Fashion Technology and Artificial Intelligence

Artificial Intelligence

Artificial intelligence (AI) refers to the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals.[1] Such machines may be called AIs.

High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Alexa); autonomous vehicles (e.g., Waymo); generative and creative tools (e.g., ChatGPT and AI art); and superhuman play and analysis in strategy games (e.g., chess and Go). However, many AI applications are not perceived as AI. Many cutting-edge AI have filtered into general applications, often without being called AI because once something becomes useful enough and common enough, it's not labeled AI anymore.

Fashion Technology and Artificial Intelligence

In the ever-evolving landscape of the fashion industry, the integration of Artificial Intelligence (AI) has emerged as a transformative force, reshaping the traditional paradigms of product development.

This synergy of technology and fashion has given rise to a new era, where data-driven insights, predictive analytics, and innovative applications of AI are revolutionizing the way garments are conceived, designed, and brought to market.

In recent years, the fashion industry has undergone a significant transformation, where technology is making waves and stealing the spotlight, with artificial intelligence (AI) at the epicenter of this transformation. This dynamic duo of fashion and AI is not just tweaking design processes and redefining our shopping experiences; it's also prompting some big questions about sustainability and ethics in the fashion industry.

AI's impact on fashion design is nothing short of revolutionary. McKinsey's analysis suggests that within the next three to five years, generative AI has the potential to significantly boost operating profits in the apparel, fashion, and luxury sectors. Conservatively estimated, this could mean an addition of $150 billion, with the possibility of reaching up to $275 billion.

Furthermore, with AI stepping into design processes, it has put creativity on autopilot. Whether it's crafting design twists or playing with patterns and textures, AI is stretching the limits. The upshot? Speedier, more efficient design workflows enable fashion houses to stay nimble in keeping up with changing tastes.

Think about predicting fashion trends, and you have AI. Take IBM's Watson Trend App, for example. This intelligently designed tool analyzes heaps of online data to predict what styles are going to be trendy. So, instead of designers relying solely on gut feelings, they can use AI insights to create collections that match what people are buzzing about.

Sustainability and Ethical Considerations

The fashion industry ranks as the second most polluting sector, responsible for 8 percent of global carbon emissions and 20 percent of global wastewater, according to MDPI. In response to growing environmental worries, AI is becoming a crucial partner in promoting sustainability within the industry. AI algorithms can optimize supply chains, reduce waste, and aid in the creation of eco-friendly materials. By predicting demand more accurately, fashion brands can minimize overproduction and contribute to a more sustainable industry.

As technology progresses, ethical concerns take center stage, especially in AI's role in fashion. Questions arise about data privacy, labor ethics, and perpetuating biased beauty standards. Balancing innovation with ethical responsibility becomes crucial. Despite its transformative potential, integrating AI into fashion faces hurdles. Challenges include data security, algorithm biases, and the demand for skilled professionals to manage AI systems.

What the Future holds for the Duo

As AI advances, we're looking at a future where it plays a bigger role in making fashion more sustainable. With AI getting better and better, more companies might join in to tackle environmental issues and find new ways to be eco-friendly. This means we could see AI used more in designing clothes, running stores, and making fashion greener.

The blend of tech and fashion, especially AI, is changing things in big ways. AI helps predict trends, makes shopping cooler, and pushes for greener practices. As fashion keeps up with these changes, it's important to be smart and ethical about how we use technology.

AI's Impact on Influencer Marketing

Influencer marketing has emerged as a cornerstone of marketing strategies for brands across all industries. With the rise of social media, consumers are increasingly turning to influencers for product recommendations and lifestyle inspiration. These digital tastemakers, with their large and engaged followings, have the power to sway consumer behavior and shape purchasing decisions.

In the fashion sector, where trends change rapidly and consumer tastes are diverse, AI is playing a crucial role in optimizing influencer collaborations. By analyzing vast amounts of data, AI identifies the most relevant influencers for brands, based on audience demographics, engagement rates, and content preferences.

This targeted approach ensures that brands collaborate with influencers who resonate with their target audience, maximizing the impact of their marketing efforts. Additionally, AI-powered tools help track and measure the effectiveness of influencer campaigns, providing valuable insights for future strategies.

Takeaway

The transformative impact of Artificial Intelligence on fashion product development is reshaping the industry's landscape, ushering in an era of unprecedented innovation and efficiency. From the initial stages of design through production and beyond, AI is proving to be a powerful ally, offering predictive insights, enhancing creativity, and optimizing processes.

In the fast-paced fashion world, adaptability is key, and AI emerges as a catalyst for agility. Whether it's streamlining supply chain processes, optimizing pricing strategies, or revolutionizing marketing approaches, Artificial Intelligence serves as a driving force behind the industry's evolution.

As we look to the future, the synergy between human ingenuity and machine intelligence promises a dynamic and continuously evolving fashion landscape. The journey of AI in fashion product development is not just a technological revolution; it is a narrative of limitless possibilities and a testament to the boundless creativity that emerges when humanity embraces the tools of tomorrow. The runway of the future is illuminated by the fusion of fashion and AI, guiding us toward a new era where innovation knows no bounds.

