Introduction

In the ever-evolving landscape of K-12 education, the powerful convergence of Artificial Intelligence (AI) and multimedia is reshaping the way students and educators interact with educational content. This chapter explores the transformative potential of AI in crafting innovative and personalized learning experiences through multimedia resources. From interactive simulations that engage students in practical experimentation to personalized learning programs tailored to individual needs, AI is redefining the future of K-12 education.

Simultaneously, the field of AI is undergoing rapid development, especially in the realm of multimedia learning materials. AI serves as the driving force behind personalized and highly effective learning resources, offering features such as intelligent tutoring systems that provide real-time feedback. However, the integration of AI in education comes with its set of challenges and ethical considerations, necessitating responsible oversight to prevent biases and discrimination.

Understanding multimedia learning delves into core concepts like meaningful learning and cognitive load. Learning, as a transformative process defined by experts like Paul Kirschner and John Sweller, emphasizes long-term memory changes. Meaningful learning, intricately tied to cognitive processes described by Mayer, involves integrating words and images for a deeper understanding. The Cognitive Theory of Multimedia Learning (CTML), developed by John Sweller, becomes pivotal in managing cognitive load effectively, laying the foundation for exploring multimedia learning.

As we navigate the landscape of AI-driven multimedia learning materials, it becomes clear that responsible implementation is paramount. This transformative force holds the potential to reshape the creation and dissemination of educational content, fostering engagement, customization, and effectiveness. Through AI, we have the opportunity to craft learning experiences that cater to the diverse needs and aspirations of every student, setting the stage for a dynamic and effective future in K-12 education.

Learning & Meaningful Learning

To know what multimedia learning is, it is important to know what learning is. The quote from the work of Paul Kirschner, John Sweller, and Richard E. Clark, who are renowned figures in the field of educational psychology proposes that “Learning is a change in long-term memory” (Kirschner, Sweller, & Clark, 2016). Learning involves acquiring new knowledge, skills, behaviors, or attitudes, often resulting in a long-term memory change. This change can include the formation of new memory traces or the strengthening of existing ones, leading to a lasting impact on how we perceive and interact with the world. If nothing has changed in long-term memory then it is believed that nothing has been learned. 

According to Mayer (2010a), meaningful learning from words and images occurs when a learner carries out the following five cognitive processes:  1. selecting relevant words for processing in verbal working memory 2. selecting relevant images for processing in visual working memory 3. organizing selected words into a verbal model 4. organizing selected images into a pictorial model 5. integrating the verbal and pictorial representations with each other and with prior knowledge. 

Meaningful learning and multimedia learning are closely related, as multimedia can be a powerful tool to facilitate meaningful learning experiences. The integration of multimedia elements, such as text, images, audio, video, and interactive components, can enhance the overall learning process by appealing to various senses and cognitive processes. Multimedia lessons risk becoming useless if they don't give enough time for incubation. According to Hasler, Kersten, and Sweller (2007), this is another reason why learner control is crucial when utilizing animation in multimodal instruction.

Cognitive Load

“Learning is a change in long-term memory” is a fundamental concept in cognitive load theory. It aims to optimize learning by considering how information is processed and stored in our memory. In simple words, it is the capacity of a learner and the need to think of the amount of learning material a learner can process at one moment. The theory was developed by John Sweller and his colleagues, and it highlights the limitations of working memory in handling information. In one of the guest interview with Paul Kirschner stated that cognitive load theory says when you're teaching, when you want to have students learn, you have to make sure that what they need to carry out the task is lower than what they actually have to carry out the task. 

Link for the full interview with Paul Kirschner

Relation between Meaningful Learning and Cognitive Load:

Working memory is a component of short-term memory that has a very limited capacity. A human brain can process a short amount of information at one time. To address this limitation, the only solution is to effectively manage the cognitive load to avoid overloading working memory. To enhance learning efficiency, instructional materials should be designed to optimize learning efficiency by managing cognitive load effectively. 

This is why cognitive load theory was introduced as a foundation for understanding how individuals remember information better through the use of schemas, which are organized chunks of information. According to this theory, the difference between an expert and a novice is not necessarily intelligence or extensive study but the development of effective schemas. The theory was developed by John Sweller and his colleagues. There are three different types of cognitive load : intrinsic, extraneous, and germane. 

Intrinsic Cognitive Load: if a task is very complex then it is called that the task is intrinsically loading.  If a task is very demanding, individuals need to put a lot of effort into understanding it. This effort is associated with intrinsic cognitive load.

