Vibe Coding Showdown: Gemini vs ChatGPT. Can AI Really Build eLearning Games?
Can artificial intelligence really build your training games? The hype around AI tools is everywhere. We are told they can write our emails, analyse our data and even design our courses. But can they really create something as complex as an interactive training game? This question matters. For learning and development teams under pressure to produce content quickly, the idea of “vibe coding” — where you simply ask an AI to code for you, is both exciting and daunting. Could this replace weeks of development time? Or is it just smoke and mirrors? In this blog, I share my own experiment where I asked ChatGPT 5 and Google Gemini to build a modular Space Invaders-style quiz game for training. The results were surprising. What is Vibe Coding and Why Does it Matter? Vibe coding is shorthand for coding by conversation. Instead of opening an IDE and writing lines of code, you describe what you want and let an AI tool generate it. The promise is simple: non-programmers can produce complex applications with natural language prompts. For the training industry, this is particularly attractive. Imagine telling an AI: “Build me a branching scenario with quiz questions that can be reused across different subjects.” If it worked, you could design interactive modules faster than ever before. But there are risks. AI models do not actually “understand” the systems they are coding. They generate text that looks like code based on patterns from their training data. This means that while they can often produce impressive demos, the code may break once you step outside the most common scenarios. The Experiment: ChatGPT 5 vs Google Gemini To test how well vibe coding really works, I gave both ChatGPT 5 and Google Gemini the same brief: Build a Space Invaders-style arcade game. Incorporate quiz questions every few plays. Use XML and JavaScript files for the questions so the game can be modular and reused. The aim was not just to create a flashy game but to test whether AI could handle modularity, a principle at the heart of scalable training content. Watch the full experiment here: https://www.youtube.com/watch?v=3pSCrWRkk5o ChatGPT 5: Familiar but Frustrating ChatGPT knew exactly how to create a Space Invaders clone. Within minutes, it produced a playable version of the classic game. But problems appeared as soon as I asked it to pull in questions from external files. File handling issues: It repeatedly failed to load the XML quiz file and instead generated its own placeholder questions. Error loops: Even after feeding it console errors and asking for fixes, the same issues resurfaced. Focus drift: ChatGPT tended to lock onto the “make a game” request and ignore the “integrate modular questions” part of the prompt. What became clear is that ChatGPT’s training has included a lot of arcade-style examples. It is very comfortable producing games that look right, but less capable when asked to stretch into less standard structures. Google Gemini: More Usable Out of the Box Gemini, on the other hand, managed to do what I wanted on the very first attempt. It loaded the quiz file correctly, integrated it with the game, and displayed real questions in the middle of gameplay. Cleaner structure: The game was more modular and easier to adapt. Responsive to prompts: When I asked for visual changes — more authentic Space Invaders graphics, faster enemy speeds, clearer “game over” states — it delivered them. Fewer repeats: Errors still cropped up but Gemini seemed to handle debugging more gracefully. The end result was not perfect, but it was significantly closer to something that could actually be used in a training context. What We Learned About AI in Training This head-to-head test highlighted a few important lessons for anyone interested in using AI in learning and development. AI can generate ideas, not finished productsBoth systems were able to spin up something playable quickly. This shows real potential for AI to support rapid prototyping and brainstorming. Modularity is hardAI often struggles with more complex requirements such as linking external files or reusing structures across multiple games. This is crucial in training where scalability matters. Iteration is essentialYou cannot simply “ask once and receive.” Both tools required repeated clarification, debugging and checks. Human oversight is not optional. Human qualities still matterCreativity, critical thinking and empathy for learners are not found in the AI. Even if the code runs, the learning design still comes from people. Is Vibe Coding Ready for Learning and Development? Right now, vibe coding is fascinating but not reliable. It is best viewed as an experimental tool for generating ideas and quick demos rather than as a replacement for trained developers or instructional designers. This does not mean it has no place. For a trainer wanting to visualise how a quiz game might look, AI can give a rough sketch in minutes. But if you need a stable, scalable product that can actually be rolled out, you will still need human expertise. A Smarter Way Forward While vibe coding is entertaining, most organisations need dependable tools that deliver learning in the formats their people need. That is why Open eLMS Learning Generator exists. Instead of wrestling with AI models to produce half-finished code, you can take your existing content and instantly transform it into video, PowerPoint, podcasts or even arcade-style games. It is fast, multilingual and creates professional content that is ready to deploy. You can try it now with a free 14-day trial. Try Open eLMS Learning Generator The verdict from this test is clear: Gemini currently outperforms ChatGPT for vibe coding training games. Yet both tools still highlight the same truth. AI can inspire and support, but it is not yet the finished solution. The real future of learning lies in combining the creativity of people with AI systems that are robust, transparent and reliable. Until then, tools like Open eLMS are a practical bridge between ambition and delivery.
