Introduction
When I started my career roughly 30 years ago, I was designing instructional systems for the Aviation industry. What we designed then was far superior to what’s being produced today. But how did we go from highly engaging, immersive content to the dull, voice-over PowerPoint-like presentations that we have today? The answer is simple: money.
The e-learning industry, as a whole, chose to pursue a direction of simplicity in its toolsets. They believed that if they could drastically reduce the cost of creating e-learning and put the creation of lessons and material in the hands of everyone instead of the professionals, they could have cheap courses for everything made by everyone. And in a sense, they were right. Today, you can access courses on almost anything you want. But at what cost?
The current state of e-learning is lacking in comparison to the past. Gone are the highly engaging content, immersive experiences, remediation, and adaptive evaluations that measured actual competency in a subject or task(s). Instead, we are left with page after page of simple content with a voice-over, with some video sprinkled in, and multiple-choice questions that allow you to test your implied knowledge. The efficacy that used to be a 7:1 reduction in time to learn a specific subject over traditional classroom learning has dwindled to nearly even.
But why did we lose the magic of instructional design? The answer lies in the relationship between instructional design and user experience (UX) design. The ADDIE process, which has been at the heart of instructional design since 1975, is almost identical to the UX process. The only difference is that the UX process is marketed as an innovation, while the ADDIE process is not. The UX process is often seen as the “sexy” option, while instructional design is seen as outdated.
But instructional design is not outdated. It’s still an essential aspect of e-learning. And if we want to bring back the magic of instructional design, we must focus on creating engaging and effective e-learning content. But how do we do that?
One solution is to overcome the challenges and limitations of e-learning. These challenges include a lack of engagement and low retention rates. To overcome these challenges, we must provide more interactive and immersive content, such as simulations and interactive quizzes. We must also provide more specific examples and case studies, and include remediation and adaptive evaluations to measure actual competency in a subject or task(s).
Another solution is to stay current with the trends and innovations in e-learning and instructional design. We must predict the future of e-learning and instructional design and adapt to the changes. This includes the incorporation of Artificial Intelligence, Virtual Reality, and Augmented Reality in e-learning content.
What happened to the highly engaging content and immersive experiences?
The decline of highly engaging content and immersive experiences in e-learning can be attributed to a number of factors. One major factor is the focus on cost-cutting and simplicity in the e-learning industry. As e-learning became more mainstream, the industry shifted its focus from creating high-quality, engaging content to creating low-cost, easily accessible content. This led to the development of simple, text-based e-learning courses with minimal interactivity and engagement.
Another factor is the lack of expertise and experience in instructional design among e-learning professionals. Instructional design is a complex and nuanced field that requires a deep understanding of learning theories, instructional strategies, and the use of technology. However, many e-learning professionals do not have the necessary expertise and experience in instructional design, leading to the creation of low-quality, unengaging e-learning content.
The proliferation of e-learning platforms and authoring tools has also played a role in the decline of highly engaging content and immersive experiences. These platforms and tools are designed to make it easy for anyone to create e-learning content, regardless of their expertise or experience. However, this has led to a flood of low-quality, generic e-learning content that lacks engagement and immersion.
Additionally, the lack of research and data-driven approach in e-learning can also be a reason for the decline of engaging content and immersive experiences. With the lack of research, it’s difficult to understand what kind of e-learning experiences are effective, engaging, and have a high retention rate.
So Has Instructional Design Become Outdated?
Instructional design has not become outdated, but it has certainly evolved over time. The principles of instructional design, such as the ADDIE process, are still relevant and essential for creating effective e-learning content. However, the field of instructional design has expanded to include new technologies and approaches, such as AI, VR, and AR. It’s important for instructional designers to stay current with these new technologies and incorporate them into their design strategies.
Additionally, instructional design has also expanded to include new areas of focus such as gamification, micro-learning, and mobile learning. These new areas of focus allow instructional designers to create more engaging and effective e-learning experiences that can adapt to the ever-changing needs of learners.
Moreover, instructional design is not only limited to e-learning, it can be applied to various other fields such as corporate training, healthcare, and education. It’s a field that is constantly evolving and adapting to the changing needs of learners and the advancements in technology.
How can Artificial Intelligence Enhance e-Learning and Instructional Design?
Artificial Intelligence (AI) has the potential to revolutionize e-learning and instructional design. AI technology can be used to create personalized and adaptive e-learning experiences, which can lead to higher engagement and retention rates.
One way AI can enhance e-learning is through personalized learning. AI algorithms can analyze student data, such as their learning style, performance, and progress, and create a personalized learning plan that is tailored to the student’s needs. This can lead to increased engagement and motivation as the student feels that the content is tailored to their specific needs.
AI can also be used to create adaptive e-learning experiences. AI algorithms can analyze student performance and adjust the content and pace of the course based on the student’s abilities and progress. This can lead to a more efficient and effective learning experience, as the student is only presented with content that they are ready to learn.
Another way AI can enhance e-learning is through natural language processing (NLP). NLP algorithms can be used to create interactive and engaging e-learning content, such as chatbots and virtual assistants. These technologies can provide instant feedback and answer questions, making the learning experience more interactive and engaging.
AI can also be used to analyze and evaluate student performance. AI algorithms can analyze student data, such as their performance on quizzes and exams, and provide feedback and recommendations for improvement. This can lead to more effective and efficient evaluations, as AI can analyze large amounts of data quickly and provide actionable feedback.