Extraneous Cognitive Load: It is related to irrelevant information or poorly designed instructional materials. Generally, if information is poorly presented, it minimizes the chance to learn. Limiting the amount of information included to that which is essential to the learning process is the easiest method to reduce extraneous cognitive load. 

Germane Cognitive Load: Germane cognitive load is associated with the relevance of the task and the cognitive capacities needed to handle it. It presents information in a manner that supports the development of expert-level schemas, contributing to deeper understanding and long-term retention.

Multimedia Learning: 

Multi means multiple technical equipment. Multimedia refers to the integration of multiple technical equipment and various forms of representation, such as texts, videos, and communication channels. The presentation of information in multiple modalities caters to the limited capacity of working memory and aims to facilitate the transition of information from sensory memory to long-term memory through effective processing and integration. The integration of modern technologies such as artificial intelligence enhances the interactive nature of multimedia. 

The Cognitive Theory of Multimedia Learning (CTML), as described by Mayer, provides a framework for understanding how people learn from multimedia presentations. In the context of multimedia learning, the theory addresses how information is processed when presented through multiple modalities, such as text and images. In multimedia learning, sensory memory briefly holds visual and auditory information. Working memory, according to CTML, is the cognitive structure where conscious processing of information takes place. A well-designed multimedia should consider the cognitive processes involved in sensory memory, working memory, and long-term memory. 

Cognitive Theory of Multimedia Learning and Principles

Richard E. Mayer and other cognitive researchers' work popularized the cognitive theory of multimodal learning. Richard E. Mayer asserted that words and pictures teach people more than words alone (Mayer 2005a). According to multimedia researchers, multimedia is often defined as text and images. They also assert that learning takes place through the creation of mental representations based on both words and pictures. (Mayer, 2005b). To maximize learning effectiveness, multimedia instructional design attempts to use cognitive research to combine words and pictures.

The cognitive multimedia theory guides the creation of effective multimedia learning materials based on the overall 12 principles generated from almost 100 experiments conducted over the last 20 years. The Mayer’s Principle of Multimedia Learning are: Coherence Principle, Signaling Principle ,Redundancy Principle, Spatial Contiguity Principle, Temporal Contiguity Principle, Segmenting Principle, Pre-training Principle, Modality Principle, Multimedia Principle, Personalization Principle, Voice Principle, Image Principle.

1. Coherence Principle – “People learn better when extraneous material is excluded rather than included.” (Mayer, 2009, p. 89)

The goal of this principle is to reduce unnecessary processing. Decorative content or pictures should be excluded as it will derive attention from the lesson. The goal should be focused on learning materials avoiding talking heads, decorative pictures, fancy backgrounds and background music so that learners can focus on essential information without unnecessary distractions.

2. Signaling Principle – “People learn better when cues that highlight the organization of the essential material are added.” (Mayer, 2009, p. 108)

For example use arrows, circles, lists, bold key words, provide learning organizers (e.g. Module overview)

3. Redundancy Principle – “People learn better from graphics and narration than some graphics, narration, and printed text.” (Mayer, 2009, p. 118)

The key takeaway of this principle is to avoid narrating text that is on-screen. Instead, use text and images that support learning rather than duplicating the lecture to prevent cognitive overload.

4. Spatial Contiguity Principle – “Students learn better when corresponding words and pictures are presented near rather than far from each other on the page or screen.” (Mayer, 2009, p. 135)

For the implementation of this principle, place text near relevant graphics, provide feedback close to questions, and integrate directions on the same screen as activities.

5. Temporal Contiguity Principle – “Students learn better when corresponding words and pictures are presented simultaneously rather than successively.” (Mayer, 2009, p. 153)

Narration and corresponding visuals should be presented simultaneously. Time narration to align with animations for optimal learning.

6. Segmenting Principle – ”People learn better when a multimedia lesson is presented in user-paced segments rather than as a continuous unit” (Mayer, 2009, p. 175)

It breaks content into user-paced segments for better learning. This principle provides information in small chunks and enables learners to stop, pause, replay, rewind, etc.

7. Pre-training Principle –“People learn more deeply from a multimedia message when they know the names and characteristics of the main concepts.”(Mayer, 2009, p. 189)

It’s always easier to learn when you already know something about the topic. By using diagnostic assessments to gauge learners' existing knowledge, and providing comprehensive module overviews outlining key topics, including glossary terms that follow.

8. Modality Principle – “People learn more deeply from pictures and spoken words than from pictures and printed words.” (Mayer, 2009, p. 200)

Uses narration with graphics instead of on-screen text. During narrated presentations, avoid on-screen text unless necessary for clarity.

