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Kil, David; Baldasare, Angela; Milliron, Mark – Current Issues in Education, 2021
Student success, both during and after college, is central to the mission of higher education. Within the higher-education and, more specifically, the student-success context, the core raison d'être of machine learning (ML) is to help institutions achieve their social mission in an efficient and effective manner. While there should be synergy…
Descriptors: Learning Analytics, Academic Achievement, College Students, Electronic Learning
James M. Castle – ProQuest LLC, 2021
This dissertation is presented in multiple article format with an introduction, a literature review, a design case, a mixed methods study, and a conclusion. The literature review outlines important concepts and theories that appear in subsequent manuscripts. The design case describes the seven-year design process that resulted in the online…
Descriptors: Learning Analytics, Electronic Learning, Physical Education, Metabolism
Haojie Li; Tongde Zhang – International Education Studies, 2024
Hands-off data-driven learning is a data-based, student-oriented learning model characterized by inquiry and discovery. English context vocabulary teaching is the key to English teaching in colleges and an important indicator to evaluate the quality and level of college English teaching, which is a language teaching paradigm focusing on the…
Descriptors: Vocabulary Development, Teaching Methods, English (Second Language), Second Language Learning
Lyndsay Grant – Research in Education, 2024
The digitalisation and datafication of education has raised profound questions about the changing role of teachers' educational expertise and agency, as automated processes, data-driven analytics and accountability regimes produce new forms of knowledge and governance. Increasingly, research is paying greater attention to the significant role of…
Descriptors: Data, Computer Networks, Computer Interfaces, Computer System Design
Shi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics
Jiangyue Liu; Siran Li; Qianyan Dong – Journal of Educational Computing Research, 2024
The emergence of Generative Artificial Intelligence (GAI) has caused significant disruption to the traditional educational teaching ecosystem. GAI possesses remarkable capabilities in generating human-like text and boasts an extensive knowledge repository, thereby paving the way for potential collaboration with humans. However, current research on…
Descriptors: Artificial Intelligence, Learning Analytics, Computer Uses in Education, Instructional Design
Namrata Srivastava; Sadia Nawaz; Yi-Shan Tsai; Dragan Gaševic – Journal of Learning Analytics, 2024
In a higher education context, students are expected to take charge of their learning by deciding "what" to learn and "how" to learn. While the learning analytics (LA) community has seen increasing research on the "how" to learn part (i.e., researching methods for supporting students in their learning journey), the…
Descriptors: Learning Analytics, Decision Making, Elective Courses, Undergraduate Students
Erkan Er; Safak Silik; Sergen Cansiz – Journal of Learning Analytics, 2024
E-learning platforms have become increasingly popular in K--8 education to promote student learning and enhance classroom teaching. Student interactions with these platforms produce trace data, which are digital records of learning processes. Although trace data have been effective in identifying learners' engagement profiles in higher education…
Descriptors: Foreign Countries, Elementary Secondary Education, Grade 1, Grade 2
Lars de Vreugd; Anouschka van Leeuwen; Renée Jansen; Marieke van der Schaaf – Journal of Learning Analytics, 2024
For university students, self-regulation of study behaviour is important. However, students are not always capable of effective self-regulation. Providing study behaviour information via a learning analytics dashboard (LAD) may support phases within self-regulated learning (SRL). However, it is unclear what information a LAD should provide, how to…
Descriptors: Learning Management Systems, Learning Analytics, Student Behavior, Behavior Patterns
Yeting Hu; Chuanzhi Fang; Xin He; Jinhua Wu – International Journal of Web-Based Learning and Teaching Technologies, 2024
This study addresses the problems in traditional English literature teaching methods for Chinese English majors, proposing a new teaching approach based on smart education concepts to enhance learning effectiveness. An evaluation of a semester-long reform in teaching methods is conducted using a quantitative methodology. The findings reveal…
Descriptors: Teaching Methods, English Literature, Learning Analytics, Outcomes of Education
Arjan J. F. Kok; Lex Bijlsma; Cornelis Huizing; Ruurd Kuiper; Harrie Passier – Informatics in Education, 2024
This paper presents the first experiences of the use of an online open-source repository with programming exercises. The repository is independent of any specific teaching approach. Students can search for and select an exercise that trains the programming concepts that they want to train and that only uses the programming concepts they already…
Descriptors: Programming Languages, Computer Science Education, Open Source Technology, Teaching Methods
Lixiang Yan; Vanessa Echeverria; Yueqiao Jin; Gloria Fernandez-Nieto; Linxuan Zhao; Xinyu Li; Riordan Alfredo; Zachari Swiecki; Dragan Gaševic; Roberto Martinez-Maldonado – British Journal of Educational Technology, 2024
Multimodal learning analytics (MMLA) offers the potential to provide evidence-based insights into complex learning phenomena such as collaborative learning. Yet, few MMLA applications have closed the learning analytics loop by being evaluated in real-world educational settings. This study evaluates the effectiveness of an MMLA solution in…
Descriptors: Learning Analytics, Cooperative Learning, Longitudinal Studies, Allied Health Occupations Education
Yuxiao Xie; Ziyi Xie; Siyu Chen; Lei Shen; Zhizhuang Duan – Education and Information Technologies, 2025
The National College English Test Band 4 (CET-4) is a key test to assess the English language ability of Chinese university students, and the success rate of the test is important to improve the quality of their English learning. Artificial intelligence technology can be used to predict and explore the factors influencing the success rate. This…
Descriptors: Language Tests, English (Second Language), Second Language Learning, Second Language Instruction
Yi-Ju Wu; Hui-Chin Yeh – Educational Technology & Society, 2025
This empirical investigation rigorously evaluated the teaching potential of Data-Driven Learning (DDL) for enhancing the ability of learners to apply 30 near-synonymous change-of-state verbs in two EFL Freshman English courses in a college setting across two semesters. In the study, 32 participants in the experimental group and 22 in the control…
Descriptors: Verbs, Computational Linguistics, Phrase Structure, North American English
Joel Weijia Lai; Wei Qiu; Maung Thway; Lei Zhang; Nurabidah Binti Jamil; Chit Lin Su; Samuel S. H. Ng; Fun Siong Lim – Journal of Learning Analytics, 2025
The growing use of generative AI (GenAI) has sparked discussions regarding integrating these tools into educational settings to enrich the learning experience of teachers and students. Self-regulated learning (SRL) research is pivotal in addressing this inquiry. One prevalent manifestation of GenAI is the large-language model (LLM) chatbot,…
Descriptors: Artificial Intelligence, Computer Software, Learning Analytics, Introductory Courses

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