The Internet has become a unique platform for learning. Its 24/7 availability and broad range of information offers allows for the creation of brand-new learning methods – not only for acquiring domain-specific and general knowledge but also for developing new learning skills. As a new learning space, the Internet has had a particularly profound effect at the university level, where the boundaries between originally very different types of learning are now becoming blurred. Where formal vs. informal and explicit vs. implicit learning were once evidently distinguishable, Internet-based learning environments allow students to do both simultaneously now, in hybrid formats where the boundaries between (disciplinary) domains are becoming less and less important. The way students are learning in the Internet space appears to be more complex than in other environments typically characterized as traditional or 'analog'. The former is clearly much more dynamic, variable, and far less formalized than the latter, especially in comparison with the traditional, highly-formalized types of learning we see at universities.
Another remarkable aspect of this development relates to the increasing significance that algorithms based on machine learning are having on learning processes. Learning on Internet-based platforms is becoming more and more dependent on the 'externalization' of human learning activities and data processing operations. These processes are no longer carried out by students and teachers themselves, but rather increasingly by algorithms that preselect information and prepare, compile, and link content (multimedia). In extreme cases, Internet users receive automatically generated documents (e.g. texts or images) for the coherence or accuracy of which they must rely on the algorithm in question. Algorithms of this kind have become artificial players or mediators in Internet-based learning processes. Researchers are now beginning to ask when the time will come that people are more likely to be reading machine-generated texts than texts written by humans. Similar questions are being posed with regard to the social interactions between learners and teachers, and the increasing tendency of students to use artificial Internet-based activity to complement or even replace face-to-face instruction by teachers.
Research into human learning has been hardly able to keep up with the fast-paced technological developments in this area. Learning processes on the Internet have been the subject of little research up to this point. Researchers at Johannes Gutenberg University Mainz (JGU), Goethe University Frankfurt, and Technische Universität Darmstadt are aiming to fill in the gaps in cooperation with the German Leibniz Institute for Research and Information on Education (DIPF), Technische Universität Kaiserslautern, and the German Research Center for Artificial Intelligence (DFKI). As part of the interdisciplinary research initiative on Positive Learning in the Age of Information (PLATO), they are investigating the fundamentals, conditions, and effects of learning on the Internet, in particular in the university context. Using a broad range of theoretical and measurement methods, they are studying the characteristics and dynamics of learning environments on the Internet as well as the learning processes that take place there. Techniques employed in education studies and psychology are being used along with methods from computer science, linguistics, neurobiology, and other academic disciplines such as medicine, physics, and economics. The objective is not only to paint a broader picture of learning in online environments, but also to make it possible to forecast how learning on the Internet may develop in the future and how these developments may shape academic learning.
Joint pilot studies have already delivered initial results on the use of online media in university study programs. They have shown, for example, that the use of online media differs significantly among students depending on whether they are studying economics, social sciences, or in the field of natural sciences. Both positive and negative effects have been observed with regard to the acquisition of domain-specific knowledge over a course of study. It also became apparent that students in all of the courses examined and even those who had already completed a Bachelor's or Master's degree course experienced difficulties in dealing with online media in a critical, reflective manner and in drawing conclusions based on a multitude of information from different online sources (e.g. social media platforms and news websites). These results are augmented by eye-tracking analyses that examine how students interact with websites and their content when solving domain-specific tasks in physics and economics. When confronted with multimedia content, there were significant variations between students in different degree programs; the acquisition of domain-specific knowledge, however, appears to be influenced in comparable ways. To explain these and other related findings, the PLATO-i researchers are currently investigating the characteristics of the various media used in learning, their representation formats, and their content as well as how these media characteristics influence students' psychological states and traits when dealing with online media. As a joint initiative within the RMU association, PLATO-i is part of a comprehensive research program on Positive Learning in the Age of Information, which also includes researchers from the German Research Center for Artificial Intelligence (DFKI), TU Kaiserslautern, TU Darmstadt, and the German Leibniz Institute for Research and Information on Education (DIPF). Also participating are researchers at Stanford University, the University of Alberta, Harvard University, the Learning Sciences Research Institute in Chicago, and many other research facilities. The objective of PLATO-i is to research learning on the Internet, both within universities and outside of them, to ultimately contribute to helping institutions of higher education find a way to keep up with their mission of teaching and conducting research in this age of the Internet and accelerated technological progress.
The RMU Initiative Funding for Research
The Rhine-Main Universities (RMU) are strengthening their mutual networks through the RMU Initiative Funding for Research. From the last call for proposals comprising a total of 49 applicants, six new research projects in African Studies, Educational Research, Computer Science, Meteorology, Pharmaceutical Sciences, and Economics Education will be funded over the coming two years, each with up to EUR 100,000 per year.
Prof. Dr. Olga Zlatkin-Troitschanskaia
Gutenberg School of Management & Economics
Johannes Gutenberg University Mainz
55099 Mainz, GERMANY
phone: +49 6131 39-22009
Prof. Dr. Alexander Mehler
Institute of Computer Science
Goethe University Frankfurt
60438 Frankfurt am Main, GERMANY
phone: +49 69 798-28921