U6 Assignment: Inclusive Learning Design Reflection

 

Figure 1. Accessible and Inclusive Learning in Scene. [AI-generated image, Microsoft Copilot, 2025]

    The image depicts diverse individuals using a digital interface: someone with a screen reader, a guide dog user, a wheelchair user, and a signer.  The interface adapts to each user’s needs with tactile, audio, and visual feedback.

My Evolving Perspectives on Accessible and Inclusive Design

Initially, I had a hazy understanding of accessible and inclusive digital learning; however, each module solidified my grasp of key concepts, pedagogical approaches, and assistive technologies that foster equitable learning opportunities. Through this course, I gained a fundamental understanding of designing accessible online learning environments catering to diverse learners, with a particular focus on learners with disabilities.  My ability to develop inclusive online courses was significantly improved, and my knowledge of technology’s role in creating accessible learning materials was substantially broadened. The course also prompted me to analyse Ethiopian educational guidelines for inclusivity.

This coursework integrated concepts and principles from previous LDT courses to facilitate the design of accessible and inclusive digital learning materials, specifically applying CARP principles and cognitive load theory. I used associative tools, including accessibility audits, to assess these materials.  Creating engaging materials for diverse learners required an iterative instructional design process, grounded in pedagogical principles.

Applying UDL and WCAG principles and incorporating varied media (text, visuals, video, and audio) have enhanced my ability to assess learning, integrate technology effectively, and critically reflect on my teaching. This experience has solidified my identity as a math educator at the forefront of math education and technology, poised to significantly contribute to the field of learning design.

Lessons from Design Choice Challenges

Integrating multimedia components, specifically visual and audio-visual elements, presented the most significant challenges across Units 3 through 4. The undertaking demanded both technical and artistic proficiency, coupled with meticulous attention to design principles emphasising clarity, relevance, and accessibility. The assignments required critical thinking and understanding of the diverse needs of learners. Despite these challenges, I gained insights into assistive technologies, such as captioning software and screen reader-friendly formats, which enhanced my technical skills and understanding of accessible and inclusive education.

Applying Principles of Accessible and Inclusive Design

My course material preparation and production will be completely guided by anchoring to the UDL framework and POUR principles (Perceivable, Operable, Understandable, Robust). I prioritized diverse representational (text, audio, visuals), action and expression (demonstrating understanding), and engagement methods, moving beyond simple information delivery.  Assignments, for example, helped me realize the importance of presenting content in multiple formats (text, visual, audio).  Cultural sensitivity prompted careful consideration of underlying assumptions in examples and content; I will use inclusive language, diverse viewpoints, and culturally relevant scenarios and imagery. 

My future practice will fully integrate inclusive design, starting with upfront planning, not just accessibility retrofits.  This includes staying current on research and best practices, continuously self-assessing, and advocating for inclusive design within my teams and organisation.  Ultimately, my designs prioritise diverse learner needs and experiences. Overall, this course offered a transformative perspective, enhancing my professional development through challenging design assignments promoting balanced, multimodal content presentation.

Lessons from Empathy Challenges

 

The diverse empathy challenge scenarios presented in the course broadened my understanding of student viewpoints, consequently informing my methodology for creating effective online learning resources. The profound impact of the module’s empathy exercises, which simulated colour blindness, dyslexia, hearing loss, and visual impairments, stemmed from their ability to illustrate the frustration and exclusion experienced due to poor design accessibility. 

My empathy for learners with varying needs has been significantly enhanced by these immersive experiences, highlighting the vital importance of inclusive design in the digital learning environment. Therefore, I am now more committed than ever to developing accessible and empowering online learning environments for all learners.

Lesson from Peer Feedback

Through peer feedback on my discussion post, I was able to refine my reflections and questions, strengthening aspects not fully developed in my initial submission. My progress has resulted in the design of course materials promoting accessible and inclusive design principles via collaboration.