Fashion Technology - Influencing factors

Technology influences

Today, technology plays a sizable role in society, and technological influences are correspondingly increasing within fashion. Wearable technology has become incorporated; for example, clothing constructed with solar panels that charge devices and smart fabrics that enhance wearer comfort by changing color or texture based on environmental changes. 3D printing technology has influenced designers such as Iris van Herpen and Kimberly Ovitz. As the technology evolves, 3D printers will become more accessible to designers and eventually, consumers — these could potentially reshape design and production in the fashion industry entirely.

Internet technology, enabling the far reaches of online retailers and social media platforms, has created previously unimaginable ways for trends to be identified, marketed, and sold immediately. Trend-setting styles are easily displayed and communicated online to attract customers. Posts on Instagram or Facebook can quickly increase awareness about new trends in fashion, which subsequently may create high demand for specific items or brands. The new "buy now button" technology can link these styles with direct sales.

Machine vision technology has been developed to track how fashions spread through society. The industry can now see the direct correlation between how fashion shows influence street-chic outfits. Effects such as these can now be quantified and provide valuable feedback to fashion houses, designers, and consumers regarding trends.

Political influences

Political figures have played a central role in the development of fashion, at least since the time of French king Louis XIV. For example, First Lady Jacqueline Kennedy was a fashion icon of the early 1960s. Wearing Chanel suits, structural Givenchy shift dresses, and soft color Cassini coats with large buttons, she inspired trends of both elegant formal dressing and classic feminine style.

Cultural upheavals have also had an impact on fashion trends. For example, during the 1960s, the U.S. economy was robust, the divorce rate was increasing, and the government approved the birth control pill. These factors inspired the younger generation to rebel against entrenched social norms. The civil rights movement, a struggle for social justice and equal opportunity for Blacks, and the women's liberation movement, seeking equal rights and opportunities and greater personal freedom for women, were in full bloom. In 1964, the leg-baring miniskirt was introduced and became a white-hot trend. Fashion designers then began to experiment with the shapes of garments: loose sleeveless dresses, micro-minis, flared skirts, and trumpet sleeves. Fluorescent colors, print patterns, bell-bottom jeans, fringed vests, and skirts became de rigueur outfits of the 1960s.

Concern and protest over U.S. involvement in the failing Vietnam War also influenced fashion. Camouflage patterns in military clothing, developed to help military personnel be less visible to enemy forces, seeped into streetwear designs in the 1960s. Camouflage trends have disappeared and resurfaced several times since then, appearing in high-fashion iterations in the 1990s. Designers such as Valentino, Dior, and Dolce & Gabbana combined camouflage into their runway and ready-to-wear collections. Today, variations of camouflage, including pastel shades, in every article of clothing or accessory, continue to enjoy popularity.

Social influences

Fashion is inherently a social phenomenon. A person cannot have a fashion by themselves, but for something to be defined as fashion, there needs to be dissemination and followers. This dissemination can take several forms, from the top-down ("trickle-down") to bottom-up ("bubble up/trickle-up"), or transversally across cultures and through viral memes and media ("trickle-across").

Fashion relates to the social and cultural context of an environment. According to Matika, "Elements of popular culture become fused when a person's trend is associated with a preference for a genre of music, like music, news, or literature, fashion has been fused into everyday lives." Fashion is not only seen as purely aesthetic; fashion is also a medium for people to create an overall effect and express their opinions and overall art.

This mirrors what performers frequently accomplish through music videos. In the music video 'Formation' by Beyoncé, according to Carlos, the annual or seasonal runway show is a reflection of fashion trends and a designer's inspirations. For designers like Vivienne Westwood, runway shows are a platform for her voice on politics and current events. For her AW15 menswear show, according to Water, "where models with severely bruised faces channeled eco-warriors on a mission to save the planet." Another recent example is a staged feminist protest march for Chanel's SS15 show, rioting models chanting words of empowerment using signs like "Feminist but feminine" and "Ladies first." According to Water, "The show tapped into Chanel's long history of championing female independence: founder Coco Chanel was a trailblazer for liberating the female body in the post-WWI era, introducing silhouettes that countered the restrictive corsets then in favour."

The annual Met Gala ceremony in Manhattan is the premier venue where fashion designers and their creations are celebrated. Social media is also a place where fashion is presented most often. Some influencers are paid huge amounts of money to promote a product or clothing item, where the business hopes many viewers will buy the product off the back of the advertisement. Instagram is the most popular platform for advertising, but Facebook, Snapchat, Twitter, and other platforms are also used. In New York, the LGBT fashion design community contributes significantly to promulgating fashion trends, and drag celebrities have developed a profound influence on New York Fashion Week.

Fashion Technology

Fashion

Fashion is not only about following trends. But fashion is all about our comfort. 

Fashion can be very personal, or in simple words, fashion is an extension of our personality. 

We should always opt for an outfit that suits our personal traits. 

We can keep the outfit stylish yet simple and comfortable at the same time. And while being fashionable, one crucial thing we should always keep in mind is that our outfit/clothes should not overpower our personality. 

So my all-time favourite fashion quote is "You're wearing the outfit; the outfit isn't wearing you!!"