9. Multimedia Principle – “People learn better from words and pictures than from words alone.” (Mayer, 2009, p. 200)

Combination of words and pictures for improved learning, including relevant images that enhance understanding without exceeding cognitive load.

10. Personalization Principle – “People learn better from multimedia presentations when words are in conversational style rather than formal style. (Mayer, 2009, p. 242)

It’s easier to learn when the information is presented in a conversational style than in a formal style. It utilizes contractions, first-person language, and a conversational style.

11. Voice Principle – “People learn better when narration is spoken in a human voice rather than in a machine voice.” (Mayer, 2009, p. 242)

Human narration is more effective than computer-generated voices. Always choose human narration over machine-generated voice for multimedia presentations.

12. Image Principle – “People do not necessarily learn better when the speaker’s image is added to the screen.” (Mayer, 2009, p. 200)

Consider excluding the instructor's image unless it adds value to specific situations.

AI Tools for Educators to Create Multimedia Learning Materials for K-12: Sensory Modalities

Finding ideal visual materials for learning, including pictures, infographics, job aids, and other images are nothing but a work of hassle. It often takes more time to find the right materials rather than generating ideas or lesson plans in mind. But with technologies continuing to evolve, creating learning materials has been made a walk in the park. Especially for educators of k-12, where they need to think of creative manners to teach students every other day, artificial intelligence works like a boon. AI offers a myriad of opportunities for educators to enhance their teaching methods and engage students. It empowers educators with innovative tools and strategies. 

Following the Cognitive Theory of Multimedia Learning (CTML), the three sensory approaches to creating multimedia materials are given below:

Image Creator Tools 

We often find it hard to express our feelings to others. It creates barriers in communicating or delivering our messages. When it comes to education, this shyness and failure to express our imagination or vision to students stands up as a barrier between learning and students. Words and pictures teach people more than words alone (Mayer 2005a). In this regard, images generated by artificial intelligence come in. 

Image-generative AI tools are a type of artificial intelligence (AI) that can be used to create images trained on a large dataset of images. Using right prompt or prompt engineering both students and educators can generate AI images. 

1. DALL·E 2 by OpenAI: This tool creates original, realistic images and art from a text description. It can combine concepts, attributes, and styles, expanding images beyond the original canvas. DALL·E 2 is capable of making realistic edits to existing images based on natural language captions, considering shadows, reflections, and textures.

2. Midjourney: A generative art tool and community that generates photorealistic images from text input. It can recreate artistic versions from originals and insert objects into images, considering lighting and shadow conditions.

3. NightCafeLinks: A growing AI art-generator tool/community that can generate images from text descriptions. It offers various styles such as oil painting, watercolor, and sketch.

4. Bing Image Creator: This free tool, based on DALL-E and requiring the Microsoft Edge Browser, generates images from text descriptions.

5. DreamStudio (Stable Diffusion): A generative art tool providing customization and control of AI images. It can generate images in styles like oil painting, watercolor, and sketch.

6. Firefly (Photoshop): An AI tool that integrates AI-generated images into photos, offering various styles such as oil painting, watercolor, and sketch.

7. Generative AI by Getty Images: An AI tool generating usable, commercially safe images in styles like abstract, conceptual, and editorial.

Example Prompt 1: Children’s book illustration: no sunrise, village, farm, harvesting Time: capturing the sadness of fail crops due to no sunlight

Purpose: To create a visually evocative illustration for a children's book that communicates the theme of agricultural challenges and conveys emotions related to crop failure.

Example Prompt 2: A futuristic cityscape with flying cars and skyscrapers. The city should be bustling with activity, and the sky should be a vibrant shade of orange. The image should be in a landscape orientation and have a resolution of 1920x1080 pixels.

Purpose: To visualize and represent a vivid and bustling futuristic city, emphasizing the concept of advanced technology and urban activity. 

Enhancing Educational Visuals with Multimedia Learning Principles:

The principles of multimedia learning serve as invaluable guidelines in harnessing the full potential of image generative AI tools. Adhering to the coherence principle, these tools can exclude extraneous details, ensuring a clear focus on essential information. The signaling principle is supported through the incorporation of visual cues and highlights in generated images, enhancing the organization of crucial material. By generating visuals without unnecessary printed text, these tools align with the redundancy principle. Spatial and temporal contiguity principles are addressed by placing relevant text and graphics near each other and synchronizing them simultaneously in the generated images. The segmenting principle is upheld by breaking down content into visually segmented parts, promoting user-paced learning. Additionally, the multimedia and personalization principles are embraced, combining text prompts with visually appealing images in a conversational style, fostering an engaging and effective learning experience.