Insights from Generative AI Integration

 Generative AI tools like ChatGPT and Microsoft Copilot have proven to be indispensable resources in the conceptualisation and modification of content for various purposes. Specifically, during my unfamiliarity with assistive technologies, I received valuable instruction on adapting and improving my course materials. I also found that generative AI tools function as collaborators in online learning development.  When I encountered limitations in realising my ideas, assistance was provided in reforming my thought processes.   

Accessibility and Inclusive Practice in Action

 

My learning design and technology studies have significantly broadened my pedagogical skills and knowledge of instructional design and technology in education, particularly mathematics education.  This has profoundly impacted my professional development and future aspirations.  All the LDT coursework has provided a strong foundation in instructional models, theories, and the role of technology in creating inclusive and accessible learning materials.

 I now prioritise a multimodal approach to online course design, beginning with empathy-driven challenges to ensure inclusivity and accessibility.  This translates to a culturally responsive approach to creating effective online learning environments that cater to diverse learner needs. This experience has solidified my identity as a math educator at the forefront of math education and technology, poised to significantly contribute to the field of learning design.

My professional development plan focuses on designing an online mathematics course within the next six to twelve months, utilising key frameworks and concepts. This plan incorporates personal experiences and insights from recent coursework and will extend to curriculum design and educational policy within higher education and teacher training. This journey has reinforced my commitment to lifelong learning and providing exceptional online education. I am eager to further my teaching career and make substantial contributions to the fields of technology and learning design.

Initiating with a foundation of inclusion and empathy

 

Aspiring accessible digital learning designers should prioritise these initial steps: Cultivate empathy, actively understanding and sharing the struggles of others.  Simulating disabilities (colour blindness, hearing loss, etc.) helps highlight often-overlooked accessibility barriers.  Empathy should guide all design choices.  Secondly, understand Universal Design for Learning (UDL) and Web Content Accessibility Guidelines (WCAG) principles. These frameworks ensure online materials meet accessibility standards and improve overall quality.  Finally, inclusive design demands collaboration.  Iterative feedback from peers and experts is crucial.  Adapt multimodal content presentation (text, images, audio/video) to cater to diverse learner needs.

The Future of Online and Blended Learning: The Next 10 Years

 

Emerging Trends in online and blended Learning in developing countries

 

Online and blended learning will rapidly grow and evolve, despite predicted challenges.  These modalities are crucial for improving education in developing countries. Significant challenges remain unreliable internet and electricity, limited digital literacy among teachers and students, high device and data costs, and resistance to change within traditional systems. The digital divide is a big challenge. Developed countries and tech innovators need to collaborate to help nations with poor ICT infrastructures.

Mobile learning is a key trend, with smartphones offering more accessible and affordable education than computers. This expands educational access via mobile-friendly platforms and apps, ideally incorporating offline functionality and low data usage for areas with poor infrastructure.  Blended learning, combining face-to-face interaction with technology, will likely surpass fully online learning due to the value of in-person communication and the high costs and accessibility challenges of purely online education across diverse urban, suburban, and rural settings.  Another trend is educational localization, driven by online and blended learning’s growth. This involves translating courses into local languages and incorporating culturally relevant content, leading to more culturally sensitive curricula.

Future online and blended learning environments will feature multimodal materials, interactive and virtual elements.  These flexible, adaptable environments will cater to diverse learning styles and paces, fostering learner autonomy.

The widespread adoption of online and blended learning necessitates addressing the digital divide to guarantee fair and inclusive access to technology and internet connectivity.  It is imperative that teachers receive continuous professional development to advance their digital literacy and expertise in designing and implementing effective online course design and creation using technology. Future investments in educational technology infrastructure and teacher training will rise.  Policies promoting digital inclusion and public-private partnerships in education are also anticipated. To ensure student engagement in online learning, it also necessitates consistent implementation of technologically advanced and innovative teaching methods.