Term

Fashion is a term used interchangeably to describe the creation of clothing, footwear, accessories, cosmetics, and jewellery of different cultural aesthetics and their mix and match into outfits that depict distinctive ways of dressing (styles and trends) as signifiers of social status, self-expression, and group belonging. 

As a multifaceted term, fashion describes an industry, designs, aesthetics, and trends.

The term 'fashion' originates from the Latin word 'Facere,' which means 'to make,' and describes the manufacturing, mixing, and wearing of outfits adorned with specific cultural aesthetics, patterns, motifs, shapes, and cuts, allowing people to showcase their group belongings, values, meanings, beliefs, and ways of life. 

Given the rise in mass production of commodities and clothing at lower prices and global reach, reducing fashion's environmental impact and improving sustainability has become an urgent issue among politicians, brands, and consumers.

Definitions

The French word mode, meaning "fashion", dates as far back as 1482, while the English word denoting something "in style" dates only to the 16th century. Other words exist related to concepts of style and appeal that precede mode. In the 12th and 13th century Old French the concept of elegance begins to appear in the context of aristocratic preferences to enhance beauty and display refinement, and cointerie, the idea of making oneself more attractive to others by style or artifice in grooming and dress, appears in a 13th-century poem by Guillaume de Lorris advising men that "handsome clothes and handsome accessories improve a man a great deal".

Fashion scholar Susan B. Kaiser states that everyone is "forced to appear", unmediated before others. Everyone is evaluated by their attire, and evaluation includes the consideration of colors, materials, silhouette, and how garments appear on the body. Garments identical in style and material also appear different depending on the wearer's body shape, or whether the garment has been washed, folded, mended, or is new.

Fashion is defined in several different ways, and its application can sometimes be unclear. Though the term fashion connotes difference, as in "the new fashions of the season", it can also connote sameness, for example, about "the fashions of the 1960s", implying a general uniformity. Fashion can signify the latest trends, but may often reference fashions of a previous era, leading to the reappearance of fashions from a different period. While what is fashionable can be defined by a relatively insular, esteemed and often rich aesthetic elite who make a look exclusive, such as fashion houses and haute couturiers, this 'look' is often designed by pulling references from subcultures and social groups who are not considered elite, and are thus excluded from making the distinction of what is fashion themselves.

Whereas a trend often connotes a peculiar aesthetic expression, often lasting shorter than a season and being identifiable by visual extremes, fashion is a distinctive and industry-supported expression traditionally tied to the fashion season and collections. Style is an expression that lasts over many seasons and is often connected to cultural movements and social markers, symbols, class, and culture (such as Baroque and Rococo). According to sociologist Pierre Bourdieu, fashion connotes "the latest difference."

Even though the terms fashion, clothing, and costume are often used together, fashion differs from both. Clothing describes the material and the technical garment, devoid of any social meaning or connections; costume has come to mean fancy dress or masquerade wear. Fashion, by contrast, describes the social and temporal system that influences and "activates" dress as a social signifier in a certain time and context. Philosopher Giorgio Agamben connects fashion to the qualitative Ancient Greek concept of kairos, meaning "the right, critical, or opportune moment", and clothing to the quantitative concept of chronos, the personification of chronological or sequential time.

While some exclusive brands may claim the label haute couture, in France, the term is technically limited to members of the Chambre Syndicale de la Haute Couture in Paris. Haute couture is more aspirational, inspired by art and culture, and in most cases, reserved for the economic elite. However, New York's fashion calendar hosts Couture Fashion Week, which strives for a more equitable and inclusive mission.

Fashion is also a source of art, allowing people to display their unique tastes, sensibilities, and styles. Different fashion designers are influenced by outside stimuli and reflect this inspiration in their work. For example, Gucci's 'stained green' jeans may look like a grass stain, but to others, they display purity, freshness, and summer.

Fashion is unique, self-fulfilling, and may be a key part of someone's identity. Similarly to art, the aims of a person's choices in fashion are not necessarily to be liked by everyone, but instead to be an expression of personal taste. A person's personal style functions as a "societal formation always combining two opposite principles. It is a socially acceptable and secure way to distinguish oneself from others and, at the same time, it satisfies the individual's need for social adaptation and imitation." While philosopher Immanuel Kant believed that fashion "has nothing to do with genuine judgements of taste", and was instead "a case of unreflected and 'blind' imitation", sociologist Georg Simmel thought of fashion as something that "helped overcome the distance between an individual and his society". American sociologist Diana Crane also mentioned in her book that fashion is closely intertwined with personal and group identity, serving as a means of expressing cultural, social, and political affiliations.

e-Learning Technology

What is e-Learning?

e-Learning, short for electronic learning, is a broad term encompassing various learning methods through electronic technologies.

These learning methods typically have a clear structure. In other words, simply consuming online information (through browsing a Wikipedia article, or watching a YouTube video, for example) doesn’t qualify as e-Learning on its own.

Here’s what sets e-Learning apart:

• Structure: e-Learning typically involves a structured learning path with objectives, activities, and assessments.
  
  
• Interactivity: e-Learning encourages interaction with the material through quizzes, simulations, or discussions.
  
  
• Outcomes: e-Learning allows for tracking progress and measuring outcomes through assessments and feedback mechanisms.

