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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
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
Hussain, Sadiq; Gaftandzhieva, Silvia; Maniruzzaman, Md.; Doneva, Rositsa; Muhsin, Zahraa Fadhil – Education and Information Technologies, 2021
Educational data mining helps the educational institutions to perform effectively and efficiently by exploiting the data related to all its stakeholders. It can help the at-risk students, develop recommendation systems and alert the students at different levels. It is beneficial to the students, educators and authorities as a whole. Deep learning…
Descriptors: Regression (Statistics), Academic Achievement, Learning Analytics, Models
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
Khan, Ijaz; Ahmad, Abdul Rahim; Jabeur, Nafaa; Mahdi, Mohammed Najah – Smart Learning Environments, 2021
A major problem an instructor experiences is the systematic monitoring of students' academic progress in a course. The moment the students, with unsatisfactory academic progress, are identified the instructor can take measures to offer additional support to the struggling students. The fact is that the modern-day educational institutes tend to…
Descriptors: Artificial Intelligence, Academic Achievement, Progress Monitoring, Data Collection
Mohamed, Mohamed Hegazy; Abdelgaber, Sayed; Abd-Ellatif, Laila – Journal of Education and e-Learning Research, 2023
Governments and educational authorities around the world are emphasizing performance evaluation of educational systems. Opinion Mining (OM) has gained acceptance among experts in various regions, including the preparation space. The proposed model involves Two modules: the data preprocessing module and the opinion mining module. The main objective…
Descriptors: Educational Practices, Program Evaluation, Opinions, Data Collection
Nahar, Khaledun; Shova, Boishakhe Islam; Ria, Tahmina; Rashid, Humayara Binte; Islam, A. H. M. Saiful – Education and Information Technologies, 2021
Information is everywhere in a hidden and scattered way. It becomes useful when we apply Data mining to extracts the hidden, meaningful, and potentially useful patterns from these vast data resources. Educational data mining ensures a quality education by analyzing educational data based on various aspects. In this paper, we have analyzed the…
Descriptors: Learning Analytics, College Students, Engineering Education, Data Collection
Bohorquez, Carlos; Marquet, Pascal – International Association for Development of the Information Society, 2019
This paper describes the first stages on the development of a design method of digital trainings using the collaborative authoring tool "ALO". Based on the theory of instrumental conflict (Marquet, 2005), this method highlights the necessity of the design digital trainings under the optimal harmonization for users/learners in didactic,…
Descriptors: Instructional Design, Programming, Conflict, Teaching Methods
Leblay, Joffrey; Rabah, Mourad; Champagnat, Ronan; Nowakowski, Samuel – International Association for Development of the Information Society, 2018
How can we learn to use properly business software, digital environments, games or intelligent tutoring systems (ITS)? Mainly, we assume that the new user will learn by doing. But what about the efficiency of such a method? Our approach proposes an answer by introducing on-line coaching. In learning process, learners may need guidance to help them…
Descriptors: Intelligent Tutoring Systems, Coaching (Performance), Efficiency, Learning Processes
Barros, Thiago M.; Souza Neto, Plácido A.; Silva, Ivanovitch; Guedes, Luiz Affonso – Education Sciences, 2019
Predicting school dropout rates is an important issue for the smooth execution of an educational system. This problem is solved by classifying students into two classes using educational activities related statistical datasets. One of the classes must identify the students who have the tendency to persist. The other class must identify the…
Descriptors: Predictor Variables, Models, Dropout Rate, Classification
Mandel, Travis Scott – ProQuest LLC, 2017
When a new student comes to play an educational game, how can we determine what content to give them such that they learn as much as possible? When a frustrated customer calls in to a helpline, how can we determine what to say to best assist them? When an ill patient comes in to the clinic, how do we determine what tests to run and treatments to…
Descriptors: Reinforcement, Learning Processes, Student Evaluation, Data Collection
Jimenez, Laura – Center for American Progress, 2020
Schools face enormous challenges regarding how to operate efficiently and safely for the 2020-21 school year. As part of that response, some state leaders are asking the U.S. Department of Education to waive the annual federal testing and accountability requirements for 2021, which are key to understanding and addressing gaps in education among…
Descriptors: COVID-19, Pandemics, Disease Control, Well Being
Ukpokodu, Omiunota N. – Urban Review: Issues and Ideas in Public Education, 2018
African immigrants in the U.S. have been headlined as America's "new model minority." The purpose of this paper is to examine if evidence exists to support the claim of African immigrant students' (AIS) educational achievement and excellence (a core indicator of the "model minority" theory) in U.S. k-12 schools. Using a…
Descriptors: Immigrants, Blacks, Models, Minority Group Students
Arnold, Kimberly E. – ProQuest LLC, 2017
In the 21st century, attainment of a college degree is more important than ever to achieve economic self-sufficiency, employment, and an adequate standard of living. Projections suggest that by 2020, 65% of jobs available in the U.S. will require postsecondary education. This reality creates an unprecedented demand for higher education, and…
Descriptors: Educational Technology, Profiles, Biographies, Demography
Rhode Island Department of Education, 2019
Rhode Island is committed to ensuring that all educators receive fair, accurate, and meaningful educator evaluations that provide information that can help all teachers improve and refine their practice. Currently, districts in Rhode Island may submit a district-designed model for approval that complies with the Educator Evaluation System…
Descriptors: Guides, Evaluation Methods, Public Schools, Educational Objectives