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Perrotta, Carlo – Learning, Media and Technology, 2023
This article proposes a pragmatic approach to data justice in education that draws upon Nancy Fraser's theory. The main argument is premised on the theoretical and practical superiority of a deontological framework for addressing algorithmic bias and harms, compared to ethical guidelines. The purpose of a deontological framework is to enable the…
Descriptors: Data, Justice, Algorithms, Bias
A. M. Sadek; Fahad Al-Muhlaki – Measurement: Interdisciplinary Research and Perspectives, 2024
In this study, the accuracy of the artificial neural network (ANN) was assessed considering the uncertainties associated with the randomness of the data and the lack of learning. The Monte-Carlo algorithm was applied to simulate the randomness of the input variables and evaluate the output distribution. It has been shown that under certain…
Descriptors: Monte Carlo Methods, Accuracy, Artificial Intelligence, Guidelines
Pargman, Teresa Cerratto; McGrath, Cormac; Viberg, Olga; Knight, Simon – Journal of Learning Analytics, 2023
The focus of ethics in learning analytics (LA) frameworks and guidelines is predominantly on procedural elements of data management and accountability. Another, less represented focus is on the duty to act and LA as a moral practice. Data feminism as a critical theoretical approach to data science practices may offer LA research and practitioners…
Descriptors: Learning Analytics, Responsibility, Feminism, Ethics
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
Chun Yan Enoch Sit; Siu-Cheung Kong – Journal of Educational Computing Research, 2024
Educational process mining aims (EPM) to help teachers understand the overall learning process of their students. Although deep learning models have shown promising results in many domains, the event log dataset in many online courses may not be large enough for deep learning models to approximate the probability distribution of students' learning…
Descriptors: Learning Processes, Learning Analytics, Algorithms, Guidelines
Conijn, Rianne; Kahr, Patricia; Snijders, Chris – Journal of Learning Analytics, 2023
Ethical considerations, including transparency, play an important role when using artificial intelligence (AI) in education. Explainable AI has been coined as a solution to provide more insight into the inner workings of AI algorithms. However, carefully designed user studies on how to design explanations for AI in education are still limited. The…
Descriptors: Ethics, Writing Evaluation, Artificial Intelligence, Essays
Brianza, Eliana; Schmid, Mirjam; Tondeur, Jo; Petko, Dominik – Contemporary Issues in Technology and Teacher Education (CITE Journal), 2022
The technology, pedagogy, and content knowledge (TPACK) framework describes seven domains of knowledge that teachers rely on for teaching with technology. The framework includes an eighth element labelled "contexts," representing the situated nature of instruction. This latter construct has been inconsistently represented and defined…
Descriptors: Technological Literacy, Pedagogical Content Knowledge, Research Reports, Teaching Methods
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
David B. Nelson; Anaelle Emma Gackiere; Samantha Elizabeth LeGrand; Daniel A. Guberman – Thresholds in Education, 2025
In response to the significant disruption posed by emergent AI technology, we propose a four part framework for teaching and learning practice and development. Rather than focus on the specific technologies of the moment, this framework provides actionable suggestions for individuals with varying views of AI and its positive and negative…
Descriptors: Teaching Methods, Learning Processes, Algorithms, Artificial Intelligence
Prinsloo, Paul; Slade, Sharon; Khalil, Mohammad – Journal of Research on Technology in Education, 2023
This article seeks to explore different combinations of human and Artificial Intelligence (AI) decision-making in the context of distributed learning. Distributed learning institutions face specific challenges such as high levels of student attrition and ensuring quality, cost-effective student support at scale using a range of technologies, such…
Descriptors: Decision Making, Algorithms, Artificial Intelligence, Cost Effectiveness
Vanermen, Lanze; Vlieghe, Joris; Decuypere, Mathias – Curriculum Inquiry, 2022
In open and higher education, digital technologies are increasingly used to enable flexible learning pathways and unbundle programs into separate courses. Whereas technologies have been praised for enhancing the flexibility of curricula, the implications of going digital have yet to be fully explored in curriculum studies. This article aims to…
Descriptors: Open Education, Higher Education, Flexible Scheduling, Learning Management Systems
Harmon, Paul; Pipe, Peter – Performance and Instruction, 1986
Describes design and presents examples of industrial use of small expert systems and guidelines for choosing problems which lend themselves to small tool solutions. Use of microcomputer facilitated decision tables to diagnose and categorize people, things, and issues is suggested, and development of three decision table formats is described. (MBR)
Descriptors: Algorithms, Artificial Intelligence, Decision Making, Design
Yelon, Stephen – Performance and Instruction, 1992
Guidelines for the integration of effective and efficient practice into the lecture format of higher education curricula are outlined and discussed. An algorithm for incorporating active learning into lecture courses is provided, with examples and discussion of possible constraints. (four references) (EA)
Descriptors: Algorithms, Experiential Learning, Flow Charts, Guidelines

McKillip, William D.; Aviv, Cherie Adler – Arithmetic Teacher, 1979
An approach is suggested to the use of sets of practice exercises that is more like the actual use of computation by adults and may be more effective in attaining accuracy and speed. (MP)
Descriptors: Algorithms, Computation, Elementary Education, Elementary School Mathematics

Vazquez-Abad, Jesus; LaFleur, Marc – Computers and Education, 1990
Reviews criticisms of the use of drill and practice programs in educational computing and describes potentials for its use in instruction. Topics discussed include guidelines for developing computer-based drill and practice; scripted training courseware; item format design; item bank design; and a performance-responsive algorithm for item…
Descriptors: Algorithms, Computer Assisted Instruction, Courseware, Drills (Practice)
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