Some Important Distinctions

In the exciting world of online learning, it’s important to understand the difference between three key elements: content, courses, and platforms. Here’s a brief breakdown of each:

• Content: This refers to the individual pieces of information you encounter online that can be used for learning. They are the building blocks of your experience. Content comes in many different shapes and forms, such as text, videos, infographics, podcasts, and more. While valuable for acquiring knowledge, this content doesn’t provide a structured learning path.
  
  
• Courses: On the other hand, courses are structured learning assets built using various content pieces. They are often created using an authoring tool and typically have defined learning objectives, activities, and assessments. They offer a more organised and focused learning experience compared to consuming isolated content. Collect enough courses together and you have yourself an online learning programme.
  
  
• Platforms: Finally, we have the online environments that host and deliver both content and courses. They provide the infrastructure for learners to access learning materials, interact with instructors, and track their progress. For instance, Growth Engineering LMS is an e-Learning platform.

Clearing Up The Confusion

The key distinction is that e-Learning focuses on the ‘how‘ of learning (electronic delivery), while individual online resources, such as content and courses, focus on the ‘what‘ of learning (the specific content).

For instance, imagine you’re ordering from a restaurant. The menu items (such as pizza, salad, dessert, etc.) are the specific content elements that you select from. In this scenario, e-Learning is just the delivery method. It’s like selecting takeaway rather than choosing to dine in.

To help hammer this point home, check out this definition from the Oxford Home Study Centre:

The term ‘e-Learning’ refers to the delivery of education and training through digital resources. Rather than attending lectures and classes in the conventional sense, e-Learning uses modern technology to connect pupils and students with course content, learning resources, and qualified tutors.

e-Learning: A Quick History Lesson

The term ‘e-Learning’ has only been around since 1999. It was originally coined by researcher, educator, conference host, and friend of Growth Engineering, Elliot Masie. However, e-Learning as an entity has been around for much longer.

Electronic learning can be traced back to the first proto-LMSs created by Sidney Pressey in 1924. These were simple ‘teaching machines’ that looked like a typewriter with an additional display window. To make progress, learners would have to input answers to multiple-choice questions.

In 1960, the first computer training programme was born. PLATO (Programmed Logic for Automatic Teaching Operations) was created at the University of Illinois. Not only was it a successful teaching system, but it also brought about one of the world’s first online communities. This expanded in the 1970s, as e-Learning started to become more dynamic and interactive.

By the mid-1990s, early iterations of the LMSs we know and love today started to spread. Naturally, with the rise of the internet and easier access to online technology, the e-Learning market grew at a pace. This was mainly driven by educational institutions, which were looking to create distance learning solutions for their students. 

Additionally, businesses started to use e-Learning in their training initiatives to help reduce costs and expand their reach. As a result, since the year 2000, the e-Learning market has grown by over 900%!

What About Now?

The e-Learning market is now worth over a whopping $250 billion. And it’s showing no signs of slowing down. It’s projected to be worth $1 trillion by 2027. 

Much of this growth can be attributed to the COVID-19 pandemic, which turbocharged digital transformation. As a result, many companies, schools, universities, and other educational bodies have embraced e-Learning and made it a permanent part of their processes.

Today, e-Learning continues to evolve with advancements in mobile learning, gamification, and artificial intelligence, offering increasingly engaging and effective learning experiences.

How Does e-Learning Differ from Other Similar Terms?

Now that we’ve defined e-Learning, you may well be wondering how it contrasts with other similar terms. Unfortunately, the learning technology landscape is cluttered with ambiguous or unnecessary terms. Please consider the following list, our attempt to cut through the noise:

1. Online Learning

As you might expect, with online learning, the main element is the internet. This can include both formal e-Learning experiences, as well as informal learning activities.

For instance, watching educational YouTube videos, reading articles on a learning platform, or participating in online forums for knowledge sharing would all fall under online learning, but not necessarily e-Learning.

2. Virtual Learning

Virtual learning centres around the creation of a simulated learning environment using technology. These learning experiences typically involve elements of immersion, real-time interaction, and collaboration within a virtual space.

This could include virtual reality simulations, classrooms in the metaverse, or even some online role-playing scenarios used for training.

3. Digital Learning

This is a broad term that incorporates the use of any digital technology to facilitate learning experiences. This includes taking courses online, internet-based research, or even using digital tools (like smartboards, mind maps, quizzes, and so on).

4. Remote Learning

Remote learning takes place when the learner and instructor aren’t both physically present within the same environment. As with virtual learning, the learner doesn’t have to be in a set location to make progress.

However, remote learning can take various forms. Furthermore, whilst it’s typically facilitated by the internet, it doesn’t have to be. For instance, you could conduct a remote learning programme via regular snail mail communications. 

5. Distance Learning

As with remote learning, distance learning emphasizes the physical separation between instructor and student. Here, technology often acts as a bridge, making education accessible regardless of location.

This convenience factor is a major draw for many students, which has prompted universities to expand their offerings in distance learning courses, including full degree programmes.

e-Learning Use Cases

e-Learning’s applications are vast and extend far beyond traditional classroom settings. Here are some key use cases where e-Learning shines:

• Online Degrees & Courses: Many universities and institutes offer complete degrees, diplomas, and individual courses entirely online, providing flexibility and accessibility for learners across the globe.
  
