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Dalia Khairy; Nouf Alharbi; Mohamed A. Amasha; Marwa F. Areed; Salem Alkhalaf; Rania A. Abougalala – Education and Information Technologies, 2024
Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…
Descriptors: Prediction, Tests, Scores, Information Retrieval
Taolin Zhang; Shuwen Jia; Charoula Angeli – International Journal of Web-Based Learning and Teaching Technologies, 2024
Considering the shortcomings of large evaluation errors, long time, human, and material resources in the evaluation process of the current college teaching mode to improve the accuracy of the evaluation of college teaching mode and reduce the cost of the evaluation, this study proposes an evaluation method for college teaching methods based on…
Descriptors: Evaluation Methods, Educational Change, Learning Analytics, Educational Technology
Catalina Lomos; J. W. Luyten; Frauke Kesting; Filipe Lima da Cunha – Interactive Learning Environments, 2024
Significant attention has been paid to the use of ICT by teachers, especially during the COVID-19 health crisis. This usage has mostly been captured through self-reported survey measurements. Learning analytics can complement such findings, by using log data to document precisely how long teachers use ICT, and what ICT behaviors they perform…
Descriptors: Learning Analytics, Information Technology, Teacher Behavior, Mathematics Education
Onur Karademir; Lena Borgards; Daniele Di Mitri; Sebastian Strauß; Marcus Kubsch; Markus Brobeil; Adrian Grimm; Sebastian Gombert; Nikol Rummel; Knut Neumann; Hendrik Drachsler – Journal of Learning Analytics, 2024
This paper presents a teacher dashboard intervention study in secondary school practice involving teachers (n = 16) with their classes (n = 22) and students (n = 403). A quasi-experimental treatment-control group design was implemented to compare student learning outcomes between classrooms where teachers did not have access to the dashboard and…
Descriptors: Learning Analytics, Intervention, Educational Technology, Secondary School Students
Hongwen Guo; Matthew S. Johnson; Kadriye Ercikan; Luis Saldivia; Michelle Worthington – Journal of Learning Analytics, 2024
Large-scale assessments play a key role in education: educators and stakeholders need to know what students know and can do, so that they can be prepared for education policies and interventions in teaching and learning. However, a score from the assessment may not be enough--educators need to know why students got low scores, how students engaged…
Descriptors: Artificial Intelligence, Learning Analytics, Learning Management Systems, Measurement
Alex Boulton; Nina Vyatkina – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2024
This paper analyses the methodologies in 148 empirical data-driven learning studies for L2 English in prestige journals to examine best practice. Manual coding and corpus analysis of key words and n-grams from the past 5 years (2018-2022) explore the field as a whole and how methodologies have evolved, suggesting improvements and future avenues…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Periodicals
Natasha Arthars; Kate Thompson; Henk Huijser; Steven Kickbusch; Samuel Cunningham; Gavin Winter; Roger Cook; Lori Lockyer – Australasian Journal of Educational Technology, 2024
Assessing group work formatively in higher education poses a significant challenge. The complexity of evaluating individual contributions is compounded by the lack of efficient and effective methods for tracking, analysing and assessing individual engagement and contributions, which can impede timely feedback and the development of group work…
Descriptors: Formative Evaluation, Cooperative Learning, College Students, Student Evaluation
Andrea Horbach; Joey Pehlke; Ronja Laarmann-Quante; Yuning Ding – International Journal of Artificial Intelligence in Education, 2024
This paper investigates crosslingual content scoring, a scenario where scoring models trained on learner data in one language are applied to data in a different language. We analyze data in five different languages (Chinese, English, French, German and Spanish) collected for three prompts of the established English ASAP content scoring dataset. We…
Descriptors: Contrastive Linguistics, Scoring, Learning Analytics, Chinese
Udi Alter; Carmen Dang; Zachary J. Kunicki; Alyssa Counsell – Teaching Statistics: An International Journal for Teachers, 2024
The biggest difference in statistical training from previous decades is the increased use of software. However, little research examines how software impacts learning statistics. Assessing the value of software to statistical learning demands appropriate, valid, and reliable measures. The present study expands the arsenal of tools by reporting on…
Descriptors: Statistics Education, Student Attitudes, Course Descriptions, Social Sciences
Earl H. McKinney Jr.; Simon Ginzinger – Journal of Information Systems Education, 2024
The growing use of analytics has increased the demand for more highly data literate graduates. Awareness of ambiguity in data has been suggested as a new data literacy skill. Here, we describe a student-centered semester-long project that can be used to teach this skill in an introductory analytics or database course. The project requires students…
Descriptors: Student Centered Learning, Student Projects, Consciousness Raising, Ambiguity (Context)
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
Ifenthaler, Dirk, Ed.; Sampson, Demetrios G., Ed.; Isaías, Pedro, Ed. – Cognition and Exploratory Learning in the Digital Age, 2021
This volume focuses on the implications of digital technologies for educators and educational decision makers that is not widely represented in the literature. While there are many volumes on how one might integrate a particular technology, there are no volumes on how digital technologies can or should be exploited to address the needs and propel…
Descriptors: Educational Technology, Technology Integration, Learning Processes, Learning Analytics
Piao, Guangyuan – International Educational Data Mining Society, 2021
Massive Open Online Courses (MOOCs) which enable large-scale open online learning for massive users have been playing an important role in modern education for both students as well as professionals. To keep users' interest in MOOCs, recommender systems have been studied and deployed to recommend courses or videos that a user might be interested…
Descriptors: Concept Formation, Online Courses, Navigation (Information Systems), Learning Analytics

Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
Yousri Attia Mohamed Abouelenein; Shaimaa Abdul Salam Selim; Tahani Ibrahim Aldosemani – Smart Learning Environments, 2025
Learning analytics provides valuable data to inform the best decisions for each learner. This study, based on adaptive environment (AE) learning analytics dashboards, examines how instructor interventions affect student self-regulation abilities and academic performance. It identifies the self-regulation categories requiring the most support to…
Descriptors: Foreign Countries, Higher Education, Preservice Teachers, Learning Analytics