Application of Generative AI in the future online and blended learning

Generative AI promises to revolutionize online, blended, and microlearning by boosting learner autonomy, personalization, accessibility, and inclusivity.  It streamlines content creation, improves quality assurance, efficiently tracks progress and provides personalized feedback, and supports diverse, multi-format learning materials. Immersive technologies like VR and AR, combined with generative AI, can integrate indigenous knowledge into existing curricula.  This transformative potential will reshape how we design and deliver education. Generative AI offers powerful tools for learning design, creating engaging and practical resources, automating tasks, and personalizing learning experiences.  It allows for optimized learning processes, individualized learning paths, and effective assessment.  Furthermore, generative AI fosters better collaboration between educators, students, and instructional designers.

Summary and Conclusion

 Online and blended learning are set to grow quickly, despite challenges like unstable internet, low digital skills, high device costs, and resistance to change. A key trend is mobile learning, which makes education accessible and affordable through smartphones. Blended learning, combining technology with face-to-face interaction, is expected to surpass fully online education due to its benefits for personal communication. Another trend is educational localization. This means adding culturally relevant content and translating courses into local languages. Future online and blended learning will include multimodal resources and interactive elements. These features will promote learner independence and 21st-century skills. Generative AI is also expected to transform blended and online learning by enhancing personalization, accessibility, and inclusivity.

 

References

·       Boumalek, K., Mezouary, A., Hmedna, B., & Bakki, A. (2024). Transforming Microlearning with Generative AI: Current Advances and Future Challenges. In: General Aspects of Applying Generative AI in Higher Education.

·       Giannakos et al. (2024). The promise and challenges of generative AI in education. Behaviour and Information Technology, 1–27.

·       UNESCO (2022). Reimagining our futures together: A new social contract for education.

·       World Bank (2020). The COVID-19 Pandemic: Shocks to Education and Policy Responses

U2: Assignment- WOL: Defining Online and Blended Learning

 

This assignment requires presenting a reflective discussion of my perception and experiences with online and blended learning, guided by three key questions:

A. How do you perceive online and blended learning environments?

Both blended and online learning modalities have recently emerged due to technological innovation, transforming traditional education into flexible, adaptable, personalized, inclusive, and equitable learning environments. Face-to-face learning occurs in a physical setting where students are seated and the teacher provides lectures or activities. Online learning is fully virtual with no physical interaction. Online courses benefit students by eliminating the requirement for physical attendance on campus. Blended learning combines both in-person and online components to deliver effective, efficient, and flexible learning experiences. It goes beyond simply transferring in-person (onsite) activities to online platforms. Blended courses can be structured in a sequential or interwoven manner, depending on the institution’s approach and orientation. Blended course designers must balance synchronous and asynchronous interactions and integrate appropriate technologies to optimize the blended learning environment.

I view online and blended learning as innovative approaches that accommodate diverse learner needs, providing flexible, adaptive, personalized, inclusive, and equitable opportunities. However, implementing these modalities requires basic ICT infrastructure, digital skills, policy guidance, support, significant investment, and institutional readiness. Blended learning, positioned between these two ends of the spectrum, merges face-to-face and online experiences to offer effective, efficient, and flexible learning.

 Blended learning is a mix of at least two of asynchronous online, real-time (synchronous) online, or onsite learning. This flexible model allows for a balanced integration of digital and face-to-face interactions, enhancing learning experiences. When enacted effectively and efficiently, the blending of these two methods complements one another, fostering real-time engagement and deeper interaction among learners.

A spectrum of technology-enhanced teaching or learning (“Freebook”, p. 10)

B.    What is the significance of online and blended learning, and what are its respective advantages and disadvantages?

Online and blended learning environments enhance lifelong learning, accommodate different learning paces, and enable institutions to offer diverse courses beyond geographical constraints. Online and blended learning environments offer flexibility and convenience, personalized learning, cost-effectiveness, and access to diverse resources. However, they also have disadvantages like limited social interaction and technological challenges.

