I am a learning strategist and technologist with a passion for making a difference. My interests include all things eLearning, learning technologies, and instructional design. If you share my interests and want to discuss - AWESOME! I look forward to the collaboration.
Friday, March 20, 2009
Evaluation: Level 2 - Learning
Answers the question - Do participants know more and can they do more after the learning event than before? This evaluation is an assessment of immediate transfer of knowledge and skill. Although it is often conducted at the posttest level only, it should be conducted by base-lining through pretest and measuring change through posttest using module-level quizzes or course-level exams. A typical example might have a learner take a pretest before a course or each module > then run through the course or module > and then take a posttest to measure knowledge or skill improvement. Minimal and optimal criteria levels should be identified during Analysis and specified in the Design so thresholds (cut-offs) for score attribution can be applied to measured changes while this level of evaluation is Developed as part of the training solution. Other examples might include having an instructor evaluate (observes and rates) transfer in class; Watch-me > Try-me > Test-me approaches created with simulation tools and LMS tracking (SCORM) of outcomes; through the use of problem-resolution scenarios built into a course – problem is presented > learner selects solution > track responses and performance through the LMS (SCORM); or by creating broken environments in certification scenarios and having learners/candidates fix them with an instructor or remote-proctor verifying success. Gagne’s model for Implementing posttests as part of a course loops the learner back into a module or course if they do not pass the tests threshold and is the basis for posttest delivery in eLearning today. More robust eLearning design also incorporates the pretest component as a filtering mechanism for the learner by prescribing only the content that was not passed. This scenario might look like the programmed instruction model, which augments the training event with the benefits of a custom learning experience and a feedback mechanism.
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