  
• Educational Supplementation: e-Learning resources can supplement traditional educational approaches by offering personalised learning paths, additional support, and knowledge sharing opportunities.
  
  
• Employee Onboarding: You can streamline your onboarding process for new hires by providing e-Learning courses covering company policies, product knowledge, and essential skills.
  
  
• Professional Development: e-Learning can also help you to offer ongoing training opportunities to your learners, ensuring they keep their skills current and ready themselves for the next step in their career.
  
  
• Compliance Training: Ensure your employees are up-to-date on mandatory compliance regulations through engaging e-Learning courses and certification mechanisms.

And so on. These are just are few examples, and the possibilities for e-Learning continue to grow as technology evolves.

Why Choose e-Learning?

More than 40% of Fortune 500 companies already use e-Learning as a delivery mechanism for their training initiatives. And this number is only set to keep growing. Here are some of the benefits that make e-Learning a genuine game-changer.

• 72% of businesses say that e-Learning is the key reason they’re ahead of their competitors.
• 42% of companies report an increase in revenue after switching to e-Learning. 
• e-Learning can help you retain 5x more knowledge for each hour of learning compared to traditional lessons.
• e-Learning reduces energy consumption by up to 90% and produces 85% fewer CO2 emissions compared to face-to-face education.
• 85% of learners rate their online learning experience as better, or at least equally as sufficient, as face-to-face classes.

And that’s just scratching the surface. Follow this link to find 110+ more mind-blowing e-Learning statistics. Or, keep reading and find out why this is such an effective approach.

1. It’s Flexible

Synchronous face-to-face training requires all learners to be in the same place at the same time. This can be incredibly restrictive. e-Learning allows for freedom. Freedom to complete content whenever it may suit you. And freedom to access content from wherever you may be.

This means that learners can fit training around their schedule and learn at their own pace. What’s more, this is now even easier due to the advancement of mobile technology. If your LMS is mobile-responsive or if you have a mobile app solution, e-Learning can take place in the form of mobile learning.

This is rapidly becoming the modern learner’s favoured approach. In fact, 52% of learners use mobile learning right after waking up!

2. It’s Time and Cost-Effective

Face-to-face training requires a venue, travel costs, accommodation, and many more expenses. However, with e-Learning, this is simply not necessary.

Of course, it’s not free! However, it is significantly cheaper. Did you know that the average company saves 50%-70% by moving from face-to-face training to e-Learning?

Here’s a great example. IBM conducted a study to find out the true value of workplace learning. They found that every dollar invested in online training results in $30 in productivity. That’s because online learners are able to learn faster and at their own pace.

3. It’s Easy to Report On

With e-Learning, each activity is typically recorded through a learning platform (such as an LMS). This means it can be reported on. As a result, you can track everything from logins to content completions, so you end up with a complete picture of your training initiative. 

Indeed, 82% of organisations agree that reporting is vital for improving their e-Learning approaches. After all, with effective reporting, you can easily tie e-Learning to business impact. For example, one of our Fortune 500 clients was able to directly link a 20% increase in revenue to their mobile app solution.

Besides, wouldn’t it be nice to move away from paper trails and manually-updated spreadsheets?

4. It’s Consistent

With e-Learning you can deliver the same content to everyone, ensuring that the same standard of training is delivered everywhere.

When you rely solely on face-to-face training, you entrust your learning programme to several trainers. Some will be fantastic and will inspire your learners. But there could be a number who fall short. Thankfully, when you use e-Learning, you’re in full control.

In a study of 283 learners across different sectors, Training Industry found that consistent training initiatives make learners: 

• Much more engaged with their learning.
• Incredibly motivated to work on their skills.
• A lot more satisfied with their roles.
• And more in tune with the benefits that training provides for them.

5. It’s Wide-Reaching and Inclusive

e-Learning removes geographical boundaries and opens your content up to a mass audience. This helps, as communication boundaries and cultural misunderstandings are estimated to cost businesses more than $2 billion annually.

Luckily, with e-Learning that no longer has to be the case. Many online learning solutions will help translate both your platform and content into different languages. This eases communication, which can improve productivity by 25-35%.

6. It Comes in a Variety of Formats

These days, learners have access to a wide range of media outside of their learning environment. Why shouldn’t their learning experiences be the same?

An online learning platform means you can integrate video, learning games, immersive learning, and more into your training approach. This broadens the definition of what ‘e-Learning’ can be. It also makes learners much more willing to engage and remain engaged. 

For example, studies show that websites that use videos have an extra two-minute dwell time on average compared to those that don’t. But the fun doesn’t have to stop there. You can also incorporate:

Gamification

Gamification is the use of game mechanics within non-gaming environments to motivate and engage learners. Indeed, a Deloitte study found that a staggering 80% of workers believe that game-based learning is more engaging than classroom-based learning.

Here at Growth Engineering, we use mechanics like experience points, badges, levels, and leaderboards to spur learners on. These features would be difficult to replicate in real life, but they’re relatively easy to integrate within an e-Learning approach.

Microlearning

The modern learner likes things short and snappy. As such, e-Learning and microlearning make for great partners. This is where learners consume information in bite-sized chunks rather than long courses. This makes e-Learning experiences more ‘snackable’ and easier to get through. 

