This paper proposes a fine-grained multi-faceted metadata schema for precise, highly individualized matching of students with learning resources ( materials and experiences) [1]. This match must consider (1) the student's present state of knowledge and their learning objectives (the student's place in a learning trajectory) and scaffolding requirements; (2) student strengths materials should draw on to support learning and student challenges materials should help the student meet; (3) the student's learning style; (4) the student's cultural and social background; (5) time and support resources available to the student; and more. The paper first looks at existing learning materials metadata standards ([2], [3]) and then examines for selected learning repositories ([4], [5]) the formal metadata used and additional information available (and possibly amenable to automatic extraction) in the descriptions of the learning materials. We then draw on the learning sciences ꟷ learning theory, brain research, teaching practice ꟷ to define additional metadata elements needed to meet the high bar set in the opening sentence. We will also discuss briefly how one can get values for all metadata elements through human expertise, automatic extraction, and feedback from students and teachers using a given learning resource
Keywords: Individualized instruction; learning materials metadata, learner characteristics.
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