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| Kyung Kim |
How knowledge is structured in the human mind fascinates Dr. Kyung Kim, a CISLL affiliate in the Department of Educational Technology, Research and Assessment, housed in NIU’s College of Education.
“Knowledge structure refers to how the concepts in a domain are related to one another in memory. We believe knowledge structures can be represented in a network form that can be depicted visually,” explains Kim.
To get an idea of how a knowledge structure can be depicted visually, imagine a diagram consisting of a dozen or so circles haphazardly placed on a page, with lines connecting some of the circles.
If the topic of the structure is the “heart”, then the individual circles might represent particular concepts related to the heart, such as “blood” “pulmonary valve”, “lung”, and so on.
A line between any two concepts indicates that they are conceptually connected in the person’s memory. Some concepts may be linked to many other concepts, whereas others may be only linked to one.
This sort of visual network of a student’s knowledge organization can help instructors assess the learning of their students.
For example, if a student knows that the pulmonary valve pumps oxygen-rich blood to the lungs, then that student would connect the concepts “pulmonary valve” and “lungs” if asked to draw their network. A lack of a line, or other deviations from an “ideal” network, would indicate that student’s knowledge is incomplete and may include misconceptions.
However, having students draw out their knowledge so that the instructor can provide timely and accurate feedback is not very efficient. Imagine being an instructor with hundreds of knowledge maps to grade every night, and you can see why. Instructors get tired and may make mistakes, and it might be days before students receive feedback.
In addition, most students are more used to writing essays than creating these types of concept maps.
In response to these and other educational needs and constraints, Kim developed a computer application called GIKS, which stands for Graphical Interface of Knowledge Structure.
Based on written input (e.g., a summary essay or a transcribed conversation), GIKS uses various existing computerized analytic tools (e.g., ALA-reader, Pathfinder) that together create a visual representation of the organization of preselected concepts mentioned in the input.
That visual representation would be similar to the circles and lines mentioned earlier.
GIKS allows an instructor (or researcher) to input a “master” text that provides the information of the to-be-learned knowledge structure (e.g., a textbook passage). A student (or research participant) can write and input a summary essay about the topic. This essay would reflect the student’s knowledge. Then GIKS produces visual representations of both the master text and the student’s essay and compares them.
“GIKS gives the student immediate feedback in an easy-to-understand visual way. It gives them information as to which concepts were correctly included, as well as missing concepts, and correct and incorrect links among the concepts,” explains Kim.
With GIKS, students do not need to wait for the instructor to provide feedback. Feedback is instantaneous.
Since the tool is web-based, it is ideal for online courses, and because it uses text as input, it can be used in many content domains. Thus far, Kim has studied learning in physics, biology, geography, and foreign language.
What is also nice about GIKS is that it allows a student to input a summary essay at different points in time. This allows the student (and possibly the instructor or researcher) to see how knowledge changes as a new domain is learned.
“In addition to being useful for assessment, we have also shown that students learn by receiving feedback via GIKS,” said Kim.
In a publication with co-authors Roy Clarianay and NIU professor Yanghee Kim, tenth-grade students in an online physics course who used GIKS as a reflective tool included more relevant connections and fewer irrelevant connections in their summary essays than did students who were given explanatory videos or test questions, other known ways to increase learning.
Excitingly, GIKS is being acclaimed by educational technology researchers as well as other academic communities.
Kim was recently awarded the 2019 AECT Young Researcher Award from the Association for Educational Communications and Technology, the most prestigious association in Educational Technology. The award recognized a GIKS study that analyzed participants’ text messages to explore the dynamics of online collaborative problem solving. His dissertation, which used GIKS to explore the influence of text structures on readers’ knowledge structures, also won the 2019 Timothy & Cynthia Shanahan Outstanding Dissertation Award from the International Literacy Association. A study that applied GIKS to geography was recently selected for the 2019 Journal of Geography Award from the National Council for Geographic Education.
Kim is now interested in augmenting GIKS with speech-recognition capability. This feature would allow him to examine how individuals’ knowledge structures, as revealed through their speech, can be harnessed and used effectively in real-world collaborative work settings.
“Groups spend too much time discussing information that everyone in the group already knows. However, there is little research on how unshared information can play a role in collaborative learning. Having GIKS analyze both text and speech would be an ideal way to help groups know what other members know and don’t know. Perhaps by emphasizing unique knowledge held by an individual, group learning could be enhanced,” volunteered Kim.
In sum, the answer to the question “Can diagrams of your knowledge help you learn?” is a resounding “Yes”—provided the diagrams were created by GIKS, of course.
If you are interested in learning more about GIKS, you can contact Professor Kim at kkim2@niu.edu.
About the author: Keith Millis is on CISLL’s executive board and is a professor of psychology at NIU.
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