Blended Learning ResearchFeb. 24, 2003 – The Thomson Corporation announced that phase two of the Thomson Job Impact Study, "The Next Generation of Corporate Learning," further reinforces that a blended learning program incorporating a combination of e-learning, online instruction, simulations, texts, mentor/instructor support, and live classroom-based training has the power to significantly increase employee productivity. These findings follow earlier study results that revealed blended learning is a far more effective approach to training than single-delivery methods alone. The Thomson Job Impact Study measures the effectiveness of blended learning against single training options, and now has taken the critical next step of pinpointing the critical components necessary to achieve a successful blended learning approach. The study was developed in collaboration with leading corporate organizations and academic institutions including Lockheed-Martin; NCR; Utah State University; University of Limerick, Ireland; Anoka-Ramsey Community College, Minnesota; Executive Service Corps of Chicago; and KnowledgePool. The first phase of the study, released in 2002, aimed to determine if there were significant differences in the accuracy and time it took learners to perform real-world tasks after using blended learning training approaches, e-learning training programs, or no training at all. As previously released, results from phase one of the research revealed that a structured curriculum of blended learning generated a 30-percent increase in accuracy of performance and a 41-percent increase in speed of performance over single-delivery options. The second phase of the study sought to identify the essential instructional components of a successful blended learning solution. The researchers studied five separate groups of learners to compare e-learning with three different types of blended learning solutions: instructor-led training, text-based programs, and scenario-based exercises. The instructor-led training (ILT Blend) group received blended learning driven by scenario-based exercises (SBEs) within the context of an instructor-led course. The text blend group received SBEs that included access to text objects. The scenario-based exercise (SBE Blend) group received SBEs that included access to e-Learning courses. The e-learning group received a standard e-learning course. The control group was established to benchmark performance and did not receive any training. All of the groups completed a post-assessment and three real-world tasks. As in phase one of the study, the new results also confirm that a defined blended learning solution heightens overall on-the-job performance achieved by e-learning alone and that either blended or single-delivery models are more effective than no training at all. When compared with the group that received no training, the research shows the e-learning group to have a 99-percent increase in on-the-job accuracy; ILT Blend achieved 163- percent increase in accuracy; Text Blend demonstrated a 153-percent increase in accuracy; and the SBE Blend showed a 159-percent increase in accuracy. When compared with the e-learning group, the blended learning groups were 27 percent to 32 percent more accurate in task performance and performed the tasks 41 percent to 51 percent faster. The overall analysis further reveals that a well-defined blended learning approach results in greater workforce productivity. The Thomson Job Impact Study, in search of the optimal blended learning model, provides insight on which components of a blended learning model appear to be essential for success and which components may be interchangeable. The three blended learning groups performed nearly identically, leading to the conclusion that the components common to the three groups represent the essential components of a successful blended learning model. The three core instructional features include: the use of scenario-based exercises as the basis for learning software, actual experience using the software, and authentic assessments designed to parallel real-world tasks. |