Welche neuen Technologien können Fakultätsmitglieder nutzen, um das Lernen zu personalisieren?

Most of the adaptive learning systems, we have to understand what's their size of the use case and the type of geography they have tested their product too. One product which can be accepted well in americas can't be predicted as that it will be accepted in Asia. Every geography students have different needs, speed of learning and learning patterns. So when we are talking about adaptive learning systems, we need to understand their test use cases.

Intelligent adaptive learning takes full advantage of the now-familiar observation that each individual has his or her own learning pace and strategies. AI is the driving force behind intelligent adaptive learning. It is entrusted with the collection and analysis of data, in this case information about learners, such as their past performance or learning preferences. This data is then used to create learner profiles and generate a personalized learning path.

Adaptive learning systems enables the students to learn at its own pace. Every student is different and so it’s their learning styles so in order to help the students understand the concept better adaptive learning systems are powered with great tools enabling the student to grasp the knowledge efficiently and effectively

We can explore adaptive learning platforms that personalize content based on individual student progress and learning styles. Platforms like Smart Sparrow or Knewton provide adaptive assessments and tailored learning paths.

Je pense que nous n'avons pas suffisamment de recul sur les outils d'IA génératives. Il faut prendre le temps d'accompagner les professeurs sur les usages pédagogiques de ces systèmes. Peut-être qu'effectivement les IA permettront dindvidualiser les parcours d'apprentissage mais aujourd'hui les IA font preuve d'"hallucinations" et les élèves n'ont pas le recul critique nécessaire pour juger de ce qui est vrai ou faux.

There are three ways to personalize a lesson plan - content, activities, and assessment. It starts with gathering survey-style feedback. For content, teachers may not have a multitude of sources. Asking ChatGPT may provide resources. Teachers could also provide a framework for students to find their own content. Armed with a framework, students could find their own content to teach story elements. In a flipped classroom environment, students could find alternative videos to teach math concepts. Personalized assessments give students latitude to show what they know in different ways. There may be a mismatch between the activities in a teacher's pedagogical toolkit and how students want to learn.

Whilst the description above might capture an element of ‘personalisation’ I’d argue that what is being described is the process of differentiating work, not personalisation. Analytics can help provide more effective feedback, and give clues regarding how to differentiate, but personalisation is about changing the nature of the task, rather than the degree of challenge; an androgogical rather than a pedagogical approach. It’s about moving beyond a one size fits all, linear curriculum, and towards structures of learning that capture students’ intrinsic motivations, more fully aligned with informal learning approaches.

Ongoing feedback is just as critical to businesses as to faculty. We give the power back to our clients to get ongoing real-time feedback. Learners can rate their learning so that improvements can be made in real-time. This is what powerful learning is about…creating ongoing feedback so that learners can have the optimal environments, content, and tools to learn.

In the intelligent adaptive learning model, the trainer is also a learning facilitator. While AI plays a key role in personalizing the learning experience, the trainer provides the affective dimension needed to reuse learning, particularly in a professional context.

An Example I've seen back in India, many of these learning analytics aren't in use. One of the main reason which I felt with these tools is pricing strategy for asia. The pricing strategy they follow in America may not be suitable for many to get the same rate of adoption in other geographies. In most Cases, these tools have to be maintained well and updated with all possible information in a timely manner. If the information and different systems aren't linked well, the analytics don't reflect in a proper manner.

I've been participated in the Virtual Reality and Augmented Reality for Education. These technology will help learners understand and interact more effectively. VR curriculum can transform the way education materials are delivered. By creating a simulated reality, actual or imaginary, and empowering learners to not only see but also interact with it. VR education encourages learners to learn for themselves.

This is the best thing to happen and the proper usage of augmented reality and virtual reality technologies is education. To enable mass reach and adaptability for these technologies, the mass production of these devices and cost of building these technologies have to come down. Then the advantages of these technologies will reach every kid who is learning in schools.

We can integrate VR and AR applications to create immersive learning experiences for math education. These technologies can visualize complex mathematical concepts, making them more tangible and engaging for preservice teachers.

One thing I found the best about gamification is that it increases engagement levels by leaps and bounds among students. The amount of time they spent on learning tools increases when they have gamification implemented as they see gratification.

When I was working at a private school, I participated in a lot of technology-assisted courses. What I can say with certainty, is that there is a great interest of teachers in Gamification and that it is something that, if used correctly, will have positive results for the students. It encourages sustained concentration, motivation, and a heightened level of engagement with the educational material. Of course, gamified solutions are not always easy to create and they are not panacea or suitable for any occasion.

Intelligent adaptive learning encourages collaboration and interaction between learners within a group training environment. Learning activities are designed to encourage cooperation and the exchange of ideas between participants, thus fostering a dynamic, interactive learning environment in which the trainer can play his or her full role as learning mediator.

When I think of games, I often think of video games, where a sense of discovery and exploration are prominent features. Yes, your course needs to provide guidance, but you can help students gain the skills to research independently, and build in opportunities where students, after being introduced to a topic, can explore ideas related to that topic that interest them. Help them build connections, and then give them the freedom to have those a-ha moments of discovery.

I have had experience with three types of tools: Kahoot, Roblox, RazKids. And it has been fantastic because, after prior exposure through direct teaching, guided practice and independent practice, students engage with the content using a dynamic modality. Sharing one: I would use Kahoot to build questions about our Science, Social Studies, Spelling, Reading and grammar topics. They would gain confidence, self-assess and review information. I would even assign students specific subjects, in groups of 2 or 3, to make a Kahoot as a study guide, to do in class. They not only used Kahoot to review and learn, they also were involved in making content to help their classmates and learn how to use the tool.

AI tutors can be effective, but not without explicit teaching prior to pushing the students to the online options. A good supplement, but not a replacement.

AI tutors are good use case in addition to other visual aids. But they can't replace a tutor. The data sets on which these tutors are built are limited. We need to have a tutor in place who is rational enough to utilise these ai tools but can't just rely on them and leave it to students. Not all students have same learning capacity.

We can implement AI-powered tutoring systems that offer personalized assistance to preservice math teachers. These systems can analyze student responses, identify misconceptions, and provide targeted feedback to enhance understanding.

Any emerging technology must be trialled before implementing into your teaching and learning. It must bring value to the students.

Personalisation shouldn't be a goal in itself. In service of an actual learning goal, it can be impactful and effective. That goal can inform the best tools to use that are fit for purpose.

We can leverage collaborative online platforms like Google Workspace or Microsoft Teams. These platforms facilitate real-time collaboration, allowing preservice math teachers to work together on projects, share resources, and engage in discussions.