How Can We Leverage Learning Data to Transform Nurse Education and Training?
Nurse educators, managers and executives have turned to learning analytics in the same way healthcare has turned to data or predictive analytics. Learning analytics provides a way to evaluate the responses of nursing students and professionals, deliver rapid feedback, and tweak content and formats to meet learners' needs and industry requirements. Learning analytics has the potential to create highly personalized learning environments that complement the learning styles and behaviors of nurse students and professionals. For that reason, nursing professionals should consider how they can champion learning analytics in the years ahead.
Nursing schools, colleges and universities have turned to blended or hybrid learning that combines face-to-face classroom instruction with online learning environments and platforms where tracking tools document student behaviors, identify numbers of clicks or specify time spent on a single page. Within nurse education and training, effective learning analytics systems create practice sessions through scenarios and case studies.
Exams evaluate learners' readiness for follow-up testing, along with their ability to apply concepts. Learners can review concepts as they move through modules or courses or immediately prior to an exam. If learners fail to perform well on an exam, they can take advantage of personalized online remediation activities. Finally, a solid learning analytics system creates reports for learners, educators and managers. Learners discover how well they performed on tests, while educators and managers gain insight into individual learner and program performance.
How should educators respond to the learning analytics revolution?
Promote the value of learning analytics: By blending data analysis with how learners interact with online tools and content, learning analytics helps to create more integrated, customized learning experiences. Learners are better able to learn and apply nursing concepts. That, in turn, means a more skilled, competent and prepared nursing workforce-one capable of addressing challenges like care coordination, meaningful use, quality improvement and patient engagement.
Focus on features, functions and opportunity: Learning analytics has the capacity to predict learner performance, deliver feedback to struggling learners, personalize the learning process, offer motivation and encouragement, build on individual learners' strengths, and identify learning barriers by tracking data like time spent on a site, log-in frequency or lack of attention and understanding.
View learning analytics as a component of healthcare transformation: Just as the healthcare industry is moving away from the assumption that patients are the same, nursing professionals have abandoned the assumption that all learners start at the same point and progress at the same speed. Learning analytics bases learners' future performance on their past performance. It views learners as distinct, unique, special and deserving of full engagement via customized, personalized content and regular feedback and reinforcement.
Work with vendors that grasp learning analytics: Learning analytics demands content management, delivery and evaluation, a learner information system or data repository and a mechanism to track and store learners' completed work. Equally important are integrated predictive models that record learners' progress and forecast learning outcomes based on demographic and learning data. Systems should allow nurse educators and managers to assist and support learners while customizing content to meet learners' needs, preferences and learning styles. A dashboard or control panel should track learning trends and deliver summaries of learner and program performance to nurse educators, managers, executives and researchers.
Prepare for roadblocks and barriers: Developers of learning analytics systems still need to resolve issues related to privacy and confidentiality, ethics, access, cost, misinterpretation of data, metrics and standardization. Equally important, nurse educators and managers will require training and coaching on how their can expand and balance their roles as teachers, content developers, information brokers, coaches and mentors, group facilitators and data analysts.
Learning analytics within nurse education and training faces a bright future. Educators and managers will be better able to identify slower learners who, with specific interventions, can evolve into learning superstars. Data-driven learning will expand nurses' critical thinking skills by compelling each learner to address each question, case or scenario. Learners will receive close to real-time feedback on performance, offering them the push they need to pursue remediation. Finally, learning analytics will build learner engagement through features like self and peer evaluation and grading and collaboration. While learning analytics poses multiple challenges, nurses can help to achieve its promise and potential.