What is an Adaptive e-learning experience?
An adaptive e-learning experience is a personalized and dynamic learning experience that adapts to the unique needs and abilities of the learner. An adaptive e-learning system uses algorithms to analyze student data, such as their learning style, performance, and progress, and adjust the content and pace of the course based on the student’s abilities and progress. This allows the system to present students with the appropriate level of content and challenge based on their current abilities and to adjust the learning experience in real time.
Adaptive e-learning systems can be used for a variety of purposes, such as providing personalized instruction, assessing student understanding, and providing feedback and guidance. The system can also adjust the learning experience based on the student’s engagement levels, providing additional support and guidance when needed. Adaptive e-learning can lead to a more efficient and effective learning experience, as the student is only presented with content that they are ready to learn. This can also help students to avoid frustration and disengagement, which can occur when they are presented with content that is too difficult or not relevant to their needs.
What is an Adaptive Evaluation?
Adaptive evaluation is an assessment method that adjusts the content, difficulty, and format of the assessment based on the student’s performance. It uses algorithms to analyze student data, such as their performance and progress, and adjust the assessment based on their abilities and progress.
One way AI can be used to improve adaptive evaluations is by providing instant feedback to students. AI-powered systems can use natural language processing and machine learning to analyze student responses and provide instant feedback, allowing students to quickly identify and correct mistakes.
AI can also be used to analyze and evaluate student performance, providing valuable insights into student understanding and progress. This information can be used to adjust the assessment content, difficulty, and format to better match the student’s abilities and needs.
Another way AI can be used to improve adaptive evaluations is by providing personalized recommendations for improvement. AI-powered systems can analyze student performance data and provide personalized recommendations for improvement, such as additional resources, exercises, or activities.
What is NLP?
Natural Language Processing (NLP) is a field of Artificial Intelligence (AI) that focuses on the interactions between computers and human languages. It is used to analyze, understand, and generate human languages, such as text and speech. NLP enables computers to understand the meaning and context of human language and to interact with humans in a way that is similar to how humans interact with each other.
NLP techniques are used in a variety of applications, such as language translation, speech recognition, sentiment analysis, text summarization, question answering, and text generation. NLP can not only be used in education, but other industries like customer service, healthcare, finance, and more.
NLP techniques include tokenization, stemming, lemmatization, named entity recognition, and part-of-speech tagging, among others. These techniques help computers understand the structure and meaning of human language and to process it in a way that is similar to how humans process language.
How can we Include Virtual Reality and Augmented Reality in e-Learning?
Virtual Reality (VR) and Augmented Reality (AR) can be used to create more immersive and engaging e-learning experiences. Here are some ways to include VR and AR in e-learning:
Virtual field trips: VR can be used to create virtual field trips that allow students to explore and learn about different places and environments. For example, students can visit historical sites, go on virtual tours of museums, or explore different parts of the world.
Simulation and role-playing: VR and AR can be used to create simulations and role-playing scenarios that allow students to practice and apply what they have learned. For example, students can practice performing a surgical procedure or flying a plane in a simulated environment.
Interactive visual aids: AR can be used to enhance traditional visual aids such as textbooks, posters, and diagrams by adding interactive elements such as animations, videos, and quizzes.
Spatial learning: VR and AR can be used to create 3D models of complex systems and structures, such as the human body or a building, which can be used for spatial learning.
Collaborative Learning: VR can be used to create virtual classrooms that allow students to collaborate and communicate with each other in real time, regardless of their physical location.
It’s important to note that incorporating VR and AR into e-learning requires a significant investment in terms of time, money, and resources. However, the benefits of immersive and engaging e-learning experiences can be worth the investment. It’s important to have a clear understanding of the objectives and goals of the e-learning course, and align the VR or AR elements with those goals. Additionally, it’s also important to have a robust evaluation process in place to measure the effectiveness of the VR or AR elements and use the feedback to improve the course.
It’s also important to keep in mind that VR and AR are not a one-size-fits-all solution, and it’s essential to evaluate the appropriateness of VR or AR for specific e-learning courses and the needs of the learners.
Another point to consider is the accessibility of VR and AR technology, as they may not be accessible to all learners. Therefore, it’s important to have a fallback plan or alternative options for those who cannot access VR or AR technology.
Incorporating VR and AR into e-learning also requires instructional designers and developers to have the necessary skills and knowledge to create and integrate VR and AR elements effectively. This may require additional training and resources to develop these skills.
Summary
In summary, e-learning has come a long way since its inception in the aviation industry, but it has lost its way in terms of creating highly engaging and immersive content. The focus on cost-cutting and simplicity in the e-learning industry, lack of expertise and experience in instructional design, the proliferation of e-learning platforms and authoring tools, and lack of research and data-driven approach in e-learning are some of the reasons why e-learning content is not as engaging as it used to be.
However, instructional design is not outdated, but it has evolved over time to include new technologies and approaches such as AI, VR, and AR. These technologies can enhance e-learning by creating personalized and adaptive e-learning experiences, providing instant feedback and answering questions, and analyzing and evaluating student performance.
Additionally, VR and AR can be powerful tools to create immersive and engaging e-learning experiences, but they also require careful consideration and planning to be used effectively. It’s important to align them with the objectives and goals of the e-learning course, have a robust evaluation process in place, and consider the accessibility and skill requirements of the technology.
It’s time to bring back the magic and raise the bar for e-learning.
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