C.    How can online or blended learning effectively address the diverse needs of students?

Online and blended learning should be designed to promote diversity and participation by incorporating differentiated instruction, accessibility strategies, scaffolded learning opportunities, collaboration platforms, and support systems. These strategies accommodate various diverse learning needs, guided by instructional design principles such as principles of universal design, and offer structured guidance through adaptive technologies and formative assessments. Efforts should be made to get students prepared for online learning preferences and communications. The rise of online and blended learning necessitates improved data analysis methods for improved access and learning outcome, facilitated by newer emerging technological tools, enabling diverse audience access to crucial information.

References:

1.     Vai, M., & Sosulski, K. (2015). Essentials Of Online Course Design. In Routledge Ebooks.

2. .   “Freebook” (n.d.).  Online and Blended Learning: Selections from The Field

Introduction to Learning Engineering: What is Learning Engineering?

 

What is Learning Engineering?  

Herbert Simon, a Carnegie Institute of Technology professor, was credited as the first to introduce the term “learning engineering” in his essay entitled “The Job of College President” aimed at enhancing institutional management and operations (Lee, 2023). The International Consortium for Innovation and Collaboration in Learning Engineering (ICICLE) defined learning engineering is a process and practice that applies the learning sciences, using human-centered engineering design methodologies and data-informed decision-making to support learners and learning (Goodell & Kolodner, 2023). This definition indicates that learning engineering employs tools and methodologies that are a combination of learning sciences research, engineering approaches, and data-driven decision-making, with a focus on using these disciplines to transform education.

Learning engineering as a transdisciplinary field

Learning engineering is a transdisciplinary field that uses learning science principles to create engaging, dynamic experiences, integrating psychology, neurology, education, engineering, and design to address learners’ challenges. In other words, learning engineering is a broad field that includes learning science, design, data science, and technology. Learning engineering is emerging as a professional discipline that combines software engineering, development knowledge, learning science, design thinking, and pedagogy to foster learner growth through human-centered design and data-driven decision-making. Learning engineering includes software development, human-computer interface design, artificial intelligence, intelligent tutoring systems, and data science. It involves a collaborative effort among specialists from various fields, including teaching, software engineering, instructional design, learning science, and data science to develop data-driven learning approach (Dede, Richards, & Saxberg, 2019).

Goals of learning engineering

Learning engineering is a rapidly evolving field that combines education, data science, and engineering to create effective, scalable learning experiences. The traditional era of education is being transformed into digitalized education as a result of emerging technologies and data-driven new perspectives. The evolution of learning engineering has been a major breakthrough in education. Learning engineering uses big data to improve learning experiences by combining learning analytics and educational data mining to understand student learning, optimal instructional tactics, and valid evidence on learners’ mastery of goals (Dede, Richards, & Saxberg, 2019). Learning engineering is a practical methodology that aims to improve the design, implementation, and assessment of learning systems and experiences through the use of empirical data and rigorous analysis. It uses data-driven, iterative techniques that aid in the continuous refinement and improvement of structured and effective learning experiences based on recurrent data collection and analysis results.

Learning engineering is the art of optimizing learning and decision-making using data analytics, computer-human interaction, modeling, measurement, instrumentation, and continuous improvement (Wagner, 2021). Learning engineering focuses on generating data-driven learning experiences that cater to learners and give learning solutions. Learning engineering optimizes learning solutions by understanding optimal conditions and learners, and developing robust, refined, and scalable alternatives (Dede, Richards, & Saxberg, 2019). Learning engineering comprises addressing challenges that extend beyond learning experience design, with a focus on identifying the underlying causes of issues influencing learners’ growth. Learning engineering can be regarded as a data-driven continuous iterative process that involves designing, redesigning, testing, redesigning, and improving learning conditions, starting with a problem associated with the learner or learning, ranging from small to large-scale projects, aiming to prepare students for challenging tasks, whereas traditional instructional design is a linear process that involves design, develop, and deliver, not initiated by evidence-based demand from learning or learner. 

