Vision

Helping teachers to teach better and helping students to learn better.

Mission

Developing experimentally validated deep teaching and learning, cultivating creators and creative user of knowledge

For a new model of education in the connected world – Meaningful learning towards advanced knowledge generators over knowledge highway

Slogan

See through connections to find the whole

Introduction

Driven by the shared research interest on “System Science in Education and Cognitive Science” and the shared vision of “helping teachers to teach better and helping students to learn better”, we established the Institute of Educational System Science (IESS), in School of Systems Science at Beijing Normal Univiersity.

Glossaries

In order to accurately understand the contents of this website, readers are reminded to go over the following glossaries, which includes terminologies such as aims of teaching and learning, disciplnary big picture, knowledge levels, knowledge generators, meaningful learning, deep learning, knowledge highway. We strongly suggest our dear serious visitors of this website to click this line to expand and read the hidden contents.

The big picture of meaningful learning

Aims of teaching and learning

The purpose of learning is to become a person who recongnizes and asks questions, solves problems, creates knowledge, uses knowledge creatively, or be able to appreciate the creation and creative use of knowledge. The purpose of teaching is to help learners better achieve the above purpose of learning, via for example helping learners to learn how to learn.

Repetitive use of knowledge,which means to use knowledge in the ways and for the situations that it has been used before, is not the primary goal of teaching and learning.

Disciplnary big picture

Or a big picture of a discipline refers to the typical subjects of interest, the typical research questions, the typical ways of thinking, the typical methods of analysis of the discipline, and how the discipline serves the world and other disciplines.

Knowledge levels and knowledge generators

Knowledge is divided into four levels. The first level refers to the factual and procedural knowledge. The second level refers to the disciplinary concepts and the connection between concepts. The third level of knowledge refers to the disciplinary big picture, especially the typical ways of thinking of each disciplines. The fourth level refers to the general ways of thinking, for example, critical thinking and connected thinking, and methods of the teaching and learning based on these thinking. Among them, the second-level knowledge is called the generator of the first-level knowledge, also called “Shallow Knowledge Generator”; the third-level knowledge is called the generator of the second and first-level knowledge; the fourth level knowledge is called the third, second, and first-level knowledge generator; the latter two are called “Advanced Knowledge Generator”.

The network formed by clearly marking the up-down, left-right connections among all the knowledge of a discipline is called the knowledge network of the discipline. The combination of all the knowledge networks of the various disciplines, plus that of those knowledge that have not become any independent disciplines, is called the “human knowledge highway”.

Meaningful learning, seeing through the up-down and left-right connections

Meaningful learning refers to the way of teaching and learning that uses the connections between the upper and lower levels of knowledge or the left-right connections between knowledge at the same level. Conversely, the process of learning knowledge through repeated memorization and recall exercises without using the up-down and left-right connections between knowledge is called rote learning. Often, we also call the bottom-up process as induction or abstraction, and the top-down process as generation, deduction or application.

Deep teaching and learning

The levels of the targeted knowledge of a teaching and learning process determines the level of that teaching and learning. For example, goals of “first-level teaching and learning” is to acquire some first-level knowledge.

Shallow teaching and learning is defined as the process of teaching and learning all four levels of knowledge rotely and also the meaningful learning of the first-level knowledge. Halfway teaching and learning is defined as the meaningful learning of the second-level knowledge. Finally, deep teaching and learning refers to the meaningful learning of the third- and forth-level knowledge. Thus, deep teaching and learning is also the meaningful learning aimed at advanced knowledge generators。

Meaningful learning aimed at advanced knowledge generators over human knowledge highway

As you might have seen from above, the new model of education that we are researching and promoting is meaningful learning aimed at advanced knowledge generators over human knowledge highway. It is also called deep teaching and learning over human knowledge highway, or sometimes shorted as deep teaching and learning, or simply meaningful learning.

With this new model of education, from making use of the up-down and left-right connections, from learning torwards the advanced knowledge generators especially the displinary big pictures, we will be able to achieve “Teach Less, Learn More”, “The more advanced we learn, the less we need to memorize, the more connections we can see, and the lower the the learning cost”. Eventually, every learner can find, learn, design and become what they want to be, of course if necessary guided by teachers. Such teaching and learning should also be able to promote the creation of knowledge and the creative use of knowledge.

Of course, all those expectations of this new model of education will have to wait for concrete investigations to either validate or falisify it.

There is a slides version of this not-so-short introduction: An overview of IESS.

Research perspective, tasks and characteristics

Added value to education

Added value provided by IESS to education and educational studies is

  • System: connecting the isolated, seeing through connections, a whole must be seen from a decomposition,
  • Science: conducting problem/data-driven researches to describe the world with and experimentally validated models and concepts.

Meaningful learning over the human knowledge highway

Constructions of human knowlesge highway including the task of its contruction and the methods to facilitate its construction, algorithms for optimal learning orders and optimal adaptive testing over the human knoledge highway, comparison of meaningful learning and rote leanring (test scores, brain activity, creative prolem solving, recognitive and emotion burden), ways to improve meaningful learning. Besides the systemic approach, the main difference between these research works and the current educational neuroscience studies is that we are aiming towards deep learning other than the rather shallow techniques of teaching and learning.

Empirical or exprimental scientific studies

A combination of data from classroom teaching and learning acticities and brain activities, mathematical modeling and analysis, and validation in labs and real classrooms.

Multiple disciplines integrated, via Systems Sceince

Driven by the core problem of how to teach and learn better, multiple disciplines including the subject-domain discipline (both expertise on domain researching and teaching are needed), neuroscience and psychology are integrated via systems science acting as the connector.

Scaffolders for teachers and learners

Exprimentally verified ideas, methods, tools, algorithms, to hold hands of teachers and learners, beyond speculative or even critical thoughts.

How we run the Insititute: problem-driven open institute

Guided by the vision of “helping teachers to teach better and helping students to learn better”, IESS will raise research funds and research questions to help researchers to be able to simply focus on their research work. If you are such a researcher, please come, talk to us, and join us.

Contact IESS

  • iess.sec@bnu.edu.cn
  • 新街口外大街19号(19 Xinjiekouwai St.), 北京(Beijing), 海淀区(Haidian) 100875