Education is in a state of flux – transitioning from traditional architectures and practices to new ecologies of teaching and learning influenced by the tremendous social and technological changes of our times. What changes are afoot today in workplaces, civic life and everyday community life? What are their implications for education? What are the possible impacts of contemporary social transformations on teaching and learning – including in the areas of technology, media, globalization, diversity, changing forms of work in the “knowledge society”, and, in these contexts, changing learner needs and sensibilities? This course explores three pedagogical paradigms: “didactic”, “authentic” and “transformative” learning. It takes an historical perspective in order to define the contemporary dimensions of what we term “new learning”. It prepares participants to make purposeful choices and link particular theories/instructional approaches to individual and group learning goals.

Sets out to provide an overview of human cognition from three disciplinary perspectives: linguistic, epistemological (philosophy of knowledge), and psychological. Taking aninterdisciplinary approach, it aims to contrast the theoretical and methodological features of each perspective, critically analyzing their relative strengths and weaknesses for teaching and learning. The focus will be both theoretical (What are the characteristic conceptual tools of each disciplinary perspective? What are its underlying assumptions about the processes of learning?) and practical (What are the consequences of each theoretical orientations for education research and pedagogical practice?).

Scholar Learning Module: Learning and Human Development with Technologies
Textbook (available as an e-book in the UofI library): New Learning: Elements of a Science of Education, Cambridge University Press, 2008 (2nd edition, 2012)
College of Education link: EPSY 408: Learning and Human Development with Educational Technologies*

Explores applications of Generative AI in Education. Topics include: AI predecessors (symbolic, data-driven, and connectionist AI); Large Language Models and statistical approaches to meaning in text; machine learning (supervised, unsupervised and reinforcement learning, including deep learning and neural nets); chatbot architectures and prompt engineering; fine-tuning for domain-specific applications; multimodal AI; guardrails (including managing AI bias, “jailbreaks,” “hallucinations,” explainability, intellectual property, privacy and security); and applications of Generative AI in education

All required material (video lectures, readings etc.) will be provided to students, as per the tentative schedule below.

An investigation of the dimensions of learner diversity: material (class, locale), corporeal (age, race, sex and sexuality, and physical and mental characteristics) and symbolic (culture, language, gender, family, affinity and persona). Examines social-cultural theories of difference, as well as considering alternative responses to these differences in educational settings – ranging from broad, institutional responses to specific pedagogical responses within classes of students. The course also focuses on the application of learning technologies and new media to meet the needs of diverse populations of learners. Its main practical question is, how do we use educational technologies to create learning environments in which learning experiences can be customized and calibrated to meet the precise needs of particular learners? Topics include: universal design for learning, differentiated instruction systems, and adaptive and personalized learning environments.

CGScholar Learning Module: Learner Differences and Digital Media
Textbook (available as an e-book in the UofI library): New Learning: Elements of a Science of Education, Cambridge University Press, 2008 (2nd edition, 2012).
College of Education link: EPOL 486 / SPED 413: New Media and Learner Differences*

This course examines the differences between machine and human learning and the ways in which machines can complement human learning. It examines technical definitions of supervised and unsupervised machine learning, as well as broader views of mechanical intelligence able to replicate or exceed human intelligence. The course will also explore practical applications of learning analytics and artificial intelligence in learning management systems and other educational tools and critically interrogate the applications of AI in education. 

CGScholar Learning Module: Machine and Human Learning
Textbook:
College of Education link: EPOL 479: Machine Human Learning

The use of mobile devices for various purposes in everyday life has been growing exponentially. Given that mobile devices are so widely used and accessible, they present an opportunity to expand the space for learning, enabling both formal education and informal learning to be available anytime and anywhere. In both scenarios, mobile devices open opportunities to provide relevant learning that engages students in real-world situations. This course provides a wide variety of examples showcasing mobile learning implementations and tools, alongside comprehensive pedagogical frameworks designed to enhance mobile learning experiences.