Approaches used in learning engineering

Learning engineering is an innovative approach to education that emphasizes student-centered design and multidisciplinary team decision-making. It employs cognitive task analysis and item response theory to produce engaging, dynamic experiences that draw on psychology, neurology, education, engineering, and technology. It involves a human-centered approach, data collection, and analysis to observe performance and learner behaviors. The approach focuses on data-generating learning design, enhancing education through feedback systems and potential advancements like personalized learning, augmented reality, virtual reality, artificial intelligence, and machine learning. Learning engineering principles involve data-driven learning, continuous activity development, human-centered design, goal achievement, and appropriate technology use to optimize learning activities. It combines education, data science, and engineering to create effective, scalable learning experiences. It involves a human-centered approach, data collection, and analysis to observe performance and learner behaviors. Learning is a multifaceted issue, influenced by context and individual preferences. Addressing this challenge requires putting students at the center of education development, a crucial aspect of learning engineering.

Learning engineering improves content and systems for diverse learners by addressing complex factors through iterative, data-informed tactics, focusing on human-centered design and multidisciplinary team decision-making within education. Learning engineering is constantly evolving with new tools, design patterns, and AI components, reducing the distinction between work and learning, with AI agents potentially joining learning teams to collaborate (Craig et al., 2023). Learning engineering is enhancing education through generating data-driven learning experiences with feedback systems for students, teachers, designers, and the learning sciences community. This data-driven design tracks performance and growth, opening the path for potential advancements such as personalized learning, augmented/virtual reality, artificial intelligence, and machine learning (Craig et al., 2023).

Conclusion

Learning engineering is a transdisciplinary field that combines learning sciences research, engineering approaches, and data-driven decision-making to transform education. It focuses on creating engaging, dynamic experiences using software development, AI, and intelligent tutoring systems. The field uses cognitive task analysis and item response theory to create data-driven learning experiences, enhancing education through feedback systems and potential advancements like personalized learning, augmented reality, and machine learning.

 

References:

1.     Craig, S. D., Goodell, J., Czerwinski, E., Lis, J., & Roscoe, R. D. (2023). Learning Engineering Perspectives for Supporting Educational Systems. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 67(1), 304-309. https://doi.org/10.1177/21695067231192886

2.     Dede, C., Richards, J., & Saxberg, B. (2019). Learning engineering for online education theoretical contexts and design-based examples. Routledge.

3.     Goodell, J., & Kolodner, J. (2023). Learning engineering toolkit introduction: Evidence-based practices from the learning sciences, instructional design, and beyond. Routledge.

https://julianstodd.wordpress.com/2023/02/20/learning-engineering-workingoutloud-on-learning-science/

4.     Julianstodd (2023, February 20). Learning Engineering: WorkingOutLoud on Learning Science. Retrieved (October 9, 2024), from

5.     Lee, V.R. (2023). Learning sciences and learning engineering: A natural or artificial distinction?  Journal of the Learning Sciences, 32(2), pp. 288–304.

6.     Wagner, E. D.  (2021). Becoming a Learning Designer. Design for Learning: Principles, Processes, and Praxis.

Learning Design and Technology ⊗Mathematics Education

 

My experience with technology and its products such as the internet and computers began during an undergraduate ICT course that primarily focused on basic computer skills and their hardware and software components. Over the last two decades, I have realized how newly emerging technologies directly and continuously influence the dynamic of the education sphere.  Furthermore, my background in mathematics and mathematics education enables me to understand the impact of emerging technologies on education. My true interest in the integration of technology into education was revitalized during the COVID-19 pandemic crisis when the world was almost completely locked down. This was the tipping point for me to critically consider the ever-changing role and application of technology in all aspects of our daily lives. I then recognized and learned about the mandatory need to transition from in-person education to online education or a hybrid approach. My growing interest in technology drives me to study technology’s role in education and its potential as an educational investment for future generations, prompting me to enroll in the Learning Design and Technology Graduate Certificate Program at Arizona State University. I aim to attend required courses, work hard, and create a collaborative learning environment to pursue a career in learning design, technology, and mathematics education, promoting personalized and adaptive learning experiences.

