Several measures were taken in this study. These include: measures on educational differences between the subjects, recording how the students navigated through hypertexts and how long it took them to read the texts when provided leads and not provided leads. Their reading comprehension was then tested by giving them a 24 question multiple choice assessment. To test prior knowledge, a domain knowledge pre-test was also given to the students. 


More specific measures were taken, as well. Metacognitive awareness was assessed using the Metacognitive Awareness Inventory. This tests what the students think, feel, and know about the information. Cognitive load measures were then tested by having students provide a self-report of their mental effort. The remaining measures included the EEG, assessing recollection, structural measures (though use of concept maps), and a multiple choice post-test on domain knowledge.


Measures taken to assess the impact of leads on cognitive load

Each hypertext consisted of one passage containing seven links. The passages were each around 500 words and the nodes were around 90 words in length. However, only the hypertexts on information processing and cognitive constructivism contained leads that were around 10 words. These texts had a Flesch score of 35, as the subjects were college students. 


A hypertext presentation system was utilized to to design nodes and prevent any tangents from what is supposed to be studied (i.e. no external links). The leads were formatted in the form of pop-ups for the passages.

Michigan State University

Four hypertexts that were based on a different learning theory (behaviorism, information processing, cognitive constructivism, and social constructivism) were selected for the study. The study aimed at measuring reading ability, metacognitive awareness, prior knowledge, cognitive load, and learning performance. 

Subject of hypertexts

Antonenko, P. D., & Niederhauser, D. S. (2010). The influence of leads on cognitive load and learning in a hypertext environment. Computers in Human Behavior, 26, 140-150. doi:lO.l016/j.chb.2009.lO.0I4


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