As it happens, learners respond to this training approach really well. Indeed, 94% of experts state that learners actually prefer bite-sized learning. And a study published in the Journal of Applied Psychology revealed that microlearning increases learning efficacy by 17%.

7. It’s All about You

Most learners want their training content to cater directly to their wants and needs. And that’s okay! With e-Learning, you can take advantage of the evolution in technology. This includes the use of artificial intelligence (AI). 

Typically, AI personalises learning for each individual learner. For example, it can customise your courses, tailor visibility settings, and control the delivery mechanism. It can even act as a coach and guide your learners on their journey to success.

Final Words

e-Learning is a tricky term to define. Unfortunately, it’s not the only industry jargon that seems purpose-built to trip people up. Luckily, we’ve got a jargon-busting glossary ready for you to enjoy.

Just remember, e-Learning is a delivery mechanism, not a content type. We’ve also seen that it’s an effective approach that can help to both reduce costs and increase your return on investment.

Whether you’re an individual seeking to upskill or an organisation looking to train your workforce, e-Learning is a powerful tool worth exploring. Are you ready to take the plunge?

A Timeline of Key Dates in Learning Technology History

1440: Hot off the Press

We have a lot to thank Johannes Gutenberg for. After all, before he invented the printing press in 1440, the spread of knowledge was a painstaking endeavor. Books were meticulously copied by hand, making them scarce and costly treasures. 

The invention of the printing press represents a pivotal point in human history. By dramatically increasing the speed of book production, it made knowledge more accessible than ever before. As a result, literacy rates soared, and new educational opportunities blossomed. 

1877: The Sound of Success

Nearly half a millennium after Gutenberg’s groundbreaking invention, another technological marvel emerged: the phonograph. Thomas Edison’s 1877 invention revolutionized the way sound could be captured, stored, and reproduced. 

Although early recordings were grainy and imperfect, the phonograph paved the way for future audio technologies, including record players and tape recorders. And as we know, these devices played a crucial role in the development of educational media. 

That educational audiobook or podcast you love? You can thank the phonograph for making it possible. 

1895: The Magic of Moving Pictures

With our auditory senses engaged, you can guess where we’ll turn our attention next. 

The dawn of the 20th century brought with it the emergence of a powerful new medium: film. The Lumiere brothers patented the ‘Cinematographe’, the first commercially viable film projector in 1895. 

This versatile device meant that for the first time, moving images could be captured, developed, and projected on film. Before long, projection technology found its way into classrooms, opening up new visual learning opportunities. 

1924: The Birth of Automated Learning

In 1924, psychologist Sidney Pressey developed a pioneering mechanical teaching machine. Indeed, some have hailed this device as a precursor to the modern learning management system (LMS) and the first automated learning platform. 

Pressey’s machine presented students with a series of multiple-choice questions. When an answer was selected, the machine would automatically display feedback. Whilst the device had its limitations, it was undeniably ahead of its time. 

1940s: The Dawn of the Digital Age

The invention of the first electronic computers in the early 1940s was a true game changer. While these early machines were massive and cumbersome (nothing like the pocket-sized supercomputers we now carry around), they did successfully lay the foundation for our current digital revolution.

The Colossus computer, developed by British codebreakers in 1943, was one of the first electronic digital computers. It was soon followed by the ENIAC in 1945, the first general-purpose digital computer. These machines were big enough to fill an entire room.

As these early computers evolved, becoming smaller and more powerful, they paved the way for a new era of learning technology. This included computer-assisted instruction programs (more on this shortly), educational software, and eventually, online learning. 

1960: Computers Start Teaching Us a Lesson

As we’ve seen, the invention of the computer opened up new possibilities for education. Indeed, in 1960, the University of Illinois introduced PLATO. This system wasn’t named after Socrates and Aristotle’s philosophical friend. It’s actually an acronym that stands for: ‘Programmed Logic for Automatic Teaching Operations’.

PLATO can safely be considered the first computer-assisted instruction system. It used a time-sharing system to deliver personalised lessons to multiple users simultaneously. These lessons included text, graphics, and some early forms of audio and video.

Users could even connect and communicate with each other through the system, enabling social learning. Many of PLATO’s features have proven to be influential, and it’s fair to say that it impacted the design of modern LMSs and online courses. 

1967: Casting a Wider Net

In 1967, the US Department of Defense established the Advanced Research Projects Agency Network (ARPANET). This early packet-switched network was a precursor to the modern internet we know and love.

The ARPANET enabled the sharing of computer resources, such as software and data, among different individuals and institutions. As a result, it transformed the way we access information. We’ll expand on this shortly with the creation of the Internet. 

1970s: You Have Mail

The digital revolution gained some serious momentum in the 1970s. In fact, in 1971, a pivotal moment in digital communication occurred: the first email was sent using the ARPANET. As a result, a new, fast, efficient, and asynchronous communication method was born. 

The momentum continued into 1973 with the first mobile phone call. While these early devices were bulky and expensive, they would eventually evolve into sleek smartphones capable of delivering powerful and engaging mobile learning experiences. 