Audiovisual generative AI tools

Audiovisual generative AI tools are a type of artificial intelligence (AI) that can create new audio and visual content from scratch. These tools use large datasets of existing audio and visual data to learn how to generate new content that is similar to the data they were trained on.

When creating AI generative videos, it is crucial to follow key principles for optimal educational impact. These include incorporating dynamic drawing, gaze guidance, and generative activities to engage users actively. Utilizing a first-person perspective and subtitles in the learner's second language can enhance understanding while avoiding seductive details and ensuring focus on relevant content. Adhering to these principles enhances the effectiveness of AI generative videos, promoting an immersive and educational experience for users (Mayer et al., 2020).

1. Sketch Animation: This is a free web tool that allows you to animate a drawing without requiring any registration. You can draw anything you like and then watch it come to life as an animation.

2. Resemble AI: This is a voice generator that can create realistic human-like voices. You can use it to generate voiceovers for videos, podcasts, and other audio content.

3. D-ID: This tool can animate photos into interactive video avatars. It uses AI to create photorealistic videos by combining premium presenters or images and text at the click of a button.

4. Descript: This is a powerful video editor where edits can be made via text. You can use it to edit videos, podcasts, and other audio content.

5. Recut: This is an AI tool that removes pauses from video and audio. It can help you create more engaging content by removing dead air and other unwanted pauses.

6. Kaiber: This is a video generator that creates videos from text prompts. You can use it to create outstanding visuals through image or text descriptions. Additionally, the Kaiber site features various styles, such as anime, impressionism, and conceptual art.

7. Astria: This tool can be trained based on image uploads. It uses AI to create interactive video avatars that can be used for a variety of purposes.

8. Elai.io: This is an AI video generator with avatar animation. You can transform a PowerPoint presentation into a captivating video using unique avatars, dynamic animations, and multiple languages and voices.

9. Pictory: This is an AI video generator that creates short and easily shareable branded videos. It gives you a feel of filming something new by consistently synthesizing new videos using an image or text prompt with higher accuracy.

Prompt: How Educators Can Create Videos Using AI Step By Step Tutorial

Applying Multimedia Principles to Audiovisual Generative AI Tools:

The application of multimedia principles is instrumental in harnessing the potential of Audiovisual generative AI tools for optimal educational impact. Key principles include incorporating dynamic drawing, gaze guidance, and generative activities to actively engage users in AI generative videos. Utilizing a first-person perspective and subtitles in the learner's second language enhances understanding and maintains focus on relevant content, avoiding seductive details. Adhering to these principles ensures an immersive and educational experience when creating AI generative videos. 

Audio Creator Tools

As described by Richard E. Mayer, When learning materials involve texts and pictures, typically processed visually, there is a risk of overload. To address this, the modality principle suggests presenting visual information to the eyes while delivering text in auditory form. Audio-visual conditions led to an intermediate reaction time, suggesting a more balanced cognitive load and improved responsiveness compared to visual-only conditions.

The advancement of artificial intelligence has opened a new door for effective multimedia learning by creating AI-generated audio. These AI tools turn text into speech using text-to-tools (TTS) sounding exactly like a human voice. To deliver educational content to students, podcasting AI tools can be very effective. Furthermore, podcasts offer enhanced accessibility compared to written resources, allowing learning during various activities. Their distinct advantage lies in fostering discussions, critical thinking, and encouraging unconventional perspectives.

1. Audiosonic by Writesonic: Transformative AI voice generator crafting realistic, human-like voices for diverse content creation, from marketing to podcasts.

2. Murf.AI: Popular AI voice generator with customizable features, offering ultra-realistic voices for podcasts, videos, and professional presentations.

3. Speechify: The advanced platform can turn PDFs, docs, ebooks, or emails into audio that anyone can listen to instead of reading.

4. LOVO: An AI voice generator that can help you generate hyper-realistic and engaging AI voices to captivate audience. 

5. Spotify: It allows podcasters create, host, distribute, and connect with their audience free of cost.

Example:

Revolutionizing-Learning-Content-Harnessing-AI-for-Customized-Image-Generation-in-eLearning-e2dnje6

Applying Multimedia Principles with Audio Creator AI Tools:

Multimedia principles play a crucial role in leveraging Audio Creator AI tools effectively for enhanced learning experiences. Following Richard E. Mayer's insights, the modality principle addresses the risk of visual overload by suggesting the presentation of visual information to the eyes while delivering text in auditory form. This approach creates a more balanced cognitive load and improved responsiveness compared to visual-only conditions. By incorporating the modality principle, educators can optimize the use of AI-generated audio to create engaging and accessible learning materials for students across various activities.