All required material (video lectures, readings etc.) will be provided to students, as per the tentative schedule below.

For several decades now, assessment has become an increasingly pressing educational priority. Teacher and school accountability systems have come to be based on analysis of large-scale, standardized summative assessments. As a consequence, assessment now dominates most conversations about reform, particularly as a measure of teacher and school accountability for learner performance. Behind the often heated and at times ideologically gridlocked debate is a genuine challenge to address gaps in achievement between different demographically identifiable groups of students. There is an urgent need to lift whole communities and cohorts of students out of cycles of underachievement. For better or for worse, testing and public reporting of achievement is seen to be one of the few tools capable of clearly informing public policy makers and communities alike about how their resources are being used to expand the life opportunities. This course is an overview of current debates about testing, and analyses the strengths and weaknesses of a variety of approaches to assessment. The course also focuses on the use of assessment technologies in learning. It will explore recent advances in computer adaptive and diagnostic testing, the use of natural language processing technologies in assessments, and embedded formative assessments in digital and online curricula. Other topics include the use of data mining and learning analytics in learning management systems and educational technology platforms. Participants will be required to consider issues of data access, privacy and the challenges raised by ‘big data’ including data persistency and student profiling. The course also addresses processes of educational evaluation.

In this course participants identify and justify the implementation of advanced learning technologies in the overall environment of learning. They investigate the ways in which advanced technologies influence the design process and how the design process may be enhanced. Areas addressed include: learning management systems, intelligent tutors, computer adaptive testing, gamification, simulations, learning in and through social media and peer interaction, universal design for learning, differentiated instruction systems, big data and learning analytics, attention monitoring, and affect-aware systems. Participants will explore the processes for selection and implementation of suitable technologies, the design of electronic learning resources, design and application of digital media in teaching and learning, familiarization with web usability and accessibility, and critical analysis of the benefits of technologies in education.

CGScholar Learning Module: Advanced Instructional Technologies
Optional Textbook: e-Learning Ecologies, Routledge, 2017.

Explores the potentials online learning to influence educational change. However, with a critical eye, we also raise the concerns, such as the use of digital media in online learning to prolong anachronistic pedagogies. The course investigates how to harness the affordances of networked digital media to make a positive difference in learner outcomes. It explores the creation of learning ecosystems that value the knowledge that all learners bring to the table and where learners’ knowledge repertoires are extended as they actively make new knowledge, enable academic success, and build high performing, collaborative knowledge cultures.

This course provides an overview of the theories, methods, and applications that educational researchers use to understand and improve learning. The course begins by exploring fundamental learning processes before examining the role of collaboration and social learning. A central assumption is that learning is a mediated process, shaped by interaction with others and deeply embedded in context and culture. This course establishes a foundation for effective learning design, especially in technology-integrated environments, and offers insights for both research and practice.

All required material (video lectures, readings etc.) will be provided to students, as per the tentative schedule below.

This course explores the dynamics of learning using mobile computing devices, broadly defined to range from mobile phones, tablets and laptops to interesting new possibilities raised by emerging technologies such as wearable devices and a potentially pervasive “internet of things”. Our journey will take us through museums, galleries and parks – real and virtual. We will visit new media and gaming spaces in which either incidental or explicit learning is taking place. We will look at sites of informal as well as formal learning – extraordinary classrooms offering blended learning opportunities, as well as new forms and modes of out-of-school and self-directed learning.

GScholar Learning Module: Ubiquitous Learning
Introductory Reading: Ubiquitous Learning, University of Illinois Press, 2009
College of Education link: EPOL 580 / EPS 506: Ubiquitous Learning*

Investigates a variety of pedagogical paradigms, including didactic, authentic, functional and critical pedagogies. Develops the concept of a pedagogical repertoire, as a means to interpret the ways in which learners engage in a variety of “knowledge processes” or task types. The course focuses for its examples on approaches literacy and academic literacy teaching and learning, but participants can address parallel examples from other discipline areas and across all levels of education including school, higher education, and workplace learning. As a counterpoint, the course also reflects on the practicalities of learning knowledge-making in informal as well as consciously designed learning environments.

