The phrase "are based on learners" is correct and usable in written English.
It can be used when discussing concepts, theories, or practices that derive from or are influenced by the needs, experiences, or characteristics of learners.
Example: "The teaching methods we implement are based on learners' preferences and learning styles to enhance engagement and understanding."
Alternatives: "derived from learners" or "informed by learners' needs".
Individual expectancies for success, they argue, are based on learners' confidence in their ability to master the challenge posed by the task, while the tasks themselves are considered in the light of importance, usefulness and pleasure (Eccles & Wigfield, 2002; Wigfield & Cambria, 2010; Wigfield & Eccles, 2000).
These works mainly use association rule mining to find the associations among the activities done by learners and then provide recommendations to the individual learner.In these works, recommendations are based on learners' activities in a course rather than learner characteristics, needs and/or profiles.
It is based on learner modifiability for improved performance.
In the latter group, descriptors are created through an empirically verifiable procedure and are based on observable learner behavior, including 'the data-based or data-driven approach,'empiricallyly derived, binary-choice, boundary definition scales,'scalingng descriptors' (Fulcher 2003, p. 92).
Chin (1997) stated that smart learning environments are based on information communication technology, centered on learners, and with the following characteristics: the environment can adapt to the learning style and learning ability of diverse learners; can support the learners for lifelong learning; can support the learners for their development.
These ontological descriptions are based on specific tasks performed by learners, which are independent of the knowledge structures examined within specific learning domains.
Traditional educational programs too often have an insular character in which the expectations of learners are based on what has been taught in the past.
Most of these ensemble methods are based on the philosophy that multiple weak learners can be leveraged to obtain one strong learner which is better than the individual weak ones.
Generic learner models are based on a simplification.
As observed above, some approaches to negotiating or interacting about the learner model are based on Toulmin's (1959) argument pattern.
They are based on the premise that we all are either figural, semantic or symbolic learners.