Educational background and work experience

I’m Mekonnen Yimam, a senior faculty member in the Department of Mathematics at Haramaya University, is currently serving as an assistant professor in Mathematics Education. In 2022, I obtained my doctorate in Mathematics Education from Bahir Dar University. I received both my first degree (B.Ed. in Mathematics) and second degree (MSc in Mathematics) from Haramaya University in 2006 and 2011 respectively. Furthermore, in 2012, I completed a Postgraduate Diploma in Mathematical Sciences at AIMS, University of Stellenbosch, South Africa.

I began my professional career by joining the Department of Mathematics at Haramaya University as a graduate assistant in July 2006. Since then, I taught undergraduate and postgraduate mathematics, as well as mathematics education, and supervised, examined, and evaluated students’ essays and theses at Haramaya University, Ethiopia. I have been taking part in the university’s research and community service activities. For example, I consistently assisted in the administration of the Department’s annual mathematics Olympiad and training program, and I eagerly participated in various departmental activities assigned to me or initiated by myself, making significant contributions. I have published four articles on mathematics education in reputable journals. I also serve as the Mathematics department’s continuing education coordinator.

Professional skill sets

My research expertise in Mathematics Education has provided me with qualitative and quantitative research skills, as well as data processing and interpretation tools. My engagement in teamwork has helped me build collaborative, problem-solving, and critical thinking skills. Also, my critical reading of current research literature on technology integration in mathematics teaching and learning prompted me to discover more about the role of developing cutting-edge technologies in transformative education. I am then encouraged to pursue a profession in the field of Learning Design and Technology plus Mathematics Education, focusing on the intersection of emerging cutting-edges technologies and mathematics education. I will maximize my ability to contribute to the advancement of Learning Design and Technology to meet the demands of the Fourth Industrial Revolution and digital world.

Short term and long-term goals

 For innovative integration of technology in mathematics education, I will make every effort to gain a solid foundation in educational technology skills and knowledge. In the short term, my goal is to enhance my understanding of the theoretical foundations and instructional models that underpin the Learning Design and Technology, with a particular focus on technological innovations applicable in mathematics education that make mathematics more accessible and real to learners’ understanding and reasoning

Some specific short term goals include

·         Developing technology-integrated course materials in Higher education

·         Creating learning environments that embeds virtual and augmented reality technologies  

·          Designing innovative assessment strategies in mathematics

·         Implementing data-driven intervention programs for maths teachers professional development 

Over the next five years, I aim to become a recognized researcher and learning design specialist in innovative education, establish an online collaborative teacher professional development forum, and create inclusive virtual math classrooms.

Below are some of my long-term goals:

·         Creating collaborative groups of learning designers for innovative education

·         Creating virtual maths platform for maths teacher professional development  

·         Set up an online school academy  

 My theoretical understanding  

 My approach to Learning Design and Technology is informed by prominent learning theories, including cognitive learning, situated learning, and sociocultural learning perspectives. From a cognitive learning perspective, educational technologies, viewed as cognitive tools, aid learners in understanding abstract concepts and enhancing thinking and problem-solving through visualization, online platforms, and multiple knowledge representation techniques. From a social learning perspective, educational technologies serve as a medium for social interactions in which people share ideas and perspectives on various online platforms, resulting in the construction of a shared knowledge. In the process of constructing knowledge, technology serves as a bridge. Technology can be viewed as a scaffolding mechanism that provides learners with technology-based support for personalized learning within the zone of proximal development. By focusing my reading on the systematic design of instruction (Dick & Carey, 1990), I have gained an understanding of a systematic approach to instructional design that includes models and methods for developing instructional materials.

Future Contribution to the Field

·      Providing a foundation for Ethiopian national policy dialogue on the potential of innovative technologies in transforming education for full-scale digitization, establishing online collaborative professional development platforms, and promoting equitable and inclusive education for all. My specific future contributions include gender equality in technology-embedded STEM fields and accessible educational technology to remote areas and students living in rural areas.

By focusing on the intersection of emerging cutting-edge technologies and mathematics education, I hope to help advance the field of Learning Design and Technology in response to the demands of the Fourth Industrial Revolution generation and the digital transformation of education.