Implementing Adi for more efficient training
Dr. Jill Stephaniak is the Chief Learning Officer in Latimos. Its interests are focused on the development and teaching design of L&D professionals. Today, she talks with us about the diagnosis of AD Framework, L&D requirement, and the diagnosis of training.
Why is the Adi Framework so relevant today, and how does the process need to be diagnosed and diagnosed in this process?
I would like to think about analysis and diagnosis because statements for the order framework. They both provide infrastructure required to support training. Although they have two separate stages of Adi, they are connected to each other because both focus on learning and improving performance.
A requirement is usually made at the beginning of a design project to indicate the difference between current and desired knowledge, skills and performance. By collecting data from systematic learners, stakeholders and organizational contexts, L&D professionals can identify where intervention is needed and preferred to learn. Basically, a full -fledged diagnosis provides a basic line against which the effectiveness of teaching interference can be measured later.
The diagnosis returns to the process of evaluating the requirements of whether the instructions designed are fulfilling their desired purpose. The insights obtained from the diagnosis can identify the first unrelated or found ballets to develop performance or learning requirements. This creates a new cycle of diagnosis and diagnosis. Diagnosis and diagnosis require a permanent feedback loop where diagnosis notifies design and diagnosis and measures its effects. The diagnosis exposes new needs, to ensure that training is related and efficient.
Based on your experience, what is the most common mistake of L&D professionals when enforcing Adi?
I think there are two common errors that L&D professionals do:
- They quickly (or completely leave) at the analysis phase. They jump right into designing content without asking important questions to understand the proportional needs of the learned audience. They also see analysis as mere learning analysis and lose the opportunity to collect important information, which can have a major impact on the results of the training.
- Another common mistake is to understand Adi as a linear process strictly. Although L&D professionals are expected to develop through the framework in order, it is important that they are flexible and complicated throughout the design process. This means that the new information is revealed to different stages of the design process as it emerges. A successful L&D project is one that accepts theory and repetition. To ensure the necessary alignment between prototype, training requirements, materials, and diagnostic matrix, it is necessary to revise the material that meets the desired results of the organization.
When can L&D teams better understand the needs of their learners by focusing more on utility, compatibility and value according to the requirement of the need?
When L&D teams focus on utility, compatibility and value in their needs studies, they get a clear picture of what is really important for learners in their organization. Utility ensures that practical training skills can be identified that learners may immediately apply to their role. Related learning directly connects job responsibilities and career goals. By testing the value, teams indicate the most effective impact on both the engagement and organizational consequences of learning the opportunities to learn. This eventually leads to the development of more efficient and targeted L&D programs.
What is a story of your success that includes the Adi Framework?
In Latimos, our L&D team formed the University of Latimos University to provide target training to help its customers. We started with the diagnosis of needs to better understand where the learners are struggling and which skills are the most important. This input shaped the design and ensured that we focused on the right material from the beginning. Through development, we submitted design documents, prototypes, feedback, and improved. The result is a set of courses that felt about learners and showed a clear improvement in both engagement and performance.
Do you have the coming event, launch, or any other move you want to know about our readers?
I will host a webinar on October 9 with Dr. Stephanie Moore, Associate Professor of New Mexico University, seeking the biggest disadvantages of AI influx learning, reinforcing stereotypes, which promotes “learning styles” myths, or unprecedented. It will cover practical strategies for writing the purposes of the measurement, setting ethical guards and keeping your training diverse, accessible and research. You can enroll here for this.
Wrap
Many thanks to Dr. Jill Stephaniak for his valuable insight and skills with us. If you want to find out more about effective and engaging training, you can look at his article on the Littos Blog, which highlights four questions in which L&D teams can ask to increase their diagnosis.
