Is cooperative learning superior to individual, competitive approaches? Does constructivism trump lecture-style "instructivism"? Among myriad such disputes in the field of education, one instructional principle has persisted with immunity to debunking; scholars and practitioners alike acknowledge the efficacy, as well as the immense challenge, of creating differentiated and personalized learning experiences. Personalizing learning means offering different pathways for students with varied levels of skill and knowledge, diverse learning preferences, and an array of attributes and interests that influence learning. While all students are challenged to master predefined learning outcomes, educators know that there are multiple avenues to the achievement of those outcomes-- differentiation optimizes learning experiences and improves student performance.
Understanding a student's unique learning profile and cultivating self-awareness about her distinct learning attributes are the first steps in building a yellow brick road to her academic and personal goals. Imagine that Dorothy is taking an English course. Like every student in ENG101, she brings to the class a complex profile of traits and skills that shape her learning experience--and influence others', as well. For example, Dorothy is a swift and strong reader; she enjoys classical literature and poetry and performs well on reading comprehension tests. But, as a writer, grammar and spelling have always been a challenge, historically causing her English grades to suffer. Armed with this information about Dorothy, we begin to build a profile that helps us shape her experience in ENG101.
What if we also know that Dorothy is a highly social learner--she is motivated and engaged when she works collaboratively with other students, and although she is shy about asking for grammar help from her instructor, she readily seeks the tutelage of her peers. What if we, the staff at her university and the architects of an innovative, personalized learning platform, also know that Dorothy is adept at critical reasoning, struggles with time management, is exceedingly motivated but equally stressed about high achievement, and aspires to be a kindergarten teacher?
Through profile builders and surveys, Dorothy can self-report much of the data that constitute her learner profile. But with the same technology that has made pioneering social networking and shopping sites successful at creating personalized experiences, e-learning platforms in higher education can truly be learning platforms, gathering and making sense of data about students that help to improve and differentiate learning for each of them.
In an online classroom--as Dorothy interacts with the instructor, her peers, and the system itself--she leaves behind a trail of data: her performance on formative assessments, the amount of time that she spends interacting with her classmates, the rating that she gives to an instructional activity to indicate its usefulness, and whether she elects to listen to a lecture on her smart phone or read an online article about Emily Dickinson instead.
There exist endless applications of such a rich and dynamic learner profile, of the mapping of each student's cognitive DNA. Making learning data available to students is valuable and motivating, but that's only the beginning. Imagine the personalized pathways to learning that become available. Dorothy's brick road is yellow; she receives some extra group study opportunities to help her master the grammar objectives for ENG101, along with frequent formative assessments to help her monitor her progress. Her classmate, Frank, is a native Spanish speaker, has limited English proficiency, and follows a purple brick road that includes video presentations on the works of Emily Dickinson, vocabulary exercises that help him interpret common colloquialisms in 19th century English, and formative assessments with personalized hints that help him avoid common mispronunciations. Both brick roads, yellow and purple, lead in the direction of success in ENG101.
With the advent of an e-learning platform that collects data and offers insight into the attributes, skills, knowledge, and interests of each learner, the personalized brick road to learning can, indeed, be rainbow-colored.
The opinions and statements made in these articles are solely those of the authors and do not represent the opinions or representations of University of Phoenix.