Methods
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Bharara, Sanyam; Sabitha, Sai; Bansal, Abhay – Education and Information Technologies, 2018
Learning Analytics (LA) is an emerging field in which sophisticated analytic tools are used to improve learning and education. It draws from, and is closely tied to, a series of other fields of study like business intelligence, web analytics, academic analytics, educational data mining, and action analytics. The main objective of this research…
Descriptors: Data Collection, Data Analysis, Correlation, Academic Achievement
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Fawcett, Darcy – set: Research Information for Teachers, 2019
This Assessment News article introduces readers to a statistical approach to making sense of student assessment data in order to help teachers understand whether or not changes in practice have made a difference to learning. It Worked! is the brainchild of Darcy Fawcett, HoD Science at Gisborne Boys' High School, and Across-School Teacher for the…
Descriptors: Data Analysis, Data Use, Evidence Based Practice, Communities of Practice
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Harvey, Annelie J.; Keyes, Helen – Innovations in Education and Teaching International, 2020
Learning Dashboards display analytics pertaining to student performance and attainment, often alongside scores for the class cohort average. Little research has considered the effects of this social comparison information on students' well-being, motivation, and engagement. The current study presented participants with hypothetical data that…
Descriptors: Self Esteem, College Students, Student Motivation, Information Management
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