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 The d-Learning Expert


Food for thought

DidacDesign is providing you a number of topics as "food for thought*. If you are interested in more and detailed information please get in contact with us to leverage our experience.


Is your content strategy reflecting the future?

Content strategies should be reviewed and aligned to the most relevant trends at least once per year. Anticipating and reflecting changes and new developments can help to avoid functional issues and cost intensive impacts in the future.

  • Implementation of "Mobile first"
  • Compliance with new standards
  • Suitability for Big Data analysis
  • Production risk analysis

Is off-shoring of content development really saving you money?

The biggest cost factors re content are the capture of the subject matter expertise, the learning design and the review and sign off processes. Standardized content development then often is accounting only for 5-10% of the overall cost. Local or near-shored development with an experienced project management can be the best sourcing option for higher quality at the same or even lower cost.

  • Cultural awareness and subject and language knowhow
  • Quality assurance by service provider
  • Reduced number of iterations

Does your compliance training really prevent incidents?

Compliance training created to satisfy the minimal audit requirements often has a low acceptance and is not changing the learners behavior in a sustainable way. New and creative scenarios can result in higher motivation of the target audience and better  prevention of compliance incidents.

  • Relevant and realistic scenarios
  • Case based content modules
  • Periodic delivery of small learning modules instead of large yearly rollouts
  • Analysis and identification of critical knowledge gaps

Do you use OER (Open Educational Resources) already?

Since the MIT in Boston has started the OpenCourseware project in 2002 more and more high quality educational resources are available globally and for free on the internet. More and more learners use OER (Open Educational Resources) such as e.g. MOOCs and other free content on a broad variety of topics for their personal and professional development. Corporate training departments will have to consider this phenomenon in the near future and plan to integrate OER in their training strategy and concepts.

  • Renowned providers
  • Free content with high quality
  • Broad variety of topics
  • Global access and availability

Curation of offers is the key

The amount of information is overwhelming and the number of learning offers easily accessible via the internet is growing very fast. Finding suitable high quality resources is getting more and more complex and time consuming. The best way to reduce the search effort for learners and assure suitability and quality is the curation of offers. Identifying, selecting and sharing the best and most relevant learning offers for a specific topic and/or audience will become a key competency of corporate training departments.

  • Minimizing search efforts
  • Assuring suitability and quality of learning offers
  • Continuous improvement via feedback cycle

Performance Support as an LMS

Performance Support is a topic getting more and more relevant and shifts learning activities to the workplace. A good performance support application can not only recognize the context a learner is working in and provide specific help but can also be the base for a detailed gap and needs analysis as well as directly recommend and deliver suitable learning activities.

  • Performance Support complements Workplace Learning
  • Performance Support can analyze learning needs
  • Performance Support can track performance progress
  • Performance Support can recommend necessary learning activities

Learning 4.0

In relation to Industry 4.0 the term Learning 4.0 gets mentioned more and more. The connectivity and automation options provided by the Internet of Things (IoT) is not only heavily impacting a number of industries but also influencing and enhancing the options for highly effective learning scenarios where activities and content are provided individualized and adapted to the user's situation.

  • Learning predominantly on demand
  • Detection of individual skills and certifications by devices
  • Integration of of location and context details to manage learning paths
  • Automated location and context based assignments of content

Ubiquitous learning

The amount of information is growing almost exponentially and existing knowledge quickly can become outdated and obsolete. Continuing education and life long learning are playing an integral role in modern work life and the ways to acquire new knowledge and skills are rapidly changing. Learning is increasingly self-directed, happening outside a formal context and becoming ubiquitous.

  • Provision of tools supporting informal learning scenarios
  • Motivation of users to document and share experiences
  • Recognition of self-directed learning results

Smart Learners and Microlearning

Research from global companies such as Google shows that there are substantial differences in the behavior, the usage and the expectations of smartphone users compared to users of other mobile devices like notebooks or tablets. Mobile learning therefore cannot just focus on delivering digital learning modules to smartphones. It is essential to consider the behavior and expectations of the smartphone audience in the design and the delivery of the content. In this context microlearning is a perfectly suitable approach.

  • Fast access to small and focused learning units
  • Offers with job aids, checklists and updates on relevant topics
  • Content types allowing spaced repetition
  • Video as a preferred medium

Use of generative AI

AI applications like ChatGPT are the talk of the town and are experiencing a tremendous upswing. "Generative AI" is not a form of intelligence, but a tool based on applying static methods to large amounts of data. The results here depend on the model and training data used. However, the language models and data sources behind AI applications are largely opaque. Generative AI is not well suited for the automation of tasks with far-reaching consequences such as examinations or personnel assessments. The results are often not repeatable and the possibility of explanation and reversibility of decisions required by data protection laws is missing due to the lack of transparency.

  • Need to build competencies in the use of AI tools
  • Efficient tool for collecting knowledge
  • Efficient tool for generating learning content in different formats
  • NOT a tool for automating far-reaching decisions