Non-degree Courses, Certificates, Masters Degrees and Doctorates
At a Glance
- What: Innovative approaches to learning, with a focus on e-learning and technology-mediated knowledge communities.
- Who: Professionals in a wide range of learning professions, or people wanting to make a career change into one of these areas, and subject matter experts who desire to incorporate learning sciences theory and practice into their professional repertoire:
- How: To enroll, visit the Learning Design and Leadership Program page at the College of Education website.
Contact
For further information, contact the LDL program and dissertation advisor, Dr Kara Francis <kstucki@illinois.edu>
Program Description
Learning Design and Leadership (LDL) addresses the theories and practices of learning in the context of digital media and learner diversity. Its focus is on innovative practices in a wide range of sites, including formal education from K-12 to higher education, workplace and community settings, and informal learning. The program offers an opportunity to learn how to design and implement purposeful, engaging learning environments, including the integration into the learning experience of new media, artificial intelligence, learning and assessment technologies. The program supports career advancement for current or aspiring teachers, college professors, instructional designers, learning resource developers, educational technology analysts, e-learning consultants, museum educators, and anyone with a personal or professional interest in the future of education.
Signature Ideas
Although learning is a pervasive phenomenon across many creatures in the natural world, education is a peculiarly human capacity to nurture learning in a conscious way, and to create social contexts that have been specially designed for that purpose: the institutions of education. Everyday learning happens naturally, everywhere, pervasively and all the time. Education – encompassing institutions, curricula and consciously formulated pedagogies – is what we have termed “Learning by Design.” There is a science to education, which adds method and reflexivity to the everyday processes of learning and the intuitive art of teaching. This science asks and attempts to answer fundamental and searching questions. How does learning happen in everyday as well as formal educational contexts? How do we design learning environments so they are most effective? Today, machine learning and artificial intelligence add new dimensions, at once exciting and troubling—to what extent and in what ways can machines support teachers and learners?
Education’s agendas are intellectually expansive and practically ambitious. It is learner-transformative, enabling productive workers, participating citizens and fulfilled persons. And it is world-transformative as we interrogate the human nature of learning and its role in imagining and enacting new ways of being human and living socially: shaping our identities; framing our ways of belonging; representing meanings in new ways and through new media; interacting with artificial intelligence constructed from machine learning processes; and creating participatory spaces where together we can collaborate to rebuild the world.
To stay connected with these ideas, please join our New Learning community in CGScholar, Bill Cope and Mary Kalantzis’ blog.
Multimodal Meanings
The program is informed by several key ideas. One key interest is educational media, and in particular the ways in which digital technologies for the representation and communication of knowledge have the potential to transform learning. This arises from a phenomenon in contemporary communications environments that we have called “Multiliteracies.” The program takes a carefully considered approach to the role of technology in learning. While rhetoric pointing to the transformational power of technology in education is widespread, relationships of learning and processes of knowing have often not fundamentally changed. Even when new technologies are introduced, the changes sometimes seem insignificant and the results disappointing. Nevertheless, these technologies do have enormous potentials, even if these are often only partly realized. How do we design and implement technologies in support of learning? And how do we prepare learners for success in a world that is increasingly dominated by digital information flows, and tools for interaction in the workplace, public spaces and personal life? We have explored these ideas in what we have called the “affordances of e-learning ecologies.”
Learner Diversity
Another key idea is learner diversity across a broad range of dimensions, material (social class, locale and family); corporeal (age, race, sex and sexuality, physical and mental abilities); and symbolic (language, ethnos, communities of commitment and gender). The challenge for education we have called, how to nurture a “productive diversity.” How do we differentiate learning so it addresses to the needs and interests of a diverse community of learners? How does education build up and transform identities?
Artificial Intelligence
In recent years this has become one of the principal questions addressed in the LDL program. Here are some of the questions we are addressing in the program.
- AI in Support of Teaching and Learning: How can AI play the role of a customized, student-calibrated, 1:1 learning helper? How can it make teaching a professionally more rewarding job? What levels and forms of AI literacy are now core foundations for teachers and learners?
- AI in Formative and Summative Assessment: How can AI realize long hoped-for aspirations for rich, formative assessment? How will it transform progress and summative assessments?
- AI for Access, Inclusion, and Diversity: As a low-cost web application, how can AI address the “wicked problem” of equitable access to education notwithstanding persistent disparities in educational resourcing? How can it help calibrate learning to address the great differences between students across many dimensions? How can it close the gap between school learning, homes, informal, and workplace learning?
- Guardrails for AI in Education: We are under no illusion about the great challenges, even dangers, that accompany AI. Here, we critically interrogate: 1) ways distinguishing and authenticating student and machine contributions to student work; 2) ways of deepening rather than undermining the teacher’s professional role; 3) ways of assuring the veracity of knowledge in the context of unreliable sources “hallucinations”; 4) AI bias; 5) privacy, security, and intellectual property.