Table 3

Practical considerations for the design and development of adaptive e-learning environments

Practical considerationsExplanations
Developing the educational content
  • Given the adaptivity and the different learning pathways inherent to adaptive e-learning environments (AEEs), it is necessary to develop more pedagogical content (eg, 60 min of learning) to reach the planned duration of each adaptive e-learning session (eg, 30 min of learning).

Selecting a theoretical framework
  • Selecting a theoretical framework coherent with the underlining principles of adaptivity of AEEs is crucial. These frameworks can be related to human cognition (eg, cognitive load theory, cognitive tutoring), behaviour change (eg, transtheoretical model, I-Change model) or learning (eg, perceptual learning, situated learning).

Selecting the adaptivity method
  • Selecting the adaptivity method refers to how the AEE will adapt its instructional sequence. There are two main adaptivity methods:

    • Designed adaptivity is based on the expertise of the educator who designs personalised pathways to guide learners to learning content mastery;

    • Algorithmic adaptivity is based on different algorithms to determine, for instance, the extent of the learner’s knowledge and the optimal instructional pathway.

Selecting the adaptivity goal(s)
  • Selecting the adaptivity goal(s) is important, since it will dictate how the instruction will be adapted in the AEE. The goal of adaptivity within an AEE may be to increase learning effectiveness, increase learning efficiency, modify behavioural predictors or improve cognitive/metacognitive processes related to learning.

Selecting the adaptivity timing
  • Selecting the timing of adaptivity within an AEE relates to when the adaptivity occurs during the learning process. Adaptivity can be implemented at the beginning of the training only, or throughout the training. Adaptivity timing is closely linked to which adaptivity factor(s) are targeted in learners.

Selecting the adaptivity factor(s)
  • Adaptivity factors are essentially data on which the adaptivity process is based. These data can be related to the learner’s performance (eg, knowledge, skills), his behaviour/actions on the page (eg, response time, requests for help), his overall learning path on the platform or any other variables of interest in the learner.

Selecting the adaptivity type(s)
  • Multiple types of adaptivity can be implemented in an AEE:

    • Content adaptivity refers to the adaptation of the textual information.

    • Navigation adaptivity refers to the adaptation of the curriculum sequence.

    • Presentation adaptivity refers to the adaptation of layout of the screen to the digital device used, or to the learner’s profile.

    • Multimedia adaptivity refers to the adaptation of multimedia elements of the training such as videos, pictures, models.

    • Tools adaptivity refers to the adaptation of training features, learning strategies or learning assessment methods (eg, interface for problem-solving).

Determining your technical resources and selecting the adaptive e-learning platform
  • After the content has been developed, the theoretical framework has been selected and the decisions related to the different subdomains’ adaptivity have been made, it is crucial to determine your technical resources and evaluate pre-existing adaptive e-learning software to determine if it meets your needs and goals. If you plan to employ a specialist or team to develop the platform, estimate development cost and timeline.