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Showing 1 to 15 of 34 results Save | Export
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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
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Smail, Boussaadi; Aliane, Hassina; Abdeldjalil, Ouahabi – Education and Information Technologies, 2023
The search for relevant scientific articles is a crucial step in any research project. However, the vast number of articles published and available online in digital databases (Google Scholar, Semantic Scholar, etc.) can make this task tedious and negatively impact a researcher's productivity. This article proposes a new method of recommending…
Descriptors: Scientific and Technical Information, Journal Articles, Online Searching, Databases
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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
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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
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Diego G. Campos; Tim Fütterer; Thomas Gfrörer; Rosa Lavelle-Hill; Kou Murayama; Lars König; Martin Hecht; Steffen Zitzmann; Ronny Scherer – Educational Psychology Review, 2024
Systematic reviews and meta-analyses are crucial for advancing research, yet they are time-consuming and resource-demanding. Although machine learning and natural language processing algorithms may reduce this time and these resources, their performance has not been tested in education and educational psychology, and there is a lack of clear…
Descriptors: Artificial Intelligence, Algorithms, Computer System Design, Natural Language Processing
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Clarivando Francisco Belizário Júnior; Fabiano Azevedo Dorça; Luciana Pereira de Assis; Alessandro Vivas Andrade – International Journal of Learning Technology, 2024
Loop-based intelligent tutoring systems (ITSs) support the learning process using a step-by-step problem-solving approach. A limitation of ITSs is that few contents are compatible with this approach. On the other hand, recommendation systems can recommend different types of content but ignore the fine-grained concepts typical of the step-by-step…
Descriptors: Artificial Intelligence, Educational Technology, Individualized Instruction, Cognitive Style
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Yao, Ching-Bang; Wu, Yu-Ling – International Journal of Information and Communication Technology Education, 2022
With the impacts of COVID-19 epidemic, e-learning has become a popular research issue. Therefore, how to upgrade the interactivity of e-learning, and allow learners to quickly access personalized and popular learning information from huge digital materials, is very important. However, chatbots are mostly used in automation, as well as simple…
Descriptors: Electronic Learning, Artificial Intelligence, Individualized Instruction, Bayesian Statistics
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Jordan M. Wheeler; Allan S. Cohen; Shiyu Wang – Journal of Educational and Behavioral Statistics, 2024
Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…
Descriptors: Semantics, Educational Assessment, Evaluators, Reliability
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Kang, Tinghu; Tang, Tinghao; Zhang, Peizhi; Luo, Shu; Qi, Huanhuan – British Journal of Educational Psychology, 2023
Background: The ability to translate concrete manipulatives into abstract mathematical formulas can aid in the solving of mathematical word problems among students, and metacognitive prompts play a significant role in enhancing this process. Aims: Based on the concept of semantic congruence, we explored the effects of metacognitive prompts and…
Descriptors: Metacognition, Eye Movements, Cues, Elementary School Students
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Fragkiadakis, Manolis – Sign Language Studies, 2022
Signs in sign languages have been mainly analyzed as composed of three formational elements: hand configuration, location, and movement. Researchers compare and contrast lexical differences and similarities among different signs and languages based on these formal elements. Such measurement requires extensive manual annotation of each feature…
Descriptors: American Sign Language, Sign Language, Contrastive Linguistics, Foreign Countries
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Miaomiao Liu; Yixun Li; Yongqiang Su; Hong Li – Scientific Studies of Reading, 2024
Purpose: This study sought to 1) identify linguistic features important for Chinese text complexity with a theory-based and systematic approach, and 2) address how feature sets and algorithms affect the performance of Chinese text complexity models. Method: Texts from Chinese language arts textbooks from Grades 1 to 6 (N = 1,478) in Mainland China…
Descriptors: Difficulty Level, Textbooks, Algorithms, Artificial Intelligence
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Ritter, Frauke; Standl, Bernhard – Informatics in Education, 2023
We live in a digital age, not least accelerated by the COVID-19 pandemic. It is all the more important in our society that students learn and master the key competence of algorithmic thinking to understand the informatics concepts behind every digital phenomena and thus is able to actively shape the future. For this to be successful, concepts must…
Descriptors: Algorithms, Information Science Education, Computer Science Education, COVID-19
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Weinstein, Theresa J.; Ceh, Simon Majed; Meinel, Christoph; Benedek, Mathias – Creativity Research Journal, 2022
Evaluating creativity of verbal responses or texts is a challenging task due to psychometric issues associated with subjective ratings and the peculiarities of textual data. We explore an approach to objectively assess the creativity of responses in a sentence generation task to (1) better understand what language-related aspects are valued by…
Descriptors: Creativity, Sentences, Natural Language Processing, Computation
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Koyama, Masafumi; Morita, Kazuhiro; Fuketa, Masao; Aoe, Jun-Ichi – Information Processing & Management, 1998
Presents a faster method for determining hierarchical relationships in information retrieval by using trie structures instead of a linear storage of a concept code. Highlights include case structures, a knowledge representation for natural-language understanding with semantic constraints; a compression algorithm of tries; and evaluation.…
Descriptors: Algorithms, Evaluation Methods, Information Retrieval, Knowledge Representation
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Shen, Sheldon – Information Processing and Management, 1988
Describes a model for a front end query processor to deal with incomplete information in a database. The effectiveness of the processor in restricting the number of objects to be processed in a query and in aiding the interpretation of a query is discussed. (26 references) (Author/CLB)
Descriptors: Algorithms, Computational Linguistics, Databases, Mathematical Formulas
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