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Adaptive Learning Technology: An Introduction

Adaptive learning technology has been used for years in computer-based testing and test prep contexts, but is also gaining ground in online learning environments. These technologies allow for the development of more personalized online learning experiences with materials that adapt to student performance and skill level. You will also find the term adaptive used to describe assistive technologies that increase the usability of computer systems for those with disabilities and special needs. This post focuses on adaptive learning technologies for personalized learning.

How does it work?

As learners interact with content presented on screen, the programming adjusts what is presented based on the learner's input, navigation, and responses to questions. These adjustments are designed to assist learners individually, meeting them at their skill and knowledge levesl, and presenting information and interactions to help them build from those levels. Adaptive learning incorporates several instructional strategies and learning theories, among them scaffolding and mastery:

  • Scaffolding. Improved learning is sought through the establishment of gradual building blocks, simple to complex, that support the student in the process of constructing learning (Bruner).
  • Mastery. The mastery learning model is based on the idea that all learners can reach a "master" level of skill through clear learning objectives, learner self-pacing, feedback and practice (Skinner), and final assessment.

As an individual student interacts with an adaptive learning system, the programming collects information on where he/she has both strengths and weaknesses in the content area (e.g. math, English). When strengths are identified, more advanced material is added while material that has been mastered is decreased or removed. When weaknesses are identified, additional material is added to include extra practice, and previously covered material in the weak areas is replayed or reviewed. 

Adaptive learning systems have a range of features and functions that work together to provide not only the subject matter content, but also support and guidance as the learner progresses through the adaptive learning modules or courses:

  • Pre-test: Some systems begin with an assessment of current knowledge and skills. These assessments gather information about individual learner characteristics, including prior knowledge.
  • Pacing and control: Adaptive learning systems are usually self-paced and learner-centered, meaning that the learner controls the speed at which the content is delivered and has some choices within the system.
  • Feedback and assessment: Adaptive systems continuously assess student progress and often provide feedback as students work through the interactions presented. This feedback can include more than just correct/incorrect responses – suggesting resources and providing opportunities for additional practice.
  • Progress tracking and reports: Systems that include learner profiles are able to track individual progress and allow users to return to where they left off, breaking their work into multiple sessions. The system can also generate periodic progress reports and also communicate these with instructors who can then provide further guidance to students based on their individual performance.
  • Motivation and reward: Interactive online games are an interesting example of adaptive technology. Players advance based on past choices and performance in the game itself. Games also often motivate players to continue with rewards for reaching higher levels, such as points or badges. These kinds of rewards are also appearing in learning systems motivating students to continue striving for their own "high score," advancing through levels of study and skill achievement.

Examples in Online Learning

Currently, you are most likely to encounter adaptive learning technologies in testing and remedial education settings. Take a look at a few examples of how these technologies are being used with learners at multiple levels.

  • Testing: If you have ever taken a standardized test on a computer (e.g. GRE and some State-level achievement tests) it may have been an adaptive test. These exams usually begin with items that have been evaluated at an average skill level, then select the following test questions based on your answers to previous questions. Adaptive practice tests are available and simulate this testing environment so that test-takers get practice both with the content of the exam and with the adaptive administration of the exam.
  • Practice and remediation: According to a recent article in The Chronicle of Higher Education, Arizona State University is using an adaptive learning system called Knewton, to assist students with basic math. There are plans to add English courses through this program as well and professors can track student progress through the system. Practice and remediation systems help students who come into college without these basic skills to catch up early in their academic programs.
  • Language learning: Educational software systems can be programmed with adaptive features. This can be particularly helpful in language learning and you'll find it in systems like iKnow, which specializes in Japanese, Chinese, and English languages, and LearnThat, which specializes in English vocabulary and spelling. Through a succession of quizzes, users are presented with a sequence of items to respond to – subsequent versions of the quiz include items that give the user more practice and additional information based on how well they performed on the previous quiz.
  • K-12: Through a Next Generation Learning Challenges grant, Texas Tech University is modifying an adaptive learning tutorial system for use at high school and junior high school levels. This system addresses math content and is accessible online. The project includes plans to incorporate this adaptive learning resource with the K-12 math curriculum in the state.

Moving Forward

Incorporating adaptive learning systems is just one way to help learners who may need extra assistance in specific areas. These systems tailor the presentation of content to the individual needs of each learner and provide feedback and incentives to advance their skills and knowledge. As these systems become more widely used and more formally evaluated, there is much more to be learned about how they may improve student learning.

Have you experienced adaptive learning as an online student? If so, consider sharing your thoughts on how the system affected your overall learning. If you are an instructor who has incorporated adaptive technologies in your online class, let us know more about your decision to do so and any results or lessons you may have learned in the process.

August 30th, 2011 written by Staff Writers

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