Abstract
This chapter highlights over a decade of literature and research findings related to new learning ecosystems such as personal learning environments including MOOCs. New structures and environments are now in place that provide opportunities for learning in open networks, but important challenges and issues persist. This chapter also highlights challenges and opportunities in the design and development of MOOC learning experience design, conditions that must exist for people to be involved and engaged in a connectivist learning environment, challenges related to personalization and support of individual learning needs, along with new ethical and privacy concerns related to the safeguarding of data in networked environments. In conclusion, further research in areas of machine-learning AI in data-driven learning systems is discussed with emphasis on human factors such as motivation, incentives, and support that encourage course participation and learning.
TopIntroduction
The proliferation of Information and Communications Technology (ICT) in recent years has changed the educational landscape. Social media and emerging informal learning ecosystems such as Personal Learning Environments, including Massive Open Online Courses, offer tremendous potential to enhance learning processes; but research and literature findings have underscored important challenges as well. This chapter presents highlights from over a decade of research on Personal Learning Environments and MOOCs with a glimpse into the new learning ecosystems. Some background will be provided which includes research on PLEs and MOOCs by the National Research Council Canada. As we enter into a new era of information abundance and learning opportunities, new ways of participating in educational experiences and learning are now available. We address possible new approaches and methods by examining next generation learning environments.
With new structures and environments in place, two areas of research are highlighted as foundational to examining learning in open networked environments: learner autonomy and a theory for learning in a digital age, that is, connectivism. Another section will look at self-directed learning, agency and autonomy as essential for learning in open networked environments with evidence from Connectivist MOOCs as a potentially disruptive pedagogy. This chapter will also look at how research on cMOOCs has informed MOOC learning experience design, specifically, what conditions must exist for people to be involved and engaged in a connectivist learning environment. The challenges related to personalization and support of individual learning needs will be highlighted along with new ethical and privacy concerns related to the safeguarding of data in networked environments. A glimpse into what the future holds in terms of next generation learning environments will also be revealed along with conclusions that will point to important area of research that are still lacking and recommendations for future areas of investigation.
Key Terms in this Chapter
Personalized Learning Environments: Provide learning opportunities and instruction paced to the learners’ needs, tailored to learning preferences and to the specific interests of different learners.
Semantic Web: An extension of the world wide web and a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.
National Research Council Canada: The Government of Canada’s largest research organization supporting industrial innovation, the advancement of knowledge and technology development, as well as fulfilling government mandates.
Learning Analytics: The measurement, collection, and analysis and reporting of data about learners and their contexts, for the purpose of understanding and optimizing learning and the environments in which learning occurs.
Moodle: A free and open-source learning management system used for blended learning and open education.
Learning Ecosystem: An entity made up of components that work together to create a whole learning experience. The overall experience becomes more than the sum of its parts.
Cloud Computing: Makes computer system resources, storage and computer power in particular, available on demand without direct active management by the user. The cloud makes data centers available to many users over the internet.
Educational Data Mining (EDM): A research field concerned with the application of data mining, machine learning, and statistics to information generated from educational settings.
Big Data: A field that addresses ways to analyze, extract, and manage data sets that are too large or complex to be dealt with by traditional data-processing application software.