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.