Learning predictions for 2014 & Beyond – Part 2

Game-like environments, learning analytics ready for adoption in mid-term horizon (within two to three years). Part 1 describes MOOC  and tablet computing for immediate horizon.(within the next 12 months).  The adoption of these technology areas can have impact to enhance  skill development initiatives in developing countries.

Game -like environments are effective tools for scaffolding concepts and simulating real world experiences. They transform tasks into challenges, reward people for dedication and efficiency, and have a positive impact on students in higher education.  Students are made to think critically in order to solve problems, game-like simulations are leveraged  to reinforce the real world applications of concepts.  Games motivate people by actively engaging them. When students deal with real-life situations similar to the game, the student is engaged in a competition with himself.

We introduce elements of games, such as levels and ranks in learning. Here students can accumulate points or other rewards by performing different action. There is  more freedom to choose the kind of assignments to perform to earn the points.  Students are also rated with a badging system of recognition enabling documentation of their skills, achievements, qualities, and interests in a visual public facing format.

Game systems need clearly defined rules and the ability to explain much more in the way of accomplishments and goals than a college transcript. Gamification carries the danger of immediately disenchanting students if executed poorly. Hence a lot of care is needed in design process to develop and integrate games relevant to the curriculum and to students’ lives. When implemented effectively, students are helped with new skill acquisition and also boosts motivation to learn. Creating a game or a game-like atmosphere is what gets you beyond passive learning.

Learning Analytics provides insights about student interaction with on-line texts and course-ware to educators and researchers.  Similar to Google and Amazon using metrics to tailor recommendations and advertisements to individuals, can learning analytics envision the ability to tailor learning to students’ personal needs and interests and provide suggestions to keep learners motivated as they master concepts or stumble upon.

How to make learning  personalized and context sensitive for individual student learning style?.  By effectively and efficiently assessing student responses, students can be provided with  immediate feedback, and adjustments can be made in content delivery and format, adapting to the learning style of students and tailor support systems to suit to their learning needs. We should be able to customize on-line courses and provide suggestions of resources to students in the same way that businesses tailor advertisements and offers to customers.

Learning analytics enables the individual student to plan his or her path in higher education. Academic advisors obtain access in to a window of the student experience, identifying both their strengths and areas of improvement and are equipped to perform counselling and advising sessions in more efficient manner with accurate data.