Step by Step Guide to Vibe Coding With Google Gemini: AI in Training
Artificial intelligence is no longer confined to generating text. It is now entering the space of interactive design, helping trainers and educators build learning experiences that once required coding expertise. One of the most exciting developments is vibe coding with Google Gemini. Vibe coding allows you to give the AI a “vibe” or overall direction, and it does the heavy lifting by generating the code, assets and interactivity. This blog explores how Gemini can be used in training through a step by step guide, with a video demonstration embedded below. What the Video Covers In the video, Emil demonstrates how Gemini can be used in learning and development through vibe coding. The step by step process includes: Creating a structured mindfulness course as the foundation. Generating supporting materials such as course outlines, learning goals and presentations. Turning that content into flashcards, handouts and interactive activities. Applying vibe coding to build fully functional online mini-games. The highlight is watching Gemini create a “Mindful Escape” game where learners must recognise and respond to stress triggers. Iteration improves the design further, making the game more challenging and relevant to workplace stress management. Gemini also attempts a snake-style game where mindfulness questions appear when the snake collides with obstacles, showing how even classic mechanics can be reimagined as learning tools. https://www.youtube.com/watch?v=choImlCJQ_U&list=PL2j5qhe5EPJtm5Qal71mGHjMAx1zCLgaR&index=1 Why Vibe Coding Matters for Training This step by step guide shows how vibe coding can empower trainers without coding expertise. For learning and development teams, the benefits are clear: Rapid prototyping of interactive activities. Gamification of training content to boost engagement. Adaptation of games and quizzes to reflect organisational themes or branding. While Gemini sometimes requires iteration and fixes, it demonstrates how AI can turn ideas into interactive, engaging formats. Vibe coding bridges the gap between imagination and implementation, giving trainers more creative options than ever before. Open eLMS Learning Generator Google Gemini shows what is possible when AI and vibe coding come together. But there is another option for those who want professional-standard results with less back and forth. The Open eLMS Learning Generator can take a single line of text or a PDF and produce a complete, high-quality course in minutes. It automatically includes narration, imagery, animation and interactivity, ready to export as SCORM, video, PowerPoint or microgames. If you want to explore how AI can transform training in a practical and efficient way, you can try the Open eLMS Learning Generator free for 14 days. Try Open eLMS Learning Generator
AI in Training: How to Use Google NotebookLM for Course Creation
The role of artificial intelligence in education and training is expanding at a rapid pace. In our AI in Training series we look at practical applications of AI tools that can make life easier for trainers, teachers and learning and development professionals. Each episode takes a popular AI tool and examines how it works, what it does well, and where it might fall short. In this episode we explore Google NotebookLM, a system designed to help professionals collate, curate and transform content into structured training resources. The Problem: Creating Training Content Efficiently One of the greatest challenges for trainers and learning designers is the time it takes to create professional course materials. Gathering documents, writing lesson plans, and developing supplementary resources such as podcasts, videos and study guides is a process that can take weeks. Most AI tools on the market today can generate content quickly, but they often rely on generic data and do not allow you to anchor learning material to your own sources. This creates a risk of inaccuracy and makes it difficult to ensure courses are specific to your learners’ needs. Google NotebookLM attempts to solve this problem by letting you import your own materials, ringfence them, and then use AI to generate tailored outputs such as schedules, videos, podcasts, mind maps and reports. Google NotebookLM in Action Here is the full walkthrough from our AI in Training series, where we build a time management course using Google NotebookLM. https://www.youtube.com/watch?v=vAaxt2g1y8g&list=PL2j5qhe5EPJu2z227YRWEkuCgg2xnB0dm Why This Matters for Learning Professionals NotebookLM demonstrates how AI can speed up course creation while still keeping the trainer in control of the source material. Instead of starting from scratch, professionals can: Upload their own documents and data sources Curate information to ensure relevance Generate multiple learning resources from a single notebook Save time while still producing accurate, professional content For trainers, teachers and L&D teams this means less time spent on manual course development and more time available for teaching, coaching and learner engagement. This is not about