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Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
Qi Lang; Shengjing Tian; Mo Wang; Jianan Wang – IEEE Transactions on Learning Technologies, 2024
Entrepreneurship education is critical in encouraging students' innovation, creativity, and entrepreneurial spirit. It provides essential skills and knowledge, enabling them to open their creative potential and apply innovative thinking across diverse professional fields. With the widespread application of large language models in education,…
Descriptors: Entrepreneurship, Business Administration Education, Artificial Intelligence, Creativity
Özcan, Halil Ziya; Batur, Zekerya – International Journal of Education and Literacy Studies, 2021
Literacy is a term generally used for adults and young people. Basically, it is an acquisition that includes the process of reading, writing and understanding symbols in any language. While this concept, whose definition and scope has expanded over time, refers to people who can only say their names in the past, today it refers to individuals who…
Descriptors: Bibliometrics, Journal Articles, Difficulty Level, Reading Comprehension
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Journal of Artificial Intelligence in Education, 2020
For decades, educators have relied on readability metrics that tend to oversimplify dimensions of text difficulty. This study examines the potential of applying advanced artificial intelligence methods to the educational problem of assessing text difficulty. The combination of hierarchical machine learning and natural language processing (NLP) is…
Descriptors: Natural Language Processing, Artificial Intelligence, Man Machine Systems, Classification
Schroeder, Noah L.; Adesope, Olusola O.; Gilbert, Rachel Barouch – Journal of Educational Computing Research, 2013
Research on the use of software programs and tools such as pedagogical agents has peaked over the last decade. Pedagogical agents are on-screen characters that facilitate instruction. This meta-analysis examined the effect of using pedagogical agents on learning by reviewing 43 studies involving 3,088 participants. Analysis of the results…
Descriptors: Meta Analysis, Cybernetics, Artificial Intelligence, Technology Uses in Education

Buckland, Michael K.; Florian, Doris – Journal of the American Society for Information Science, 1991
Examines the relationship between users' expertise, task complexity of information system use, and artificial intelligence to provide the basis for a conceptual framework for considering the role that artificial intelligence might play in information systems. Cognitive and conceptual models are discussed, and cost effectiveness is considered. (27…
Descriptors: Artificial Intelligence, Computer System Design, Cost Effectiveness, Difficulty Level

Sweller, John – Australian Journal of Education, 1990
A review of research and theory on cognitive processes and their relationship to instructional technique since the early 1970s looks at the contributions of schema theory and artificial intelligence and their instructional implications, including cognitive load theory, worked examples for learning problem solving, and physical vs. mental…
Descriptors: Artificial Intelligence, Classroom Techniques, Cognitive Processes, Difficulty Level