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Designing Assignments to Assess Adaptive Learning Capabilities

In assessment practice, it is useful to explore ways of differentiating between well-presented expression of established knowledge and methods and the kind of subject understanding, appreciation and reasoning demonstrated by an 'expert'. In this way, the identification and assessment of adaptive learning can be based upon the intended aims of the course and the academic ability of the course tutor, as "expert". If assessment is designed for adoptive learning, students will tend to use and develop adoptive learning processes, while if it is designed for adaptive learning students will use and develop higher cognitive processes (to the best of their ability). The course design can be enhanced, therefore, by balancing the adoptive and adaptive components of the assessment such that it reflects the overall intended nature of the course.

Course assignments can be used as part of the learning support in general as well as for assessing the extent to which a student has developed particular capabilities (Table 2). In terms of developing adaptive learning or assessing the extent to which a student has developed expertise, four basic questions act as a guide:

1.    Will the assignment task enable expertise to be demonstrated?
2.    Does the task allow students fully to demonstrate their level of expertise?
3.    Are students in a position to judge the quality of their work before it is assessed?
4.    Could students complete the assignment successfully through purely adoptive learning?

Although academic experts are often intuitively aware of appropriate assignments for determining the students’ level of expertise, some generic guidance is suggested below that may assist in making more explicit statements about the assessment process. Assignments that assess expertise have the following characteristics (among others for each discipline):

  • There is no unique, established solution or correct response. Assignments tend to be open, novel and discursive in nature and form (at least for the students) with no fixed approach.
  • No purely procedural, 'algorithmic' or learned response will suffice. The assignment thus requires modelling such that the student must bring unidentified structure to a problem.
  • Judgements of value, likelihood and probability are required. These require the development of a view, perspective or approach and a coherent trend of reasoning with supportive evidence.
  • Originality, innovation, creativity, insight, personal interpretation, contemplation and reflection are required. This requires qualitative, descriptive, information-rich approaches based on a broad remit.
  • Tasks are concerned primarily with the conceptualisation of the subject as opposed to the substantive knowledge and techniques content of the subject.
  • Scope within the task for creative input is provided so that the students can demonstrate fully their level of expertise.

The interpretations of these generic descriptions will clearly be subject-specific, but the basic learning outcomes (Table 2) are surprisingly subject-independent. This cross-discipline commonality is a reflection of the transferability of a student's ability to create form from information, situations and knowledge.