1980s: This Time it’s Personal

The rise of personal computers (PCs) during the 1980s marked a significant shift in technology and society. Before this decade, computers were often housed in climate-controlled rooms and operated by specialized technicians. Now, however, they have become accessible to the masses. 

In 1981, the IBM PC was released, alongside the first 3.5-inch floppy disk drive. A few years later, in 1984, the Apple Macintosh was released, setting a new standard for personal computing. This was followed by Microsoft’s release of Windows in 1985, an operating system that would go on to dominate the market. 

These systems empowered learners, providing them with a new set of tools to explore, create, and learn at their own pace.

1989: Welcome to the Web

As the ARPANET grew, new protocols were needed to manage data transmission efficiently. This led to the creation of the Transmission Control Protocol/Internet Protocol (TCP/IP) in 1974 and the Domain Name System (DNS) in 1983.

In turn, this generated an explosion of activity, but there was still no standardized way to format documents on the network. That was until 1989, when British computer scientist Tim Berners-Lee proposed a solution: the World Wide Web. This system introduced hypertext to link documents together in a ‘web of information’. 

This transformation turned the internet from a network primarily used by researchers into a global information space accessible to anybody with a connection. The stage was now set for the rise of online learning.

1989 Part Two: Charting a New Course

At a point in history when most people didn’t even have email, the University of Phoenix took a bold step. They launched the first online course in 1989. This innovative online MBA program initially targeted users of an early online service called Prodigy. 

For the first time, higher education was more accessible to working adults, single parents, and others with scheduling constraints. Now, online courses like these are commonplace. Indeed, according to Oxford College, 21% of British people use some form of online learning.

1990: All Learning Systems Are Go

Today, the learning management system (LMS) is considered the standard bearer for delivering online and blended learning experiences across a range of different contexts. But how did we get here?

The first commercially available LMS platform, ‘FirstClass’, was developed by SoftArc in 1990. While it was initially designed for communication and file sharing, it eventually embraced features like course management and assessment tools. Thus, the LMS was born. 

EKKO, launched in 1991, refined the concept further. However, it wasn’t until the release of Blackboard LMS in 1997 that the technology truly gained widespread popularity, particularly in the higher education space.

Now, modern solutions like Growth Engineering LMS focus on driving learner engagement through gamification, social learning, and deep personalization. 

1993: The First Interoperability Standard Takes Flight

Formed in 1988, the Aviation Industry Computer-Based Training Committee (AICC) was an association of training professionals dedicated to developing guidelines for the creation and delivery of computer-based training in the aviation industry.

In 1993, the AICC published ‘CMI001 – AICC/CMI Guidelines for Interoperability’. This was the first runtime interoperability specification for learning management systems. It helped to standardize eLearning content, ensuring it would play nicely across different systems. 

By 1998, the AICC updated its specification to include a web-based interface called HACP. This expanded its reach beyond the aviation industry. While AICC has since been eclipsed by SCORM and xAPI (see below), its legacy continues, particularly in industries that prioritize security. 

1999: The Name of the Game

While the term ‘eLearning’ may be ubiquitous today, it was only initially coined in 1999 by Elliott Masie at his TechLearn conference. He used it to describe the emerging field of electronic learning, driven by learning management systems, e-learning courses, and online classes. 

2000: SCORM Sets a New Standard

Like AICC, SCORM (or Sharable Content Object Reference Model) is a set of technical interoperability standards for eLearning content. It was developed by the Advanced Distributed Learning (ADL) Initiative, a US Department of Defense program. 

SCORM is the most widely adopted eLearning standard (by a sizeable margin). According to Software Advice, 62% of organizations use SCORM in their LMS. Here are the key versions you should be aware of: 

• SCORM 1.0: The first version of the standard, released in January 2000.
• SCORM 1.2: The ‘industry workhorse’, released in October 2001.
• SCORM 2004 4th Edition: The most modern version of the standard, released in March 2009.

While SCORM has its limitations, its widespread adoption has driven the uptake of eLearning. After all, it has established itself as a ‘go-to’ standard for interoperability, ensuring content reusability across various systems. 

2002: Moodle Puts Learning Out in the Open

Although development began in 1999, the first version of Moodle (Modular Object-Oriented Dynamic Learning Environment) was released in August 2002. That made it the earliest open-source LMS, meaning that its source code is freely available for modification and distribution. 

The open-source nature of the platform contributed to Moodle’s widespread adoption and customization. Today, it’s one of the most popular LMS platforms globally, hosting 425+ million users and 48+ million courses (as of 2024). 

2004: A Star is Born

In 2004, something truly momentous happened. Growth Engineering was founded by Juliette Denny. Our organization initially started as a consultancy firm focused on providing sales management training to new businesses.

However, over time, the focus shifted to developing innovative online learning solutions. This led to the launch of Growth Engineering LMS (2007), Growth Engineering Authoring Tool (2013), and Growth Engineering Learning App (2017).

Today, Growth Engineering is a B Corp Certified organization known for its focus on learner engagement. We’ve won 120+ awards alongside our client partners and continue to push learning technology in new directions. 

2007: The Year Phones Got Smart

While the IBM Simon, released in 1994, is widely considered the first smartphone, it was the introduction of the iPhone that truly transformed the mobile industry. Indeed, Steve Jobs’ iconic announcement in January 2007 marked the beginning of a new era of mobile learning. 

