Adaptive learning is a concept that traces its roots back to at least the 1950s, but the ability to
capture learner data through online learning has provided a breakthrough.
Not exact matches
a) Ideas for investigating the SportAtSchool
Data; b) A spreadsheet containing the counts and percentages of the results and seven random samples from the SportAtSchool data (captured from learners up to January 2012); c) A learners» planning worksheet to help them plan their investigat
Data; b) A spreadsheet containing the counts and percentages of the results and seven random samples from the SportAtSchool
data (captured from learners up to January 2012); c) A learners» planning worksheet to help them plan their investigat
data (
captured from
learners up to January 2012); c) A
learners» planning worksheet to help them plan their investigation.
Yet, much of that work depends on a simple, often unstated, assumption: that the short list of control variables
captured in educational
data systems — prior achievement, student demographics, English language
learner status, eligibility for federally subsidized meals or programs for gifted and special education students — include the relevant factors by which students are sorted to teachers and schools.
This is especially important for teachers of English language
learners and English as a second language teachers, who may not have had any
data captured in the past if they provided additional instruction for part of a school day or week but were not the main content teacher.
Whether that's through tests or
data captured by your LMS, you're left in the perfect position to see how your
learners are progressing, and whether your training programme is meeting its goals.
The same continuous formative assessment that delivers personalization of path, pace, and sequence for every
learner also
captures the instructional insights and learning
data needed to make informed decisions about instruction and instructional programming.