Publication Date
In 2025 | 1 |
Since 2024 | 7 |
Since 2021 (last 5 years) | 16 |
Since 2016 (last 10 years) | 19 |
Since 2006 (last 20 years) | 19 |
Descriptor
Artificial Intelligence | 19 |
Automation | 19 |
Learning Analytics | 19 |
Feedback (Response) | 7 |
Technology Uses in Education | 6 |
Natural Language Processing | 5 |
Educational Technology | 4 |
Algorithms | 3 |
Computer Assisted Testing | 3 |
Electronic Learning | 3 |
Visual Aids | 3 |
More ▼ |
Source
Author
Adolfo Ruiz-Calleja | 1 |
AlZoubi, Dana | 1 |
Alexandron, Giora | 1 |
Ali, Saba Rasheed | 1 |
Anderson, Evan | 1 |
Andrés Chiappe | 1 |
Anique de Bruin | 1 |
Ariely, Moriah | 1 |
Avraamidou, Lucy | 1 |
Baran, Evrim | 1 |
Bearman, Margaret | 1 |
More ▼ |
Publication Type
Journal Articles | 18 |
Reports - Research | 12 |
Information Analyses | 3 |
Reports - Descriptive | 3 |
Reports - Evaluative | 2 |
Education Level
Higher Education | 4 |
Postsecondary Education | 4 |
Elementary Secondary Education | 2 |
Elementary Education | 1 |
Audience
Researchers | 1 |
Location
China | 1 |
Netherlands | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
Buckingham Shum, Simon; Lim, Lisa-Angelique; Boud, David; Bearman, Margaret; Dawson, Phillip – International Journal of Educational Technology in Higher Education, 2023
Effective learning depends on effective feedback, which in turn requires a set of skills, dispositions and practices on the part of both students and teachers which have been termed "feedback literacy." A previously published teacher "feedback literacy competency framework" has identified what is needed by teachers to implement…
Descriptors: Automation, Feedback (Response), Learning Analytics, Artificial Intelligence
Pankaj Chejara; Luis P. Prieto; Yannis Dimitriadis; Maria Jesus Rodriguez-Triana; Adolfo Ruiz-Calleja; Reet Kasepalu; Shashi Kant Shankar – Journal of Learning Analytics, 2024
Multimodal learning analytics (MMLA) research has shown the feasibility of building automated models of collaboration quality using artificial intelligence (AI) techniques (e.g., supervised machine learning (ML)), thus enabling the development of monitoring and guiding tools for computer-supported collaborative learning (CSCL). However, the…
Descriptors: Learning Analytics, Attribution Theory, Acoustics, Artificial Intelligence
Jonathan K. Foster; Peter Youngs; Rachel van Aswegen; Samarth Singh; Ginger S. Watson; Scott T. Acton – Journal of Learning Analytics, 2024
Despite a tremendous increase in the use of video for conducting research in classrooms as well as preparing and evaluating teachers, there remain notable challenges to using classroom videos at scale, including time and financial costs. Recent advances in artificial intelligence could make the process of analyzing, scoring, and cataloguing videos…
Descriptors: Learning Analytics, Automation, Classification, Artificial Intelligence
Ariely, Moriah; Nazaretsky, Tanya; Alexandron, Giora – International Journal of Artificial Intelligence in Education, 2023
Machine learning algorithms that automatically score scientific explanations can be used to measure students' conceptual understanding, identify gaps in their reasoning, and provide them with timely and individualized feedback. This paper presents the results of a study that uses Hebrew NLP to automatically score student explanations in Biology…
Descriptors: Artificial Intelligence, Algorithms, Natural Language Processing, Hebrew
Baran, Evrim; AlZoubi, Dana; Morales, Anasilvia Salazar – TechTrends: Linking Research and Practice to Improve Learning, 2023
Computational analysis methods and machine learning techniques introduce innovative ways to capture classroom interactions and display data on analytics dashboards. Automated classroom analytics employ advanced data analysis, providing educators with comprehensive insights into student participation, engagement, and behavioral trends within…
Descriptors: Automation, Learning Analytics, Stakeholders, Computation
Ling Wang; Shen Zhan – Education Research and Perspectives, 2024
Generative Artificial Intelligence (GenAI) is transforming education, with assessment design emerging as a crucial area of innovation, particularly in computer science (CS) education. Effective assessment is critical for evaluating student competencies and guiding learning processes, yet traditional practices face significant challenges in CS…
Descriptors: Artificial Intelligence, Computer Science Education, Technology Uses in Education, Student Evaluation
Tsiakmaki, Maria; Kostopoulos, Georgios; Kotsiantis, Sotiris; Ragos, Omiros – Journal of Computing in Higher Education, 2021
Predicting students' learning outcomes is one of the main topics of interest in the area of Educational Data Mining and Learning Analytics. To this end, a plethora of machine learning methods has been successfully applied for solving a variety of predictive problems. However, it is of utmost importance for both educators and data scientists to…
Descriptors: Active Learning, Predictor Variables, Academic Achievement, Learning Analytics
Edwin Gonzalo Vargas; Andrés Chiappe; Julio Durand – Journal of Social Studies Education Research, 2024
This review explores how artificial intelligence (AI henceforth) can reshape education through insights from situated learning literature. The objective was to critically examine opportunities and challenges of situated learning, and how AI could augment strengths while overcoming obstacles. A systematic review using the PRISMA method analyzed 60…
Descriptors: Artificial Intelligence, Situated Learning, Computer Software, Technology Uses in Education
Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
Luzhen Tang; Kejie Shen; Huixiao Le; Yuan Shen; Shufang Tan; Yueying Zhao; Torsten Juelich; Xinyu Li; Dragan Gaševic; Yizhou Fan – Journal of Computer Assisted Learning, 2024
Background: Learners' writing skills are critical to their academic and professional development. Previous studies have shown that learners' self-assessment during writing is essential for assessing their writing products and monitoring their writing processes. However, conducting practical self-assessments of writing remains challenging for…
Descriptors: Self Evaluation (Individuals), Formative Evaluation, Writing Assignments, Writing Skills
Gillani, Nabeel; Eynon, Rebecca; Chiabaut, Catherine; Finkel, Kelsey – Educational Technology & Society, 2023
Recent advances in Artificial Intelligence (AI) have sparked renewed interest in its potential to improve education. However, AI is a loose umbrella term that refers to a collection of methods, capabilities, and limitations--many of which are often not explicitly articulated by researchers, education technology companies, or other AI developers.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Technology, Educational Benefits
Talebinamvar, Mobina; Zarrabi, Forooq – Language Testing in Asia, 2022
Feedback is an essential component of learning environments. However, providing feedback in populated classes can be challenging for teachers. On the one hand, it is unlikely that a single kind of feedback works for all students considering the heterogeneous nature of their needs. On the other hand, delivering personalized feedback is infeasible…
Descriptors: Feedback (Response), Writing Evaluation, Writing (Composition), Learning Analytics
Tran, Tich Phuoc; Meacheam, David – IEEE Transactions on Learning Technologies, 2020
The use of learning management systems (LMSs) for learning and knowledge sharing has accelerated quickly both in education and corporate worlds. Despite the benefits brought by LMSs, the current systems still face significant challenges, including the lack of automation in generating quiz questions and managing courses. Over the past decade, more…
Descriptors: Integrated Learning Systems, Test Construction, Test Items, Automation
Previous Page | Next Page »
Pages: 1 | 2