After all, the smartphone has made it possible to learn anytime and anywhere. This process is supported by mobile learning apps, which now offer a wide range of high-quality educational content. Learning on the go has never been easier. 

2008: MOOCs Run Amok

A MOOC, or a Massive Open Online Course, is a free online course that’s available to anybody with access to the internet. They’re designed for a mass audience and use video lectures, resources, quizzes, and discussion forums to achieve their learning objectives.

The first MOOC is widely considered to be ‘Connectivism and Connective Knowledge’, created by George Siemens and Stephen Downes for the University of Manitoba in 2008. It attracted over 2,000 students from around the world.

This led to an explosion of different MOOCs in the early 2010s and the launch of popular platforms like Khan Academy (2008), Udacity (2011), Coursera (2012), and edX (2013).

2012: Google Glass Looks into the Future

Back in 2012, after we survived the Mayan apocalypse, Google made a big announcement. They introduced Google Glass at their I/O conference. These smart glasses were then shipped to consumers in May 2014.

They worked by projecting information onto a small display in front of the wearer’s eyes. While the initial hype didn’t last, this device did manage to spark real interest in wearable technology. 

They also helped to make augmented reality educational experiences more accessible and affordable. After all, by overlaying digital information onto the real world, it was now possible to create immersive learning experiences. 

As this technology has evolved, more innovative educational applications have emerged. 

2013: A New X-Factor in Learning

As we’ve seen, SCORM remains the most popular eLearning interoperability standard. However, it’s not the most modern or flexible. That honor belongs to Experience API (more commonly known as xAPI). 

In 2010, when SCORM was almost a decade old, the Advanced Distributed Learning (ADL) Initiative issued a call for research into the next generation of eLearning standards. This led to the launch of the community-driven Project Tin Can, spearheaded by Rustici Software. 

Tin Can API version 1.0.0 was launched in April 2013. It was officially renamed Experience API later that same year. This modern standard can capture a wider range of learning activities than SCORM, including informal learning, simulations, and real-world experiences. 

While xAPI has not reached the same level of adoption as SCORM (yet!), it continues to evolve and has the potential to significantly impact the future of learning technology.

2016: A Virtual Reality Check

The concept of virtual reality (VR) has been around for decades. But it always felt like an abstract notion from science fiction. However, the release of consumer-friendly VR headsets like the Oculus Rift and HTC Vive in 2016 brought virtual reality to the mainstream. 

These advancements sparked increased interest in VR for educational purposes. After all, in a virtual reality environment, students can explore, interact, and engage in hands-on experiences that might be impractical in traditional classrooms. This leads to deeper and more immersive learning experiences. 

While VR technology has become more affordable, it has yet to achieve widespread adoption in education. As a result, it is typically applied to niche or specialized learning experiences. We expect this will change over the coming years as virtual reality solutions continue to evolve. 

2019: The Rise of the Machines

Artificial intelligence (AI) has captivated our imaginations since the early 20th century. Just think of iconic portrayals such as Maria from Metropolis (1927), the Tin Man from The Wizard of Oz (1939), and The Terminator (1984). 

However, it wasn’t until the late 2010s that significant advancements in natural language processing and machine learning started to influence the learning technology landscape. Indeed, the release of OpenAI’s GPT-2 in 2019 marked a turning point, as it demonstrated AI’s potential to generate human-quality text. 

Soon, AI-powered features like personalized recommendations and automated feedback began to be integrated into learning systems. Of course, this was just the beginning. We’ll circle back to artificial intelligence shortly. 

2020: The World Goes Remote

The COVID-19 pandemic and subsequent lockdowns of 2020 forced a rapid acceleration of digital transformation across all sectors. The education space was no exception. Indeed, as schools and universities closed their doors, educators had no choice but to adapt quickly and embrace remote learning. 

As a result, online learning surged in popularity, and software like video conference tools and virtual reality classrooms were rapidly adopted. Even now, in our post-pandemic world, many of these technologies continue to play an important role in shaping learning experiences. 

2023: GenAI Generates Excitement

In March 2023, OpenAI released GPT-4, a breakthrough learning model that significantly advanced the field of generative AI. As a result, McKinsey, New Scientist, and The University of Oxford all claimed that 2023 was the year that artificial intelligence went mainstream. 

Generative AI is a type of artificial intelligence that can create various forms of content, such as text, images, audio, and even video. In the context of learning technology, GenAI can be used to create highly personalised learning experiences, produce learning materials, and provide intelligent coaching. 

As a result, learning systems across the globe have been rapidly implementing AI features and touting their benefits. While we’re yet to see the full impact of this technology on education, it’s hard not to get excited about its potential.

Final Words

This comprehensive timeline highlights the significant milestones in the history and evolution of learning technology. It’s inspiring to witness the remarkable progress that has been made over the past century. 

During this time, we’ve progressed from rudimentary teaching machines to sophisticated automated learning systems. It’s fascinating to imagine what early pioneers like Sidney Pressey would make of today’s advanced learning technologies. 

As we look to the future, we can’t help but wonder what possibilities lie ahead. How will more complex AI learning tools, improved data analytics, and our increasingly digital world shape the future of education?