Adult Learning Methods for Data Intelligence and Data Governance Training

Adult Learning Methods for Data Intelligence and Data Governance Training

StockSnap_3PLFDQQZ5M_AdultWhiteboard_AdultLearning_BPParticipants in data governance and data literacy programs require training. Adopting adult learning methods in the delivery of training sessions makes the training effective and enjoyable for the trainer and the learner. Adult learning methods place control of the learning experience with the learner. Learning objectives are tied to work tasks, and material is presented in both on-demand (self-service) and customized face-to-face environments. This blog post covers methods to use for data intelligence and data governance training.

Trainers can help adult learners control the learning experience in several ways. One way is to place responsibility for self-assessment on learners. To do this, indicate at the beginning of a training session which tasks each learner should be able to accomplish at the conclusion of the training. Include concepts as well, setting the expectation for the theoretical or background information learners will be expected to know. This motivates learners to ask questions near the end of the session if they are not confident in their skills. It does not matter why a learner did not understand part of the material. Perhaps the trainer did not explain it well, or maybe concentration wavered. The point is to engage the learner with self-assessment, and then the trainer fills in gaps or repeats information to assist the learner.

Another method used in adult learning is to immediately focus on tasks that learners need to perform in their job and avoid extensive background information. Briefly provide context for the purpose of the training and then quickly get to the tasks that learners need to perform. Invite learners to ask for more contextual information, and be prepared to provide it. The trainer should observe learners to see if there is confusion. If so, provide additional context or more details at that moment.

A tip for trainers to keep a session task-focused is to separate learners by role or department. For example, train all data stewards together, or all report writers, or all Human Resources staff. This allows the trainer to tailor examples and use cases very narrowly to the tasks for a specific role or position. This might mean that the trainer must repeat content multiple times. This is more time consuming for the trainer, however in the long run this can be more effective for learners and simpler to deliver for trainers.

Adult learners like to control the content. Maybe the important points in the training are things that a participant learned in a different job. If a learner demonstrates proficiency, allow them to opt out, or skip it, or ask advanced questions on the first day, or in the first 10 minutes! With adult learners, the trainer cannot gage pre-existing knowledge. Be prepared to respond with more basic information or more advanced information to accommodate the variety of life and work experiences learners bring to the training.

Offer adult learners a mix of recorded and live sessions that let the learner experience different levels of autonomy. The range of options includes prerecorded videos, standard modules delivered live, or customized modules delivered prerecorded or live. Offer some material on-demand to be delivered at the convenience of the learner. A trainer can use a framework that gives control to the trainer's schedule in these flexible offerings. For example, standard modules can be delivered on the first Wednesday of the month, to accommodate the constant influx of new staff. Or, customized modules must be scheduled 2 weeks in advance and offered only Tuesday – Thursday. Also offer print documentation to support autonomy.  Provide both a comprehensive overview and short job aids. A job aid is a short document that calls attention to common avoidable mistakes and assumes the learner already knows the basics.

To put these tips together in the context of data management, a trainer might record a 20-minute overview session on data governance tenants that learners are required to watch at the learner's convenience by a certain date. This is followed by role-specific training for data stewards, report writers, and data quality managers. Role specific training is offered live either weekly or monthly. Last, offer an invitation to departments for optional customized training with tips and use cases for the comprehensive data management strategy for the data in their domain. Learners would be expected to have mastered the content in earlier sessions.

In summary, put the learner in control of the format, pace, and actual content. Be very specific to the work of participants. Clearly tie learning objectives to job expectations. Offer sessions that support multiple learning styles and multiple departments or control areas. The trainer should make an informed assumption of the skills of an average learner targeted for the training program and design the program accordingly.  Then, be prepared with more basic or more advanced information if necessary. Trainers should offer a mix of session formats through self-service pre-recorded sessions and live face-to-face sessions.

Data governance and data intelligence is critical for all organizations because it instills trust in data, improves decision making and helps people.  For successful data governance, a data governance solution like the Data Cookbook  provides the framework, processes and content that is required.  We hope that this blog post helps in training others about data governance and data intelligence.  Additional people related resources related to data governance can be found here.  And additional resources on training and communication regarding data governance can be found here

If you need help implementing data governance or data intelligence, remember that IData provides data governance services.  A data governance solution like the Data Cookbook can help in successful implementation of data governance at an organization thus improving data quality, trust in data, and decision-making.  Feel free to Contact Us.

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Brenda Reeb
About the Author

Brenda is a consultant in data management, data governance, and the information needs of users. She has over 20 years' experience providing services and solutions in higher education. Brenda has designed and implemented data management policies, established workflows, and created metadata. She is an experienced advocate for data management at all levels of an organization.

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