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Bao Wang; Philippe J. Giabbanelli – International Journal of Artificial Intelligence in Education, 2024
Knowledge maps have been widely used in knowledge elicitation and representation to evaluate and guide students' learning. To effectively evaluate maps, instructors must select the most informative map features that capture students' knowledge constructs. However, there is currently no clear and consistent criteria to select such features, as…
Descriptors: Concept Mapping, Evaluation Methods, Student Evaluation, Algorithms
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Rachel Moylan; Jillianne Code – Teachers and Teaching: Theory and Practice, 2024
Algorithmic systems shape every aspect of our daily lives and impact our perceptions of the world. The ubiquity and profound impact of algorithms mean that algorithm literacy--awareness and knowledge of algorithm use, and the ability to evaluate algorithms critically and exercise agency when engaging with algorithmic systems--is a vital competence…
Descriptors: Algorithms, Teacher Competencies, Digital Literacy, Knowledge Level
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Eeshan Hasan; Erik Duhaime; Jennifer S. Trueblood – Cognitive Research: Principles and Implications, 2024
A crucial bottleneck in medical artificial intelligence (AI) is high-quality labeled medical datasets. In this paper, we test a large variety of wisdom of the crowd algorithms to label medical images that were initially classified by individuals recruited through an app-based platform. Individuals classified skin lesions from the International…
Descriptors: Algorithms, Human Body, Classification, Knowledge Level
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Arshia K. Lodhi; Patricia J. Brooks; C. Donnan Gravelle; Jessica E. Brodsky; Maryam Syed; Donna Scimeca – Journal of Media Literacy Education, 2025
Internet users are bombarded with information and need strategies to evaluate its trustworthiness. Expert fact-checkers rely on lateral reading, which involves investigating sources, finding better coverage, and tracing information back to original contexts. This study contrasted college students' preference for and use of lateral reading to…
Descriptors: Encyclopedias, Electronic Publishing, Algorithms, Reading Comprehension
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Scruggs, Richard; Baker, Ryan S.; Pavlik, Philip I., Jr.; McLaren, Bruce M.; Liu, Ziyang – Educational Technology Research and Development, 2023
Despite considerable advances in knowledge tracing algorithms, educational technologies that use this technology typically continue to use older algorithms, such as Bayesian Knowledge Tracing. One key reason for this is that contemporary knowledge tracing algorithms primarily infer next-problem correctness in the learning system, but do not…
Descriptors: Algorithms, Prediction, Knowledge Level, Video Games
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de Groot, Tjitske; de Haan, Mariëtte; van Dijken, Maartje – Learning, Media and Technology, 2023
Whereas 'Web 2.0 technology' has pushed the learning agenda towards connectivity and boundary crossing, in the current 'new new media ontology' the fear that algorithms might block our avenues to knowledge and connections prevails. In response to this, media scholars have argued that knowledge based on the algorithmic experiences of users is key…
Descriptors: Social Media, Algorithms, Media Literacy, Secondary School Students
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Asiye Toker Gokce; Arzu Deveci Topal; Aynur Kolburan Geçer; Canan Dilek Eren – Education and Information Technologies, 2025
Artificial intelligence (AI) literacy is critical to shaping students' academic experiences and future opportunities inhigher education. This study examines AI literacy among university students, examining variables such as gender, frequency of use of AI applications, completion of AI-related courses, and field of study. The research involved 664…
Descriptors: Artificial Intelligence, Technological Literacy, College Students, Decision Making
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Ma, Hua; Huang, Zhuoxuan; Tang, Wensheng; Zhu, Haibin; Zhang, Hongyu; Li, Jingze – IEEE Transactions on Learning Technologies, 2023
To provide intelligent learning guidance for students in e-learning systems, it is necessary to accurately predict their performance in future exams by analyzing score data in past exams. However, existing research has not addressed the uncertain and dynamic features of students' cognitive status, whereas these features are essential for improving…
Descriptors: Prediction, Student Evaluation, Performance, Tests
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Line Have Musaeus; Deborah Tatar; Peter Musaeus – Journal of Biological Education, 2024
Computational modelling is widely used in biological science. Therefore, biology students need to learn computational modelling. However, there is a lack of evidence about how to teach computational modelling in biology and what the effects are on student learning. The purpose of this intervention-control study was to investigate how knowledge in…
Descriptors: Computation, Models, High School Students, Biology
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Tanjea Ane; Tabatshum Nepa – Research on Education and Media, 2024
Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…
Descriptors: Artificial Intelligence, Prediction, Models, Teaching Methods
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Huo, Rongrong – European Journal of Science and Mathematics Education, 2023
In our investigation of university students' knowledge about real numbers in relation to computer algebra systems (CAS) and how it could be developed in view of their future activity as teachers, we used a computer algorithm as a case to explore the relationship between CAS and the knowledge of real numbers as decimal representations. Our work was…
Descriptors: Numbers, Computer Science Education, Knowledge Level, Algorithms
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Tague, Jean; And Others – Library Trends, 1981
Discusses the notion that knowledge grows exponentially and describes its growth mathematically by an exponential function. Growth patterns in subfields of knowledge or research areas are described citing related research. Interpretation of growth rate statistics and forecasts are included. Thirty-three references and statistics used for graphs…
Descriptors: Abstracts, Algorithms, Functions (Mathematics), Graphs
Zuckerman, June T. – 1992
Various researchers have associated meaningful problem solving with methods guided directly by a conceptual knowledge base. By contast, a meaningless solving course, or sequence of operations, is essentially independent of the solver's conceptual understanding of the problem under consideration. This paper is the first to document a meaningless,…
Descriptors: Algorithms, Biology, Cognitive Processes, Conceptual Tempo
Williams, Carol G. – 1995
Reform efforts in mathematics aim to increase conceptual understanding, an aim that can be supported through concept maps. This study compared the conceptual knowledge of function held by college students in reform and traditional calculus sections at a large state university. Fourteen students from reform sections and 14 from traditional sections…
Descriptors: Algorithms, Calculus, College Students, Comprehension
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Niaz, Mansoor; Robinson, William R. – Research in Science and Technological Education, 1992
Compares performances of students on gas-law problems that require two distinct approaches, either the algorithmic technique or the conceptual gestalt. Indicates that student effectiveness is considerably different utilizing each approach and that training or experience with the algorithm process should not be expected to facilitate the…
Descriptors: Algorithms, Chemistry, Cognitive Ability, Cognitive Style