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Showing 1 to 15 of 71 results Save | Export
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Amine Boulahmel; Fahima Djelil; Gregory Smits – Technology, Knowledge and Learning, 2025
Self-regulated learning (SRL) theory comprises cognitive, metacognitive, and affective aspects that enable learners to autonomously manage their learning processes. This article presents a systematic literature review on the measurement of SRL in digital platforms, that compiles the 53 most relevant empirical studies published between 2015 and…
Descriptors: Independent Study, Educational Research, Classification, Educational Indicators
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Senay Kocakoyun Aydogan; Turgut Pura; Fatih Bingül – Malaysian Online Journal of Educational Technology, 2024
In every culture and era, education is considered the most fundamental reality and rule that societies prioritize and deem essential. Throughout the process spanning thousands of years, from the emergence of writing to the present day, education has undergone various forms and formats of change. Education has been a continuous guide for shaping,…
Descriptors: Prediction, Academic Achievement, Artificial Intelligence, Algorithms
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Möller, Annette; George, Ann Cathrice; Groß, Jürgen – International Journal of Research & Method in Education, 2023
Methods based on machine learning have become increasingly popular in many areas as they allow models to be fitted in a highly-data driven fashion and often show comparable or even increased performance in comparison to classical methods. However, in the area of educational sciences, the application of machine learning is still quite uncommon.…
Descriptors: Foreign Countries, Learning Analytics, Classification, Artificial Intelligence
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Anagha Vaidya; Sarika Sharma – Interactive Technology and Smart Education, 2024
Purpose: Course evaluations are formative and are used to evaluate learnings of the students for a course. Anomalies in the evaluation process can lead to a faulty educational outcome. Learning analytics and educational data mining provide a set of techniques that can be conveniently applied to extensive data collected as part of the evaluation…
Descriptors: Course Evaluation, Learning Analytics, Formative Evaluation, Information Retrieval
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Logan Sizemore; Brian Hutchinson; Emily Borda – Chemistry Education Research and Practice, 2024
Education researchers are deeply interested in understanding the way students organize their knowledge. Card sort tasks, which require students to group concepts, are one mechanism to infer a student's organizational strategy. However, the limited resolution of card sort tasks means they necessarily miss some of the nuance in a student's strategy.…
Descriptors: Artificial Intelligence, Chemistry, Cognitive Ability, Abstract Reasoning
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Sghir, Nabila; Adadi, Amina; Lahmer, Mohammed – Education and Information Technologies, 2023
The last few years have witnessed an upsurge in the number of studies using Machine and Deep learning models to predict vital academic outcomes based on different kinds and sources of student-related data, with the goal of improving the learning process from all perspectives. This has led to the emergence of predictive modelling as a core practice…
Descriptors: Prediction, Learning Analytics, Artificial Intelligence, Data Collection
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Abdullahi Yusuf; Norah Md Noor; Shamsudeen Bello – Education and Information Technologies, 2024
Studies examining students' learning behavior predominantly employed rich video data as their main source of information due to the limited knowledge of computer vision and deep learning algorithms. However, one of the challenges faced during such observation is the strenuous task of coding large amounts of video data through repeated viewings. In…
Descriptors: Learning Analytics, Student Behavior, Video Technology, Classification
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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
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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
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Fein, Benedikt; Graßl, Isabella; Beck, Florian; Fraser, Gordon – International Educational Data Mining Society, 2022
The recent trend of embedding source code for machine learning applications also enables new opportunities in learning analytics in programming education, but which code embedding approach is most suitable for learning analytics remains an open question. A common approach to embedding source code lies in extracting syntactic information from a…
Descriptors: Artificial Intelligence, Learning Analytics, Programming, Programming Languages
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Hamal, Oussama; El Faddouli, Nour-Eddine; Harouni, Moulay Hachem Alaoui – World Journal on Educational Technology: Current Issues, 2021
Nowadays, AI is a real springboard for finding solutions to optimize and improve learning and teaching processes. This issue has been a focus of humanity for millennia, and very significant advances have been made in this quest. This article aims to address the issue of optimizing and improving learning and teaching processes through AI…
Descriptors: Artificial Intelligence, Learning Analytics, Computer Uses in Education, Classification
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Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
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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
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Ben-Yaacov, Anat; Hershkovitz, Arnon – Journal of Educational Computing Research, 2023
Block programming has been suggested as a way of engaging young learners with the foundations of programming and computational thinking in a syntax-free manner. Indeed, syntax errors--which form one of two broad categories of errors in programming, the other one being logic errors--are omitted while block programming. However, this does not mean…
Descriptors: Programming, Computation, Thinking Skills, Error Patterns
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Kenneth David Strang; Narasimha Rao Vajjhala – Industry and Higher Education, 2024
This study explores integrating industry-crowdsourced projects within capstone courses of a 4-year Bachelor of Science program at an accredited American university. A unique business consulting model was developed for the final year course, aligning students with 16-weeks industry projects that reflected their academic goals and the program's…
Descriptors: Industry, Universities, Higher Education, Capstone Experiences
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