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Direct linkShan Zhang; Priyadharshini Ganapathy Prasad; Noah L. Schroeder – Journal of Educational Computing Research, 2025
Given the ubiquity of artificial intelligence (AI), it is essential to empower students to become creators, designers, and producers of AI technologies, rather than limiting them to the role of informed consumers. To achieve this, learners need to be equipped with AI knowledge and concepts and develop AI literacy. Paradoxically, it is largely…
Descriptors: Artificial Intelligence, Technological Literacy, Teaching Methods, Instructional Materials
Reigeluth, Charles M.; Aslan, Sinem; Chen, Zengguan; Dutta, Pratima; Huh, Yeol; Lee, Dabae; Lin, Chun-Yi; Lu, Ya-Huei; Min, Mina; Tan, Verily; Watson, Sunnie Lee; Watson, William R. – Journal of Educational Computing Research, 2015
The learner-centered paradigm of instruction differs in such fundamental ways from the teacher-centered paradigm that it requires technology to serve very different functions. In 2006, a research team at Indiana University began to work on identifying those functions and published their results in 2008. Subsequently, the team elaborated and…
Descriptors: Individualized Instruction, Learner Controlled Instruction, Intelligent Tutoring Systems, Interdisciplinary Approach
Moridis, C. N.; Economides, A. A. – Journal of Educational Computing Research, 2008
The aim of this survey is to provide an overview of the various components of "computer aided affective learning systems." The research is classified into 3 main scientific areas that are integral parts of the development of these kinds of systems. The three main scientific areas are: i) emotions and their connection to learning; ii) affect…
Descriptors: Educational Technology, Literature Reviews, Interdisciplinary Approach, Cognitive Science