Prompt Design and Engineering:

To generate an image, a video, or an audio, the model will ask for prompts to generate the desired output. A clear constructed prompt will help to get a better understanding and result. Prompt Engineering is an ongoing process of refining and optimizing the original prompt design.

To improve the performance and output quality of the language model, experimenting with different prompts, adding context, customizing instructions, or providing additional hints helps control the model's behavior for better results.

Interview of an Educator on using AI

In this section, I share insights from my interview with Habibun Nahar Bithi, a lecturer at Uttara University in Dhaka, Bangladesh. Habibun Nahar has excelled academically, holding top honors in both her BBA and MBA with a specialization in HRM. As a contractual lecturer at BGC Trust University and currently teaching Management at Uttara University, she brings a wealth of HRM expertise to her role. 

The reason I chose Habibun Nahar for this interview is due to her unique perspective as an individual who transitioned from being a student in a traditional educational setting, devoid of AI, to becoming an educator during the AI revolution. Her personal journey provides valuable insights into the transformative impact of AI in education, having experienced both sides of the educational spectrum.

Our conversation delves into the intersection of education, technology, and AI, specifically focusing on its role in creating effective multimedia for students. Through this interview, we aim to uncover valuable perspectives on how AI is transforming the educational landscape and enhancing the learning experience.

https://podcasters.spotify.com/pod/show/sanjida-rahman0/episodes/Interview-with-a-guest-e2dukr0

Common Challenges in Integrating AI in K-12 Education

In the world of AI where nothing can stop educators and students from acquiring and sharing knowledge, subscriptions become the biggest obstacle. The freemium and premium versions of these AI tools will create inequality. The authenticity, artistic process, and copyright of these generated images pose questions of the teacher's credibility. The future of work for learning can be made easier and more productive with proper preparation and consideration of the moral use of AI-generated images. Also, due to the fluctuating nature of working memory, the future of AI is challenging.

AI-generated audio-visuals create questions about authenticity, artistic process, and copyright. They can also raise problems of fake news, misinformation, and disinformation. A robust and informed societal debate is needed on how to regulate AI to prevent misuse and harmful output. Another concern in educational settings is the freemium/premium nature of most AI tools, which may create equity issues. 

Conclusion

In conclusion, the journey through the intricacies of multimedia learning reveals a landscape where the effective integration of various modalities, guided by the principles of CTML, can significantly enhance the learning experience. The principles such as coherence, signaling, redundancy, spatial and temporal contiguity, segmenting, pre-training, modality, multimedia, personalization, voice, and image, provide a roadmap for designing multimedia materials that align with cognitive processes and promote optimal learning outcomes. As we embrace the role of artificial intelligence in education, particularly in creating multimedia learning materials, it's essential to acknowledge the transformative potential it holds. However, this transformative power comes with challenges, including issues of authenticity, equity, and ethical considerations that demand thoughtful navigation. The future of AI in education rests not only on technological advancements but on our ability to address these challenges responsibly and inclusively.

References:

Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: An analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41, 75-86.

Mayer, R. E. (2009). Multimedia learning (2nd ed.). Cambridge, England: Cambridge University Press.

Sorden, S. D. (2012). The cognitive theory of multimedia learning. In Handbook of Educational Theories. Charlotte, NC: Information Age Publishing. Retrieved from http://sorden.com/portfolio/sorden_draft_multimedia2012.pdf

Swindell, A., & Wright, J. (2022). Historical, contemporary, and future issues on the nexus of globalisation, human rights, and education. In Globalisation, Comparative Education and Policy Research: Discourses of Globalisation, Ideology, and Human Rights (pp. 29-51). Springer International Publishing. https://doi.org/10.1007/978-3-030-90590-3_3

Mayer, R. E., Fiorella, L., & Stull, A. (2020). Five ways to increase the effectiveness of instructional video. Association for Educational Communications and Technology.

Padlet Board:

Link for Padlet Board

Utilization of Artificial Intelligence Tools in Crafting this Chapter

1. https://openai.com/dall-e-2
2. https://www.bing.com/images/create
3. https://pictory.ai/
4. https://podcasters.spotify.com/
5. https://chat.openai.com/
6. https://padlet.com/