GScholar Learning Module: Literacy Teaching and Learning: Aims, Approaches and Pedagogies
Textbook (available as an e-book in the UofI library): Literacies, Cambridge University Press 2012 (2nd edition, 2016), Chapters 1-8.
College of Education link: EPOL 581 / EPS 532: Knowledge, Learning and Pedagogy

This course Introduces the ‘Multiliteracies’ theory of literacy learning, recognizing that contemporary communications are increasingly multimodal, connecting written text with oral, visual, gestural, tactile and spatial modes. The course will explore current trends in literacy instruction, not only in language arts or composition classes, but academic literacies across all curriculum areas and all levels of learning. This reflects an expansive view of literacy in which reading and writing includes media objects such as video, datasets, and infographics. 

Follow-on Learning Module: Multimodal Literacies: Communication and Learning in the Era of Digital Media
Textbook (available as an e-book in the UofI library): Literacies, Cambridge University Press 2012 (2nd edition, 2016), Chapters 9-16.
College of Education link: EPOL 582 / EPS 554: New Media and Literacies*

An examination of emerging environments of e-learning, some setting out to emulate the heritage social relationships and discourses of the classroom, others attempting to create new forms of learning. Aims to push the imaginative boundaries of what might be possible in e-learning environments. Explores the ways in which assessments can be constructed and implemented which are integral to the learning process, with the assistance of today’s new media, ‘big data’ and other information technologies.

CGScholar Learning Module: e-Learning Ecologies
Optional Textbook: e-Learning Ecologies, Routledge, 2017.
College of Education link: EPOL 583 / HRD 572: e-Learning Ecologies*

This course addresses the ways in which knowledge is represented, with special reference to the knowledge representations of teachers and learners. Its interdisciplinary bases are functional linguistics, semiotics, philosophy, history of ideas, media/communication studies, and ontology in computer science. The focal point of the course is the five questions about meaning posed by Cope and Kalantzis in their transpositional grammar: “what is this about?” (reference); “who or what is doing this?” (agency); “what holds this together?” (structure); “how does this fit with its surroundings?” (context); and “what is this for?” (interest). Along these lines of inquiry, a transpositional grammar addresses language, image, embodied action, object and space. “Transposition” refers to the movement across these various forms of meaning, intensified in the era of pervasively multimodal, digitally-mediated communications. Applied to education, not only does this provide a valuable heuristic to reframe literacy teaching and learning (the original impulse for the development of this grammar). It also offers an integrated account of meaning-to-learn across all subject areas, including pedagogical content knowledge and learner knowledge representations. Conceived in the broader terms of social-scientific research methods, transpositional grammar is an attempt to overcome the narrowness and logocentrism of “the language turn” which dominated social sciences in the twentieth century. In a practical sense, semiotics of the kind explored in this course also provides tools for reading and interpreting multimodal texts and research data.

How do you build a sense of your field and its gaps? This course aims to make sense of a term – academic literature – at once mundane and mystical. It starts with fundamentals: how to build, annotate, analyze, map and translate a literature database into a literature review. It progresses to think about how AI and other technology can help foster more critical, analytic and reflexive modes of interpretation and understandings of the field.

All required material (video lectures, readings etc.) will be provided to students, as per the tentative schedule below

When we want to convince people of our arguments, we rely upon evidence. Quality evidence in turn depends upon rigorous design and use of research methods. In this course we study methods through two lenses. The first, theory, refers to explanations of society and learning that help make sense of our work. The second, technology, refers to the tools we use to find themes, apply codes and identify patterns in data. AI does not change foundational research axioms, but across both qualitative and quantitative methods it challenges us, revising how we collect, analyze and think about data. In this course we examine how AI can work alongside human expertise in the research process.

All required material (video lectures, readings etc.) will be provided to students, as per the tentative schedule below