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Axel Langner; Lea Sophie Hain; Nicole Graulich – Journal of Chemical Education, 2025
Often, eye-tracking researchers define areas of interest (AOIs) to analyze eye-tracking data. Although AOIs can be defined with systematic methods, researchers in organic chemistry education eye-tracking research often define them manually, as the semantic composition of the stimulus must be considered. Still, defining appropriate AOIs during data…
Descriptors: Organic Chemistry, Science Education, Eye Movements, Educational Research
Deepak, Gerard; Trivedi, Ishdutt – International Journal of Adult Education and Technology, 2023
Recommender systems have been actively used in many areas like e-commerce, movie and video suggestions, and have proven to be highly useful for its users. But the use of recommender systems in online learning platforms is often underrated and less likely used. But many of the times it lacks personalisation especially in collaborative approach…
Descriptors: Learning Strategies, Artificial Intelligence, Information Systems, Algorithms
Jing Chen; Bei Fang; Hao Zhang; Xia Xue – Interactive Learning Environments, 2024
High dropout rate exists universally in massive open online courses (MOOCs) due to the separation of teachers and learners in space and time. Dropout prediction using the machine learning method is an extremely important prerequisite to identify potential at-risk learners to improve learning. It has attracted much attention and there have emerged…
Descriptors: MOOCs, Potential Dropouts, Prediction, Artificial Intelligence
Hadis Anahideh; Nazanin Nezami; Abolfazl Asudeh – Grantee Submission, 2025
It is of critical importance to be aware of the historical discrimination embedded in the data and to consider a fairness measure to reduce bias throughout the predictive modeling pipeline. Given various notions of fairness defined in the literature, investigating the correlation and interaction among metrics is vital for addressing unfairness.…
Descriptors: Correlation, Measurement Techniques, Guidelines, Semantics
Oliveira Moraes, Laura; Pedreira, Carlos Eduardo – IEEE Transactions on Learning Technologies, 2021
Manually determining concepts present in a group of questions is a challenging and time-consuming process. However, the process is an essential step while modeling a virtual learning environment since a mapping between concepts and questions using mastery level assessment and recommendation engines is required. In this article, we investigated…
Descriptors: Computer Science Education, Semantics, Coding, Matrices
Jia Tracy Shen – ProQuest LLC, 2023
In education, machine learning (ML), especially deep learning (DL) in recent years, has been extensively used to improve both teaching and learning. Despite the rapid advancement of ML and its application in education, a few challenges remain to be addressed. In this thesis, in particular, we focus on two such challenges: (i) data scarcity and…
Descriptors: Artificial Intelligence, Electronic Learning, Data, Generalization
Xue Wang; Gaoxiang Luo – Society for Research on Educational Effectiveness, 2024
Background: Despite the usefulness of systematic reviews and meta-analyses, they are time-consuming and labor-intensive (Michelson & Reuter, 2019). The technological advancements in recent years have led to the development of tools aimed at streamlining the processes of systematic reviews and meta-analyses. Innovations such as Paperfetcher…
Descriptors: Meta Analysis, Artificial Intelligence, Computational Linguistics, Computer Software
Stéphane Favier; Jean-Luc Dorier – Educational Studies in Mathematics, 2024
In this research, our objective is to characterize the problem-solving procedures of primary and lower secondary students when they solve problems in real class conditions. To do so, we rely first on the concept of heuristics. As this term is very polysemic, we exploit the definition proposed by Rott (2014) to develop a coding manual and thus…
Descriptors: Heuristics, Semantics, Student Evaluation, Mathematics Skills
Chansanam, Wirapong; Jaroenruen, Yuttana; Kaewboonma, Nattapong; Tuamsuk, Kulthida – Education for Information, 2022
This article describes the development process of the Thai cultural knowledge graph, which facilitates a more precise and rapid comprehension of the culture and customs of Thailand. The construction process is as follows: First, data collection technologies and techniques were used to obtain text data from the Wikipedia encyclopedia about cultural…
Descriptors: Foreign Countries, Graphs, Data Collection, Semantics
Bingbing Yan; Chixiang Ma; Mingfei Wang; Ana Isabel Molina – International Journal of Web-Based Learning and Teaching Technologies, 2024
With the emergence of short video and the development of mobile internet, short video software, such as TikTok and Kwai, has emerged. Based on the semantic understanding technology of teaching short videos, a teaching management platform was built to push healthy and positive short video for students' content in a targeted way. Taking the 21st…
Descriptors: Video Technology, Semantics, Visual Aids, Data
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Grantee Submission, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Sun-Joo Cho; Amanda Goodwin; Matthew Naveiras; Paul De Boeck – Journal of Educational Measurement, 2024
Explanatory item response models (EIRMs) have been applied to investigate the effects of person covariates, item covariates, and their interactions in the fields of reading education and psycholinguistics. In practice, it is often assumed that the relationships between the covariates and the logit transformation of item response probability are…
Descriptors: Item Response Theory, Test Items, Models, Maximum Likelihood Statistics
Andrea Domínguez-Lara; Wulfrano Arturo Luna-Ramírez – International Association for Development of the Information Society, 2022
The automatic code generation is the process of generating source code snippets from a program, i.e., code for generating code. Its importance lies in facilitating software development, particularly important is helping in the implementation of software designs such as engineering diagrams, in such a case, automatic code generation copes with the…
Descriptors: Programming, Coding, Computer Software, Programming Languages
Castillo-Zúñiga, Iván; Luna-Rosas, Francisco-Javier; López-Veyna, Jaime-Iván – Comunicar: Media Education Research Journal, 2022
This article presents an Internet data analysis model based on Web Mining with the aim to find knowledge about large amounts of data in cyberspace. To test the proposed method, suicide web pages were analyzed as a study case to identify and detect traits in students with suicidal tendencies. The procedure considers a Web Scraper to locate and…
Descriptors: Psychological Patterns, Suicide, Web Sites, Student Characteristics
Julia Schillo; Mark Turin – Language Documentation & Conservation, 2022
Despite considerable typographical innovations over the past twenty years that have enabled and facilitated typing capabilities for many Indigenous language orthographies, typographical errors continue to disproportionately affect Indigenous languages. These include errors in glyph shapes, which impact legibility, and issues with glyph…
Descriptors: Layout (Publications), Semantics, Language Research, Written Language
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