The NMC horizon report is ALWAYS an inspiration. Although I do think about latest trends, this 52 page report always brings the most important trends together in a comprehensive and brief overview. The report also addresses some challenges that are still standing in this digital age (scaling teaching innovation, relative lack of rewards for teaching, low digital fluency of faculty, competing educational models - although I like the debates coming from the competition). While reading the challenges I did wonder whether the priorities were complete. I mean, maybe it is not being the best that matters, but getting all on board? Allowing people to grow and reach their own potential, and not necessarily reach the potential society/higher ed is setting out for most of us. Will need to take that up in a more philosophical post later on.
The pdf version is available at http://www.nmc.org/pdf/2014-nmc-horizon-report-he-EN.pdf.
My top 3 topics suggested as upcoming learning trends are:
Learning analytics (time-to-adoption: now): although I will address some of my own doubts on the current trust in the learning analytics overall, I do feel this (together with a lot of other big data) will result in new findings that can (CAN) enhance learning for all of us as well as each of us. As online learning becomes a more frequent reality, data of learners becomes visible. Based on these data assumptions can be deduced, which in turn can be researched and added as best/worst practices. The logic behind learning analytics is simple: learning analytics has the potential to develop or generate early warning systems based on metrics that make predictions using linguistic, social, and behavioral data coming from learners. As such each learner can be supported in a more personalized - and hopefully efficient - manner.
Games and gamification (time-to-adoption 2 years): a learning style that most of us knows and adopts from an early age. And thanks to really nice visuals and algorithms, it becomes a teaching tool that can provide efficient and fun learning. I first saw this in practice in a program designed to teach disaster response in case of epidemics. Serious games are simply wonderful virtual worlds in which death can be revoked, and success follows multiple failures... a nice exercise in persistence as well.
Virtual assistants (time-to-adoption: 4 - 5 years) this is a growing pleasure (if a seamless user experience can be assured). At the centre of virtual assistants are the natural user interfaces (NUIs), which enable me and you to simply voice what we want (or gesture it) and an answer will be provided by our preferred learning machine (tablet, phone...). The most eye catching was the Siri which comes with the iPhone, and some of Android’s Jelly Bean options. The virtual assistants are being deployed for other instruments as well (e.g. smartTV), the key thing is that they can be merged with semantic based algorithms allowing a more tailored information to be sent to the questions users direct to these devices. Me, being lazy at times, I would like answers to come once I think of the question. But of course this means that by the time that option becomes a reality, we will all be drones, connected to the hive (Star Trek Borg)
The pdf version is available at http://www.nmc.org/pdf/2014-nmc-horizon-report-he-EN.pdf.
My top 3 topics suggested as upcoming learning trends are:
Learning analytics (time-to-adoption: now): although I will address some of my own doubts on the current trust in the learning analytics overall, I do feel this (together with a lot of other big data) will result in new findings that can (CAN) enhance learning for all of us as well as each of us. As online learning becomes a more frequent reality, data of learners becomes visible. Based on these data assumptions can be deduced, which in turn can be researched and added as best/worst practices. The logic behind learning analytics is simple: learning analytics has the potential to develop or generate early warning systems based on metrics that make predictions using linguistic, social, and behavioral data coming from learners. As such each learner can be supported in a more personalized - and hopefully efficient - manner.
Games and gamification (time-to-adoption 2 years): a learning style that most of us knows and adopts from an early age. And thanks to really nice visuals and algorithms, it becomes a teaching tool that can provide efficient and fun learning. I first saw this in practice in a program designed to teach disaster response in case of epidemics. Serious games are simply wonderful virtual worlds in which death can be revoked, and success follows multiple failures... a nice exercise in persistence as well.
Virtual assistants (time-to-adoption: 4 - 5 years) this is a growing pleasure (if a seamless user experience can be assured). At the centre of virtual assistants are the natural user interfaces (NUIs), which enable me and you to simply voice what we want (or gesture it) and an answer will be provided by our preferred learning machine (tablet, phone...). The most eye catching was the Siri which comes with the iPhone, and some of Android’s Jelly Bean options. The virtual assistants are being deployed for other instruments as well (e.g. smartTV), the key thing is that they can be merged with semantic based algorithms allowing a more tailored information to be sent to the questions users direct to these devices. Me, being lazy at times, I would like answers to come once I think of the question. But of course this means that by the time that option becomes a reality, we will all be drones, connected to the hive (Star Trek Borg)
No comments:
Post a Comment