Intelligent adaptation of digital game-based learning

Abstract

Games for learning cannot take the same design approach as games when targeting audiences. While players of entertainment games have the luxury of choosing games that suit them, students using digital games for learning typically have a single game for them to learn from, regardless of whether or not it fits their playing style or learning needs. We contend that this problem can be addressed by creating games that identify the kind of player-learner using the game and adapts itself to best fit that individual. These adaptive games can specialize themselves according to a student's learning needs, gameplay preferences, and learning style. We present a prototype mini-game, called S.C.R.U.B., which employs this method for teaching microbiology concepts.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 51 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.