replacing trainers, but about equipping them with smarter tools that extend their capability. There’s Another Way: Open eLMS Learning Generator At Open eLMS we believe that AI should empower learning professionals to create engaging, multimodal courses quickly and effectively. That is why we built the Open eLMS Learning Generator. With a single line of text or a document upload, the Learning Generator instantly produces a full professional e-learning course complete with video presenters, quizzes, animations and voiceovers in any language. You can edit the content online and export it as e-learning, a PowerPoint presentation or a video. Soon, you will also be able to export it as a podcast or even a game-based experience. You can try the Learning Generator free for 14 days and see how AI can transform the way you build training. Try Open eLMS Learning Generator
Step-by-Step Guide to Using ChatGPT for Creating Tailored Learning Content
The Challenge of Training Design In business training, one of the biggest challenges is making content relevant for learners. Generic courses often fail to meet expectations, which leaves participants disengaged. Effective training isn’t just about sharing information – it’s about aligning material with specific learner needs. ChatGPT provides trainers and learning professionals with a powerful way to streamline preparation while delivering personalised content. Instead of spending hours creating surveys, designing slides or restructuring agendas, ChatGPT can take on the heavy lifting. Trainers stay in control, but the AI saves time and ensures each session is better targeted. What the Video Covers In the video below, I demonstrate how to use ChatGPT to design a time management course. The walkthrough covers: Generating pre-course surveys to understand learner needs Analysing survey data and applying insights to course design Creating a one-day session plan tailored to participants Producing PowerPoint slides automatically Developing handouts such as glossaries and planners Rehearsing scenarios with role-play to prepare for challenging learners Drafting marketing emails to promote the training to specific industries https://www.youtube.com/watch?v=r5MjxiafnVA&t=9s&list=PL2j5qhe5EPJu2z227YRWEkuCgg2xnB0dm Practical Benefits of ChatGPT in Training The value of ChatGPT lies in more than speed. By tailoring every element of a course, trainers can: Deliver sessions that feel highly relevant to each audience Scale training design without adding extra staff Adapt existing content quickly to new contexts Focus more on facilitation and learner engagement rather than admin ChatGPT also enhances trainer confidence by enabling rehearsal. Role-playing interactions with “difficult students” allows facilitators to refine their communication strategies before stepping into the classroom. What This Means for Learning Professionals For learning and development teams, ChatGPT opens the door to agile training design. No longer restricted by rigid, pre-set materials, trainers can adapt courses in minutes. Whether it’s creating session outlines, generating slides or producing supporting resources, ChatGPT acts as a capable assistant – leaving the trainer free to focus on impact. The Bigger Picture ChatGPT is one tool in a growing landscape of AI for learning. Platforms such as Google NotebookLM and Anthropic’s Claude offer complementary features, from knowledge organisation to coding support. Together, these tools provide exciting opportunities to enhance and scale training delivery. If you’re working in business training or presentations, now is the time to start experimenting. Begin with surveys and outlines, then expand into slide creation, role-play and marketing. The more you explore, the more you’ll discover how AI can transform your learning design process. Try a Faster Way to Create eLearning While ChatGPT is a powerful assistant for building tailored training, there’s an even simpler way to create professional eLearning from start to finish. With Open eLMS Learning Generator, you can produce high-quality, fully designed courses in minutes. Just type a single line of text and the platform does the rest – from structuring content to generating polished eLearning ready for your learners. Try it free for 14 days and see how quickly you can transform your training. Try Open eLMS Learning Generator
Open eLMS MD Interview on Generative AI tool openelms.ai
Our Managing Director, Emil Reisser-Weston, was interviewed recently by Learning News regarding it’s AI powered elearning authoring system: openelms.ai. In this interview Emil explains how AI is used to automatically generate a script, organize learning objectives, and divide them into different sections within the course. It also generates visuals, videos, and animations, mimicking the process used by human designers who apply design heuristics. Despite sounding unbelievable, the tool has proven to be effective. To gain a comprehensive understanding of this innovative tool, watch the video where Emil Reisser-Weston explains its features and functionality, then visit www.openelms.ai and try it out.
