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Jia Zhu; Xiaodong Ma; Changqin Huang – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT) for evaluating students' knowledge is an essential task in personalized education. More and more researchers have devoted themselves to solving KT tasks, e.g., deep knowledge tracing (DKT), which can capture more sophisticated representations of student knowledge. Nonetheless, these techniques ignore the reconstruction of…
Descriptors: Teaching Methods, Knowledge Level, Algorithms, Attribution Theory
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Alexandra Morrison; Adam M. Wellstead; Helen Dickinson – Teaching Public Administration, 2024
The use of algorithms and automation of public services is not new, but in recent years there has been a step change in processing power and a decrease in the price of these technologies, which means we are seeing more widespread use. These advances are reframing our perception of what matters in ways that impact the ethical dimensions of…
Descriptors: Algorithms, Public Administration, Ethics, Teaching Methods
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Vassoyan, Jean; Vie, Jill-Jênn – International Educational Data Mining Society, 2023
Adaptive learning is an area of educational technology that consists in delivering personalized learning experiences to address the unique needs of each learner. An important subfield of adaptive learning is learning path personalization: it aims at designing systems that recommend sequences of educational activities to maximize students' learning…
Descriptors: Reinforcement, Networks, Simulation, Educational Technology
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Punya Mishra; Danah Henriksen; Lauren J. Woo; Nicole Oster – TechTrends: Linking Research and Practice to Improve Learning, 2025
The emergence of generative artificial intelligence (GenAI) has reignited long-standing debates about technology's role in education. While GenAI potentially offers personalized learning, adaptive tutoring, and automated support, it also raises concerns about algorithmic bias, de-skilling educators, and diminishing human connection. This…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational History, Influence of Technology
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Christine Ladwig; Dana Schwieger – Information Systems Education Journal, 2024
Hollywood screenwriters worry about Artificial Intelligence (AI) replacements taking over their jobs. Famous museums litigate to protect their art from AI infringement. A major retailer scraps a machine-learning based recruitment program that was biased against women. These are just a few examples of how AI is affecting the world of work,…
Descriptors: Computer Science Education, Curriculum Development, Information Systems, Information Science Education
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Beena Joseph; Sajimon Abraham – Knowledge Management & E-Learning, 2023
Currently, the majority of e-learning lessons created and disseminated advocate a "one-size-fits-all" teaching philosophy. The e-learning environment, however, includes slow learners in a noticeable way, just like in traditional classroom settings. Learning analytics of educational data from a learning management system (LMS) have been…
Descriptors: Electronic Learning, Learning Management Systems, Slow Learners, Educational Environment
Coscarelli, William C.; Schwen, Thomas M. – Educational Communication and Technology: A Journal of Theory, Research, and Development, 1979
Presented three algorithms to university students in an introductory laboratory chemistry course and found that differences in the effects of representation modes--flow charts, lists, and standard prose--were complex and changed over 10 lab sessions. There was no evidence that representation mode affected critical thinking ability or final grade.…
Descriptors: Algorithms, Chemistry, Comparative Analysis, Critical Thinking
Landa, L. – 1995
The reasons people most often give for the failures of U.S. schools involve poverty, racial inequality, and a host of social problems. This paper argues that even if all these conditions were remedied, the schools would not produce many more people with the ability to think than they do today. Teachers, who are usually able to think, do not know…
Descriptors: Algorithms, Concept Teaching, Elementary Secondary Education, Generalization
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Dios, R.; Geller, J. – Computers & Education, 1998
Focuses on identifying the educational effects of "activity oriented" instructional techniques. Examines which instructional methods produce enhanced learning and comprehension. Discusses the problem of learning "sorting algorithms," a major topic in every Computer Science curriculum. Presents a low-tech, hands-on teaching method for sorting…
Descriptors: Active Learning, Algorithms, Computer Science Education, Experiential Learning
Landa, Lev N. – Educational Technology, 1998
After reviewing 50 educational software titles produced by 21 companies to assess how thinking and thinking skills were developed, the author found most had similar methodological drawbacks. Describes the algo-heuristic methodological position and outlines drawbacks of current software. (PEN)
Descriptors: Algorithms, Comparative Analysis, Computer Assisted Instruction, Computer Software Evaluation
Halavin, James; Sommer, Charles – 1990
Hypertext and its more advanced form Hypermedia represent a powerful authoring tool with great potential for allowing statistics teachers to develop documents to assist students in an algorithmic fashion. An introduction to the use of Hypertext is presented, with an example of its use. Hypertext is an approach to information management in which…
Descriptors: Algorithms, Authoring Aids (Programing), Computer Assisted Instruction, Computer Software Development
Ogletree, Earl J.; Chavez, Maria – 1981
The instruction of finger counting and finger calculation, also known as Chisanbop, is promoted as a natural method of introducing and teaching the basic processes of addition, subtraction, multiplication and division to children, particularly to those who are mentally and physically handicapped. The sequential process for teaching finger…
Descriptors: Algorithms, Computation, Elementary Education, Elementary School Mathematics
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Willems, J. – Instructional Science, 1981
Discusses the structure of a problem-based curriculum based on the complexity of the problems that the students must solve, taking into account the level they must attain and their previous experience with problem-based teaching. This approach is compared with the conventional teaching methods. Twenty-two references are listed. (CHC)
Descriptors: Algorithms, Cognitive Processes, Conventional Instruction, Educational Strategies