CAPE is an authoring environment for adaptive online learning based on the model-integrated computing paradigm. CAPE supports a domain-specific modeling language for representing the design of online learning experiences and the various ways that they can respond to individual learners as the experiences unfold.  CAPE is companioned with a web-based learning platform called eLMS that supports delivery of the adaptive courseware to learners.

Unique among design environments created with the Generic Modeling Environment (GME) infrastructure, CAPE incorporates support for a dynamic programming language (Python) directly into its modeling paradigm. This support includes visual representations of data modeling elements and computational components that support adaptive aspects of CAPE designs, as well as content sequencing logic of these designs. Python is further used for lightweight design environment automation (wizards and builders), for paradigm-specific GME extension components that scaffold the design language, and for interoperability with the courseware delivery platform (eLMS) that employs a form of embedded model interpretation when enacting CAPE designs with individual learners.

Support for using Python to build GME components (model interpreters and event-based addons) has been generalized and provided in a package called PyGME.

CAPE makes extensive use of GME's model abstraction facility to support instructional design patterns that capture recurring pedagogical strategies and elements.  An integrated web-based design repository can be used to share these patterns with other authors, along with pattern instances and unique designs.   Such sharing is further scaffolded by the CAPE Wizard, a Flash-based extension component for pattern instancing.

Learn more about CAPE and eLMS at the Adaptive Learning Technologies page.