The advantages of AI for elearning creation
Introduction Artificial Intelligence (AI) has been rapidly transforming various industries, and eLearning is no exception. With AI-powered tools, elearning content creation has become faster, easier, and more personalized than ever before. In this article, we will explore the benefits of AI in eLearning content creation and how it can improve the learning experience for students. Personalized Learning One of the most significant benefits of AI in eLearning content creation is personalized learning. With AI-powered tools, educators can create personalized content based on a student’s learning style, preferences, and performance data. This allows students to learn at their own pace and level, improving their engagement and overall learning outcomes. Personalized learning also helps educators identify knowledge gaps and provide targeted interventions to improve student understanding. Increased Efficiency AI-powered eLearning content creation is more efficient than traditional methods. It can create content quickly, accurately, and consistently, allowing educators to focus on other aspects of their job, such as teaching and engaging with students. This efficiency saves time and reduces costs, making eLearning more accessible to a broader audience. Elearning can be created in seconds using openelms.ai Enhanced Engagement AI-powered eLearning content creation can significantly enhance student engagement. With interactive content, such as videos and simulations, students are more likely to retain information and engage with the material. AI-powered content can also adapt to a student’s performance, providing feedback and adjusting the difficulty level of the content accordingly. This personalized approach can improve student motivation and interest in learning. Improved Accessibility AI-powered eLearning content creation can improve accessibility for students with disabilities. For example, text-to-speech technology can convert written content into audio format, making it accessible to students with visual impairments. This technology can also benefit students with dyslexia or other learning disabilities, providing them with alternative ways to learn and engage with the material. All openelms.ai courses include voiceovers and video presenters in up to 27 different languages Consistent Quality AI-powered eLearning content creation provides consistent quality across all content, regardless of the amount produced. The use of AI-powered tools ensures that content is created in a standardized format and is free of human error, ensuring high quality and accuracy. This consistency is essential in eLearning, where learners expect high-quality content that is easy to understand and learn from. AI elearning creation tool – openelms.ai – produces elearning of consistent quality Cost Savings AI-powered eLearning content creation can be cost-effective for educational institutions. The use of AI-powered tools reduces the need for human labor, saving time and costs associated with traditional content creation methods. Additionally, AI can generate content at a faster pace than humans, enabling educators to create more content in less time. Conclusion AI-powered eLearning content creation has numerous benefits, including personalized learning, increased efficiency, enhanced engagement, improved accessibility, consistent quality, and cost savings. With AI-powered tools, educators can create engaging and effective eLearning content that meets the needs of individual learners, providing an optimal learning experience. As AI technology continues to evolve, we can expect to see even more innovative solutions for eLearning content creation.
5 AI systems to revolutionise EdTech
AI has taken a lot of media attention of late. What I’d like to do in this article is to cut through the hype and show you 5 products which will dramatically affect your approach to EdTech in the coming months. These products (or similar ones) will be invaluable to you whether you are a manager, content creator or consumer of edTech content. We will then examine where this fast-moving field is heading and what exciting and truly remarkable developments you can expect in the near future. Chat GPT Chat GPT – now serving as the flagship of AI – has been adopted at a rate never seen before in the history of the internet. To reach a million users, Netflix took 3.5 years, Twitter took 2 years, Facebook took 10 months, Spotify took 5 months, and Instagram took 2.5 months. Chat GPT took only five days to reach one million users. Only two months after its launch, it had 100 million active users. The best way to explain the success is to use it, visit https://chat.openai.com/chat and ask it to write you a Shakespearean sonnet, a pub quiz or summarise War and Peace in 200 words. If you have not done so, so it, take your jaw floor and then start to have a conversation with it. Ask it to change the sonnet to a song by Bob Dylan, make the pub quiz about the 1980s or ask for the book summary to be condensed to 50 words. The engine adapts and will bend to your wishes. It is not a search engine; its answers are generated from scratch each time rather than regurgitated from a website. So how can this apply to edTech? Ask Chat GPT to construct a curriculum, write a training script or a quiz on any given topic. The results may not always be quite what you are looking for, but they can be edited and are generally pretty good. Chat GPT does this by absorbing vast quantities of data from forums, posts and websites and it is constantly fine-tuned by human feedback. It also knows about learning styles and pedagogical models, selecting the best approach for the training material. It may not be perfect, but it’s getting close. You can of course find holes in the interpretation of facts, but the point is that AI engines such as this one are growing and training themselves all the time. They are getting better to the point that in 6 months’ time, the results we are seeing now will be primitive by comparison. The time to get used to working with an AI engine is no. I would also say that despite bad press, Google is coming back into this space with its engine Bard. They have been working a lot longer and buying up experts in this area for over 10 years now so I’d look into their offering with interest when it’s launched. Midjourney Midjourney is one of the most fun AI tools on the market at the moment. Midjourney is an image creation AI engine which has been trained on millions of images in a variety of styles and uses that knowledge to create images from scratch. Midjourney works through the Discord chat engine, simply add the Midjourney server and type an /imagine command, here you can see 4 examples it has given, these can be enlarged and utilised in elearning to create immersive environments in which you can place your training. There is no need for any design input, simply type in the description, desired aspect ratio etc and voila: an image is born! Midjourney has a gothic feel to it, if you don’t mind a bit of ‘drama’ in your images. If that’s not for you, then other image creation tools do exist (e.g. DALL-E from Open AI the people behind Chat GPT) but we have found Midjourney gives the most impressive results. Microsoft Power BI / Excel / Google Sheets It may surprise you to see these data analysis tools listed in an article about AI, but AI has been embedded in these systems for years. AI can be used to ask natural language questions about the data to get meaningful results. For instance, in Google Sheets hold down Shift + Ctrl + X and you will now see an Explore menu come up on the right-hand side of the screen. Use this to ask questions directly from the data; for example, what is the most popular category, or how many subcategories are there? It will also automatically create graphical views of the data. Learning Management Systems will increasingly move to adopt this method of analysis rather than putting the onus on the user to create data views and analyse reports. I believe you will see features like this in your LMS (as well as your connected Management Information Systems) very soon. Mykeyworder Mykeyworder is a handy tool for ‘reading’ images. The traditional view of image data is that the image itself is a blank slate; you would need a human to analyse the data and add a list of keywords to describe the image. AI – and specifically mykeyworder (www.mykeyworder.com/) – can automate this process. It has an easy-to-use API which can link to your application to bring meaning to your imagery. This will enable content curators to compile a list of imagery to be used for learning purposes and learners to search the same repository for appropriate content. D-id D-id (www.D-id.com) allows you to create video presenters from text or uploaded voice. Editors can upload the face of anyone and it will create a video character. The videos it creates are convincing, using lip synching technology with any pre-selected voice. The video can be downloaded and used in elearning or as stand-alone resources to add personalisation to learning content. Other Tools I have previewed my favourite AI tools, but there are plenty more which we are using on a daily basis to shape the Edtech systems and